Atle Bjørnerud

• Roe, James Michael; J., Jagust, William; M., Landau, Susan; M., Harrison, Theresa; Grydeland, Håkon & Slivka, Maksim [Vis alle 19 forfattere av denne artikkelen] (2026). Cortical thickness changes precede high levels of amyloid by at least 7 years | Nature Neuroscience. Nature Neuroscience. ISSN 1097-6256. doi: 10.1038/s41593-026-02363-4. Fulltekst i vitenarkiv Vis sammendrag

  Alzheimer’s disease is now defined by underlying pathology, with elevated amyloid-beta (Aβ) sufficient for diagnosis in the absence of cognitive symptoms. We combined longitudinal magnetic resonance imaging and Aβ positron emission tomography data from three cognitively healthy cohorts to examine cortical thickness trajectories in individuals who later converted to Aβ-positive status, using magnetic resonance images acquired years before conversion. Individuals who subsequently developed elevated Aβ showed a thicker cortex and reduced cortical thinning, detectable up to 7 years before conversion. Many effects persisted after accounting for quantitative Aβ levels, suggesting some cortical thickness changes may be partly independent of Aβ. Differences in cortical thickness and its change showed moderate spatial correspondence with Aβ deposition patterns, and the timing of thickness changes tracked the progression of Aβ accumulation. These findings indicate that cortical thickness alterations can precede positron emission tomography-detectable amyloid positivity by several years, suggesting high amyloid burden may not represent the earliest imaging marker of Alzheimer’s disease. Longitudinal MRI reveals that the cortex becomes relatively thicker years before amyloid positivity is detected on PET, providing insight into the earliest brain changes and potential consequences of amyloid accumulation in Alzheimer’s disease.

• Jarholm, Jonas Alexander; Teceläo, Sandra Raquel Ramos; Kirsebom, Bjørn-Eivind; Ghazi, Mostafa Mehdipour; Pålhaugen, Lene & Gisladottir, Berglind [Vis alle 17 forfattere av denne artikkelen] (2026). Independent prognostic value of peak width of skeletonized mean diffusivity on clinical progression in Alzheimer's disease. Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring. 18(3). doi: 10.1002/dad2.70416. Fulltekst i vitenarkiv Vis sammendrag

  INTRODUCTION Peak width of skeletonized mean diffusivity (PSMD) is a candidate magnetic resonance imaging marker for global white matter integrity. We investigated the value of PSMD in predicting clinical progression in amyloid-positive and amyloid-negative individuals. METHODS PSMD, cognition, and amyloid status were measured in 254 subjects from the Dementia Disease Initiation (DDI) cohort and 211 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Survival analysis was conducted on 166 DDI subjects and validated in 178 ADNI subjects using Clinical Dementia Rating scale. RESULTS High PSMD amyloid-positive individuals had an increased risk of clinical progression relative to those with low PSMD, driven by independent additive effects of amyloid pathology and PSMD. Higher PSMD was predominantly associated with slower processing speed and reduced executive function, but not with memory performance. DISCUSSION Combining PSMD with amyloid status may improve the prediction of clinical progression in Alzheimer's disease, particularly in relation to executive and processing speed domains.

• Pedersen, Mads Lund; Mowinckel, Athanasia Monika; Ziegler, Sigurd; Fredriksen, Mats; Bjørnerud, Atle & Endestad, Tor [Vis alle 7 forfattere av denne artikkelen] (2026). Selective enhancement of cost sensitivity by methylphenidate in adult ADHD: a randomized placebo-controlled trial. Psychological Medicine. ISSN 0033-2917. 56. doi: 10.1017/S0033291726104954. Fulltekst i vitenarkiv Vis sammendrag

  Background Attention-deficit hyperactivity disorder (ADHD) is associated with impairments in real-life decisions, many involving balancing costs and benefits. Increasing dopamine and norepinephrine with stimulant medication improves decision-making in ADHD. However, it is unclear whether stimulant medication affects sensitivity to costs and/or benefits or alters the speed-accuracy tradeoff. Here, we applied the drift diffusion model (DDM) to assess how the stimulant medication methylphenidate (MPH) affects subprocesses of cost-benefit decision-making in ADHD. Methods Sixty-one adult participants with ADHD and 63 healthy controls completed a cost-benefit decision-making task in a randomized double-blind placebo-controlled design. ADHD participants were tested once on and once off MPH. Control participants performed the task in two sessions without medication. The task entailed deciding whether to accept or reject a stimulus based on learned cost and benefit value associations. The effect of ADHD and medication on subprocesses of decision-making was disentangled by estimating task performance with DDM parameters drift rate, starting point bias, and decision threshold, representing evidence accumulation, a priori accept/reject bias, and the speed-accuracy tradeoff, respectively. Primary analyses used a modified intention-to-treat sample, including participants with main-phase data from both sessions. Results The DDM analysis identified impaired evidence accumulation combined with premature responding in participants with ADHD, indicated by reduced sensitivity to costs and benefits and narrower decision thresholds. MPH altered the cost-benefit balance by improving sensitivity to costs. Lastly, lower cost sensitivity was associated with greater symptom severity and higher prescribed dosage in ADHD. Conclusions Methylphenidate alters cost-benefit decision-making in ADHD by increasing sensitivity to costs.

• MacIntosh, Bradley J; Morberg, Pål; Murugesu, Elakkyen; Beyer, Mona K.; Larsen, Karianne & Skogen, Karoline [Vis alle 13 forfattere av denne artikkelen] (2026). Automated volume estimate of the brain’s lateral ventricles reveals a persistent association with cognitive performance among stroke survivors. Cerebral Circulation - Cognition and Behavior. ISSN 2666-2450. 11. doi: 10.1016/j.cccb.2026.100556. Fulltekst i vitenarkiv Vis sammendrag

  Background: Post-stroke cognitive impairment (PSCI) is a significant barrier to recovery. While computed tomography (CT) is the dominant modality for acute stroke diagnosis, it can also quantify brain anatomy, such as lateral ventricular volume (LVV). This study investigates whether initial LVV is associated with Montreal Cognitive Assessment (MoCA) scores over long-term follow-up. Methods: Initial head CT, longitudinal MoCA, and functional assessments were collected at sites from the Norwegian COgnitive impairment After STroke (Nor-COAST) study. LVV was estimated using an established deep learning segmentation tool. Associations between initial LVV and repeat MoCA were tested across four timepoints (up to three years) using a linear mixed effects model. To provide context, we explored the independent influence of LVV in relation to National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), and Global Deterioration Scale (GDS). Results: The sample of N = 547 participants were 74 ± 12 years (range: 35-97 years) and 54% female. Log-transformed LVV was inversely associated with longitudinal MoCA scores (t=-3.75, p < 0.001). This relationship was consistent across cross-sectional analyses at individual time points. Secondary analyses revealed significant LVV associations with NIHSS, mRS, and GDS scores (all p < 0.05). Conclusion: LVV was independently associated with lower MoCA scores across the three-year follow-up after stroke. Specifically, a patient with twice the initial LVV scored 0.7 points lower on the MoCA across three years of follow-up. These findings reveal that CT obtained at stroke admission may yield prognostic information about long-term cognitive outcomes, supporting the case for automated LVV estimation.

• Grødem, Edvard Olaf Sætersdal; Pineiro, Didac Vidal; Sørensen, Øystein; Bartrés-Faz, David; Brandmaier, Andreas M. & Cattaneo, Gabriele [Vis alle 20 forfattere av denne artikkelen] (2026). Stable individual differences dominate adult brain volume variation until later life. Imaging Neuroscience. 4. doi: 10.1162/IMAG.a.1242. Fulltekst i vitenarkiv
• Murugesu, Elakkyen; Liu, Qinghui; SCHELLHORN, TILL; Kristoffersen, Espen Saxhaug; Groote, Inge Rasmus & Bjørnerud, Atle [Vis alle 8 forfattere av denne artikkelen] (2026). Monitoring the lateral ventricles in the presence of intracranial hemorrhage using automated dual segmentation. Medical Physics. ISSN 0094-2405. 53(2). doi: 10.1002/mp.70308. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Background Segmentation of intracranial hemorrhage (ICH) alongside the brain's ventricles can provide crucial information in the management stroke or traumatic brain injury (TBI). Automated computed tomography (CT) based segmentation is time‐efficient and desirable when manual annotation is not feasible. Purpose To develop a fully automated and simultaneous segmentation method capable of quantifying ICH and the lateral ventricle volumes. Segmentation results are evaluated in patients with a range of TBI conditions and patients with hemorrhage in the ventricles, known as intraventricular hemorrhage (IVH). Methods Five deep learning models were trained using 154 non‐contrast CT images with manual annotations of the ICH and lateral ventricles. Model performance was evaluated using Dice and Hausdorff Distance metrics. A top performing model was applied to three clinical samples: 1) N  = 591 patients with mild TBI without ICH; 2) N  = 91 moderate‐to‐severe TBI with baseline and follow‐up CT; and 3) N  = 5 patients with IVH and repeat CT. Statistical tests assessed model performance, and one model was selected to: test for relationship between lateral ventricle volume and age and sex, and investigate volume estimates from baseline to follow‐up. Results Significant segmentation differences were observed between models for the Dice score ( F  = 3.3, p  = 0.012), but not Hausdorff Distance ( F  = 0.58, p  = 0.68). The 3D nnU‐Net model had the highest performance with a mean Dice score of 0.92 ± 0.05 for the lateral ventricles and 0.88 ± 0.05 for ICH. In mild TBI, a quadratic association between lateral ventricle volume and age was found for the whole sample and after stratifying by sex. There were six ICH false positives out of 591 with mild TBI. In moderate‐to‐severe TBI patients, volume changes in both lateral ventricle and ICH were observed from baseline and follow‐up ( p  < 0.04, Wilcoxon signed rank test). Follow‐up lateral ventricle volume was significantly associated with the baseline estimates, but this was not the case for serial ICH estimates. The IVH case series demonstrated the feasibility of measuring lateral ventricle volume changes despite the presence of IVH. Conclusions Automated dual segmentation of lateral ventricles and ICH using deep learning provides a reliable method to monitor TBI severity over time. The approach yielded clinically relevant information, including ICH and lateral ventricle volume changes across sessions. This approach offers an efficient analysis of CT images in ICH and particularly patients that develop IVH.

• Kim, Bo Kyung; Yang, Dal Mo; Jahng, Geon Ho; Kim, Hyun Cheol; Kim, Sang Won & Lee, Hyung Lae [Vis alle 10 forfattere av denne artikkelen] (2025). Comparison of Biparametric MRI and Multiparametric MRI Using Split Dynamic MRI in Prostate Cancer Diagnosis. Journal of the Korean Society of Radiology. 86(6), s. 1037–1051. doi: 10.3348/jksr.2024.0102. Fulltekst i vitenarkiv Vis sammendrag

  Purpose To compare the diagnostic performance between biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) using split dynamic MRI for detecting clinically significant prostate cancer (csPCa) with Prostate Imaging and Reporting Data System (PI-RADS) v2.1, using prostatectomy as the reference standard of pathologic analysis. Materials and Methods We retrospectively analyzed 77 PCa cases in 60 patients who underwent radical prostatectomy for biopsy-proven prostate cancer. The MR Images of the prostate were interpreted in consensus by two experienced radiologists (aged 3 and 35 years). We retrospectively reviewed the MRI images according to PI-RADS v2.1 and recorded the scores from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) imaging, and peak relaxation rate (R2*) for each lesion at three different time points: 1) bpMRI (T2WI, DWI, and ADC), 2) mpMRI1 (T2WI, DWI, ADC, and DCE), and 3) mpMRI2 (T2WI, DWI, ADC, DCE, and peak R2*). The diagnostic performances of bpMRI, mpMRI1, and mpMRI2 in detecting csPCa using PI-RADS V2.1 were evaluated. Additionally, we evaluated the diagnostic performance of DCE-MRI and peak R2* for csPCa detection. Results The area under the curve, sensitivity, specificity, and accuracy for diagnosing csPCa with PI-RADS v2.1 in all lesions and peripheral zone (PZ) lesions were not significantly different between the bpMRI, mpMRI1, and mpMRI2 protocols (p > 0.05). DCE-MRI was better than the peak R2* for diagnosing csPCa in PZ lesions (p < 0.001). Conclusion mpMRI using split dynamic MRI has diagnostic performance similar to that of bpMRI for detecting csPCa using PI-RADS v2.1.

• Kirsebom, Bjørn-Eivind; Nilsson, Johanna; Vromen, Ellen; Arnesen, Peter Mikael; Bjørnerud, Atle & Brinkmalm, Ann [Vis alle 23 forfattere av denne artikkelen] (2025). Cerebrospinal fluid markers link to synaptic plasticity responses and Alzheimer’s disease genetic pathways. Molecular Neurodegeneration. 20(1), s. 1–21. doi: 10.1186/s13024-025-00899-w. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Background Synapse loss is linked to cognitive symptoms in Alzheimer’s Disease (AD) and Cerebrospinal fluid (CSF) synaptic biomarkers may clarify disease heterogeneity and disease mechanisms for progression beyond amyloid (Aβ) and tau pathologies, potentially revealing new drug targets. Methods We used a mass-spectrometry panel of 17 synaptic biomarkers including neuronal pentraxins (NPTXs) linked to glutamatergic signaling, and 14-3-3 proteins linked to tau-pathology and synaptic plasticity. Synapse markers were evaluated in two independent cohorts: Dementia Disease Initiation (DDI) ( n  = 346) and Amsterdam Dementia Cohort (n =  397 ), both with cognitive assessments up to 10 years. We used linear regression to compare synapse marker differences between CSF-determined Aβ + cognitively normal (CN) and Mild Cognitive Impairment (MCI) groups, with or without CSF tau pathology (Tau+/-), relative to CN Aβ-/Tau- controls; and associations between synapse markers and medial temporal lobe (MTL) MRI volumetrics in the DDI cohort and with verbal memory in both cohorts. A funneling procedure identified proteins related to Aβ/Tau pathology and memory impairment in both cohorts, which were used to evaluate relations to Aβ/Tau biological progression in the DDI cohort and memory decline in both cohorts. Finally, we explored genetic pathways associated with these synaptic proteins. Results In both cohorts, most markers were elevated in Aβ+/Tau + cases compared to controls, particularly 14-3-3ζ/δ. Several proteins were reduced in Aβ+/Tau- cases, especially NPTX-2, while 14-3-3ζ/δ remained elevated. However, the increase in e.g. 14-3-3ζ/δ and reduction in e.g. NPTX2 were more pronounced in patients with MCI than CN cases regardless of tau-pathology, corresponding to verbal memory impairment and MTL atrophy. Elevated baseline 14-3-3ζ/δ and rab GDP Dissociation Inhibitor Alpha (GDI-1) associated with future progression from Aβ+/Tau- to Aβ+/Tau+. Significant associations (all p  < 0.001) were found between 14-3-3 protein genes ( YWHAZ , YWHAE ) and pathways linked to AD, including the p38 MAPK, IGF, PIK3/AKT and between GDI1 and p38 MAPK upstream pathway ( p  < 0.05) all connected to synaptic plasticity. Correspondingly, a robust 14-3-3ζ/δ association with future memory decline was observed in both cohorts. Conclusions Reduced markers for excitatory signaling in Aβ+/Tau- and increased synaptic plasticity markers in Aβ+/Tau + cases suggest differential but linked processes underlying disease progression and resilience in the groups.

• Padrela, Beatriz E.; Teceläo, Sandra Raquel Ramos; Kirsebom, Bjørn-Eivind; Geier, Oliver Marcel; Tranfa, Mario & Masserini, Federico [Vis alle 22 forfattere av denne artikkelen] (2025). Blood-brain barrier water exchange in relation to amyloid, cognition and cerebrovascular burden. NeuroImage: Clinical. 49. doi: 10.1016/j.nicl.2025.103926. Fulltekst i vitenarkiv Vis sammendrag

  Blood-brain barrier (BBB) water exchange may serve as a sensitive early biomarker for Alzheimer’s disease and age-related cognitive decline. This study applied a non-invasive multi-echo arterial spin labeling (ASL) technique to measure BBB water exchange time (Tex), cerebral blood flow (CBF), and arterial transit time (ATT) in 160 adults aged 50 years and older. Participants were classified as cognitively normal (CN), having subjective cognitive decline (SCD), or mild cognitive impairment (MCI). They were assessed for amyloid status and cerebrovascular burden. Compared to CN participants, Tex was significantly lower in both SCD (−9.5 %) and MCI (−14.5 %) groups, suggesting that reductions in BBB water exchange emerge early in the course of cognitive decline. In contrast, CBF was reduced only in MCI participants (−20.8 % compared to CN), and ATT was significantly increased only in individuals with severe cerebrovascular burden (Fazekas score 3). Notably, Tex showed a stepwise decrease with increasing Fazekas scores (1–2), supporting its sensitivity to moderate small vessel disease. No associations were found between Tex and amyloid positivity after adjusting for age and sex. These findings indicate that Tex alterations may precede changes in traditional perfusion markers and are more closely related to vascular and early cognitive changes than to amyloid pathology. BBB water exchange mapping may therefore provide a promising, non-invasive tool to detect early neurovascular dysfunction that contributes to cognitive decline in aging populations, potentially offering a useful biomarker for early intervention trials targeting vascular contributions to dementia.

• Skattør, Thor Håkon; Bjørnerud, Atle; Nome, Terje; Bakke, Kine Mari; Enriquez, Brian Anthony & Digernes, Ingrid [Vis alle 10 forfattere av denne artikkelen] (2025). Predicting lesion reversal in acute cerebral ischaemia via apparent diffusion coefficient threshold on diffusion-weighted MRI. European Radiology. ISSN 0938-7994. s. 1–11. doi: 10.1007/s00330-025-12014-0. Fulltekst i vitenarkiv Vis sammendrag

  Objectives Diffusion-weighted imaging (DWI) quickly detects early ischaemic changes, but does not necessarily signify irreversible tissue damage, as DWI lesion reversal (DWI-R) can occur. Apparent diffusion coefficient (ADC) thresholds have been proposed to distinguish salvageable from irreversibly damaged tissue. This study aimed to evaluate the predictive value of a single ADC threshold for DWI-R following rapid and successful recanalization with voxel-level methodology. Materials and methods In this cohort study, we retrospectively analysed consecutive patients examined with DWI before and the day after endovascular therapy, with successful recanalization within 120 min of baseline MRI. DWI-R was assessed voxel-wise for ADC values between 200 mm2/s and 760 × 10−6 mm2/s. Predictive accuracy of ADC thresholds was evaluated using receiver operating characteristic (ROC) analyses. Results Seventy-one patients with a mean baseline DWI lesion volume of 18.13 mL (IQR: 6.15, 26.25) were included. Median time from MRI to recanalization was 84.0 min (IQR: 72.0, 95.5). On average, 37.5% of voxels demonstrated reversal. The area under the curve for predicting reversal based on ADC was 0.708, and the optimal threshold was 555 × 10–6 mm2/s (sensitivity 73.8%, specificity 58.6%). The voxel-wise probability of reversal declined with lower ADC, but even low ADC values exhibited some degree of reversal. Conclusion This study reinforces existing concerns about using fixed ADC thresholds to define irreversible injury. A single ADC cut-off showed only modest sensitivity and poor specificity for predicting DWI-R. No definitive lower ADC boundary was identified across clinically relevant ranges below which the likelihood of DWI-R became negligible.

