Localizing Sources of Brain Disease Progression with Network Diffusion Model

IEEE Journal of Selected Topics in Signal Processing
Chenhui HuQuanzheng Li

Abstract

Pinpointing the sources of dementia is crucial to the effective treatment of neurodegenerative diseases. In this paper, we propose a diffusion model with impulsive sources over the brain connectivity network to model the progression of brain atrophy. To reliably estimate the atrophy sources, we impose sparse regularization on the source distribution and solve the inverse problem with an efficient gradient descent method. We localize the possible origins of Alzheimer's disease (AD) based on a large set of repeated magnetic resonance imaging (MRI) scans in Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The distribution of the sources averaged over the sample population is evaluated. We find that the dementia sources have different concentrations in the brain lobes for AD patients and mild cognitive impairment (MCI) subjects, indicating possible switch of the dementia driving mechanism. Moreover, we demonstrate that we can effectively predict changes of brain atrophy patterns with the proposed model. Our work could help understand the dynamics and origin of dementia, as well as monitor the progression of the diseases in an early stage.

Citations

Feb 7, 2018·Brain : a Journal of Neurology·Justin TorokAshish Raj
Mar 7, 2019·Frontiers in Neuroinformatics·Artemis Zavaliangos-PetropuluPaul M Thompson
May 29, 2019·Brain : a Journal of Neurology·Jeffrey S PhillipsMurray Grossman
Dec 31, 2020·Neuromodulation : Journal of the International Neuromodulation Society·Jordan LamDarrin J Lee
Feb 23, 2021·Network Neuroscience·Arseny A SokolovKarl J Friston
Sep 2, 2018·Biological Psychiatry : Cognitive Neuroscience and Neuroimaging·Ashish Raj, Fon Powell

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