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

  • Sean Ryan
  • , Julia Visgauss
  • , David Kerr
  • , Joshua Helmkamp
  • , Nicholas Said
  • , Emily Vinson
  • , Patrick O'Donnell
  • , Xuechan Li
  • , Sin Ho Jung
  • , Diana Cardona
  • , William Eward
  • , Brian Brigman

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

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 (=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.

Original languageEnglish
Article number1901896
JournalSarcoma
Volume2018
DOIs
StatePublished - 2018

Bibliographical note

Publisher Copyright:
© 2018 Sean Ryan et al.

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging

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