• Skattør, Thor Håkon; Offersen, Cecilie Mørck; Nome, Terje; Bakke, Kine Mari; Enriquez, Brian Anthony & Carlsen, Jonathan Frederik [Vis alle 9 forfattere av denne artikkelen] (2025). Mapping DWI signal reversal and long-term tissue outcomes following endovascular therapy in acute ischemic stroke. European Radiology. ISSN 0938-7994. s. 1–12. doi: 10.1007/s00330-025-11943-0. Fulltekst i vitenarkiv Vis sammendrag

  Objectives Diffusion-weighted imaging lesion reversal (DWI-R) is commonly observed on MRI after treatment for acute ischemic stroke. However, its extent across different brain regions post-endovascular therapy (EVT) and its long-term tissue-specific consequences are inadequately described in the literature. This study evaluated DWI-R across brain regions and tissue types and assessed long-term changes after 1 month. Materials and methods This cohort study included acute ischemic stroke patients with MRI acquired before and 12 to 36 h after EVT. DWI lesions were segmented and co-registered to MNI space to generate probabilistic maps of DWI-R distribution. The probability of DWI-R was analyzed in relation to the involvement of white matter, cortical regions, and deep gray matter. Changes indicative of tissue damage were evaluated in a subgroup with follow-up imaging > 1 month post-EVT. Results Of 565 consecutive EVT patients in the period January 2017-March 2022, 303 were included. DWI-R was observed in all major vascular territories. White matter showed 1.95 times higher probability of DWI-R compared to deep gray matter (p < 0.001), with no significant difference compared to cortical regions. Among 62 DWI-R cases with follow-up imaging, 29 (47%) showed no signal changes in areas of the initial lesion, with no significant difference between white and gray matter. Conclusions Caution is advised when excluding patients from EVT based on restrictive diffusion, as both white and gray matter frequently responded to treatment in this study.

• Tungesvik, Helene Melsom; Padrela, Beatriz; Groote, Inge Rasmus; Bjørnerud, Atle; Geier, Oliver Marcel & Hisdal, Jonny [Vis alle 8 forfattere av denne artikkelen] (2025). Imaging cerebral circulation in long-term anabolic-androgenic steroid users and non-using weightlifters. Drug and Alcohol Dependence. ISSN 0376-8716. 275, s. 112829–112829. doi: 10.1016/j.drugalcdep.2025.112829. Fulltekst i vitenarkiv Vis sammendrag

  Background: Anabolic-androgenic steroids (AAS) are commonly used by recreational weightlifters for performance enhancement, despite associated health risks, including cardiovascular and brain effects. This study investigates the cerebrovascular effects of prolonged AAS use in male weightlifters, focusing on cerebral blood flow (CBF) and other indicators of cerebrovascular health. Methods: Eighty-six males were included, with 41 current consumers of AAS and 45 non-using weightlifting controls. Cerebrovascular health was evaluated using magnetic resonance imaging (MRI) pseudo-continuous arterial spin labeling (PCASL) derivatives to measure CBF and spatial coefficient of variation (sCoV) of CBF in gray matter. Additionally, MRI T2-weighted fluid-attenuated inversion recovery (FLAIR) sequences were used to analyze white matter hyperintensities as a marker of small-vessel disease. Results: AAS consumers had significantly higher sCoV than weightlifting controls (p = 0.001). Further, sCoV in total gray matter correlated with testosterone/epitestosterone ratio and total years of AAS use. No significant differences were found in CBF or white matter hyperintensity volume. Conclusion: These findings indicate that long-term AAS use may impact cerebrovascular health, evidenced by increased sCoV. Although cerebral perfusion was unaffected, elevated sCoV suggest that AAS use may pose a risk for cerebrovascular pathology later in life. Keywords: Anabolic androgenic steroids; Arterial spin labeling (ASL) perfusion MRI; Cerebral blood flow; Spatial coefficient of variation; Substance misuse.

• Ottesen, Jon André; Storås, Tryggve Holck; Vatnehol, Svein Are Sirirud; Løvland, Grethe; Vik-Mo, Einar Osland & Schellhorn, Till [Vis alle 11 forfattere av denne artikkelen] (2025). Deep learning-based Intraoperative MRI reconstruction. European Radiology Experimental. 9(1). doi: 10.1186/s41747-024-00548-9. Fulltekst i vitenarkiv Vis sammendrag

  Background We retrospectively evaluated the quality of deep learning (DL) reconstructions of on-scanner accelerated intraoperative MRI (iMRI) during respective brain tumor surgery. Methods Accelerated iMRI was performed using dual surface coils positioned around the area of resection. A DL model was trained on the fastMRI neuro dataset to mimic the data from the iMRI protocol. The evaluation was performed on imaging material from 40 patients imaged from Nov 1, 2021, to June 1, 2023, who underwent iMRI during tumor resection surgery. A comparative analysis was conducted between the conventional compressed sense (CS) method and the trained DL reconstruction method. Blinded evaluation of multiple image quality metrics was performed by two neuroradiologists and one neurosurgeon using a 1-to-5 Likert scale (1, nondiagnostic; 2, poor; 3, acceptable; 4, good; and 5, excellent), and the favored reconstruction variant. Results The DL reconstruction was strongly favored or favored over the CS reconstruction for 33/40, 39/40, and 8/40 of cases for readers 1, 2, and 3, respectively. For the evaluation metrics, the DL reconstructions had a higher score than their respective CS counterparts for 72%, 72%, and 14% of the cases for readers 1, 2, and 3, respectively. Still, the DL reconstructions exhibited shortcomings such as a striping artifact and reduced signal. Conclusion DL shows promise in allowing for high-quality reconstructions of iMRI. The neuroradiologists noted an improvement in the perceived spatial resolution, signal-to-noise ratio, diagnostic confidence, diagnostic conspicuity, and spatial resolution compared to CS, while the neurosurgeon preferred the CS reconstructions across all metrics. Relevance statement DL shows promise to allow for high-quality reconstructions of iMRI, however, due to the challenging setting of iMRI, further optimization is needed. Key Points iMRI is a surgical tool with a challenging image setting. DL allowed for high-quality reconstructions of iMRI. Additional optimization is needed due to the challenging intraoperative setting. Graphical Abstract

• Martiniussen, Marit Almenning; Larsen, Marthe; Hovda, Tone; SANDHAUG, MERETE; Dahl, Fredrik Andreas & Eikvil, Line [Vis alle 11 forfattere av denne artikkelen] (2025). Performance of Two Deep Learning–based AI Models for Breast Cancer Detection and Localization on Screening Mammograms from BreastScreen Norway. Radiology: Artificial Intelligence (RAI). 7(3). doi: 10.1148/ryai.240039. Fulltekst i vitenarkiv Vis sammendrag

  Two deep learning–based artificial intelligence (AI) models, one commercially available and one in-house, showed good performance for stand-alone cancer detection on retrospective mammography screening data. AI markings on the mammograms corresponded well to the true cancer location. Purpose - To evaluate cancer detection and marker placement accuracy of two artificial intelligence (AI) models developed for interpretation of screening mammograms. Materials and Methods - This retrospective study included data from 129 434 screening examinations (all female patients; mean age, 59.2 years ± 5.8 [SD]) performed between January 2008 and December 2018 in BreastScreen Norway. Model A was commercially available and model B was an in-house model. Area under the receiver operating characteristic curve (AUC) with 95% CIs were calculated. The study defined 3.2% and 11.1% of the examinations with the highest AI scores as positive, threshold 1 and 2, respectively. A radiologic review assessed location of AI markings and classified interval cancers as true or false negative. Results - The AUC value was 0.93 (95% CI: 0.92, 0.94) for model A and B when including screen-detected and interval cancers. Model A identified 82.5% (611 of 741) of the screen-detected cancers at threshold 1 and 92.4% (685 of 741) at threshold 2. Model B identified 81.8% (606 of 741) at threshold 1 and 93.7% (694 of 741) at threshold 2. The AI markings were correctly localized for all screen-detected cancers identified by both models and 82% (56 of 68) of the interval cancers for model A and 79% (54 of 68) for model B. At the review, 21.6% (45 of 208) of the interval cancers were identified at the preceding screening by either or both models, correctly localized and classified as false negative (n = 17) or with minimal signs of malignancy (n = 28). Conclusion - Both AI models showed promising performance for cancer detection on screening mammograms. The AI markings corresponded well to the true cancer locations.

• Høgestøl, Einar August; Rinker, Daniel Allen; Maximov, Ivan; Sowa, Piotr; Celius, Elisabeth Gulowsen & Hope, Tuva Roaldsdatter [Vis alle 26 forfattere av denne artikkelen] (2025). A cross-sectional multicentre study of multishell diffusion MRI in multiple sclerosis. Multiple Sclerosis and Related Disorders. ISSN 2211-0348. 98. doi: 10.1016/j.msard.2025.106435. Fulltekst i vitenarkiv Vis sammendrag

  Background and objectives White matter (WM) microstructural properties from advanced multishell diffusion MRI (dMRI) have been linked to clinical disability in multiple sclerosis (MS). This multicentre study used multishell dMRI to compute WM metrics and test for differences between people with MS (pwMS) and healthy controls (HCs). Methods We included multishell dMRI data from 251 pwMS or clinically isolated syndrome (CIS) (mean age 40.7 years, 72.4 % women, 88.8 % relapsing remitting MS) at six MAGNIMS centres and 543 HCs. Eleven scalar metric maps were estimated from multishell dMRI sequences, based on diffusion tensor imaging (DTI) and restriction spectrum imaging (RSI). The maps were analysed using tract-based spatial statistics (TBSS). The diffusion output was submitted to paired sampled t-tests to test for case-control differences and linear regression models to test for associations with Expanded Disability Status Scale (EDSS) scores, while accounting for confounders. In a sub-sample from Oslo, we tested for correlations between EDSS and dMRI metrics within WM lesions. Results Significant group differences were found in nine out of eleven dMRI metrics. Linear regression models revealed significant correlations between EDSS and fractional anisotropy (FA) fast (β=-4.54, p = 0.01) and apparent diffusion coefficient (ADC) fast (β=10.92, p = 8.7 × 10−3). Conclusions Diffusion MRI based on clinically feasible multishell sequences uncovers WM group differences between pwMS and HCs, but only a selection of the advanced multishell parameters were sensitive to disability, and no statistically significant correlations with disability remained after Bonferroni correction.

• Ottesen, Jon André; Tong, Elizabeth; Emblem, Kyrre Eeg; Latysheva, Anna; Zaharchuk, Greg & Bjørnerud, Atle [Vis alle 7 forfattere av denne artikkelen] (2025). Semi-Supervised Learning Allows for Improved Segmentation With Reduced Annotations of Brain Metastases Using Multicenter MRI Data. Journal of Magnetic Resonance Imaging. ISSN 1053-1807. 61(6), s. 2469–2479. doi: 10.1002/jmri.29686. Fulltekst i vitenarkiv Vis sammendrag

  Background Deep learning-based segmentation of brain metastases relies on large amounts of fully annotated data by domain experts. Semi-supervised learning offers potential efficient methods to improve model performance without excessive annotation burden. Purpose This work tests the viability of semi-supervision for brain metastases segmentation. Study Type Retrospective. Subjects There were 156, 65, 324, and 200 labeled scans from four institutions and 519 unlabeled scans from a single institution. All subjects included in the study had diagnosed with brain metastases. Field Strength/Sequences 1.5 T and 3 T, 2D and 3D T1-weighted pre- and post-contrast, and fluid-attenuated inversion recovery (FLAIR). Assessment Three semi-supervision methods (mean teacher, cross-pseudo supervision, and interpolation consistency training) were adapted with the U-Net architecture. The three semi-supervised methods were compared to their respective supervised baseline on the full and half-sized training. Statistical Tests Evaluation was performed on a multinational test set from four different institutions using 5-fold cross-validation. Method performance was evaluated by the following: the number of false-positive predictions, the number of true positive predictions, the 95th Hausdorff distance, and the Dice similarity coefficient (DSC). Significance was tested using a paired samples t test for a single fold, and across all folds within a given cohort. Results Semi-supervision outperformed the supervised baseline for all sites with the best-performing semi-supervised method achieved an on average DSC improvement of 6.3% ± 1.6%, 8.2% ± 3.8%, 8.6% ± 2.6%, and 15.4% ± 1.4%, when trained on half the dataset and 3.6% ± 0.7%, 2.0% ± 1.5%, 1.8% ± 5.7%, and 4.7% ± 1.7%, compared to the supervised baseline on four test cohorts. In addition, in three of four datasets, the semi-supervised training produced equal or better results than the supervised models trained on twice the labeled data. Data Conclusion Semi-supervised learning allows for improved segmentation performance over the supervised baseline, and the improvement was particularly notable for independent external test sets when trained on small amounts of labeled data. Plain Language Summary Artificial intelligence requires extensive datasets with large amounts of annotated data from medical experts which can be difficult to acquire due to the large workload. To compensate for this, it is possible to utilize large amounts of un-annotated clinical data in addition to annotated data. However, this method has not been widely tested for the most common intracranial brain tumor, brain metastases. This study shows that this approach allows for data efficient deep learning models across multiple institutions with different clinical protocols and scanners. Level of Evidence 3 Technical Efficacy Stage 2

• Liu, Qinghui; Fuster-Garcia, Elies; Hovden, Ivar Thokle; MacIntosh, Bradley; Grødem, Edvard Olaf Sætersdal & Brandal, Petter [Vis alle 12 forfattere av denne artikkelen] (2025). Treatment-aware Diffusion Probabilistic Model for Longitudinal MRI Generation and Diffuse Glioma Growth Prediction. IEEE Transactions on Medical Imaging. ISSN 0278-0062. 44(6). doi: 10.1109/TMI.2025.3533038. Fulltekst i vitenarkiv
• Bao, Rina; Weiss, Rebecca J.; Bates, Sara V.; Song, Ya'nan; He, Sheng & Li, Jingpeng [Vis alle 10 forfattere av denne artikkelen] (2025). PARADISE: Personalized and regional adaptation for HIE disease identification and segmentation. Medical Image Analysis. ISSN 1361-8415. 102, s. 1–13. doi: 10.1016/j.media.2024.103419. Fulltekst i vitenarkiv
• Ghazi, Mostafa Mehdipour; Selnes, Per; Reina, Santiago Timon; Teceläo, Sandra Raquel Ramos; Ingala, Silvia & Bjørnerud, Atle [Vis alle 9 forfattere av denne artikkelen] (2024). Comparative analysis of multimodal biomarkers for amyloid-beta positivity detection in Alzheimer's disease cohorts. Frontiers in Aging Neuroscience. 16. doi: 10.3389/fnagi.2024.1345417. Fulltekst i vitenarkiv Vis sammendrag

  Introduction: Efforts to develop cost-effective approaches for detecting amyloid pathology in Alzheimer’s disease (AD) have gained significant momentum with a focus on biomarker classification. Recent research has explored non-invasive and readily accessible biomarkers, including magnetic resonance imaging (MRI) biomarkers and some AD risk factors.<p> <p>Methods: In this comprehensive study, we leveraged a diverse dataset, encompassing participants with varying cognitive statuses from multiple sources, including cohorts from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and our in-house Dementia Disease Initiation (DDI) cohort. As brain amyloid plaques have been proposed as sufficient for AD diagnosis, our primary aim was to assess the effectiveness of multimodal biomarkers in identifying amyloid plaques, using deep machine learning methodologies. <p>Results: Our findings underscore the robustness of the utilized methods in detecting amyloid beta positivity across multiple cohorts. Additionally, we investigated the potential of demographic data to enhance MRI-based amyloid detection. Notably, the inclusion of demographic risk factors significantly improved our models’ ability to detect amyloid-beta positivity, particularly in early-stage cases, exemplified by an average area under the ROC curve of 0.836 in the unimpaired DDI cohort. <p>Discussion: These promising, non-invasive, and cost-effective predictors of MRI biomarkers and demographic variables hold the potential for further refinement through considerations like APOE genotype and plasma markers.

• Prysiazhniuk, Yeva; Server, Andrés; Leske, Henning; Gadmar, Øystein Bech; Helseth, Eirik & Eijgelaar, Roelant Sjouke [Vis alle 12 forfattere av denne artikkelen] (2024). Diffuse glioma molecular profiling with arterial spin labeling and dynamic susceptibility contrast perfusion MRI: A comparative study. Neuro-Oncology Advances (NOA). 6(1). doi: 10.1093/noajnl/vdae113. Fulltekst i vitenarkiv Vis sammendrag

  Background Evaluation of molecular markers (IDH, pTERT, 1p/19q codeletion, and MGMT) in adult diffuse gliomas is crucial for accurate diagnosis and optimal treatment planning. Dynamic Susceptibility Contrast (DSC) and Arterial Spin Labeling (ASL) perfusion MRI techniques have both shown good performance in classifying molecular markers, however, their performance has not been compared side-by-side. Methods Pretreatment MRI data from 90 patients diagnosed with diffuse glioma (54 men/36 female, 53.1 ± 15.5 years, grades 2–4) were retrospectively analyzed. DSC-derived normalized cerebral blood flow/volume (nCBF/nCBV) and ASL-derived nCBF in tumor and perifocal edema were analyzed in patients with available IDH-mutation (n = 67), pTERT-mutation (n = 39), 1p/19q codeletion (n = 33), and MGMT promoter methylation (n = 31) status. Cross-validated uni- and multivariate logistic regression models assessed perfusion parameters’ performance in molecular marker detection. Results ASL and DSC perfusion parameters in tumor and edema distinguished IDH-wildtype (wt) and pTERT-wt tumors from mutated ones. Univariate classification performance was comparable for ASL-nCBF and DSC-nCBV in IDH (maximum AUROCC 0.82 and 0.83, respectively) and pTERT (maximum AUROCC 0.70 and 0.81, respectively) status differentiation. The multivariate approach improved IDH (DSC-nCBV AUROCC 0.89) and pTERT (ASL-nCBF AUROCC 0.8 and DSC-nCBV AUROCC 0.86) classification. However, ASL and DSC parameters could not differentiate 1p/19q codeletion or MGMT promoter methylation status. Positive correlations were found between ASL-nCBF and DSC-nCBV/-nCBF in tumor and edema. Conclusions ASL is a viable gadolinium-free replacement for DSC for molecular characterization of adult diffuse gliomas.

