Meeting Banner
Abstract #2238

A Novel Events-Based Model for Mapping Disease Progression & Its Application to Familial Alzheimer's Disease

Hubert Martinus Fonteijn1, Matt J. Clarkson2, Marc Modat1, Josephine Barnes2, Manja Lehmann2, Sebastien Ourselin1, Nick C. Fox2, Daniel C. Alexander1

1Computer Science, Centre for Medical Image Computing, London, United Kingdom; 2Institute of Neurology, Dementia Research Centre, London, United Kingdom

This abstract introduces a novel method for studying disease progression using cross-sectional data. The model describes disease progression as a series of events and treats each data point as a snapshot of this series. We calculate the probability that an event has happened and use a MCMC algorithm to construct plausible series of events from this probability. We demonstrate our model on serial T1 MRI data from a familial Alzheimers disease cohort. We calculate regional atrophy using non-linear registration methods and show progression of atrophy on a much finer level than previous studies, confirming progression patterns from pathological studies.