Role of chemical shift imaging in characterizing musculoskeletal soft tissue tumors

Objectives: The use of chemical shift imaging (CSI) for characterizing localized and diffuse bone marrow lesions is well established. However, the CSI characteristics of soft-tissue musculoskeletal tumors have not yet been established. The aim of this study is to describe the CSI features of soft-tissue tumors and establish their potential clinical usefulness. Material and Methods: Magnetic resonance imaging with CSI of eighty histopathologically proven musculoskeletal soft tissue tumors was retrospectively assessed. In-phase and out-of-phase signal intensity was measured to calculate the percentage reduction in signal (drop-out). Signal drop-out was correlated with histopathological diagnosis. Results: Based on the histopathological diagnosis, 80 patients in our study were grouped in 5 cohorts comprising lipomatous, lipomatous variant, neural, myxoid, and other soft tissue tumors. The mean signal drop was highest in the lipoma variant cohort (−27.4 ± 18.5%), followed by the lipoma cohort (−12.4 ± 5.9%), the neural tumors cohort (−2.7 ± 5.2%), the myxoid tumors cohort (−1.9 ± 5.2%), and the other soft tissue tumor cohort (0.8±18.3%). The difference was statistically significant ( P < 0.001). Signal dropout demonstrated good ability to identify lipoma variants with an area-under-the curve of 0.85 (95% confidence interval [CI] = 0.69–0.99). There was excellent intra-observer reliability (intra-class co-efficient [ICC] = 0.996, 95% C.I. 0.990–0.998) and inter-observer reliability (ICC 0.990, 95% C.I. 0.971–0.996). Conclusion: Lipoma variants demonstrate increased signal dropout compared to other soft-tissue tumors; CSI shows promise in augmenting the diagnostic pathway in the evaluation of soft tissue tumors.