• Fernandez, Lidia Luque; Skogen, Karoline; MacIntosh, Bradley; Emblem, Kyrre E; Larsson, Christopher & Bouget, David Nicolas Jean-Marie [Vis alle 14 forfattere av denne artikkelen] (2024). Standardized evaluation of the extent of resection in glioblastoma with automated early post-operative segmentation. Frontiers in Radiology. 4. doi: 10.3389/fradi.2024.1357341. Fulltekst i vitenarkiv Vis sammendrag

  Standard treatment of patients with glioblastoma includes surgical resection of the tumor. The extent of resection (EOR) achieved during surgery significantly impacts prognosis and is used to stratify patients in clinical trials. In this study, we developed a U-Net-based deep-learning model to segment contrast-enhancing tumor on post-operative MRI exams taken within 72 h of resection surgery and used these segmentations to classify the EOR as either maximal or submaximal. The model was trained on 122 multiparametric MRI scans from our institution and achieved a mean Dice score of 0.52 ± 0.03 on an external dataset (n = 248), a performance ­on par with the interrater agreement between expert annotators as reported in literature. We obtained an EOR classification precision/recall of 0.72/0.78 on the internal test dataset (n = 462) and 0.90/0.87 on the external dataset. Furthermore, Kaplan-Meier curves were used to compare the overall survival between patients with maximal and submaximal resection in the internal test dataset, as determined by either clinicians or the model. There was no significant difference between the survival predictions using the model's and clinical EOR classification. We find that the proposed segmentation model is capable of reliably classifying the EOR of glioblastoma tumors on early post-operative MRI scans. Moreover, we show that stratification of patients based on the model's predictions offers at least the same prognostic value as when done by clinicians.

• Grødem, Edvard Olaf Sætersdal; Leonardsen, Esten Høyland; MacIntosh, Bradley; Bjørnerud, Atle; SCHELLHORN, TILL & Sørensen, Øystein [Vis alle 8 forfattere av denne artikkelen] (2024). A minimalistic approach to classifying Alzheimer's disease using simple and extremely small convolutional neural networks. Journal of Neuroscience Methods. ISSN 0165-0270. 411. doi: 10.1016/j.jneumeth.2024.110253. Fulltekst i vitenarkiv
• Gómez-Valadés, Alba; Martínez-Tomás, Rafael; García-Herranz, Sara; Bjørnerud, Atle & Rincón, Mariano (2024). Early detection of mild cognitive impairment through neuropsychological tests in population screenings: a decision support system integrating ontologies and machine learning. Frontiers in Neuroinformatics. 18, s. 1–15. doi: 10.3389/fninf.2024.1378281. Fulltekst i vitenarkiv
• Gonzalez-Ortiz, Fernando; Kirsebom, Bjørn-Eivind Seljelid; Contador, José; Tanley, Jordan E.; Selnes, Per & Gisladottir, Berglind [Vis alle 33 forfattere av denne artikkelen] (2024). Plasma brain-derived tau is an amyloid-associated neurodegeneration biomarker in Alzheimer’s disease. Nature Communications. 15(1). doi: 10.1038/s41467-024-47286-5. Fulltekst i vitenarkiv Vis sammendrag

  Staging amyloid-beta (Aβ) pathophysiology according to the intensity of neurodegeneration could identify individuals at risk for cognitive decline in Alzheimer’s disease (AD). In blood, phosphorylated tau (p-tau) associates with Aβ pathophysiology but an AD-type neurodegeneration biomarker has been lacking. In this multicenter study (n = 1076), we show that brain-derived tau (BD-tau) in blood increases according to concomitant Aβ (“A”) and neurodegeneration (“N”) abnormalities (determined using cerebrospinal fluid biomarkers); We used blood-based A/N biomarkers to profile the participants in this study; individuals with blood-based p-tau+/BD-tau+ profiles had the fastest cognitive decline and atrophy rates, irrespective of the baseline cognitive status. Furthermore, BD-tau showed no or much weaker correlations with age, renal function, other comorbidities/risk factors and self-identified race/ethnicity, compared with other blood biomarkers. Here we show that blood-based BD-tau is a biomarker for identifying Aβ-positive individuals at risk of short-term cognitive decline and atrophy, with implications for clinical trials and implementation of anti-Aβ therapies.

• Poirot, Maarten G.; Ruhe, Henricus G.; Mutsaerts, Henk J. M. M.; Maximov, Ivan; Groote, Inge Rasmus & Bjørnerud, Atle [Vis alle 9 forfattere av denne artikkelen] (2024). Treatment Response Prediction in Major Depressive Disorder Using Multimodal MRI and Clinical Data: Secondary Analysis of a Randomized Clinical Trial. American Journal of Psychiatry. ISSN 0002-953X. 181(3), s. 223–233. doi: 10.1176/appi.ajp.20230206. Fulltekst i vitenarkiv
• Lindland, Elisabeth S.; Røvang, Martin S.; Solheim, Anne Marit; Andreassen, Silje; Skarstein, Ingerid & Dareez, Nazeer [Vis alle 17 forfattere av denne artikkelen] (2024). Are white matter hyperintensities associated with neuroborreliosis? The answer is twofold. Neuroradiology. ISSN 0028-3940. 67, s. 37–48. doi: 10.1007/s00234-024-03482-0. Fulltekst i vitenarkiv Vis sammendrag

  Purpose Many consider white matter hyperintensities (WMHs) to be important imaging findings in neuroborreliosis. However, evidence regarding association with WMHs is of low quality. The objective was to investigate WMHs in neuroborreliosis visually and quantitatively. Materials and methods Patients underwent brain MRI within one month of diagnosis and six months after treatment. Healthy controls were recruited. WMHs were counted by visual rating and the volume was calculated from automatic segmentation. Biochemical markers and scores for clinical symptoms and findings were used to explore association with longitudinal volume change of WMHs. Results The study included 74 patients (37 males) with early neuroborreliosis and 65 controls (30 males). Mean age (standard deviation) was 57.4 (13.5) and 57.7 (12.9) years, respectively. Baseline WMH lesion count was zero in 14 patients/16 controls, < 10 in 36/31, 10–20 in 9/7 and > 20 in 13/11, with no difference between groups (p = 0.90). However, from baseline to follow-up the patients had a small reduction in WMH volume and the controls a small increase, median difference 0.136 (95% confidence interval 0.051–0.251) ml. In patients, volume change was not associated with biochemical or clinical markers, but with degree of WMHs (p values 0.002–0.01). Conclusion WMH lesions were not more numerous in patients with neuroborreliosis compared to healthy controls. However, there was a small reduction of WMH volume from baseline to follow-up among patients, which was associated with higher baseline WMH severity, but not with disease burden or outcome. Overall, non-specific WMHs should not be considered suggestive of neuroborreliosis.

• Martiniussen, Marit Almenning; Larsen, Marthe; Larsen, Anne Sofie Frøyshov; Hovda, Tone; Koch, Henrik Wethe & Bjørnerud, Atle [Vis alle 7 forfattere av denne artikkelen] (2023). Norwegian radiologists’ expectations of artificial intelligence in mammographic screening – A cross-sectional survey. European Journal of Radiology. ISSN 0720-048X. 167. doi: 10.1016/j.ejrad.2023.111061. Fulltekst i vitenarkiv Vis sammendrag

  Purpose: To explore Norwegian breast radiologists’ expectations of adding artificial intelligence (AI) in the interpretation procedure of screening mammograms.<p> <p>Methods: All breast radiologists involved in interpretation of screening mammograms in BreastScreen Norway during 2021 and 2022 (n = 98) were invited to take part in this anonymous cross-sectional survey about use of AI in mammographic screening. The questionnaire included background information of the respondents, their expectations, considerations of biases, and ethical and social implications of implementing AI in screen reading. Data was collected digitally and analyzed using descriptive statistics. <p>Results: The response rate was 61% (60/98), and 67% (40/60) of the respondents were women. Sixty percent (36/60) reported ≥10 years’ experience in screen reading, while 82% (49/60) reported no or limited experience with AI in health care. Eighty-two percent of the respondents were positive to explore AI in the interpretation procedure in mammographic screening. When used as decision support, 68% (41/60) expected AI to increase the radiologists’ sensitivity for cancer detection. As potential challenges, 55% (33/60) reported lack of trust in the AI system and 45% (27/60) reported discrepancy between radiologists and AI systems as possible challenges. The risk of automation bias was considered high among 47% (28/60). Reduced time spent reading mammograms was rated as a potential benefit by 70% (42/60). <p>Conclusion: The radiologists reported positive expectations of AI in the interpretation procedure of screening mammograms. Efforts to minimize the risk of automation bias and increase trust in the AI systems are important before and during future implementation of the tool.

• Ottesen, Jon André; Yi, Darvin; Tong, Elizabeth; Iv, Michael; Latysheva, Anna & Saxhaug, Cathrine [Vis alle 13 forfattere av denne artikkelen] (2023). 2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data. Frontiers in Neuroinformatics. 16, s. 1–12. doi: 10.3389/fninf.2022.1056068. Fulltekst i vitenarkiv Vis sammendrag

  Introduction: Management of patients with brain metastases is often based on manual lesion detection and segmentation by an expert reader. This is a time- and labor-intensive process, and to that end, this work proposes an end-to-end deep learning segmentation network for a varying number of available MRI available sequences. Methods: We adapt and evaluate a 2.5D and a 3D convolution neural network trained and tested on a retrospective multinational study from two independent centers, in addition, nnU-Net was adapted as a comparative benchmark. Segmentation and detection performance was evaluated by: (1) the dice similarity coefficient, (2) a per-metastases and the average detection sensitivity, and (3) the number of false positives. Results: The 2.5D and 3D models achieved similar results, albeit the 2.5D model had better detection rate, whereas the 3D model had fewer false positive predictions, and nnU-Net had fewest false positives, but with the lowest detection rate. On MRI data from center 1, the 2.5D, 3D, and nnU-Net detected 79%, 71%, and 65% of all metastases; had an average per patient sensitivity of 0.88, 0.84, and 0.76; and had on average 6.2, 3.2, and 1.7 false positive predictions per patient, respectively. For center 2, the 2.5D, 3D, and nnU-Net detected 88%, 86%, and 78% of all metastases; had an average per patient sensitivity of 0.92, 0.91, and 0.85; and had on average 1.0, 0.4, and 0.1 false positive predictions per patient, respectively. Discussion/Conclusion: Our results show that deep learning can yield highly accurate segmentations of brain metastases with few false positives in multinational data, but the accuracy degrades for metastases with an area smaller than 0.4 cm2.

• Bakke, Kine Mari; Meltzer, Sebastian; Grøvik, Endre; Negård, Anne; Holmedal, Stein Harald & Mikalsen, Lars Tore Gyland [Vis alle 13 forfattere av denne artikkelen] (2023). Imaging the tumour microenvironment in rectal cancer: Decline in tumour blood flow during radiotherapy predicts good outcome. Physics and imaging in radiation oncology (PIRO). 25, s. 1–7. doi: 10.1016/j.phro.2023.100417. Fulltekst i vitenarkiv Vis sammendrag

  Background and purpose Measuring rectal tumour response to radiation is pivotal to restaging patients and for possibly stratification to a watch-and-wait strategy. Recognizing the importance of the tumour microenvironment, we investigated a less explored quantitative imaging marker assessing tumour blood flow (BF) for its potential to predict overall survival (OS). Materials and methods 24 rectal cancer patients given curative-intent neoadjuvant radiotherapy underwent a multi-echo dynamic magnetic resonance imaging (MRI) sequence with gadolinium contrast for quantification of tumour BF before either 25x2 Gy (n = 18) with concomitant chemotherapy or 5x5 Gy (n = 6). CD34 staining of excised tumour tissue was performed and baseline blood samples were analysed for lactate dehydrogenase (LDH) and angiopoietin-2 (ANGPT-2). Tumour volumes were measured before and after treatment. After subsequent surgery, ypTN scoring assessed tumour response. Cox regression for 5-year OS analysis and t-test for group comparisons were performed. Results The change in tumour BF (ΔBF) during neoadjuvant radiotherapy was a significant marker of OS, whereas tumour stage and volume were not related to OS. All patients with >20 % decline in BF were long-term survivors. Separating cases in two groups based on ΔBF revealed that patients with increase or a low decrease had higher baseline LDH (p = 0.032) and ANGPT-2 (p = 0.028) levels. Conclusion MRI-assessed tumour ΔBF during neoadjuvant treatment is a significant predictor of OS in rectal cancer patients, making ΔBF a potential quantitative imaging biomarker for treatment stratification. Blood LDH and ANGPT-2 indicate that non-responding tumours may have a hypoxic microenvironment resistant to radiotherapy.

• Røvang, Martin Soria; Selnes, Per; MacIntosh, Bradley; Groote, Inge Rasmus; Pålhaugen, Lene & Sudre, Carole H [Vis alle 8 forfattere av denne artikkelen] (2023). Segmenting white matter hyperintensities on isotropic three-dimensional Fluid Attenuated Inversion Recovery magnetic resonance images: Assessing deep learning tools on a Norwegian imaging database. PLOS ONE. 18(8). doi: 10.1371/journal.pone.0285683. Fulltekst i vitenarkiv Vis sammendrag

  An important step in the analysis of magnetic resonance imaging (MRI) data for neuroimaging is the automated segmentation of white matter hyperintensities (WMHs). Fluid Attenuated Inversion Recovery (FLAIR-weighted) is an MRI contrast that is particularly useful to visualize and quantify WMHs, a hallmark of cerebral small vessel disease and Alzheimer’s disease (AD). In order to achieve high spatial resolution in each of the three voxel dimensions, clinical MRI protocols are evolving to a three-dimensional (3D) FLAIR-weighted acquisition. The current study details the deployment of deep learning tools to enable automated WMH segmentation and characterization from 3D FLAIR-weighted images acquired as part of a national AD imaging initiative. Based on data from the ongoing Norwegian Disease Dementia Initiation (DDI) multicenter study, two 3D models—one off-the-shelf from the NVIDIA nnU-Net framework and the other internally developed—were trained, validated, and tested. A third cutting-edge Deep Bayesian network model (HyperMapp3r) was implemented without any de-novo tuning to serve as a comparison architecture. The 2.5D in-house developed and 3D nnU-Net models were trained and validated in-house across five national collection sites among 441 participants from the DDI study, of whom 194 were men and whose average age was (64.91 +/- 9.32) years. Both an external dataset with 29 cases from a global collaborator and a held-out subset of the internal data from the 441 participants were used to test all three models. These test sets were evaluated independently. The ground truth human-in-the-loop segmentation was compared against five established WMH performance metrics. The 3D nnU-Net had the highest performance out of the three tested networks, outperforming both the internally developed 2.5D model and the SOTA Deep Bayesian network with an average dice similarity coefficient score of 0.76 +/- 0.16. Our findings demonstrate that WMH segmentation models can achieve high performance when trained exclusively on FLAIR input volumes that are 3D volumetric acquisitions. Single image input models are desirable for ease of deployment, as reflected in the current embedded clinical research project. The 3D nnU-Net had the highest performance, which suggests a way forward for our need to automate WMH segmentation while also evaluating performance metrics during on-going data collection and model retraining.

• Jarholm, Jonas Alexander; Bjørnerud, Atle; Dalaker, Turi Olene; Akhavi, Mehdi Sadat; Kirsebom, Bjørn-Eivind & Pålhaugen, Lene [Vis alle 14 forfattere av denne artikkelen] (2023). Medial Temporal Lobe Atrophy in Predementia Alzheimer's Disease: A Longitudinal Multi-Site Study Comparing Staging and A/T/N in a Clinical Research Cohort. Journal of Alzheimer's Disease. ISSN 1387-2877. 94(1), s. 259–279. doi: 10.3233/JAD-221274. Fulltekst i vitenarkiv Vis sammendrag

  Background: Atrophy of the medial temporal lobe (MTL) is a biological characteristic of Alzheimer’s disease (AD) and can be measured by segmentation of magnetic resonance images (MRI). Objective: To assess the clinical utility of automated volumetry in a cognitively well-defined and biomarker-classified multi-center longitudinal predementia cohort. Methods: We used Automatic Segmentation of Hippocampal Subfields (ASHS) to determine MTL morphometry from MRI. We harmonized scanner effects using the recently developed longitudinal ComBat. Subjects were classified according to the A/T/N system, and as normal controls (NC), subjective cognitive decline (SCD), or mild cognitive impairment (MCI). Positive or negative values of A, T, and N were determined by cerebrospinal fluid measurements of the Aβ42/40 ratio, phosphorylated and total tau. From 406 included subjects, longitudinal data was available for 206 subjects by stage, and 212 subjects by A/T/N. Results: Compared to A–/T–/N– at baseline, the entorhinal cortex, anterior and posterior hippocampus were smaller in A+/T+orN+. Compared to NC A– at baseline, these subregions were also smaller in MCI A+. Longitudinally, SCD A+ and MCI A+, and A+/T–/N– and A+/T+orN+, had significantly greater atrophy compared to controls in both anterior and posterior hippocampus. In the entorhinal and parahippocampal cortices, longitudinal atrophy was observed only in MCI A+ compared to NC A–, and in A+/T–/N– and A+/T+orN+ compared to A–/T–/N–. Conclusion: We found MTL neurodegeneration largely consistent with existing models, suggesting that harmonized MRI volumetry may be used under conditions that are common in clinical multi-center cohorts.

• Lindland, Elisabeth Margrete Stokke; Solheim, Anne Marit; Andreassen, Silje; Bugge, Robin Antony Birkeland; Eikeland, Randi & Reiso, Harald [Vis alle 10 forfattere av denne artikkelen] (2023). Dynamic contrast-enhanced MRI shows altered blood–brain barrier function of deep gray matter structures in neuroborreliosis: a case–control study. European Radiology Experimental. 7(1). doi: 10.1186/s41747-023-00365-6. Fulltekst i vitenarkiv Vis sammendrag

  Background Main aim was assessment of regional blood–brain barrier (BBB) function by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with neuroborreliosis. Secondary aim was to study the correlation of BBB function with biochemical, clinical, and cognitive parameters. Methods Regional ethical committee approved this prospective single-center case–control study. Within 1 month after diagnosis of neuroborreliosis, 55 patients underwent DCE-MRI. The patient group consisted of 25 males and 30 females with mean age 58 years, and the controls were 8 males and 7 females with mean age 57 years. Pharmacokinetic compartment modelling with Patlak fit was applied, providing estimates for capillary leakage rate and blood volume fraction. Nine anatomical brain regions were sampled with auto-generated binary masks. Fatigue, severity of clinical symptoms and findings, and cognitive function were assessed in the acute phase and 6 months after treatment. Results Leakage rates and blood volume fractions were lower in patients compared to controls in the thalamus (p = 0.027 and p = 0.018, respectively), caudate nucleus (p = 0.009 for both), and hippocampus (p = 0.054 and p = 0.009). No correlation of leakage rates with fatigue, clinical disease severity or cognitive function was found. Conclusions In neuroborreliosis, leakage rate and blood volume fraction in the thalamus, caudate nucleus, and hippocampus were lower in patients compared to controls. DCE-MRI provided new insight to pathophysiology of neuroborreliosis, and can serve as biomarker of BBB function and regulatory mechanisms of the neurovascular unit in infection and inflammation. Relevance statement DCE-MRI provided new insight to pathophysiology of neuroborreliosis, and can serve as biomarker of blood–brain barrier function and regulatory mechanisms of the neurovascular unit in infection and inflammation.

