Clinical Utility of AI-Enabled CT-to-MRI Translation for Degenerative Spinal Disorders: A Retrospective Reader Study

Background/Objectives: MRI is preferred for disc-related assessment in suspected degenerative spinal disorders, but it may be delayed, unavailable, or contraindicated; in such cases, CT findings often guide initial decisions. To address these limitations in MRI accessibility, we developed Dr.Magic (DRM-S-01), an AI-enabled CT-to-MRI translation system that converts non-contrast spine CT into MRI-like translated images (T^-MRI), and conducted a retrospective reader study to assess its clinical utility. Methods: Ninety-two paired CT/MRI examinations were independently reviewed by three board-certified radiologists under three conditions: MRI-only, CT-only, and CT augmented with T^-MRI. MRI-only interpretation served as the per-reader reference standard. Results: CT augmented with T^-MRI improved diagnostic accuracy for disc-related assessment versus CT-only for all readers (34.78% to 72.83%, 42.39% to 77.17%, and 40.22% to 69.57%; all p < 0.01), increasing mean accuracy from 39.13% ± 3.20% to 73.19% ± 3.12%. Inter-reader agreement also improved (Fleiss’ κ: 0.5617 to 0.6621; observed agreement: 0.6630 to 0.8116). Conclusions: Overall, these findings suggest that augmenting CT interpretation with T^-MRI may improve diagnostic performance and reading consistency when timely MRI is not feasible. In our implementation, Dr.Magic completed T^-MRI translation in a median of 10.90 s per CT examination (IQR, 10.39–11.79), supporting practical use within CT-based workflows.