Assessing brain involvement in Fabry disease with deep learning and the brain‐age paradigm
Alfredo Montella,
Mario Tranfa,
Alessandra Scaravilli
et al.
Abstract:While neurological manifestations are core features of Fabry disease (FD), quantitative neuroimaging biomarkers allowing to measure brain involvement are lacking. We used deep learning and the brain‐age paradigm to assess whether FD patients' brains appear older than normal and to validate brain‐predicted age difference (brain‐PAD) as a possible disease severity biomarker. MRI scans of FD patients and healthy controls (HCs) from a single Institution were, retrospectively, studied. The Fabry stabilization index… Show more
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