• MacIntosh, Bradley; Liu, Qinghui; SCHELLHORN, TILL; Beyer, Mona K.; Groote, Inge Rasmus & Morberg, Pål [Vis alle 20 forfattere av denne artikkelen] (2023). Radiological features of brain hemorrhage through automated segmentation from computed tomography in stroke and traumatic brain injury. Frontiers in Neurology. 14. doi: 10.3389/fneur.2023.1244672. Fulltekst i vitenarkiv Vis sammendrag

  Introduction Radiological assessment is necessary to diagnose spontaneous intracerebral hemorrhage (ICH) and traumatic brain injury intracranial hemorrhage (TBI-bleed). Artificial intelligence (AI) deep learning tools provide a means for decision support. This study evaluates the hemorrhage segmentations produced from three-dimensional deep learning AI model that was developed using non-contrast computed tomography (CT) imaging data external to the current study. Methods Non-contrast CT imaging data from 1263 patients were accessed across seven data sources (referred to as sites) in Norway and Sweden. Patients were included based on ICH, TBI-bleed, or mild TBI diagnosis. Initial non-contrast CT images were available for all participants. Hemorrhage location frequency maps were generated. The number of estimated haematoma clusters was correlated with the total haematoma volume. Ground truth expert annotations were available for one ICH site; hence, a comparison was made with the estimated haematoma volumes. Segmentation volume estimates were used in a receiver operator characteristics (ROC) analysis for all samples (i.e., bleed detected) and then specifically for one site with few TBI-bleed cases. Results The hemorrhage frequency maps showed spatial patterns of estimated lesions consistent with ICH or TBI-bleed presentations. There was a positive correlation between the estimated number of clusters and total haematoma volume for each site (correlation range: 0.45–0.74; each p -value &amp;lt; 0.01) and evidence of ICH between-site differences. Relative to hand-drawn annotations for one ICH site, the VIOLA-AI segmentation mask achieved a median Dice Similarity Coefficient of 0.82 (interquartile range: 0.78 and 0.83), resulting in a small overestimate in the haematoma volume by a median of 0.47 mL (interquartile range: 0.04 and 1.75 mL). The bleed detection ROC analysis for the whole sample gave a high area-under-the-curve (AUC) of 0.92 (with sensitivity and specificity of 83.28% and 95.41%); however, when considering only the mild head injury site, the TBI-bleed detection gave an AUC of 0.70. Discussion An open-source segmentation tool was used to visualize hemorrhage locations across multiple data sources and revealed quantitative hemorrhage site differences. The automated total hemorrhage volume estimate correlated with a per-participant hemorrhage cluster count. ROC results were moderate-to-high. The VIOLA-AI tool had promising results and might be useful for various types of intracranial hemorrhage.

• Ottesen, Jon André; Caan, Matthan; Groote, Inge Rasmus & Bjørnerud, Atle (2022). A densely interconnected network for deep learning accelerated MRI. Magnetic Resonance Materials in Physics, Biology and Medicine. ISSN 0968-5243. s. 1–13. doi: 10.1007/s10334-022-01041-3. Fulltekst i vitenarkiv Vis sammendrag

  To improve accelerated MRI reconstruction through a densely connected cascading deep learning reconstruction framework. Materials and methods A cascading deep learning reconstruction framework (reference model) was modified by applying three architectural modifications: input-level dense connections between cascade inputs and outputs, an improved deep learning sub-network, and long-range skip-connections between subsequent deep learning networks. An ablation study was performed, where five model configurations were trained on the NYU fastMRI neuro dataset with an end-to-end scheme conjunct on four- and eightfold acceleration. The trained models were evaluated by comparing their respective structural similarity index measure (SSIM), normalized mean square error (NMSE), and peak signal to noise ratio (PSNR). Results The proposed densely interconnected residual cascading network (DIRCN), utilizing all three suggested modifications achieved a SSIM improvement of 8% and 11%, a NMSE improvement of 14% and 23%, and a PSNR improvement of 2% and 3% for four- and eightfold acceleration, respectively. In an ablation study, the individual architectural modifications all contributed to this improvement for both acceleration factors, by improving the SSIM, NMSE, and PSNR with approximately 2–4%, 4–9%, and 0.5–1%, respectively. Conclusion The proposed architectural modifications allow for simple adjustments on an already existing cascading framework to further improve the resulting reconstructions.

• Voldsbekk, Irene; Bjørnerud, Atle; Groote, Inge Rasmus; Zak, Nathalia; Roelfs, Daniël & Maximov, Ivan [Vis alle 18 forfattere av denne artikkelen] (2022). Evidence for widespread alterations in cortical microstructure after 32 h of sleep deprivation. Translational Psychiatry. 12(161). doi: 10.1038/s41398-022-01909-x. Fulltekst i vitenarkiv Vis sammendrag

  Cortical microstructure is influenced by circadian rhythm and sleep deprivation, yet the precise underpinnings of these effects remain unclear. The ratio between T1-weighted and T2-weighted magnetic resonance images (T1w/T2w ratio) has been linked to myelin levels and dendrite density and may offer novel insight into the intracortical microstructure of the sleep deprived brain. Here, we examined intracortical T1w/T2w ratio in 41 healthy young adults (26 women) before and after 32 h of either sleep deprivation (n = 18) or a normal sleep-wake cycle (n = 23). Linear models revealed significant group differences in T1w/T2w ratio change after 32 h in four clusters, including bilateral effects in the insular, cingulate, and superior temporal cortices, comprising regions involved in attentional, auditory and pain processing. Across clusters, the sleep deprived group showed an increased T1w/T2w ratio, while the normal sleep-wake group exhibited a reduced ratio. These changes were not explained by in-scanner head movement, and 95% of the effects across clusters remained significant after adjusting for cortical thickness and hydration. Compared with a normal sleep-wake cycle, 32 h of sleep deprivation yields intracortical T1w/T2w ratio increases. While the intracortical changes detected by this study could reflect alterations in myelin or dendritic density, or both, histological analyses are needed to clarify the precise underlying cortical processes.

• Poirot, M. G.; Caan, Matthan W.A.; Ruhe, H.G.; Bjørnerud, Atle; Groote, Inge Rasmus & Reneman, L: [Vis alle 7 forfattere av denne artikkelen] (2022). Robustness of radiomics to variations in segmentation methods in multimodal brain MRI. Scientific Reports. 12(1), s. 1–10. doi: 10.1038/s41598-022-20703-9. Fulltekst i vitenarkiv Vis sammendrag

  Radiomics in neuroimaging uses fully automatic segmentation to delineate the anatomical areas for which radiomic features are computed. However, differences among these segmentation methods affect radiomic features to an unknown extent. A scan-rescan dataset (n = 46) of T1-weighted and diffusion tensor images was used. Subjects were split into a sleep-deprivation and a control group. Scans were segmented using four segmentation methods from which radiomic features were computed. First, we measured segmentation agreement using the Dice-coefficient. Second, robustness and reproducibility of radiomic features were measured using the intraclass correlation coefficient (ICC). Last, difference in predictive power was assessed using the Friedman-test on performance in a radiomics-based sleep deprivation classification application. Segmentation agreement was generally high (interquartile range = 0.77–0.90) and median feature robustness to segmentation method variation was higher (ICC > 0.7) than scan-rescan reproducibility (ICC 0.3–0.8). However, classification performance differed significantly among segmentation methods (p < 0.001) ranging from 77 to 84%. Accuracy was higher for more recent deep learning-based segmentation methods. Despite high agreement among segmentation methods, subtle differences significantly affected radiomic features and their predictive power. Consequently, the effect of differences in segmentation methods should be taken into account when designing and evaluating radiomics-based research methods.

• Fuster-Garcia, Elies; Hovden, Ivar Thokle; Svensson, Siri Fløgstad; Larsson, Christopher; Vardal, Jonas & Bjørnerud, Atle [Vis alle 7 forfattere av denne artikkelen] (2022). Quantification of Tissue Compression Identifies High-Grade Glioma Patients with Reduced Survival. Cancers. 14(7). doi: 10.3390/cancers14071725. Fulltekst i vitenarkiv
• Brandis, Elisabeth von; Jenssen, Håvard Bjørke; Avenarius, Derk Frederik Matthaus; Bjørnerud, Atle; Flatø, Berit & Tomterstad, Anders [Vis alle 11 forfattere av denne artikkelen] (2022). Automated segmentation of magnetic resonance bone marrow signal: a feasibility study. Pediatric Radiology. ISSN 0301-0449. 52, s. 1104–1114. doi: 10.1007/s00247-021-05270-x. Fulltekst i vitenarkiv Vis sammendrag

  Background - Manual assessment of bone marrow signal is time-consuming and requires meticulous standardisation to secure adequate precision of findings.<p> <p>Objective - We examined the feasibility of using deep learning for automated segmentation of bone marrow signal in children and adolescents.<p> <p>Materials and methods - We selected knee images from 95 whole-body MRI examinations of healthy individuals and of children with chronic non-bacterial osteomyelitis, ages 6–18 years, in a longitudinal prospective multi-centre study cohort. Bone marrow signal on T2-weighted Dixon water-only images was divided into three color-coded intensity-levels: 1 = slightly increased; 2 = mildly increased; 3 = moderately to highly increased, up to fluid-like signal. We trained a convolutional neural network on 85 examinations to perform bone marrow segmentation. Four readers manually segmented a test set of 10 examinations and calculated ground truth using simultaneous truth and performance level estimation (STAPLE). We evaluated model and rater performance through Dice similarity coefficient and in consensus.<p> <p>Results - Consensus score of model performance showed acceptable results for all but one examination. Model performance and reader agreement had highest scores for level-1 signal (median Dice 0.68) and lowest scores for level-3 signal (median Dice 0.40), particularly in examinations where this signal was sparse.<p> <p>Conclusion - It is feasible to develop a deep-learning-based model for automated segmentation of bone marrow signal in children and adolescents. Our model performed poorest for the highest signal intensity in examinations where this signal was sparse. Further improvement requires training on larger and more balanced datasets and validation against ground truth, which should be established by radiologists from several institutions in consensus.

• Kaiser, Antonia; Reneman, Liesbeth; Solleveld, Michelle M.; Coolen, Bram F.; Scherder, Erik J. A. & Knutsson, Linda [Vis alle 11 forfattere av denne artikkelen] (2022). A Randomized Controlled Trial on the Effects of a 12-Week High- vs. Low-Intensity Exercise Intervention on Hippocampal Structure and Function in Healthy, Young Adults. Frontiers in Psychiatry. 12. doi: 10.3389/fpsyt.2021.780095. Fulltekst i vitenarkiv Vis sammendrag

  Physical exercise affects hippocampal structure and function, but the underlying neural mechanisms and the effects of exercise intensity remain incompletely understood. Therefore, we undertook a comprehensive, multi-modal 3T and 7T MRI randomized controlled trial (Netherlands Trial Register - NL5847) in which we randomized 52 young, non-athletic volunteers to a 12-week low- or high-intensity exercise program. Using state-of-the-art methods, we investigated changes in hippocampal volume, as well as changes in vasculature, neuro-metabolites, and peripheral growth factors as potential underpinnings. Cardiorespiratory fitness improved over time ( p &amp;lt; 0.001), but no interaction with exercise intensity was found ( p = 0.48). Accordingly, we did not observe significant interactions between exercise condition and time on MRI measures (all p &amp;gt; 0.06). However, we found a significant decrease in right hippocampal volume ( p &amp;lt; 0.01), an increase in left hippocampal glutathione ( p &amp;lt; 0.01), and a decrease of left hippocampal cerebral blood volume ( p = 0.01) over time, regardless of exercise condition. Additional exploratory analyses showed that changes in brain-derived neurotrophic factor ( p = 0.01), insulin-like growth-factor ( p = 0.03), and dorsal anterior cingulate cortex N-acetyl-aspartate levels ( p = 0.01) were positively associated with cardiorespiratory fitness changes. Furthermore, a trend toward a positive association of fitness and gray-matter cerebral blood flow ( p = 0.06) was found. Our results do not provide evidence for differential effects between high-intensity (aerobic) and low-intensity (toning) exercise on hippocampal structure and function in young adults. However, we show small but significant effects of exercise on hippocampal volume, neurometabolism and vasculature across exercise conditions. Moreover, our exploratory results suggest that exercise might not specifically only benefit hippocampal structure and function, but rather has a more widespread effect. These findings suggest that, in agreement with previous MRI studies demonstrating moderate to strong effects in elderly and diseased populations, but none to only mild effects in young healthy cohorts, the benefits of exercise on the studied brain measures may be age-dependent and restorative rather than stimulatory. Our study highlights the importance of a multi-modal, whole-brain approach to assess macroscopic and microscopic changes underlying exercise-induced brain changes, to better understand the role of exercise as a potential non-pharmacological intervention.

• Kamkova, Yuliia; Pelanis, Egidijus; Bjørnerud, Atle; Edwin, Bjørn von Gohren; Elle, Ole Jakob & Kumar, Rahul Prasanna (2022). A Fast Method for Whole Liver-and Colorectal Liver Metastasis Segmentations from MRI Using 3D FCNN Networks. Applied Sciences. 12(10). doi: 10.3390/app12105145. Fulltekst i vitenarkiv
• Kleppestø, Magne; Bjørnerud, Atle; Groote, Inge Rasmus; Kim, Minjae; Vardal, Jonas & Larsson, Christopher (2021). Operator dependency of arterial input function in dynamic contrast-enhanced MRI. Magnetic Resonance Materials in Physics, Biology and Medicine. ISSN 0968-5243. doi: 10.1007/s10334-021-00926-z. Fulltekst i vitenarkiv Vis sammendrag

  Objective To investigate the effect of inter-operator variability in arterial input function (AIF) definition on kinetic parameter estimates (KPEs) from dynamic contrast-enhanced (DCE) MRI in patients with high-grade gliomas. Methods The study included 118 DCE series from 23 patients. AIFs were measured by three domain experts (DEs), and a population AIF (pop-AIF) was constructed from the measured AIFs. The DE-AIFs, pop-AIF and AUC-normalized DE-AIFs were used for pharmacokinetic analysis with the extended Tofts model. AIF-dependence of KPEs was assessed by intraclass correlation coefficient (ICC) analysis, and the impact on relative longitudinal change in Ktrans was assessed by Fleiss’ kappa (κ). Results There was a moderate to substantial agreement (ICC 0.51–0.76) between KPEs when using DE-AIFs, while AUC-normalized AIFs yielded ICC 0.77–0.95 for Ktrans, kep and ve and ICC 0.70 for vp. Inclusion of the pop-AIF did not reduce agreement. Agreement in relative longitudinal change in Ktrans was moderate (κ = 0.591) using DE-AIFs, while AUC-normalized AIFs gave substantial (κ = 0.809) agreement. Discussion AUC-normalized AIFs can reduce the variation in kinetic parameter results originating from operator input. The pop-AIF presented in this work may be applied in absence of a satisfactory measurement.

• Wendel, Kristina; Pfeiffer, Helle Cecilie; Fugelseth, Drude; Nestaas, Eirik; Domellöf, Magnus & Skålhegg, Bjørn Steen [Vis alle 42 forfattere av denne artikkelen] (2021). Effects of nutrition therapy on growth, inflammation and metabolism in immature infants: a study protocol of a double-blind randomized controlled trial (ImNuT). BMC Pediatrics. 21. doi: 10.1186/s12887-020-02425-x. Fulltekst i vitenarkiv Vis sammendrag

  Background: Current nutritional management of infants born very preterm results in significant deficiency of the essential fatty acids (FAs) arachidonic acid (ARA) and docosahexaenoic acid (DHA). The impact of this deficit on brain maturation and inflammation mediated neonatal morbidities are unknown. The aim of this study is to determine whether early supply of ARA and DHA improves brain maturation and neonatal outcomes in infants born before 29 weeks of gestation. Methods: Infants born at Oslo University Hospital are eligible to participate in this double-blind randomized controlled trial. Study participants are randomized to receive an enteral FA supplement of either 0.4 ml/kg MCT-oil™ (medium chain triglycerides) or 0.4 ml/kg Formulaid™ (100 mg/kg of ARA and 50 mg/kg of DHA). The FA supplement is given from the second day of life to 36 weeks' postmenstrual age (PMA). The primary outcome is brain maturation assessed by Magnetic Resonance Imaging (MRI) at term equivalent age. Secondary outcomes include quality of growth, incidence of neonatal morbidities, cardiovascular health and neuro-development. Target sample size is 120 infants (60 per group), this will provide 80% power to detect a 0.04 difference in mean diffusivity (MD, mm2/sec) in major white matter tracts on MRI. Discussion: Supplementation of ARA and DHA has the potential to improve brain maturation and reduce inflammation related diseases. This study is expected to provide valuable information for future nutritional guidelines for preterm infants. Trial registration: Clinicaltrials.gov ID: NCT03555019 . Registered 4 October 2018- Retrospectively registered.

• Bjørke, Agnes Balint; Østby, Ylva; Grahl, Simon Gevert; Larsson, Pål Gunnar; Olsen, Ketil Berg & Nævra, Marianne C. Johansen [Vis alle 11 forfattere av denne artikkelen] (2021). Cognition in adult patients with newly diagnosed non-lesional temporal lobe epilepsy. Epilepsy & Behavior. ISSN 1525-5050. 116. doi: 10.1016/j.yebeh.2021.107771. Fulltekst i vitenarkiv Vis sammendrag

  Objective To evaluate whether cognitive performance is affected in newly diagnosed temporal lobe epilepsy (TLE) and to determine the most vulnerable cognitive domains. Methods In this baseline longitudinal study, differences in memory and non-memory cognitive functions were assessed using comprehensive neuropsychological test batteries in 21 adult patients with newly diagnosed non-lesional TLE and individually matched controls. In addition, the analyses included ratings of self-perceived emotional status. Results The patients performed more poorly than the control group regarding delayed visual memory (p = 0.013) and executive function tasks related to switching (Trail Making Test and verbal fluency shifting; p = 0.025 and p = 0.03, respectively). We found no differences in verbal learning and memory, attention/working memory/processing speed, and other executive functions. Significance Our results show that patients with TLE often have specific cognitive deficits at time of diagnosis, even in the absence of structural brain abnormalities. This supports the hypothesis that memory dysfunction is linked to an underlying pathology rather than to the effect of recurrent seizures, long-term use of anti-seizure medication, or other epilepsy-related factors. As certain executive functions are affected at an early stage, the pathology may involve brain regions beyond the temporal lobe and may comprise larger brain networks. These results indicate the need for greater awareness of cognition at the time of diagnosis of TLE and before initiation of treatment, and integration of neuropsychological assessment into early routine clinical care.

