Patient-Tailored, Connectivity-Based Forecasts of Spreading Brain Atrophy

Abstract

Neurodegenerative diseases appear to progress by spreading via brain connections. Here we evaluated this transneuronal degeneration hypothesis by attempting to predict future atrophy in a longitudinal cohort of patients with behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA). We determined patient-specific "epicenters" at baseline, located each patient's epicenters in the healthy functional connectome, and derived two region-wise graph theoretical metrics to predict future atrophy: (1) shortest path length to the epicenter and (2) nodal hazard, the cumulative atrophy of a region's first-degree neighbors. Using these predictors and baseline atrophy, we could accurately predict longitudinal atrophy in most patients. The regions most vulnerable to subsequent atrophy were functionally connected to the epicenter and had intermediate levels of baseline atrophy. These findings provide novel, longitudinal evidence that neurodegeneration progresses along connectional pathways and, further developed, could lead to network-based clinical tools for prognostication and disease monitoring.

Network-based atrophy modelling in the common epilepsies: a worldwide ENIGMA study

“…To elucidate how grey matter atrophy targets hub regions in TLE and IGE, we tested the hypothesis that the underlying connectivity of specific regions-or epicenters-constrains syndrome-specific patterns of atrophy. Other neuroimaging studies of psychiatric and neurodegenerative diseases have employed epicenter mapping techniques to track and predict the spread of atrophy in individual patients (Brown et al, 2019) and disease cohorts (Raj et al, 2012;Shafiei et al, 2019;Zhou et al, 2012). Critically, each epilepsy syndrome harbored distinct epicenters and reflected its own pathophysiology: temporo-limbic cortical regions, ipsilateral to the seizure focus, emerged as epicenters of atrophy in TLE, while fronto-central cortices were identified as disease epicenters in IGE.…”

Genetic, Cellular, and Connectomic Characterization of the Adult Human Brain Regions Commonly Plagued by Glioma

“…An extensive body of work has demonstrated the utility of network models in predicting the spread of disease [53][54][55] as well as the vulnerability of particular brain regions to disease 14,15,17 . In this work, we use network models for the latter purpose and demonstrate for the first time that gliomas localize to hub regions of the brain, similar to other neuropsychiatric illnesses.…”

Cerebral Atrophy in Amyotrophic Lateral Sclerosis Parallels the Pathological Distribution of TDP43

“…To investigate brain changes related to ALS in relation to the confounds of normative aging as well as sex differences, a regression procedure was developed involving the images from the age-matched controls, as similarly performed in previous studies (La Joie et al, 2012;Moradi et al, 2015;Zeighami et al, 2017;Brown et al, 2019)). The following voxel-wise mixed effects models were estimated based on the controls:…”

“…eq. 1), also referred to in the literature as a W-score map (La Joie et al, 2012;Brown et al, 2019). The resulting maps were corrected for multiple comparisons using False Discovery Rate (FDR) with a significance threshold of 0.05.…”