Data-driven simulation of network-based tau spreading tailored to individual Alzheimer's patients

Citations

SCOPUS

0

초록

"Tau tangles in the brain cortex spread along the brain network in distinct patterns among Alzheimer's patients. We aim to simulate their network-based spreading within the cortex, tailored to each individual along the Alzheimer's continuum, without assuming any assumptions about the network architecture. A group-level intrinsic spreading network was constructed to model the pathways for the proximal and distal spreading of tau tangles by optimizing the biophysical model based on a discovery dataset of longitudinal tau positron emission tomography images for 78 amyloid-positive individuals. Group-level spreading parameters were also obtained and subsequently adjusted to produce individuated tau trajectories. By simulating these individuated tau spreading models for every individual in the discovery dataset, we successfully captured proximal and distal tau spreading, allowing reliable inferences about the underlying mechanism of tau spreading. Simulating the models also allowed highly accurate prediction of future tau topography for both discovery and independent validation datasets. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

키워드

Alzheimer's disease; Data-driven approach; Individuated tau spreading model; Longitudinal dataset; Network reaction–diffusion system; Tau positron emission tomography
제목
Data-driven simulation of network-based tau spreading tailored to individual Alzheimer's patients
저자
Kim, Sung-Woo; Cho, Hanna; Lee, Yeonjeong; Lyoo, Chul Hyoung; Seong, Joon-Kyung
DOI
10.1007/s00366-024-01988-y
발행일
2025-02
유형
Article in press
저널명
Engineering with Computers
권
41
호
1
페이지
159 ~ 177