• Voldsbekk, Irene; Groote, Inge Rasmus; Zak, Nathalia; Roelfs, Daniël Thomas Heimen; Geier, Oliver & Due-Tønnessen, Paulina [Vis alle 14 forfattere av denne artikkelen] (2021). Sleep and sleep deprivation differentially alter white matter microstructure: A mixed model design utilising advanced diffusion modelling. NeuroImage. ISSN 1053-8119. 226. doi: 10.1016/j.neuroimage.2020.117540. Fulltekst i vitenarkiv Vis sammendrag

  Sleep deprivation influences several critical functions, yet how it affects human brain white matter (WM) is not well understood. The aim of the present work was to investigate the effect of 32 hours of sleep deprivation on WM microstructure compared to changes observed in a normal sleep-wake cycle (SWC). To this end, we utilised diffusion weighted imaging (DWI) including the diffusion tensor model, diffusion kurtosis imaging and the spherical mean technique, a novel biophysical diffusion model. 46 healthy adults (23 sleep deprived vs 23 with normal SWC) underwent DWI across four time points (morning, evening, next day morning and next day afternoon, after a total of 32 hours). Linear mixed models revealed significant group × time interaction effects, indicating that sleep deprivation and normal SWC differentially affect WM microstructure. Voxel-wise comparisons showed that these effects spanned large, bilateral WM regions. These findings provide important insight into how sleep deprivation affects the human brain

• Kim, M.; Park, J.E.; Emblem, K.; Bjørnerud, Atle & Kim, H.S. (2021). Vessel type determined by vessel architectural imaging improves differentiation between early tumor progression and pseudoprogression in glioblastoma. American Journal of Neuroradiology. ISSN 0195-6108. 42(4), s. 663–670. doi: 10.3174/AJNR.A6984. Fulltekst i vitenarkiv Vis sammendrag

  BACKGROUND AND PURPOSE: Currently available perfusion parameters are limited in differentiating early tumor progression and pseudoprogression with no insight about vessel size and type. We aimed to investigate differences in vessel size and type between early tumor progression and pseudoprogression in posttreatment glioblastoma and to demonstrate diagnostic performance using vessel architectural imaging. MATERIALS AND METHODS: Fifty-eight patients with enlarging contrast-enhancing masses in posttreatment glioblastomas underwent simultaneous gradient recalled-echo and spin-echo dynamic susceptibility contrast imaging. Relative CBV and vessel architectural imaging parameters, including the relative vessel size index, peak shift between gradient recalled echo and spin-echo bolus signal peaks, and arterial dominance scores using spatial dominance of arterial/venous vessel type, were calculated and compared between the 2 conditions. The area under the curve and cross-validation were performed to compare the diagnostic performance of the relative CBV, vessel architectural imaging parameters, and their combinations. RESULTS: There were 41 patients with early tumor progression and 17 patients with pseudoprogression. Relative to pseudoprogression, early tumor progression showed a lower peak shift (−0.02 versus 0.33, P = .02) and a lower arterial dominance score (1.46 versus 2.11, P = .001), indicating venous dominance. Patients with early tumor progression had higher relative CBV (1.88 versus 1.38, P = .02) and a tendency toward a larger relative vessel size index (99.67 versus 83.17, P = .15) than those with pseudoprogression. Combining arterial dominance scores and relative CBV showed significantly higher diagnostic performance (area under the curve = 0.82; 95% CI, 0.70–0.94; P = .02) than relative CBV alone (area under the curve = 0.64; 95% CI, 0.49–0.79) in distinguishing early tumor progression from pseudoprogression. CONCLUSIONS: Vessel architectural imaging significantly improved the diagnostic performance of relative CBV by demonstrating venous dominance and a tendency toward larger vessel size in early tumor progression.

• Sederevicius, Donatas; Vidal-Piñeiro, Didac; Sørensen, Øystein; Leemput, Koen van; Iglesias, Juan Eugenio & Dalca, Adrian V. [Vis alle 11 forfattere av denne artikkelen] (2021). Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer – ASEG and SAMSEG. NeuroImage. ISSN 1053-8119. 237:118113, s. 1–14. doi: 10.1016/j.neuroimage.2021.118113. Fulltekst i vitenarkiv
• Digernes, Ingrid; Nilsen, Line; Grøvik, Endre; Bjørnerud, Atle; Løvland, Grethe & Vik-Mo, Einar O. [Vis alle 12 forfattere av denne artikkelen] (2020). Noise dependency in vascular parameters from combined gradient-echo and spin-echo DSC MRI. Physics in Medicine and Biology. ISSN 0031-9155. 65(22), s. 225020–225020. doi: 10.1088/1361-6560/abb71a. Fulltekst i vitenarkiv Vis sammendrag

  Dynamic susceptibility contrast (DSC) imaging is a widely used technique for assessment of cerebral blood volume (CBV). With combined gradient-echo and spin-echo DSC techniques, measures of the underlying vessel size and vessel architecture can be obtained from the vessel size index (VSI) and vortex area, respectively. However, how noise, and specifically the contrast-to-noise ratio (CNR), affect the estimations of these parameters has largely been overlooked. In order to address this issue, we have performed simulations to generate DSC signals with varying levels of CNR, defined by the peak of relaxation rate curve divided by the standard deviation of the baseline. Moreover, DSC data from 59 brain cancer patients were acquired at two different 3 T-scanners (N = 29 and N = 30, respectively), where CNR and relative parameter maps were obtained. Our simulations showed that the measured parameters were affected by CNR in different ways, where low CNR led to overestimations of CBV and underestimations of VSI and vortex area. In addition, a higher noise-sensitivity was found in vortex area than in CBV and VSI. Results from clinical data were consistent with simulations, and indicated that CNR < 4 gives highly unreliable measurements. Moreover, we have shown that the distribution of values in the tumour regions could change considerably when voxels with CNR below a given cut off are excluded when generating the relative parameter maps. The widespread use of CBV and attractive potential of VSI and vortex area, makes the noise-sensitivity of these parameters found in our study relevant for further use and development of the DSC imaging technique. Our results suggest that the CNR has considerable impact on the measured parameters, with the potential to affect the clinical interpretation of DSC-MRI, and should therefore be taken into account in the clinical decision-making process.

• Yogananda, Chandan Ganesh B.; Shah, Bhavya R.; Vejdani-Jahromi, Maryam; Nalawade, Sahil S.; Murugesan, Gowtham K. & Yu, Frank F. [Vis alle 13 forfattere av denne artikkelen] (2020). A Fully Automated Deep Learning Network for Brain Tumor Segmentation. Tomography. ISSN 2379-1381. 6(2), s. 186–193. doi: 10.18383/j.tom.2019.00026. Fulltekst i vitenarkiv
• Larsson, Christopher; Groote, Inge Rasmus; Vardal, Jonas; Kleppestø, Magne Mørk; Odland, Audun & Brandal, Petter [Vis alle 13 forfattere av denne artikkelen] (2020). Prediction of survival and progression in glioblastoma patients using temporal perfusion changes during radiochemotherapy. Magnetic Resonance Imaging. ISSN 0730-725X. 68, s. 106–112. doi: 10.1016/j.mri.2020.01.012. Fulltekst i vitenarkiv Vis sammendrag

  Background The aim of this study was to investigate changes in structural magnetic resonance imaging (MRI) according to the RANO criteria and perfusion- and permeability related metrics derived from dynamic contrast-enhanced MRI (DCE) and dynamic susceptibility contrast MRI (DSC) during radiochemotherapy for prediction of progression and survival in glioblastoma. Methods Twenty-three glioblastoma patients underwent biweekly structural and perfusion MRI before, during, and two weeks after a six weeks course of radiochemotherapy. Temporal trends of tumor volume and the perfusion-derived parameters cerebral blood volume (CBV) and blood flow (CBF) from DSC and DCE, in addition to contrast agent capillary transfer constant (Ktrans) from DCE, were assessed. The patients were separated in two groups by median survival and differences between the two groups explored. Clinical- and MRI metrics were investigated using univariate and multivariate survival analysis and a predictive survival index was generated. Results Median survival was 19.2 months. A significant decrease in contrast-enhancing tumor size and CBV and CBF in both DCE- and DSC-derived parameters was seen during and two weeks past radiochemotherapy (p < 0.05). A 10%/30% increase in Ktrans/CBF two weeks after finishing radiochemotherapy resulted in significant shorter survival (13.9/16.8 vs. 31.5/33.1 months; p < 0.05). Multivariate analysis revealed an index using change in Ktrans and relative CBV from DSC significantly corresponding with survival time in months (r2 = 0.843; p < 0.001). Conclusions Significant temporal changes are evident during radiochemotherapy in tumor size (after two weeks) and perfusion-weighted MRI-derived parameters (after four weeks) in glioblastoma patients. While DCE-based metrics showed most promise for early survival prediction, a multiparametric combination of both DCE- and DSC-derived metrics gave additional information.

• Bakke, Kine Mari; Meltzer, Sebastian; Grøvik, Endre; Negård, Anne; Holmedal, Stein Harald & Gjesdal, Kjell-Inge [Vis alle 9 forfattere av denne artikkelen] (2020). Sex differences and tumor blood flow from dynamic susceptibility contrast MRI are associated with treatment response after chemoradiation and long-term survival in rectal cancer. Radiology. ISSN 0033-8419. 297(2), s. 352–360. doi: 10.1148/RADIOL.2020200287. Fulltekst i vitenarkiv Vis sammendrag

  Sex differences, tumor vascularity, and blood flow seen on multiecho dynamic contrast–based MRI scans enabled prediction of treatment response and overall survival in patients with rectal cancer. Background: MRI is the standard tool for rectal cancer staging. However, more precise diagnostic tests that can assess biologic tumor features decisive for treatment outcome are necessary. Tumor perfusion and hypoxia are two important features; however, no reference methods that measure these exist in clinical use. Purpose: To assess the potential predictive and prognostic value of MRI-assessed rectal cancer perfusion, as a surrogate measure of hypoxia, for local treatment response and survival. Materials and Methods: In this prospective observational cohort study, 94 study participants were enrolled from October 2013 to December 2017 (ClinicalTrials.gov: NCT01816607). Participants had histologically confirmed rectal cancer and underwent routine diagnostic MRI, an extended diffusion-weighted sequence, and a multiecho dynamic contrast agent–based sequence. Predictive and prognostic values of dynamic contrast-enhanced, dynamic susceptibility contrast (DSC), and intravoxel incoherent motion MRI were investigated with response to neoadjuvant treatment, progression-free survival, and overall survival as end points. Secondary objectives investigated potential sex differences in MRI parameters and relationship with lymph node stage. Statistical methods used were Cox regression, Student t test, and Mann-Whitney U test.Results: A total of 94 study participants (mean age, 64 years ± 11 [standard deviation]; 61 men) were evaluated. Baseline tumor blood flow from DSC MRI was lower in patients who had poor local tumor response to neoadjuvant treatment (96 mL/min/100 g ± 33 for ypT2–4, 120 mL/min/100 g ± 21 for ypT0–1; P = .01), shorter progression-free survival (hazard ratio = 0.97; 95% confidence interval: 0.96, 0.98; P < .001), and shorter overall survival (hazard ratio = 0.98; 95% confidence interval: 0.98, 0.99; P < .001). Women had higher blood flow (125 mL/min/100 g ± 27) than men (74 mL/min/100 g ± 26, P < .001) at stage 4. Volume transfer constant and plasma volume from dynamic contrast-enhanced MRI as well as ΔR2* peak and area under the curve for 30 and 60 seconds from DSC MRI were associated with local malignant lymph nodes (pN status). Median area under the curve for 30 seconds was 0.09 arbitrary units (au) ± 0.03 for pN1–2 and 0.19 au ± 0.12 for pN0 (P = .001). Conclusion:Low tumor blood flow from dynamic susceptibility contrast MRI was associated with poor treatment response in study participants with rectal cancer.

• Voldsbekk, Irene; Maximov, Ivan; Zak, Nathalia; Roelfs, Daniël Thomas Heimen; Geier, Oliver & Due-Tønnessen, Paulina [Vis alle 10 forfattere av denne artikkelen] (2020). Evidence for wakefulness-related changes to extracellular space in human brain white matter from diffusion-weighted MRI. NeuroImage. ISSN 1053-8119. 212, s. 116682–116682. doi: 10.1016/j.neuroimage.2020.116682. Fulltekst i vitenarkiv Vis sammendrag

  Recently, several magnetic resonance imaging (MRI) studies have reported time-of-day effects on brain structure and function. Due to the possibility that time-of-day effects reflect mechanisms of circadian regulation, the aim of this prospective study was to assess these effects while under strict experimental control of variables that might influence biological clocks, such as caffeine intake and exposure to blue-emitting light. In addition, the current study assessed whether time-of-day effects were driven by changes to extracellular space, by including estimations of non-Gaussian diffusion metrics obtained from diffusion kurtosis imaging, white matter tract integrity and the spherical mean technique, in addition to conventional diffusion tensor imaging -derived parameters. Participants were 47 healthy adults who underwent diffusion-weighted imaging in the morning and evening of the same day. Morning and evening scans were compared using voxel-wise tract based spatial statistics and permutation testing. A day of wakefulness was associated with widespread increases in fractional anisotropy, indices of kurtosis and indices of the axonal water fraction. In addition, wakefulness was associated with widespread decreases in radial diffusivity, both in the single compartment and in extra-axonal space. These results suggest that an increase in the intra-axonal space relative to the extra-axonal volume underlies time-of-day effects in human white matter, which is in line with activity-induced reductions to the extracellular volume. These findings provide important insight into possible mechanisms driving time-of-day effects in MRI.

• Vatnehol, Svein Are Sirirud; Hol, Per Kristian; Bjørnerud, Atle; Amiry-Moghaddam, Mahmood; Haglerød, Camilla & Storås, Tryggve (2020). Effect of drinking oxygenated water assessed by in vivo MRI relaxometry. Journal of Magnetic Resonance Imaging. ISSN 1053-1807. 52(3), s. 720–728. doi: 10.1002/jmri.27104. Fulltekst i vitenarkiv Vis sammendrag

  Grant Support This project was funded by the Research Council of Norway. Background Oxygen uptake through the gastrointestinal tract after oral administration of oxygenated water in humans is not well studied and is debated in the literature. Due to the paramagnetic properties of oxygen and deoxyhemoglobin, MRI as a technique might be able to detect changes in relaxometry values caused by increased oxygen levels in the blood. Purpose To assess whether oxygen dissolved in water is absorbed from the gastrointestinal tract and transported into the bloodstream after oral administration. Study Type A randomized, double‐blinded, placebo‐controlled crossover trial. Population/Subjects Thirty healthy male volunteers age 20–35. Field Strength/Sequence 3T/Modified Look–Locker inversion recovery (MOLLI) T1‐mapping and multi fast field echo (mFFE) T2*‐mapping. Assessment Each volunteer was scanned in two separate sessions. T1 and T2* maps were acquired repeatedly covering the hepatic portal vein (HPV) and vena cava inferior (VCI, control vein) before and after intake of oxygenated or control water. Assessments were done by placing a region of interest in the HPV and VCI. Statistical Test A mixed linear model was performed to the compare control vs. oxygen group. Results Drinking caused a mean 1.6% 95% CI (1.1–2.0% P < 0.001) increase in T1 of HPV blood and water oxygenation attributed another 0.70% 95% confidence interval (CI) (0.07–1.3% P = 0.028) increase. Oxygenation did not change T1 in VCI blood. Mean T2* increased 9.6% 95% CI (1.7–17.5% P = 0.017) after ingestion of oxygenated water and 1.2% 95% CI (−4.3–6.8% P = 0.661) after ingestion of control water. The corresponding changes in VCI blood were not significant. Data Conclusion Ingestion of water caused changes in T1 and T2* of HPV blood compatible with dilution due to water absorption. The effects were enhanced by oxygen. Assessment of oxygen enrichment of HPV blood was not possible due to the dilution effect. Level of Evidence 2 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2020;52:720–728.

• Walhovd, Kristine B; Amlien, Inge Kasbohm; Schrantee, Anouk; Rohani, Darius Adam; Groote, Inge Rasmus & Bjørnerud, Atle [Vis alle 8 forfattere av denne artikkelen] (2020). Methylphenidate effects on cortical thickness in children and adults with attention-deficit/hyperactivity disorder: A randomized clinical trial. American Journal of Neuroradiology. ISSN 0195-6108. 41(5), s. 758–765. doi: 10.3174/AJNR.A6560. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Background and purpose: Although methylphenidate is frequently used to treat children with attention-deficit/hyperactivity disorder, it is currently unknown how methylphenidate affects brain development. In a randomized controlled trial, we investigated whether the cortical effects of methylphenidate are modulated by age. Materials and methods: Between June 1, 2011, and June 15, 2015, we conducted a randomized, double-blind, placebo-controlled trial (Effects of Psychotropic Drugs on Developing Brain-Methylphenidate) in 99 males with attention-deficit/hyperactivity disorder (according to Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, criteria) from referral centers in the greater Amsterdam area in the Netherlands. The trial was registered on March 24, 2011 (identifier NL34509.000.10) and subsequently at the Netherlands National Trial Register (identifier NTR3103). Participants (first enrolled October 13, 2011) were 10-12 years or 23-40 years of age and randomized to treatment with either methylphenidate or a placebo for 16 weeks. Our main outcome was a change in cortical thickness in predefined ROIs as measured by MR imaging pre- and posttreatment. Results: We observed a time × medication × age interaction (F[1,88.825] = 4.316, P < .05) for the right medial cortex ROI, where methylphenidate treatment yielded less cortical thinning in children, but not in adults or the placebo groups. Conclusions: Our finding that the effects of methylphenidate on right medial cortical thickness differ between children and adults infers that the drug affects gray matter development in this brain region. This warrants replication in larger groups with longer follow-up to determine whether this effect can also be observed in other cortical brain regions and whether it may have long-term consequences.

