ArticleJournal of imaging informatics in medicine2026
Seeing the Risk in Virtual Fat-Suppressed Spine MRI: External Benchmarking and Uncertainty-Guided Selective Risk Analysis.
Article in Journal of imaging informatics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Virtual fat-suppressed spine MRI may recover clinically useful contrast from routine T1-weighted and T2-weighted images, but visually plausible synthesis can conceal local failure. We evaluated a reliability-centered framework that reframed this task from replacement imaging to uncertainty-guided selective review. This retrospective study included 5119 cases or examinations from two in-house and four external or public datasets. A multi-source encoder was transferred to a 2.5-dimensional dual-output generator for virtual STIR and water-dominant fat-suppressed synthesis, followed by frozen-generator post hoc Laplace uncertainty and exploratory Effective-EPG analyses. On locked test sets, body-mask SSIM was 0.602 for internal lumbar STIR, 0.567 for internal cervical STIR, 0.496 for IDEAL-derived water, and 0.376 in C43, a patient- and examination-independent held-out cohort drawn from the same public source as Dataset C. Restormer-Small achieved the strongest internal body-based fidelity, whereas the proposed model achieved the highest body-mask PSNR and SSIM and the lowest MAE in the held-out C43 stress test cohort. Protocol conditioning showed very small and inconsistent differences. Post hoc uncertainty provided the strongest reliability signal: the highest uncertainty decile contained 1.79-2.11 times the slice-average error, and retaining the lowest uncertainty 50% of pixels reduced normalized MAE to 0.537-0.565. Uncertainty retained incremental error-ranking information beyond input-derived proxies, but its raw scale did not transfer quantitatively to C43; Effective-EPG associations attenuated after adjustment for input image covariates. In a four-reader study, virtual image balanced accuracy was 0.813-0.975, and 79.1% of auxiliary acceptability ratings were at least 4. Virtual fat-suppressed MRI is best positioned as uncertainty-guided auxiliary information for selective review, not replacement imaging.
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