HMP Global November 11, 2024
A new study published in Neurology aimed to differentiate age-related brain changes from multiple sclerosis (MS)-specific neurodegeneration using MRI. The study proposed a disease-specific model to complement the brain-age gap (BAG).
Age is often treated as a confounder in neuroimaging analyses; however, brain aging and MS are intertwined. A deep learning 3D DenseNet architecture was trained to predict disease duration (DD) from brain MRI scans in people with MS (PwMS), alongside the DeepBrainNet model for age predictions. MRI scans from 4392 patients with MS were analyzed cross-sectionally. Additionally, 252 patients with early MS were studied longitudinally. The “DD gap” was calculated as the difference between predicted and actual DD, serving as a potential MS-specific biomarker.
Researchers found that the model...
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