• Pålhaugen, Lene; Sudre, Carole H; Teceläo, Sandra Raquel Ramos; Nakling, Arne; Almdahl, Ina Selseth & Kalheim, Lisa Flem [Vis alle 13 forfattere av denne artikkelen] (2020). Brain amyloid and vascular risk are related to distinct white matter hyperintensity patterns. Journal of Cerebral Blood Flow and Metabolism. ISSN 0271-678X. 41(5), s. 1–13. doi: 10.1177/0271678X20957604. Fulltekst i vitenarkiv Vis sammendrag

  White matter hyperintensities (WMHs) are associated with vascular risk and Alzheimer’s disease. In this study, we examined relations between WMH load and distribution, amyloid pathology and vascular risk in 339 controls and cases with either subjective (SCD) or mild cognitive impairment (MCI). Regional deep (DWMH) and periventricular (PWMH) WMH loads were determined using an automated algorithm. We stratified on Aβ1-42 pathology (Aβ+/−) and analyzed group differences, as well as associations with Framingham Risk Score for cardiovascular disease (FRS-CVD) and age. Occipital PWMH (p = 0.001) and occipital DWMH (p = 0.003) loads were increased in SCD-Aβ+ compared with Aβ− controls. In MCI-Aβ+ compared with Aβ− controls, there were differences in global WMH (p = 0.003), as well as occipital DWMH (p = 0.001) and temporal DWMH (p = 0.002) loads. FRS-CVD was associated with frontal PWMHs (p = 0.003) and frontal DWMHs (p = 0.005), after adjusting for age. There were associations between global and all regional WMH loads and age. In summary, posterior WMH loads were increased in SCD-Aβ+ and MCI-Aβ+ cases, whereas frontal WMHs were associated with vascular risk. The differences in WMH topography support the use of regional WMH load as an early-stage marker of etiology.

• Mutsaerts, Henk J.M.M.; Petr, Jan; Groot, Paul; Vandemaele, Pieter; Ingala, Silvia & Robertson, Andrew D. [Vis alle 43 forfattere av denne artikkelen] (2020). ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies. NeuroImage. ISSN 1053-8119. 219:117031, s. 1–17. doi: 10.1016/j.neuroimage.2020.117031. Fulltekst i vitenarkiv
• Lee, Ji Ye; Bjørnerud, Atle; Park, Ji Eun; Lee, Bo Eun; Kim, Joo Hyun & Kim, Ho Sung (2019). Permeability measurement using dynamic susceptibility contrast magnetic resonance imaging enhances differential diagnosis of primary central nervous system lymphoma from glioblastoma. European Radiology. ISSN 0938-7994. s. 1–10. doi: 10.1007/s00330-019-06097-9. Fulltekst i vitenarkiv
• Hope, Tuva Roaldsdatter; Selnes, Per; Rektorová, Irena; Anderkova, Lubomira; Nemcova-Elfmarkova, Nela & Balážová, Zuzana [Vis alle 9 forfattere av denne artikkelen] (2019). Diffusion tensor and restriction spectrum imaging reflect different aspects of neurodegeneration in Parkinson's disease. PLOS ONE. 14(5), s. 1–13. doi: 10.1371/journal.pone.0217922. Fulltekst i vitenarkiv Vis sammendrag

  To meet the need for Parkinson’s disease biomarkers and evidence for amount and distribution of pathological changes, MRI diffusion tensor imaging (DTI) has been explored in a number of previous studies. However, conflicting results warrant further investigations. As tissue microstructure, particularly of the grey matter, is heterogeneous, a more precise diffusion model may benefit tissue characterization. The purpose of this study was to analyze the diffusion-based imaging technique restriction spectrum imaging (RSI) and DTI, and their ability to detect microstructural changes within brain regions associated with motor function in Parkinson’s disease. Diffusion weighted (DW) MR images of a total of 100 individuals, (46 Parkinson’s disease patients and 54 healthy controls) were collected using b-values of 0–4000s/mm2. Output diffusion-based maps were estimated based on the RSI-model combining the full set of DW-images (Cellular Index (CI), Neurite Density (ND)) and DTI-model combining b = 0 and b = 1000 s/mm2 (fractional anisotropy (FA), Axial-, Mean- and Radial diffusivity (AD, MD, RD)). All parametric maps were analyzed in a voxel-wise group analysis, with focus on typical brain regions associated with Parkinson’s disease pathology. CI, ND and DTI diffusivity metrics (AD, MD, RD) demonstrated the ability to differentiate between groups, with strongest performance within the thalamus, prone to pathology in Parkinson’s disease. Our results indicate that RSI may improve the predictive power of diffusion-based MRI, and provide additional information when combined with the standard diffusivity measurements. In the absence of major atrophy, diffusion techniques may reveal microstructural pathology. Our results suggest that protocols for MRI diffusion imaging may be adapted to more sensitive detection of pathology at different sites of the central nervous system.

• Due-Tønnessen, Paulina; Pinho, Marco C.; Emblem, Kyrre E; Hald, John K; Kanoto, Masafumi & Abildgaard, Andreas [Vis alle 10 forfattere av denne artikkelen] (2019). The impact of MRI features and observer confidence on the treatment decision-making for patients with untreated glioma. Scientific Reports. 9:19898, s. 1–10. doi: 10.1038/s41598-019-56333-x. Fulltekst i vitenarkiv Vis sammendrag

  In a blind, dual-center, multi-observer setting, we here identify the pre-treatment radiologic features by Magnetic Resonance Imaging (MRI) associated with subsequent treatment options in patients with glioma. Study included 220 previously untreated adult patients from two institutions (94 + 126 patients) with a histopathologically confirmed diagnosis of glioma after surgery. Using a blind, cross-institutional and randomized setup, four expert neuroradiologists recorded radiologic features, suggested glioma grade and corresponding confidence. The radiologic features were scored using the Visually AcceSAble Rembrandt Images (VASARI) standard. Results were retrospectively compared to patient treatment outcomes. Our findings show that patients receiving a biopsy or a subtotal resection were more likely to have a tumor with pathological MRI-signal (by T2-weighted Fluid-Attenuated Inversion Recovery) crossing the midline (Hazard Ratio; HR = 1.30 [1.21–1.87], P < 0.001), and those receiving a biopsy sampling more often had multifocal lesions (HR = 1.30 [1.16–1.64], P < 0.001). For low-grade gliomas (N = 50), low observer confidence in the radiographic readings was associated with less chance of a total resection (P = 0.002) and correlated with the use of a more comprehensive adjuvant treatment protocol (Spearman = 0.48, P < 0.001). This study may serve as a guide to the treating physician by identifying the key radiologic determinants most likely to influence the treatment decision-making process.

• Bakke, Kine Mari; Grøvik, Endre; Meltzer, Sebastian; Negård, Anne; Holmedal, Stein Harald & Mikalsen, Lars Tore G [Vis alle 11 forfattere av denne artikkelen] (2019). Comparison of Intravoxel incoherent motion imaging and multiecho dynamic contrast-based MRI in rectal cancer. Journal of Magnetic Resonance Imaging. ISSN 1053-1807. 50(4), s. 1114–1124. doi: 10.1002/jmri.26740. Fulltekst i vitenarkiv Vis sammendrag

  Background Dynamic contrast‐based MRI and intravoxel incoherent motion imaging (IVIM) MRI are both methods showing promise as diagnostic and prognostic tools in rectal cancer. Both methods aim at measuring perfusion‐related parameters, but the relationship between them is unclear. Purpose To investigate the relationship between perfusion‐ and permeability‐related parameters obtained by IVIM‐MRI, T1‐weighted dynamic contrast‐enhanced (DCE)‐MRI and T2*‐weighted dynamic susceptibility contrast (DSC)‐MRI. Study Type Prospective. Subjects In all, 94 patients with histologically confirmed rectal cancer. Field Strength/Sequence Subjects underwent pretreatment 1.5T clinical procedure MRI, and in addition a study‐specific diffusion‐weighted sequence (b = 0, 25, 50, 100, 500, 1000, 1300 s/mm2) and a multiecho dynamic contrast‐based echo‐planer imaging sequence. Assessment Median tumor values were obtained from IVIM (perfusion fraction [f], pseudodiffusion [D*], diffusion [D]), from the extended Tofts model applied to DCE data (Ktrans, kep, vp, ve) and from model free deconvolution of DSC (blood flow [BF] and area under curve). A subgroup of the excised tumors underwent immunohistochemistry with quantification of microvessel density and vessel size. Statistical Test Spearman's rank correlation test. Results D* was correlated with BF (rs = 0.47, P < 0.001), and f was negatively correlated with kep (rs = –0.31, P = 0.002). BF was correlated with Ktrans (rs = 0.29, P = 0.004), but this correlation varied extensively when separating tumors into groups of low (rs = 0.62, P < 0.001) and high (rs = –0.06, P = 0.68) BF. Ktrans was negatively correlated with vessel size (rs = –0.82, P = 0.004) in the subgroup of tumors with high BF. Data Conclusion We found an association between D* from IVIM and BF estimated from DSC‐MRI. The relationship between IVIM and DCE‐MRI was less clear. Comparing parameters from DSC‐MRI and DCE‐MRI highlights the importance of the underlying biology for the interpretation of these parameters. Level of Evidence: 2 Technical Efficacy: Stage 1

• Vatnehol, Svein Are Sirirud; Hol, Per Kristian; Bjørnerud, Atle; Amiry-Moghaddam, Mahmood; Haglerød, Camilla Margrete & Storås, Tryggve (2019). Precision of T1-relaxation time measurements in the hepatic portal vein: influence of measurement technique and sequence parameters. Magnetic Resonance Materials in Physics, Biology and Medicine. ISSN 0968-5243. 32(3), s. 359–368. doi: 10.1007/s10334-018-00731-1. Fulltekst i vitenarkiv
• Vatnehol, Svein Are Sirirud; Hol, Per Kristian; Bjørnerud, Atle; Amiry-Moghaddam, Mahmood; Haglerød, Camilla Margrete & Storås, Tryggve (2019). Determination of oxygen r1 at 3 Tesla using samples with a concentration range of dissolved oxygen. Magnetic Resonance Materials in Physics, Biology and Medicine. ISSN 0968-5243. s. 1–7. doi: 10.1007/s10334-019-00783-x. Fulltekst i vitenarkiv Vis sammendrag

  Objective To investigate the sensitivity of modified Look–Locker inversion recovery (MOLLI) to measure changes in dissolved oxygen (DO) concentrations in water samples and to calculate sequence-specific relaxivity (r1m) and limit of detection (LOD). Materials and methods Ten water samples with a range of DO concentrations were scanned at 3 T using two variations of MOLLI schemes. Using linear regression the r1 of DO was estimated from the measured DO concentrations and T1 relaxation rates (R1). The results were combined with previously reported values on in vivo stability measures of the MOLLI sequences and used to estimate a LOD. Results DO concentrations ranged from 0.5 to 21.6 mg L−1. A linear correlation between DO and R1 was obtained with both MOLLI sequences, with an average correlation coefficient (R2) 0.9 and an average estimated r1 (r^1) of 4.45 × 10−3 s−1 mg−1 L. Estimated LOD was ≈ 10 mg L−1. Conclusion MOLLI T1-mapping sequences may be used for detecting dissolved oxygen in vivo at 3 T with an r^1 in the range 4.18–4.8 × 10−3 s−1 mg−1 L and a corresponding LOD for dissolved oxygen of approximately 10 mg L−1. MOLLI-based T1 mapping may be a useful non-invasive tool for quantification of in vivo changes of DO concentration during oxygen challenges.

• Grydeland, Håkon; Vértes, Petra; Váša, František; Romero-Garcia, Rafael; Whitaker, Kirstie & F., Alexander-Bloch Aaron [Vis alle 15 forfattere av denne artikkelen] (2019). Waves of Maturation and Senescence in Microstructural MRI Markers of Human Cortical Myelination over the Lifespan. Cerebral Cortex. ISSN 1047-3211. 29(3), s. 1369–1381. doi: 10.1093/cercor/bhy330. Fulltekst i vitenarkiv Vis sammendrag

  Seminal human brain histology work has demonstrated developmental waves of myelination. Here, using a micro-structural magnetic resonance imaging (MRI) marker linked to myelin, we studied fine-grained age differences to deduce waves of growth, stability, and decline of cortical myelination over the life-cycle. In 484 participants, aged 8–85 years, we fitted smooth growth curves to T1- to T2-weighted ratio in each of 360 regions from one of seven cytoarchitectonic classes. From the first derivatives of these generally inverted-U trajectories, we defined three milestones: the age at peak growth; the age at onset of a stable plateau; and the age at the onset of decline. Age at peak growth had a bimodal distribution comprising an early (pre-pubertal) wave of primary sensory and motor cortices and a later (post-pubertal) wave of association, insular and limbic cortices. Most regions reached stability in the 30-s but there was a second wave reaching stability in the 50-s. Age at onset of decline was also bimodal: in some right hemisphere regions, the curve declined from the 60-s, but in other left hemisphere regions, there was no significant decline from the stable plateau. These results are consistent with regionally heterogeneous waves of intracortical myelinogenesis and age-related demyelination.

• Kalheim, Lisa Flem; Fladby, Tormod; Coello, Christopher; Bjørnerud, Atle & Selnes, Per (2018). [18F]-Flutemetamol Uptake in Cortex and White Matter: Comparison with Cerebrospinal Fluid Biomarkers and [18F]-Fludeoxyglucose. Journal of Alzheimer's Disease. ISSN 1387-2877. 62(4), s. 1595–1607. doi: 10.3233/JAD-170582. Fulltekst i vitenarkiv Vis sammendrag

  Flutemetamol (18F-Flut) is an [18F]-labelled amyloid PET tracer with increasing availability. The main objectives of this study were to investigate 1) cerebrospinal fluid (CSF) Aβ 1-42 (Aβ42) concentrations associated with regional 18F-Flut uptake, 2) associations between cortical 18F-Flut and [18F]-fludeoxyglucose (18F-FDG)-PET, and 3) the potential use of 18F-Flut in WM pathology. Cognitively impaired, nondemented subjects were recruited (n = 44). CSF was drawn, and 18F-Flut-PET, 18F-FDG-PET, and MRI performed. Our main findings were: 1) Different Alzheimer’s disease predilection areas showed increased 18F-Flut retention at different CSF Aβ42 concentrations (posterior regions were involved at higher concentrations). 2) There were strong negative correlations between regional cortical 18F-Flut and 18F-FDG uptake. 3) Increased 18F-Flut uptake were observed in multiple subcortical regions in amyloid positive subjects, including investigated reference regions. However, WM hyperintensity 18F-Flut standardized uptake value ratios (SUVr) were not significantly different, thus we cannot definitely conclude that the higher uptake in 18F-Flut(+) is due to amyloid deposition. In conclusion, our findings support clinical use of CSF Aβ42, putatively relate decreasing CSF Aβ42 concentrations to a sequence of regional amyloid deposition, and associate amyloid pathology to cortical hypometabolism. However, we cannot conclude that 18F-Flut-PET is a suitable marker for WM pathology due to high aberrant WM uptake.

• Lee, B; Park, JE; Bjørnerud, Atle; Kim, J. H.; Lee, JY & Kim, H. S. (2018). Clinical value of vascular permeability estimates using dynamic susceptibility contrast MRI: Improved diagnostic performance in distinguishing hypervascular primary CNS Lymphoma from Glioblastoma. American Journal of Neuroradiology. ISSN 0195-6108. 39(8), s. 1415–1422. doi: 10.3174/ajnr.A5732. Fulltekst i vitenarkiv
• Sowa, Piotr; Harbo, Hanne Flinstad; White, Nathan S.; Celius, Elisabeth Gulowsen; Bartsch, Hauke & Berg-Hansen, Pål [Vis alle 12 forfattere av denne artikkelen] (2018). Restriction spectrum imaging of white matter and its relation to neurological disability in multiple sclerosis. Multiple Sclerosis. ISSN 1352-4585. s. 1–12. doi: 10.1177/1352458518765671. Fulltekst i vitenarkiv Vis sammendrag

  Background: Restriction spectrum imaging (RSI) is a recently introduced magnetic resonance imaging diffusion technique. The utility of RSI in multiple sclerosis (MS) is unknown. Objective: To investigate the association between RSI-derived parameters and neurological disability in MS. Methods: Seventy-seven relapsing-remitting MS patients were scanned with RSI on a 3-Tesla scanner. RSI-derived parameters: fast and slow apparent diffusion coefficient (sADC), fractional anisotropy, restricted fractional anisotropy, neurite density (ND), cellularity, extracellular water fraction and free water fraction were obtained in white matter lesions (WML) and normal appearing white matter (NAWM). Patients were divided into three groups according to their expanded disability status scale (EDSS): with minimal, low and substantial disability (<2.5, 2.5–3 and >3, respectively). Group comparisons and correlation analyses were performed. Results: All tested RSI-derived parameters differed between WML and NAWM (p<0.001 for all pairwise comparisons). The sADC in WML showed largest difference across disability subgroups (ANOVA: F=5.1, η2=0.12 p=0.008). ND in NAWM showed strongest correlation with disability (ϱ=-0.39, p<0.001). Conclusion: The strongest correlation with EDSS of ND obtained in NAWM indicates that processes outside lesions are important for disability in MS. Our study suggests that RSIderived parameters may help understand the “clinico-radiological paradox” and improve disease monitoring in MS.

• Krogsrud, Stine Kleppe; Fjell, Anders Martin; Tamnes, Christian Krog; Grydeland, Håkon; Due-Tønnessen, Paulina & Bjørnerud, Atle [Vis alle 10 forfattere av denne artikkelen] (2018). Development of white matter microstructure in relation to verbal and visuospatial working memory - A longitudinal study. PLOS ONE. 13:e0195540(4), s. 1–22. doi: 10.1371/journal.pone.0195540. Fulltekst i vitenarkiv Vis sammendrag

  Working memory capacity is pivotal for a broad specter of cognitive tasks and develops throughout childhood. This must in part rely on development of neural connections and white matter microstructure maturation, but there is scarce knowledge of specific relations between this and different aspects of working memory. Diffusion tensor imaging (DTI) enables us to study development of brain white matter microstructure. In a longitudinal DTI study of 148 healthy children between 4 and 11 years scanned twice with an on average 1.6 years interval, we characterized change in fractional anisotropy (FA), mean (MD), radial (RD) and axial diffusivity (AD) in 10 major white matter tracts hypothesized to be of importance for working memory. The results showed relationships between change in several tracts and change in visuospatial working memory. Specifically, improvement in visuospatial working memory capacity was significantly associated with decreased MD, RD and AD in inferior longitudinal fasciculus (ILF), inferior fronto-occipital fasciculus (IFOF) and uncinate fasciculus (UF) in the right hemisphere, as well as forceps major (FMaj). No significant relationships were found between change in DTI metrics and change in verbal working memory capacity. These findings yield new knowledge about brain development and corresponding working memory improvements in childhood.

