Simulating Patient Specific Multiple Time-point MRIs From a Biophysical Model of Brain Deformation in Alzheimer's Disease

Abstract : This paper proposes a framework to simulate patient specific structural Magnetic Resonance Images (MRIs) from the available MRI scans of Alzheimer’s Disease(AD) subjects. We use a biophysical model of brain deformation due to atrophy that can generate biologically plausible deformation for any given desired volume changes at the voxel level of the brain MRI. Large number of brain regions are segmented in 45 AD patients and the atrophy rates per year are estimated in these regions from the available two extremal time-point scans. Assuming linear progression of atrophy, the volume changes in scans closest to the half way time period is computed. These atrophy maps are prescribed to the baseline images to simulate the middle time-point images by using the biophysical model of brain deformation. From the baseline scans, the volume changes in real middle time-point scans are compared to the ones in simulated middle time-point images. This present framework also allows to introduce desired atrophy patterns at different time-points to simulate non-linear progression of atrophy. This opens a way to use a biophysical model of brain deformation to evaluate methods that study the temporal progression and spatial relationships of atrophy of different regions in the brain with AD.
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Communication dans un congrès
Workshop on Computational Biomechanics for Medicine - X, Oct 2015, Munich, France. Springer International Publishing, pp.167--176, 2015, Computational Biomechanics for Medicine: Imaging, Modeling and Computing. 〈10.1007/978-3-319-28329-6_15〉
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Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, Xavier Pennec. Simulating Patient Specific Multiple Time-point MRIs From a Biophysical Model of Brain Deformation in Alzheimer's Disease. Workshop on Computational Biomechanics for Medicine - X, Oct 2015, Munich, France. Springer International Publishing, pp.167--176, 2015, Computational Biomechanics for Medicine: Imaging, Modeling and Computing. 〈10.1007/978-3-319-28329-6_15〉. 〈hal-01217080〉

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