The Value of MRI in Distinguishing Subtypes of Lipomatous Extremity Tumors Needs Reassessment in the Era of MDM2 and CDK4 Testing

Abstract

Introduction Extremity lipomas and well-differentiated liposarcomas (WDLs) are difficult to distinguish on MR imaging. We sought to evaluate the accuracy of MRI interpretation using MDM2 amplification, via fluorescence in-situ hybridization (FISH), as the gold standard for pathologic diagnosis. Furthermore, we aimed to investigate the utility of a diagnostic formula proposed in the literature. Methods We retrospectively collected 49 patients with lipomas or WDLs utilizing MDM2 for pathologic diagnosis. Four expert readers interpreted each patient's MRI independently and provided a diagnosis. Additionally, a formula based on imaging characteristics (i.e. tumor depth, diameter, presence of septa, and internal cystic change) was used to predict the pathologic diagnosis. The accuracy and reliability of imaging-based diagnoses were then analyzed in comparison to the MDM2 pathologic diagnoses. Results The accuracy of MRI readers was 73.5% (95% CI 61–86%) with substantial interobserver agreement (κ=0.7022). The formula had an accuracy of 71%, which was not significantly different from the readers (p=0.71). The formula and expert observers had similar sensitivity (83% versus 83%) and specificity (64.5% versus 67.7%; p=0.659) for detecting WDLs. Conclusion The accuracy of both our readers and the formula suggests that MRI remains unreliable for distinguishing between lipoma and WDLs.

The Utility of Chest Imaging for Surveillance of Atypical Lipomatous Tumors

“…ALTs account for approximately 25% of all deep lipomatous tumors of the extremities and are most frequently located in the thigh [ 8 ]. Historically, ALTs were difficult to distinguish from benign lipomas as the two lesions have an overlapping gross, histologic, and radiologic appearance [ 9 , 10 ]. However, the recent identification of amplification of the MDM2 oncogene in ALTs has facilitated accurate differentiation from benign lipomas.…”

Pilot study to differentiate lipoma from atypical lipomatous tumour/well-differentiated liposarcoma using MR radiomics-based texture analysis

“…However, MR imaging features have documented only moderate accuracy for predicting the final diagnosis, compared to pathology. Ryan at al (12) suggested that the accuracy is in the region of 73% Therefore, there is a requirement to improve the differentiation of these entities noninvasively using MRI. In the present study, we evaluated intra-tumoural heterogeneity using MRI radiomics-based textual analysis to discriminate lipoma from ALT/WDL.…”

“…In recent years, fluoresence in situ hybridisation (FISH) identification of murine double minute 2 (MDM2) gene amplification has become the gold standard for diagnosis of ALT/WDLs (9-11). There have been several studies assessing the ability of magnetic resonance imaging (MRI) to differentiate these lesions (12,13). The previously well documented MRI accuracy for distinguishing these two tumours is in the region of 70% (12), with suggested reliable imaging discriminators being size and lipomatous content (13).…”

“…There have been several studies assessing the ability of magnetic resonance imaging (MRI) to differentiate these lesions (12,13). The previously well documented MRI accuracy for distinguishing these two tumours is in the region of 70% (12), with suggested reliable imaging discriminators being size and lipomatous content (13). It has however been noted that the imaging features of lipoma and ALT/WDL certainly overlap; with several studies concluding that discrimination using MRI is unreliable (12,13).…”

“…The previously well documented MRI accuracy for distinguishing these two tumours is in the region of 70% (12), with suggested reliable imaging discriminators being size and lipomatous content (13). It has however been noted that the imaging features of lipoma and ALT/WDL certainly overlap; with several studies concluding that discrimination using MRI is unreliable (12,13). A further study suggested slightly improved sensitivity, specificity and accuracy in differentiating liposarcoma from lipoma with computer-assisted-diagnosis (CAD) (14).…”