• Elvsåshagen, Torbjørn; Mutsaerts, Henri J.M.M; Zak, Nathalia; Norbom, Linn Christin Bonaventure; Quiraishi, Sophia & Pedersen, Per Øystein Heiberg [Vis alle 11 forfattere av denne artikkelen] (2018). Cerebral blood flow changes after a day of wake, sleep, and sleep deprivation. NeuroImage. ISSN 1053-8119. 186, s. 497–509. doi: 10.1016/j.neuroimage.2018.11.032. Fulltekst i vitenarkiv Vis sammendrag

  Elucidating the neurobiological effects of sleep and wake is an important goal of the neurosciences. Whether and how human cerebral blood flow (CBF) changes during the sleep-wake cycle remain to be clarified. Based on the synaptic homeostasis hypothesis of sleep and wake, we hypothesized that a day of wake and a night of sleep deprivation would be associated with gray matter resting CBF (rCBF) increases and that sleep would be associated with rCBF decreases. Thirty-eight healthy adult males (age 22.1 ± 2.5 years) underwent arterial spin labeling perfusion magnetic resonance imaging at three time points: in the morning after a regular night's sleep, the evening of the same day, and the next morning, either after total sleep deprivation (n = 19) or a night of sleep (n = 19). All analyses were adjusted for hematocrit and head motion. rCBF increased from morning to evening and decreased after a night of sleep. These effects were most prominent in bilateral hippocampus, amygdala, thalamus, and in the occipital and sensorimotor cortices. Group × time interaction analyses for evening versus next morning revealed significant interaction in bilateral lateral and medial occipital cortices and in bilateral insula, driven by rCBF increases in the sleep deprived individuals and decreases in the sleepers, respectively. Furthermore, group × time interaction analyses for first morning versus next morning showed significant effects in medial and lateral occipital cortices, in anterior cingulate gyrus, and in the insula, in both hemispheres. These effects were mainly driven by CBF increases from TP1 to TP3 in the sleep deprived individuals. There were no associations between the rCBF changes and sleep characteristics, vigilant attention, or subjective sleepiness that remained significant after adjustments for multiple analyses. Altogether, these results encourage future studies to clarify mechanisms underlying sleep-related rCBF changes.

• Fasmer, Kristine Eldevik; Bjørnerud, Atle; Ytre-Hauge, Sigmund; Grüner, Renate; Tangen, Ingvild Løberg & Werner, Henrica Maria Johanna [Vis alle 11 forfattere av denne artikkelen] (2018). Preoperative quantitative dynamic contrast-enhanced MRI and diffusion-weighted imaging predict aggressive disease in endometrial cancer. Acta Radiologica. ISSN 0284-1851. 59(8), s. 1010–1017. doi: 10.1177/0284185117740932. Fulltekst i vitenarkiv
• Bjørnerud, Atle; Vatnehol, Svein Are Sirirud; Larsson, Christopher; Due-Tønnessen, Paulina; Hol, Per Kristian & Groote, Inge Rasmus (2017). Signal enhancement of the dentate nucleus at unenhanced MR imaging after very high cumulative doses of the macrocyclic gadolinium-based contrast agent gadobutrol: An observational study. Radiology. ISSN 0033-8419. 285(2), s. 434–444. doi: 10.1148/radiol.2017170391. Fulltekst i vitenarkiv Vis sammendrag

  Purpose: To test for measurable visual enhancement of the dentate nucleus (DN) on unenhanced T1-weighted magnetic resonance (MR) images in a cohort of patients with a primary brain tumor who had not received linear gadolinium-based contrast agents (GBCAs) but had received many injections of macrocyclic GBCAs. Materials and Methods: Seventeen patients with high-grade gliomas who had received 10–44 administrations of the macrocyclic GBCA gadobutrol (0.1 mmol/kg of body weight) were retrospectively included in this regional ethics committee–approved study. Two neuroradiologists inspected T1-weighted MR images with optimized window settings to visualize small differences in contrast at the baseline and at the last examination for the presence of visual DN signal enhancement. Signal intensity (SI) in the DN was normalized to the SI of the pons, and a one-sample t test was used to test for differences between baseline normalized SI (nSI) in the DN (nSIDN) and the average change in nSIDN of all postbaseline MR imaging sessions (ΔnSIDNavg) or the change in nSIDN from baseline to the last MR imaging session (ΔnSIDN). Linear and quadratic correlation analyses were used to examine the association between the number of macrocyclic GBCA administrations and ΔnSIDN or ΔnSIDNavg. Results: The mean ± standard deviation number of macrocyclic GBCA administrations was 22.2 ± 10.6 administered throughout 706 days ± 454. Visually appreciable signal enhancement was observed in two patients who had received 37 and 44 macrocyclic GBCA injections. Mean ΔnSIDN was greater than zero (0.03 ± 0.05; P = .016), and there was a significant linear association between the number of macrocyclic GBCA injections and ΔnSIDN (r = 0.69, P = .002) and ΔnSIDNavg (r = 0.77, P < .001). Conclusion: A small but statistically significant dose-dependent T1-weighted signal enhancement was observed in the DN after multiple macrocyclic GBCA injections. Visually appreciable enhancement in the DN was observed on contrast-optimized images in two patients who had received 37 and 44 standard doses of macrocyclic GBCAs.

• Sowa, Piotr; Nygaard, Gro Owren; Bjørnerud, Atle; Celius, Elisabeth Gulowsen; Harbo, Hanne Flinstad & Beyer, Mona K. (2017). Magnetic resonance imaging perfusion is associated with disease severity and activity in multiple sclerosis. Neuroradiology. ISSN 0028-3940. 59(7), s. 655–664. doi: 10.1007/s00234-017-1849-4. Fulltekst i vitenarkiv Vis sammendrag

  Purpose The utility of perfusion-weighted imaging in multiple sclerosis (MS) is not well investigated. The purpose of this study was to compare baseline normalized perfusion measures in subgroups of newly diagnosed MS patients. We wanted to test the hypothesis that this method can differentiate between groups defined according to disease severity and disease activity at 1 year follow-up. Methods Baseline magnetic resonance imaging (MRI) including a dynamic susceptibility contrast perfusion sequence was performed on a 1.5-T scanner in 66 patients newly diagnosed with relapsing-remitting MS. From the baseline MRI, cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) maps were generated. Normalized (n) perfusion values were calculated by dividing each perfusion parameter obtained in white matter lesions by the same parameter obtained in normal-appearing white matter. Neurological examination was performed at baseline and at follow-up approximately 1 year later to establish the multiple sclerosis severity score (MSSS) and evidence of disease activity (EDA). Results Baseline normalized mean transit time (nMTT) was lower in patients with MSSS >3.79 (p = 0.016), in patients with EDA (p = 0.041), and in patients with both MSSS >3.79 and EDA (p = 0.032) at 1-year follow-up. Baseline normalized cerebral blood flow and normalized cerebral blood volume did not differ between these groups. Conclusion Lower baseline nMTT was associated with higher disease severity and with presence of disease activity 1 year later in newly diagnosed MS patients. Further longitudinal studies are needed to confirm whether baseline-normalized perfusion measures can differentiate between disease severity and disease activity subgroups over time.

• Almdahl, Ina; Lauridsen, Camilla; Selnes, Per; Kalheim, Lisa Flem; Coello, Christopher & Gajdzik, Beata [Vis alle 14 forfattere av denne artikkelen] (2017). Cerebrospinal fluid levels of amyloid beta 1-43 mirror 1-42 in relation to imaging biomarkers of Alzheimer's disease. Frontiers in Aging Neuroscience. 9, s. 1–13. doi: 10.3389/fnagi.2017.00009. Fulltekst i vitenarkiv Vis sammendrag

  Introduction: Amyloid beta 1-43 (Aβ43), with its additional C-terminal threonine residue, is hypothesized to play a role in early Alzheimer’s disease pathology possibly different from that of amyloid beta 1-42 (Aβ42). Cerebrospinal fluid (CSF) Aβ43 has been suggested as a potential novel biomarker for predicting conversion from mild cognitive impairment (MCI) to dementia in Alzheimer’s disease. However, the relationship between CSF Aβ43 and established imaging biomarkers of Alzheimer’s disease has never been assessed. Materials and Methods: In this observational study, CSF Aβ43 was measured with ELISA in 89 subjects; 34 with subjective cognitive decline (SCD), 51 with MCI, and four with resolution of previous cognitive complaints. All subjects underwent structural MRI; 40 subjects on a 3T and 50 on a 1.5T scanner. Forty subjects, including 24 with SCD and 12 with MCI, underwent 18F-Flutemetamol PET. Seventy-eight subjects were assessed with 18F-fluorodeoxyglucose PET (21 SCD/7 MCI and 11 SCD/39 MCI on two different scanners). Ten subjects with SCD and 39 with MCI also underwent diffusion tensor imaging. Results: Cerebrospinal fluid Aβ43 was both alone and together with p-tau a significant predictor of the distinction between SCD and MCI. There was a marked difference in CSF Aβ43 between subjects with 18F-Flutemetamol PET scans visually interpreted as negative (37 pg/ml, n = 27) and positive (15 pg/ml, n = 9), p < 0.001. Both CSF Aβ43 and Aβ42 were negatively correlated with standardized uptake value ratios for all analyzed regions; CSF Aβ43 average rho -0.73, Aβ42 -0.74. Both CSF Aβ peptides correlated significantly with hippocampal volume, inferior parietal and frontal cortical thickness and axial diffusivity in the corticospinal tract. There was a trend toward CSF Aβ42 being better correlated with cortical glucose metabolism. None of the studied correlations between CSF Aβ43/42 and imaging biomarkers were significantly different for the two Aβ peptides when controlling for multiple testing. Conclusion: Cerebrospinal fluid Aβ43 appears to be strongly correlated with cerebral amyloid deposits in the same way as Aβ42, even in non-demented patients with only subjective cognitive complaints. Regarding imaging biomarkers, there is no evidence from the present study that CSF Aβ43 performs better than the classical CSF biomarker Aβ42 for distinguishing SCD and MCI.

• Selnes, Per; Stav, Ane Løvli; Johansen, Krisztina Kunszt; Bjørnerud, Atle; Coello, Christopher & Auning, Eirik [Vis alle 13 forfattere av denne artikkelen] (2017). Impaired synaptic function is linked to cognition in Parkinson's disease. Annals of clinical and translational neurology. 4(10), s. 700–713. doi: 10.1002/acn3.446. Fulltekst i vitenarkiv Vis sammendrag

  Objective Cognitive impairment is frequent in Parkinson's disease, but the underlying mechanisms are insufficiently understood. Because cortical metabolism is reduced in Parkinson's disease and closely associated with cognitive impairment, and CSF amyloid‐β species are reduced and correlate with neuropsychological performance in Parkinson's disease, and amyloid‐β release to interstitial fluid may be related to synaptic activity; we hypothesize that synapse dysfunction links cortical hypometabolism, reduced CSF amyloid‐β, and presynaptic deposits of α‐synuclein. We expect a correlation between hypometabolism, CSF amyloid‐β, and the synapse related‐markers CSF neurogranin and α‐synuclein. Methods Thirty patients with mild‐to‐moderate Parkinson's disease and 26 healthy controls underwent a clinical assessment, lumbar puncture, MRI, 18F‐fludeoxyglucose‐PET, and a neuropsychological test battery (repeated for the patients after 2 years). Results All subjects had CSF amyloid‐β 1‐42 within normal range. In Parkinson's disease, we found strong significant correlations between cortical glucose metabolism, CSF Aβ, α‐synuclein, and neurogranin. All PET CSF biomarker‐based cortical clusters correlated strongly with cognitive parameters. CSF neurogranin levels were significantly lower in mild‐to‐moderate Parkinson's disease compared to controls, correlated with amyloid‐β and α‐synuclein, and with motor stage. There was little change in cognition after 2 years, but the cognitive tests that were significantly different, were also significantly associated with cortical metabolism. No such correlations were found in the control group. Interpretation CSF Aβ, α‐synuclein, and neurogranin concentrations are related to cortical metabolism and cognitive decline. Synaptic dysfunction due to Aβ and α‐synuclein dysmetabolism may be central in the evolution of cognitive impairment in Parkinson's disease.

• Zamorano, Mariano Rincón; Díaz-López, Estela; Selnes, Per; Vegge, Kjetil; Altmann, Marianne & Fladby, Tormod [Vis alle 7 forfattere av denne artikkelen] (2017). Improved Automatic Segmentation of White Matter Hyperintensities in MRI Based on Multilevel Lesion Features. Neuroinformatics. ISSN 1539-2791. 15(3), s. 231–245. doi: 10.1007/s12021-017-9328-y. Fulltekst i vitenarkiv
• Kalheim, Lisa Flem; Bjørnerud, Atle; Fladby, Tormod; Vegge, Kjetil & Selnes, Per (2017). White matter hyperintensity microstructure in amyloid dysmetabolism. Journal of Cerebral Blood Flow and Metabolism. ISSN 0271-678X. 37(1), s. 356–365. doi: 10.1177/0271678X15627465. Fulltekst i vitenarkiv
• Digernes, Ingrid; Bjørnerud, Atle; Vatnehol, Svein Are Sirirud; Løvland, Grethe; Courivaud, Fredric A A & Vik-Mo, Einar O. [Vis alle 8 forfattere av denne artikkelen] (2017). A theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast MRI. Journal of Cerebral Blood Flow and Metabolism. ISSN 0271-678X. 37(6), s. 2237–2248. doi: 10.1177/0271678X17694187. Fulltekst i vitenarkiv Vis sammendrag

  Mapping the complex heterogeneity of vascular tissue in the brain is important for understanding cerebrovascular disease. In this translational study, we build on previous work using vessel architectural imaging (VAI) and present a theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast magnetic resonance imaging (MRI). Our tissue model covers realistic structural architectures for vessel branching and orientations, as well as a range of hemodynamic scenarios for blood flow, capillary transit times and oxygenation. In a typical image voxel, our findings show that the apparent MRI relaxation rates are independent of the mean vessel orientation and that the vortex area, a VAI-based parameter, is determined by the relative oxygen saturation level and the vessel branching of the tissue. Finally, in both simulated and patient data, we show that the relative distributions of the vortex area parameter as a function of capillary transit times show unique characteristics in normal-appearing white and gray matter tissue, whereas tumour-voxels in comparison display a heterogeneous distribution. Collectively, our study presents a comprehensive framework that may serve as a roadmap for in vivo and per-voxel determination of vascular status and heterogeneity in cerebral tissue.

• Quintana, Daniel; Elvsåshagen, Torbjørn; Zak, Nathalia; Norbom, Linn Christin Bonaventure; Pedersen, Per Øystein Heiberg & Quraishi, Sophia H. [Vis alle 12 forfattere av denne artikkelen] (2017). Diurnal Variation and twenty-four hour sleep deprivation do not alter supine heart rate variability in healthy male young adults. PLOS ONE. 12:e0170921(2), s. 1–16. doi: 10.1371/journal.pone.0170921. Fulltekst i vitenarkiv Vis sammendrag

  Heart rate variability (HRV) has become an increasingly popular index of cardiac autonomic control in the biobehavioral sciences due to its relationship with mental illness and cognitive traits. However, the intraindividual stability of HRV in response to sleep and diurnal disturbances, which are commonly reported in mental illness, and its relationship with executive function are not well understood. Here, in 40 healthy adult males we calculated high frequency HRV-an index of parasympathetic nervous system (PNS) activity-using pulse oximetry during brain imaging, and assessed attentional and executive function performance in a subsequent behavioral test session at three time points: morning, evening, and the following morning. Twenty participants were randomly selected for total sleep deprivation whereas the other 20 participants slept as normal. Sleep deprivation and morning-tonight variation did not influence high frequency HRV at either a group or individual level; however, sleep deprivation abolished the relationship between orienting attention performance and HRV. We conclude that a day of wake and a night of laboratory-induced sleep deprivation do not alter supine high frequency HRV in young healthy male adults.

• Elvsåshagen, Torbjørn; Zak, Nathalia; Norbom, Linn Christin Bonaventure; Pedersen, Per Øystein Heiberg; Quraishi, Sophia H. & Bjørnerud, Atle [Vis alle 11 forfattere av denne artikkelen] (2017). Evidence for cortical structural plasticity in humans after a day of waking and sleep deprivation. NeuroImage. ISSN 1053-8119. 156, s. 214–223. doi: 10.1016/j.neuroimage.2017.05.027. Fulltekst i vitenarkiv
• Grøvik, Endre; Redalen, Kathrine Røe; Storås, Tryggve; Negard, Anne; Holmedal, Stein Harald & Ree, Anne Hansen [Vis alle 9 forfattere av denne artikkelen] (2017). Dynamic multi-echo DCE- and DSC-MRI in rectal cancer: Low primary tumor Ktrans and ΔR2* peak are significantly associated with lymph node metastasis. Journal of Magnetic Resonance Imaging. ISSN 1053-1807. 46(1), s. 194–206. doi: 10.1002/jmri.25566. Fulltekst i vitenarkiv Vis sammendrag

  Purpose: To implement a dynamic contrast-based multi-echo MRI sequence in assessment of rectal cancer and evaluate associations between histopathologic data and the acquired dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) -MRI parameters. Materials and Methods: This pilot study reports results from 17 patients with resectable rectal cancer. Dynamic contrast-based multi-echo MRI (1.5T) was acquired using a three-dimensional multi-shot EPI sequence, yielding both DCE- and DSC-data following a single injection of contrast agent. The Institutional Review Board approved the study and all patients provided written informed consent. Quantitative analysis was performed by pharmacokinetic modeling on DCE data and tracer kinetic modeling on DSC data. Mann-Whitney U-test and receiver operating characteristics curve statistics was used to evaluate associations between histopathologic data and the acquired DCE- and DSC-MRI parameters. Results: For patients with histologically confirmed nodal metastasis, the primary tumor demonstrated a significantly lower Ktrans and peak change in R 2, R 2-peakenh, than patients without nodal metastasis, showing a P-value of 0.010 and 0.005 for reader 1, and 0.043 and 0.019 for reader 2, respectively. Conclusion: This study shows the feasibility of acquiring DCE- and DSC-MRI in rectal cancer by dynamic multi-echo MRI. A significant association was found between both Ktrans and R 2-peakenh in the primary tumor and histological nodal status of the surgical specimen, which may improve stratification of patients to intensified multimodal treatment.

