title: Can Abdominal Computed Tomography Imaging Help Accurately Identify a Dedifferentiated Component in a Well-Differentiated Liposarcoma?
abstract: OBJECTIVE
  To assess the ability of computed tomography (CT) to differentiate an atypical lipomatous tumor/well-differentiated liposarcoma (WDLPS) from a WDLPS with a dedifferentiated component (DDLPS) within it.
  
  
  METHODS
  Forty-nine untreated patients with abdominal atypical lipomatous tumors/well-differentiated liposarcomas who had undergone contrast-enhanced CT were identified using an institutional database. Three radiologists who were blinded to the pathology findings evaluated all the images independently to determine whether a dedifferentiated component was present within the WDLPS. The CT images were evaluated for fat content (≤25% or >25%); presence of ground-glass density, enhancing and/or necrotic nodules; presence of a capsule surrounding the mass; septations; and presence and pattern of calcifications. A multivariate logistic regression model with generalized estimating equations was used to correlate imaging features with pathology findings. Kappa statistics were calculated to assess agreement between the three radiologists.
  
  
  RESULTS
  On the basis of pathological findings, 12 patients had been diagnosed with DDLPS within a WDLPS and 37 had been diagnosed with WDLPS. The presence of an enhancing or a centrally necrotic nodule within the atypical lipomatous tumor was associated with dedifferentiated liposarcoma (P = 0.02 and P = 0.0003, respectively). The three readers showed almost perfect agreement in overall diagnosis (κ r = 0.83; 95% confidence interval, 0.67-0.99).
  
  
  CONCLUSIONS
  An enhancing or centrally necrotic nodule may be indicative of a dedifferentiated component in well-differentiated liposarcoma. Ground-glass density nodules may not be indicative of dedifferentiation.
authors.affiliation: From the *Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX; †University of Kentucky College of Medicine, Lexington, KY; ‡Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX; §Department of Radiology, University of Pennsylvania, Philadelphia, PA; and Departments of ∥Surgical Oncology, and ¶Sarcoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
authors.forename: Priya
authors.initials: P
authors.lastname: Bhosale
authors.forename: Jieqi
authors.initials: J
authors.lastname: Wang
authors.forename: Datla
authors.initials: D
authors.lastname: Varma
authors.forename: Corey
authors.initials: C
authors.lastname: Jensen
authors.forename: Madhavi
authors.initials: M
authors.lastname: Patnana
authors.forename: Wei
authors.initials: W
authors.lastname: Wei
authors.forename: Anil
authors.initials: A
authors.lastname: Chauhan
authors.forename: Barry
authors.initials: B
authors.lastname: Feig
authors.forename: Shreyaskumar
authors.initials: S
authors.lastname: Patel
authors.forename: Neeta
authors.initials: N
authors.lastname: Somaiah
authors.forename: Tara
authors.initials: T
authors.lastname: Sagebiel
mesh_terms: D000008:Abdominal Neoplasms / Q000000981:diagnostic imaging*; D000328:Adult; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008080:Liposarcoma / Q000000981:diagnostic imaging* / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D011860:Radiography, Abdominal / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*