Keywords: Aging, Aging, LATE, TDP-43, Neuropathology, Aging, Biomarkers, Brain, Neurodegeneration, Diagnosis/Prediction, Ex-vivo Applications, Machine Learning/Artificial Intelligence, Dementia
Motivation: Limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is common in older adults but lacks a validated biomarker.
Goal(s): To develop an MRI-based in-vivo marker of LATE-NC.
Approach: An MRI-based classifier of LATE-NC was trained using machine learning on ex-vivo MRI and pathology data on the same community-based older adults, was translated to in-vivo, and packaged into an automated software container named ‘MARBLE’ (MARker of Brain LatE) which takes raw in-vivo MRI data as input and provides a LATE-NC prediction score.
Results: The ex-vivo classifier achieved a mean AUC=0.85±0.05 in the training group (N=863). In-vivo, MARBLE achieved an AUC=0.81 in the test group (N=60).
Impact: LATE-NC is common in older adults and can only be diagnosed at autopsy. MARBLE is a novel in-vivo marker of LATE-NC and may significantly contribute towards diagnosis, monitoring, prevention, and treatment of this devastating disease.
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