Do contrast-enhanced and advanced MRI sequences improve diagnostic accuracy for indeterminate lipomatous tumors?

PURPOSE

Benign, intermediate-grade and malignant tumors sometimes have overlapping imaging and clinical characteristics. The purpose of this study was to evaluate the added value of contrast-enhanced sequences (dynamic contrast enhancement (DCE)), diffusion-weighted imaging (DWI), and chemical shift imaging (CSI) to noncontrast MRI sequences for the characterization of indeterminate lipomatous tumors.

MATERIALS AND METHODS

Thirty-two consecutive patients with histologically proven peripheral lipomatous tumors were retrospectively evaluated. Two musculoskeletal radiologists recorded the MRI features in three sessions: (1) with noncontrast T1-weighted and fluid-sensitive sequences; (2) with addition of static pre- and post-contrast 3D volumetric T1-weighted sequences; and (3) with addition of DCE, DWI, and CSI. After each session, readers recorded a diagnosis (benign, intermediate/atypical lipomatous tumor (ALT), or malignant/dedifferentiated liposarcoma (DDL)). Categorical imaging features (presence of septations, nodules, contrast enhancement) and quantitative metrics (apparent diffusion coefficient values, CSI signal loss) were recorded.

RESULTS

For 32 tumors, the diagnostic accuracy of both readers did not improve with the addition of contrast-enhanced sequences, DWI, or CSI (53% (17/32) session 1; 50% (16/30) session 2; 53% (17/32) session 3). Noncontrast features, including thick septations (p = 0.025) and nodules ≥ 1 cm (p < 0.001), were useful for differentiating benign tumors from ALTs and DDLs, as were DWI (p = 0.01) and CSI (p = 0.009) metrics.

CONCLUSION

The addition of contrast-enhanced sequences (static, DCE), DWI, and CSI to a conventional, noncontrast MRI protocol did not improve diagnostic accuracy for differentiating benign, intermediate-grade, and malignant lipomatous tumors. However, we identified potentially useful imaging features by DCE, DWI, and CSI that may help distinguish these entities.