Disputas: Lars Magnus Valnes
M.Sc. Lars Magnus Valnes ved Matematisk institutt vil forsvare sin avhandling for graden ph.d.
Patient-specific Modeling of the Human Brain using Magnetic Resonance Imaging
Lars Magnus Valnes
Tid og sted for prøveforelesning
Professor Marcela Szopos, Université Paris Descartes and CNRS
Associate Professor Erik Andreas Hanson, Universitetet i Bergen
Professor Karsten Trulsen, Universitetet i Oslo
Leder av disputas
Instituttleder Geir Dahl, Matematisk institutt, Universitet i Oslo
Professor Kent-Andre Mardal, Matematisk institutt, Universitet i Oslo
PhD Erika Lindstrøm, Forsvarets Forskningsinstitutt
Chief research scientist Marie Elisabeth Rognes, Simula Research Laboratory
Professor Per Kristian Eide, Institutt for klinisk medisin, Universitet i Oslo
Førsteamanuensis Unn Kristin H. Haukvik, Institutt for klinisk medisin, Universitet i Oslo
Dementia is a growing concern for the health-care in the world and most treatment strategies are not successful. Dementia is associated with accumulation of metabolic waste in the form of protein fragments. Recent breakthroughs have suggested that the accumulation of waste is caused by malfunction of clearance mechanism, called the glymphatic system, that provides bulk flow through the extracellular matrix. To what extent this system accelerates transport provided by extracellular diffusion, is an open question. Recent research also shows that transport can be accelerated during sleep and by deep breathing.
In this work, I have investigated the enrichment and clearance of a tracer in the brain using magnetic resonance imaging (MRI), developed methods for constructing computational geometries from MRI and evaluated the tracer diffusion using patient-specific computational simulations. The medical data used in this study are novel imaging recently performed at Rikshopspitalet where MRI tracer was administrated into fluid compartment along the spine and transported up and into the brain. Based on these data I have analyzed the tracer movement, and observed that the tracer had a brain-wide distribution. Additionally, this thesis aims to provide methodology and software tools for constructing computational geometries from brain MRI in a patient-specific manner. In particular, I have solved PDE constrained optimization problems with finite elements to assess the efficiency of the transport mechanism in a patient-specific manner.
Compared to controls, in the patients with dementia the tracers demonstrated a slower clearance. Thus suggesting a brain-wide clearance system and an impairment in the waste-removal in dementia. Additionally, these observations may provide the possibility for a new and more effective method for administrating medicine to the brain. Diffusion coefficients were found to be higher than the expected, henceforth diffusion alone does not explain the clearance of waste from the brain.
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