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

Neuron. 2019 Dec 4;104(5):856-868.e5. doi: 10.1016/j.neuron.2019.08.037. Epub 2019 Oct 14.


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.

Keywords: brain networks; frontotemporal dementia; functional connectivity; graph theory; neurodegeneration; voxel-based morphometry.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Atrophy / pathology
  • Atrophy / physiopathology
  • Brain / pathology*
  • Brain / physiopathology
  • Female
  • Frontotemporal Dementia / pathology*
  • Frontotemporal Dementia / physiopathology
  • Humans
  • Male
  • Middle Aged
  • Models, Neurological*
  • Nerve Degeneration / pathology*
  • Nerve Degeneration / physiopathology
  • Neural Pathways / pathology*
  • Neural Pathways / physiopathology