title: Differentiation of Uterine Leiomyosarcoma from Atypical Leiomyoma: Diagnostic Accuracy of Qualitative MR Imaging Features and Feasibility of Texture Analysis.
abstract: OBJECTIVE
  To investigate whether qualitative magnetic resonance (MR) features can distinguish leiomyosarcoma (LMS) from atypical leiomyoma (ALM) and assess the feasibility of texture analysis (TA).
  
  
  METHODS
  This retrospective study included 41 women (ALM = 22, LMS = 19) imaged with MRI prior to surgery. Two readers (R1, R2) evaluated each lesion for qualitative MR features. Associations between MR features and LMS were evaluated with Fisher's exact test. Accuracy measures were calculated for the four most significant features. TA was performed for 24 patients (ALM = 14, LMS = 10) with uniform imaging following lesion segmentation on axial T2-weighted images. Texture features were pre-selected using Wilcoxon signed-rank test with Bonferroni correction and analyzed with unsupervised clustering to separate LMS from ALM.
  
  
  RESULTS
  Four qualitative MR features most strongly associated with LMS were nodular borders, haemorrhage, "T2 dark" area(s), and central unenhanced area(s) (p ≤ 0.0001 each feature/reader). The highest sensitivity [1.00 (95%CI:0.82-1.00)/0.95 (95%CI: 0.74-1.00)] and specificity [0.95 (95%CI:0.77-1.00)/1.00 (95%CI:0.85-1.00)] were achieved for R1/R2, respectively, when a lesion had ≥3 of these four features. Sixteen texture features differed significantly between LMS and ALM (p-values: <0.001-0.036). Unsupervised clustering achieved accuracy of 0.75 (sensitivity: 0.70; specificity: 0.79).
  
  
  CONCLUSIONS
  Combination of ≥3 qualitative MR features accurately distinguished LMS from ALM. TA was feasible.
  
  
  CONCLUSIONS
  • Four qualitative MR features demonstrated the strongest statistical association with LMS. • Combination of ≥3 these features could accurately differentiate LMS from ALM. • Texture analysis was a feasible semi-automated approach for lesion categorization.
authors.affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. lakhmany@mskcc.org.
authors.forename: Yulia
authors.identifier: http://orcid.org/0000-0003-3626-4502
authors.initials: Y
authors.lastname: Lakhman
authors.affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Harini
authors.initials: H
authors.lastname: Veeraraghavan
authors.affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Joshua
authors.initials: J
authors.lastname: Chaim
authors.affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.|Department of Radiology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
authors.forename: Diana
authors.initials: D
authors.lastname: Feier
authors.affiliation: Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Debra A
authors.initials: DA
authors.lastname: Goldman
authors.affiliation: Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Chaya S
authors.initials: CS
authors.lastname: Moskowitz
authors.affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.|Department of Radiology, Institut Régional du Cancer de Montpellier, Montpellier, France.
authors.forename: Stephanie
authors.initials: S
authors.lastname: Nougaret
authors.affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Ramon E
authors.initials: RE
authors.lastname: Sosa
authors.affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Hebert Alberto
authors.initials: HA
authors.lastname: Vargas
authors.affiliation: Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Robert A
authors.initials: RA
authors.lastname: Soslow
authors.affiliation: Gynecologic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Nadeem R
authors.initials: NR
authors.lastname: Abu-Rustum
authors.affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Hedvig
authors.initials: H
authors.lastname: Hricak
authors.affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
authors.forename: Evis
authors.initials: E
authors.lastname: Sala
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003937:Diagnosis, Differential; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007889:Leiomyoma / Q000473:pathology*; D007890:Leiomyosarcoma / Q000175:diagnosis*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D015203:Reproducibility of Results; D012189:Retrospective Studies; D014594:Uterine Neoplasms / Q000473:pathology*; D055815:Young Adult
keywords: Atypical Uterine Leiomyoma; Magnetic Resonance Imaging; Texture Analysis; Uterine Leiomyoma; Uterine Leiomyosarcoma