Introducing Beyond FA: Crowdsourcing Imaging Biomarkers for Alzheimer’s Disease

Elyssa M. McMaster, Nancy Newlin, Trent Schwartz, Adam M. Saunders, Gaurav Rudravaram, Yehyun Suh, Jongyeon Yoon, Michael Eugene Kim, Chloe Cho, Karthik Ramadass, Yihao Liu, Lianrui Zuo, Eleftherios Garyfallidis, Talia M. Nir, Neda Jahanshad, Kurt Schilling, Daniel Moyer, Bennett Allan Landman

Keywords: Diffusion MRI, harmonization, microstructure, tractography, connectome, feature extraction

TL;DR: We propose a challenge to compare white matter metrics and their association with Alzheimer's Disease.

Abstract:

The inclusion of diffusion weighted magnetic resonance imaging (DW-MRI) in neuroimaging
studies has enabled deeper understanding of white matter structure of the human brain.
Fractional anisotropy (FA), a commonly used metric for assessing white matter integrity,
offers high sensitivity but often suffers from low specificity in detecting pathology. FA’s
limitations as a biomarker are often reflected in its inconsistency across different age
groups and disease stages, especially in heterogeneous populations. With the emergence
of alternative white matter models and metrics—such as complex network measures and
tract-specific tractography—researchers now have access to various methods for assessing
white matter integrity, especially in the context of lower-quality and heterogeneous data.
Given the growing number of white matter models and metrics, there is a pressing need
to explore and evaluate these metrics in order to move beyond the constraints of FA. To
address this, we introduce Beyond FA, an open challenge that invites teams to submit the
imaging biomarker(s) of their choice. The goal is to compare and gain deeper understanding
of white matter metrics and their association with Alzheimer’s Disease (AD).

Submission Number: 34