• Langleite, Torgrim Mikal; Jensen, Jørgen; Norheim, Frode; Gulseth, Hanne Løvdal; Tangen, Daniel S. & Kolnes, Kristoffer Jensen [Vis alle 19 forfattere av denne artikkelen] (2016). Insulin sensitivity, body composition and adipose depots following 12 w combined endurance and strength training in dysglycemic and normoglycemic sedentary men. Archives of Physiology and Biochemistry. ISSN 1381-3455. 122(4), s. 167–179. doi: 10.1080/13813455.2016.1202985. Fulltekst i vitenarkiv
• Hope, Tuva Roaldsdatter; White, Nathan S.; Kuperman, Joshua; Chao, Ying; Yamin, Ghiam & Bartch, Hauke [Vis alle 13 forfattere av denne artikkelen] (2016). Demonstration of non-gaussian restricted diffusion in tumor cells using diffusion time-dependent diffusion-weighted magnetic resonance imaging contrast. Frontiers in Oncology. 6:179. doi: 10.3389/fonc.2016.00179. Fulltekst i vitenarkiv Vis sammendrag

  The diffusion-weighted magnetic resonance imaging (DWI) technique enables quantification of water mobility for probing microstructural properties of biological tissue and has become an effective tool for collecting information about the underlying pathology of cancerous tissue. Measurements using multiple b-values have indicated biexponential signal attenuation, ascribed to “fast” (high ADC) and “slow” (low ADC) diffusion components. In this empirical study, we investigate the properties of the diffusion time (Δ)-dependent components of the diffusion-weighted (DW) signal in a constant b-value experiment. A xenograft gliobastoma mouse was imaged using Δ = 11 ms, 20 ms, 40 ms, 60 ms, and b = 500–4000 s/mm2 in intervals of 500 s/mm2. Data were corrected for EPI distortions, and the Δ-dependence on the DW-signal was measured within three regions of interest [intermediate- and high-density tumor regions and normal-appearing brain (NAB) tissue regions]. In this study, we verify the assumption that the slow decaying component of the DW-signal is non-Gaussian and dependent on Δ, consistent with restricted diffusion of the intracellular space. As the DW-signal is a function of Δ and is specific to restricted diffusion, manipulating Δ at constant b-value (cb) provides a complementary and direct approach for separating the restricted from the hindered diffusion component. We found that Δ-dependence is specific to the tumor tissue signal. Based on an extended biexponential model, we verified the interpretation of the diffusion time-dependent contrast and successfully estimated the intracellular restricted ADC, signal volume fraction, and cell size within each ROI.

• Walhovd, Kristine B; Krogsrud, Stine Kleppe; Amlien, Inge Kasbohm; Bartsch, Hauke; Bjørnerud, Atle & Due-Tønnessen, Paulina [Vis alle 22 forfattere av denne artikkelen] (2016). Neurodevelopmental origins of lifespan changes in brain and cognition. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 113(33), s. 9357–9362. doi: 10.1073/pnas.1524259113. Fulltekst i vitenarkiv Vis sammendrag

  Neurodevelopmental origins of functional variation in older age are increasingly being acknowledged, but identification of how early factors impact human brain and cognition throughout life has remained challenging. Much focus has been on age-specific mechanisms affecting neural foundations of cognition and their change. In contrast to this approach, we tested whether cerebral correlates of general cognitive ability (GCA) in development could be extended to the rest of the lifespan, and whether early factors traceable to prenatal stages, such as birth weight and parental education, may exert continuous influences. We measured the area of the cerebral cortex in a longitudinal sample of 974 individuals aged 4–88 y (1,633 observations). An extensive cortical region was identified wherein area related positively to GCA in development. By tracking area of the cortical region identified in the child sample throughout the lifespan, we showed that the cortical change trajectories of higher and lower GCA groups were parallel through life, suggesting continued influences of early life factors. Birth weight and parental education obtained from the Norwegian Mother–Child Cohort study were identified as such early factors of possible life-long influence. Support for a genetic component was obtained in a separate twin sample (Vietnam Era Twin Study of Aging), but birth weight in the child sample had an effect on cortical area also when controlling for possible genetic differences in terms of parental height. Our results provide novel evidence for stability in brain–cognition relationships throughout life, and indicate that early life factors impact brain and cognition for the entire life course.

• Kalheim, Lisa Flem; Selnes, Per; Bjørnerud, Atle; Coello, Christopher; Vegge, Kjetil & Fladby, Tormod (2016). Amyloid dysmetabolism relates to reduced glucose uptake in white matter hyperintensities. Frontiers in Neurology. 7. doi: 10.3389/fneur.2016.00209. Fulltekst i vitenarkiv
• Berg, Anna; Fasmer, Kristine Eldevik; Mauland, Karen Klepsland; Ytre-Hauge, Sigmund; Høivik, Erling Andre & Husby, Jenny Hild Aase [Vis alle 16 forfattere av denne artikkelen] (2016). Tissue and imaging biomarkers for hypoxia predict poor outcome in endometrial cancer. OncoTarget. 7(43), s. 69844–69856. doi: 10.18632/oncotarget.12004. Fulltekst i vitenarkiv Vis sammendrag

  Hypoxia is frequent in solid tumors and linked to aggressive phenotypes and therapy resistance. We explored expression patterns of the proposed hypoxia marker HIF-1α in endometrial cancer (EC) and investigate whether preoperative functional imaging parameters are associated with tumor hypoxia. Expression of HIF-1α was explored both in the epithelial and the stromal tumor component. We found that low epithelial HIF-1α and high stromal HIF-1α expression were significantly associated with reduced disease specific survival in EC. Only stromal HIF-1α had independent prognostic value in Cox regression analysis. High stromal HIF-1α protein expression was rare in the premalignant lesions of complex atypical hyperplasia but increased significantly to invasive cancer. High stromal HIF-1α expression was correlated with overexpression of important genes downstream from HIF-1α, i.e. VEGFA and SLC2A1 (GLUT1). Detecting hypoxic tumors with preoperative functional imaging might have therapeutic benefits. We found that high stromal HIF-1α expression associated with high total lesion glycolysis (TLG) at PET/CT. High expression of a gene signature linked to hypoxia also correlated with low tumor blood flow at DCE-MRI and increased metabolism measured by FDG-PET. PI3K pathway inhibitors were identified as potential therapeutic compounds in patients with lesions overexpressing this gene signature. In conclusion, we show that high stromal HIF-1α expression predicts reduced survival in EC and is associated with increased tumor metabolism at FDG-PET/CT. Importantly; we demonstrate a correlation between tissue and imaging biomarkers reflecting hypoxia, and also possible treatment targets for selected patients.

• Stav, Ane Løvli; Johansen, Krisztina Kunszt; Auning, Eirik; Kalheim, Lisa Flem; Selnes, Per & Bjørnerud, Atle [Vis alle 9 forfattere av denne artikkelen] (2016). Hippocampal subfield atrophy in relation to cerebrospinal fluid biomarkers and cognition in early Parkinson’s disease: a cross-sectional study. NPJ Parkinson's Disease. 2. doi: 10.1038/npjparkd.2015.30. Fulltekst i vitenarkiv
• Usinskiene, Jurgita; Ulyte, Agne; Bjørnerud, Atle; Venius, Jonas; Katsaros, Vasileios K. & Rynkeviciene, Ryte [Vis alle 12 forfattere av denne artikkelen] (2016). Optimal differentiation of high- and low-grade glioma and metastasis: a meta-analysis of perfusion, diffusion, and spectroscopy metrics. Neuroradiology. ISSN 0028-3940. 58(4), s. 339–350. doi: 10.1007/s00234-016-1642-9. Fulltekst i vitenarkiv
• Skurdal, Mikjel Johannes; Bjørnerud, Atle; Osch, Matthias J.P. Van; Nordhøy, Wibeke; Lagopoulos, Jim & Groote, Inge Rasmus (2015). Voxel-wise perfusion assessment in cerebral white matter with PCASL at 3T; Is it possible and how long does it take? PLOS ONE. 10:e0135596(8). doi: 10.1371/journal.pone.0135596. Fulltekst i vitenarkiv Vis sammendrag

  Purpose To establish whether reliable voxel-wise assessment of perfusion in cerebral white matter (WM) is possible using arterial spin labeling (ASL) at 3T in a cohort of healthy subjects. Materials and Methods Pseudo-continuous ASL (PCASL) with background suppression (BS) optimized for WM measurements was performed at 3T in eight healthy male volunteers aged 25–41. Four different labeling schemes were evaluated by varying the labeling duration (LD) and post-labeling delay (PLD). Eight slices with voxel dimension 3.75x3.75x5 mm3 were acquired from the anterosuperior aspect of the brain, and 400 image/control pairs were collected for each run. Rigid head immobilization was applied using individually fitted thermoplastic masks. For each voxel in the resulting ASL time series, the time needed to reach a 95% significance level for the ASL signal to be higher than zero (paired t-test), was estimated. Results The four protocols detected between 88% and 95% (after Bonferroni correction: 75% and 88%) of WM voxels at 95% significance level. In the most efficient sequence, 80% was reached after 5 min and 95% after 53 min (after Bonferroni correction 40% and 88% respectively). For all protocols, the fraction of significant WM voxels increased in an asymptotic fashion with increasing scan time. A small subgroup of voxels was shown to not benefit at all from prolonged measurement. Conclusion Acquisition of a significant ASL signal from a majority of WM voxels is possible within clinically acceptable scan times, whereas full coverage needs prohibitively long scan times, as a result of the asymptotic trajectory.

Se alle arbeider i NVA

• Li, Jingpeng; He, Sheng; Bao, Rina; Bjørnerud, Atle; Grant, Ellen & Ou, Yangming (2025). Using Off-Target-Disease Data to Improve Target-Disease Lesion Segmentation. IEEE International Symposium on Biomedical Imaging. ISSN 1945-7928. doi: 10.1109/ISBI60581.2025.10981230. Fulltekst i vitenarkiv
• Grødem, Edvard Olaf Sætersdal; Vidal-Piñeiro, Didac; Sørensen, Øystein; Garrido, Pablo F.; Nyberg, Lars Erik & Walhovd, Kristine B [Vis alle 8 forfattere av denne artikkelen] (2025). Distinguishing Lifelong Individual Differences from Divergent Aging Trajectories of Adult Brain Volumes. bioRxiv (preprint article). 2025.05.26.655710. doi: 10.1101/2025.05.26.655710. Fulltekst i vitenarkiv
• Padrela, Beatriz; Mahroo, Amnah; Tee, Mervin; Sneve, Markus Handal; Moyaert, Paulien & Geier, Oliver [Vis alle 43 forfattere av denne artikkelen] (2024). Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol. BMJ Open. 14(3). doi: 10.1136/bmjopen-2023-081635. Fulltekst i vitenarkiv Vis sammendrag

  Introduction Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer’s disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD). Methods and analysis DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and AD-related pathologies. Ethics and dissemination Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.

• Voldsbekk, Irene; Groote, Inge Rasmus; Zak, Nathalia; Roelfs, Daniël; Geier, Oliver & Due-Tønnessen, Paulina [Vis alle 14 forfattere av denne artikkelen] (2023). Corrigendum to “Sleep and sleep deprivation differentially alter white matter microstructure: A mixed model design utilising advanced diffusion modelling”. NeuroImage. ISSN 1053-8119. 270. doi: 10.1016/j.neuroimage.2023.119939. Fulltekst i vitenarkiv
• Bakke, Kine Mari; Meltzer, Sebastian; Grøvik, Endre; Negård, Anne; Holmedal, Stein Harald & Lyckander, Lars Gustav [Vis alle 11 forfattere av denne artikkelen] (2022). Imaging the tumor microenvironment in rectal cancer: Decline in tumor blood flow (BF) during neoadjuvant treatment predicts excellent outcome. Cancer Research. ISSN 0008-5472. 82. doi: 10.1158/1538-7445.AM2022-5269. Fulltekst i vitenarkiv
• Brandis, Elisabeth von; Avenarius, Derk Frederik Matthaus; Bjørnerud, Atle; Flatø, Berit; Tomterstad, Anders & Lilleby, Vibke [Vis alle 11 forfattere av denne artikkelen] (2022). Correction to: Automated segmentation of magnetic resonance bone marrow signal: a feasibility study (Pediatric Radiology, (2022), 10.1007/s00247-021-05270-x). Pediatric Radiology. ISSN 0301-0449. 52. doi: 10.1007/s00247-022-05315-9. Fulltekst i vitenarkiv
• Due-Tønnessen, Paulina; Pinho, Marco C.; Emblem, Kyrre E; Hald, John K; Kanoto, Masafumi & Abildgaard, Andreas [Vis alle 10 forfattere av denne artikkelen] (2021). Author Correction: The Impact of MRI Features and Observer Confidence on the Treatment Decision-Making for Patients with Untreated Glioma (Scientific Reports, (2019), 9, 1, (19898), 10.1038/s41598-019-56333-x). Scientific Reports. 11(1). doi: 10.1038/s41598-021-99776-x. Fulltekst i vitenarkiv
• Tomasgard, Jørn-Arne; Gjesdal, Kjell Inge; Grøvik, Endre & Bjørnerud, Atle (2021). Kan avsløre kreft raskere. [Journal]. Teknisk ukeblad. Fulltekst i vitenarkiv Vis sammendrag

  Forskerne Kjell-Inge Gjesdal og Endre Grøvik mener de har utviklet en metode som gjør at kvinner kan slippe å vente to uker på diagnose ved funn av svulst i bryst

• Vardal, Jonas; Garcia, Elies Fuster i; Groote, Inge Rasmus; Larsson, Christopher & Bjørnerud, Atle (2020). Efficiency of deep learning on segmenting longitudinal postoperative glioblastomas. Fulltekst i vitenarkiv
• Voldsbekk, Irene; Roelfs, Daniël Thomas Heimen; Bjørnerud, Atle; Groote, Inge Rasmus & Maximov, Ivan (2019). White matter microstructure changes as a function of time-of-day: a biomarker of accumulating sleep pressure? Fulltekst i vitenarkiv
• Abildgaard, Andreas; Hopp, Einar; Sakinis, Tomas; Roterud, Håvard; Bjørnerud, Atle & Beyer, Mona K. [Vis alle 7 forfattere av denne artikkelen] (2018). Vil radiologer bli erstattet av kunstig intelligens? 138(17). doi: 10.4045/tidsskr.18.0587. Fulltekst i vitenarkiv
• Grøvik, Endre; Redalen, Kathrine Røe; Storås, Tryggve; Holmedal, Stein Harald; Negard, Anne & Ree, Anne Hansen [Vis alle 9 forfattere av denne artikkelen] (2017). Improved sensitivity for rectal cancer differentiation by T2*-correction in DCE-MRI. Fulltekst i vitenarkiv
• Usinskiene, Jurgita; Ulyte, Agne; Bjørnerud, Atle; Venius, Jonas; Katsaros, Vasileios K. & Rynkeviciene, Ryte [Vis alle 12 forfattere av denne artikkelen] (2016). Erratum to: Optimal differentiation of high- and low-grade glioma and metastasis: a meta-analysis of perfusion, diffusion, and spectroscopy metrics. Neuroradiology. ISSN 0028-3940. 58(7), s. 741–741. doi: 10.1007/s00234-016-1702-1. Fulltekst i vitenarkiv
• Grødem, Edvard Olaf Sætersdal; Fjell, Anders Martin; Bjørnerud, Atle; MacIntosh, Bradley & Edin, Nina Frederike Jeppesen (2025). Characterizing Brain MRI with Machine Learning Methods with Applications to Alzheimer’s Disease. Universitetet i Oslo. Fulltekst i vitenarkiv Vis sammendrag

  The human brain undergoes lifelong structural changes that reflect both normal aging and pathological processes. Alzheimer’s disease (AD) is neurodegenerative disorder that causes pronounced structural changes in the brain in the form of atrophy. In AD, patients’ cognitive function is permanently reduced, and treatment options are limited. Magnetic resonance imaging (MRI) makes it possible to observe these structural changes in vivo. Over the past twenty years, large open imaging databases (e.g., the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and UK Biobank) have enabled studies involving tens of thousands of participants. At the same time, there have been major advances in machine-learning methods, for example in deep learning, Bayesian statistics and image processing. Together, large databases and new machine-learning techniques open up deeper insights into the brain’s evolving anatomy. Nevertheless, challenges remain. There is considerable inter-individual anatomical differences, and distinguishing natural variation from pathology can be difficult. The MRI data themselves present additional hurdles: the mages are large three-dimensional scans that must be processed to obtain measurable quantities such as regional volume and cortical thickness. Although the imaging databases are extensive, scans often originate from many different scanners, leading to contrast differences that complicate direct comparisons. In longitudinal studies, the morphological changes of interest are often smaller than the measurement noise. Consequently, new methods are needed to analyze changes in brain MRI reliably. In this thesis, the aim is to develop and improve machine-learning methods for analyzing brain MRI. These methods are intended to quantify changes in brain structures, to characterize the brain’s Natural development across the lifespan and to diagnose AD. The work comprises three papers. In Paper I we use deep learning to diagnose Alzheimer’s disease from brain MRI. We investigate how the architecture of the deep convolutional network influences the classification outcome. MRI scans of individuals with AD and healthy controls from ADNI serve as material. We find that more complex and deeper architectures such as EfficientNet do not outperform simpler and shallower architectures such as the Simple Fully Convolutional Network (SFCN). Further analyses show that SFCN can be scaled down to very small sizes while still providing strong results. These findings indicate that straightforward preprocessing combined with simple convolutional networks yields classification performance comparable to the more elaborate methods reported in the literature. In Paper II we study volume changes of various brain structures across the lifespan. We aim to determine when there are individual changes in the brain due to normal aging and to what extent these can be estimated at the individual level. A large dataset of longitudinal brain MRI collected from 14 studies is employed. We model the volume of the brain structures as a stochastic dynamical system and fit the model to the data using a Markov chain Monte Carlo approach. The results show that the brain changes throughout life, but up to the age of 50 there are only small individual differences in the rate of change. After 50 years we observe greater individual variation. From the model we calculate the explained variance from the structure volume at age 18 to the volume later in life, finding that up to 60 years almost all variance is explained by the young-adult volume. The lateral ventricles stand out: here, individual variation in change persists throughout life. We further estimate how accurately individual change can be inferred for single subjects. For individuals under 50 years there is virtually no correlation between an estimated change and the actual individualchange; after 50 years this correlation increases with age. Increasing the interval between volume measurements effectively increases this correlation, whereas adding more measurements within a given interval has a smaller effect. Paper III examines medical image-registration algorithms, in which a deformation field that aligns two images is estimated so that anatomically identical regions overlap. This can be used both to compare images across individuals and to study anatomical changes over time. Registration is often performed by minimising the image-similarity loss Local Normalised Cross-Correlation (LNCC). We show that using LNCC can lead to erroneous deformation estimates in homogeneous regions where noise dominates the signal. Two new variants are proposed: Regularized-LNCC (R-LNCC) and Weighted-LNCC (W-LNCC). We use real MRI from a wide range of scanners and generate synthetic deformations to test how well the similarity metrics recover them. LNCC produces incorrect deformation estimates in low-variance regions, whereas R-LNCC and W-LNCC resolve this issue. We also find that R-LNCC generally yields significantly better deformation estimates than LNCC, even in more heterogeneous regions. Together, Papers I, II and III constitute a framework for studying changes in the brain. Our aim is that these tools will be utilized to better understand Alzheimer’s disease and promote healthy aging.

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