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‹ Mon · 29 Jun 2026
Promising but preliminary

Deep Learning-Based Automated Detection and Burden Assessment of Paramagnetic Rim Lesions on Quantitative Susceptibility Mapping in Patients With Multiple Sclerosis.

Automated deep-learning detection of key MS brain lesions removes a barrier to using this important imaging marker in disease monitoring and trials.

Deep learning automates accurate detection and quantification of paramagnetic rim lesions on QSM in MS patients, addressing a key barrier to clinical adoption of this prognostically important imaging biomarker. Automation enables scalable use in MS disease monitoring and treatment trials.

What the study was

Study design
Retrospective single-centre cohort
Population
Multiple sclerosis patients; single academic centre
Category
Diagnostics
Maturity
Exploratory
Journal
Korean journal of radiology

Why it surfaced

Novel DL automation of QSM paramagnetic rim lesions in MS; important biomarker; single-centre retrospective limits generalizability.

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