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Objectives Dermatomyositis (DM) requires advanced imaging to assess muscle inflammation and timely malignancy screening. Hybrid positron emission tomography (PET) imaging combines metabolic and anatomical data; however, whether it can comprehensively evaluate DM is unclear. We evaluated the ability of 18 F-fluorodeoxyglucose PET/magnetic resonance imaging (MRI) and PET/computed tomography (CT) to detect muscle involvement and cancer-associated myositis (CAM) in DM. Methods This retrospective study evaluated 41 patients, including 39 with classic DM and 2 with clinically amyopathic DM (CADM), who underwent PET/MRI (n=27) or PET/CT (n=14). Whole-body MRI was scored for muscle edema, fatty infiltration and atrophy. FDG uptake was quantified using region-based maximum standardized uptake value (SUV max ) ratios (muscle-to-blood pool) and Deauville scores. Imaging parameters (edema scores, SUV max ratios, Deauville scores) and clinical data (muscle enzymes and myositis-specific autoantibodies) were analyzed. Results The sensitivity of PET/MRI was higher than that of PET/CT for detecting muscle involvement in classic DM (100% [25/25] vs. 78.6% [11/14]; P = 0.04). No muscle involvement was detected in CADM. Total edema scores correlated with creatine kinase (ρ=0.505, 95% CI 0.147–0.747; P<0.01) and lactate dehydrogenase (ρ=0.723, 95% CI 0.466–0.867; P<0.0001). Ten patients fulfilled the temporal definition of CAM (10/41, 24.4%), with nasopharyngeal carcinoma being the most common subtype (4/10, 40.0%). Stratified by modality, 2 malignancies were observed in the PET/MRI cohort (2/27, 7.4%), and 8 malignancies were identified in the PET/CT cohort (8/14, 57.1%). Anti-transcription intermediary factor-1γ antibody grade correlated with the SUV max ratio (ρ=0.452, 95% CI 0.168–0.667; P<0.01). Conclusions PET/MRI detected muscle involvement more frequently than PET/CT in classic DM, while both PET/MRI and PET/CT contributed to malignancy assessment in this cohort. Hybrid PET imaging may aid disease phenotyping and cancer surveillance in DM.
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Liao et al. (2026) studied this question.
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