Abstract

Background Current terms used to describe the MRI findings for musculoskeletal infections are nonspecific and inconsistent. Purpose To develop and validate an MRI-based musculoskeletal infection classification and scoring system. Materials and Methods In this retrospective cross-sectional internal validation study, a Musculoskeletal Infection Reporting and Data System (MSKI-RADS) was designed. Adult patients with radiographs and MRI scans of suspected extremity infections with a known reference standard obtained between June 2015 and May 2019 were included. The scoring categories were as follows: 0, incomplete imaging; I, negative for infection; II, superficial soft-tissue infection; III, deeper soft-tissue infection; IV, possible osteomyelitis (OM); V, highly suggestive of OM and/or septic arthritis; VI, known OM; and NOS (not otherwise specified), nonspecific bone lesions. Interreader agreement for 20 radiologists from 13 institutions (intraclass correlation coefficient [ICC]) and true-positive rates of MSKI-RADS were calculated and the accuracy of final diagnoses rendered by the readers was compared using generalized estimating equations for clustered data. Results Among paired radiographs and MRI scans from 208 patients (133 male, 75 female; mean age, 55 years ± 13 [SD]), 20 were category I; 34, II; 35, III; 30, IV; 35, V; 18, VI; and 36, NOS. Moderate interreader agreement was observed among the 20 readers (ICC, 0.70; 95% CI: 0.66, 0.75). There was no evidence of correlation between reader experience and overall accuracy (P = .94). The highest true-positive rate was for MSKI-RADS I and NOS at 88.7% (95% CI: 84.6, 91.7). The true-positive rate was 73% (95% CI: 63, 80) for MSKI-RADS V. Overall reader accuracy using MSKI-RADS across all patients was 65% ± 5, higher than final reader diagnoses at 55% ± 7 (P < .001). Conclusion MSKI-RADS is a valid system for standardized terminology and recommended management of imaging findings of peripheral extremity infections across various musculoskeletal-fellowship-trained reader experience levels. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Schweitzer in this issue.

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