DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders

Publication date: Available online 4 March 2019Source: NeuroImageAuthor(s): Răzvan V. Marinescu, Arman Eshaghi, Marco Lorenzi, Alexandra L. Young, Neil P. Oxtoby, Sara Garbarino, Sebastian J. Crutch, Daniel C. Alexander, for the Alzheimer's Disease Neuroimaging InitiativeAbstractCurrent models of progression in neurodegenerative diseases use neuroimaging measures that are averaged across pre-defined regions of interest (ROIs). Such models are unable to recover fine details of atrophy patterns; they tend to impose an assumption of strong spatial correlation within each ROI and no correlation among ROIs. Such assumptions may be violated by the influence of underlying brain network connectivity on pathology propagation – a strong hypothesis e.g. in Alzheimer's Disease. Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-term patterns of brain pathology from short-term longitudinal data sets. DIVE clusters vertex-wise (i.e. point-wise) biomarker measurements on the cortical surface that have similar temporal dynamics across a patient population, and concurrently estimates an average trajectory of vertex measurements in each cluster. DIVE uniquely outputs a parcellation of the cortex into areas with common progression patterns, leading to a new signature for individual diseases. DIVE further estimates the disease stage and progression speed for every vis...

Source: NeuroImage - March 9, 2019 Category: Neuroscience Source Type: research