Evaluation of Classic and Quantitative Imaging Features in the Differentiation of Benign and Atypical Lipomatous Soft Tissue Tumors Using a Standardized Multiparametric MRI Protocol: A Prospective Single-Centre Study in 45 Patients

Abstract

Background: Discrimination between benign and atypical lipomatous tumors (ALT) is important due to potential local complications and recurrence of ALT but can be difficult due to the often-similar imaging appearance. Using a standardized MRI protocol, this study aimed to rank established and quantitative MRI features by diagnostic value in the differentiation of benign and atypical lipomatous tumors and to develop a robust scoring system. Methods: Patients with clinical or sonographic suspicion of a lipomatous tumor were prospectively and consecutively enrolled from 2015 to 2019 after ethic review board approval. Histology was confirmed for all ALT and 85% of the benign cases. Twenty-one demographic and morphologic and twenty-three quantitative features were extracted from a standardized MRI protocol (T1/T2-proton-density-weighting, turbo-inversion recovery magnitude, T2* multi-echo gradient-echo imaging, qDIXON-Vibe fat-quantification, T1 relaxometry, T1 mapping, diffusion-weighted and post-contrast sequences). A ranking of these features was generated through a Bayes network analysis with gain-ratio feature evaluation. Results: Forty-five patients were included in the analysis (mean age, 61.2 ± 14.2 years, 27 women [60.0%]). The highest-ranked ALT predictors were septation thickness (gain ratio merit [GRM] 0.623 ± 0.025, p = 0.0055), intra- and peritumoral STIR signal discrepancy (GRM 0.458 ± 0.046, p < 0.0001), orthogonal diameter (GRM 0.554 ± 0.188, p = 0.0013), contrast enhancement (GRM 0.235 ± 0.015, p = 0.0010) and maximum diameter (GRM 0.221 ± 0.075, p = 0.0009). The quantitative features did not provide a significant discriminatory value. The highest-ranked predictors were used to generate a five-tiered score for the identification of ALTs (correct classification rate 95.7% at a cut-off of three positive items, sensitivity 100.0%, specificity 94.9%, likelihood ratio 19.5). Conclusions: Several single MRI features have a substantial diagnostic value in the identification of ALT, yet a multiparametric approach by a simple combination algorithm may support radiologists in the identification of lipomatous tumors in need for further histological assessment.

The Predictive Role of the Histopathological Scoring System in Adipose Tumors—Lipoma, Atypical Lipomatous Tumor, and Liposarcoma

“…Aspects that strongly correlate with atypical lipomatous differentiation are a low fraction of adipose tissue, higher cellularity, and a higher content of fibrous tissue. Strongly indicative of ALT is also the nodular contrast pattern or the entire heterogeneous lesion [16]. The sensitivity and specificity of the MRI detection of ALT varies between 90.1 and 90.9%, respectively, and 37 and 51.5% [17,18].…”