Deep learning improves quality of intracranial vessel wall MRI for better characterization of potentially culprit plaques.

Sci Rep · 2024 · PMC11329665 · PMID 39152167

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marginal significanceP = 0.10so close (0.05 < p ≤ 0.1)

When combination of enhancement and IPH was used for culprit plaque classification, DL-VWI showed higher AUROC (0.91; sensitivity 100%, specificity 81.6%) in diagnosing culprit plaques than Conv-VWI (0.84; sensitivity 88.2%, specificity 79.6%), with marginal significance ( P = 0.10).

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