title: Diagnostic Accuracy of Ultrasound, Contrast-enhanced CT, and Conventional MRI for Differentiating Leiomyoma From Leiomyosarcoma.
abstract: This study aimed to determine whether uterine leiomyoma can be distinguished from uterine leiomyosarcoma on ultrasound (US), computed tomography (CT), and/or magnetic resonance imaging (MRI) without diffusion-weighted imaging.
  
  
  
  Institutional review board approval was obtained and informed consent was waived for this Health Insurance Portability and Accountability Act-compliant retrospective case-control diagnostic accuracy study. All subjects with resected uterine leiomyosarcoma diagnosed over a 17-year period (1998-2014) at a single institution for whom pre-resection US (n = 10), CT (n = 11), or MRI (n = 7) was available were matched by tumor size and imaging modality with 28 subjects with resected uterine leiomyoma. Six blinded radiologists (three attendings, three residents) assigned 5-point Likert scores for the following features: (1) margins, (2) necrosis, (3) hemorrhage, (4) vascularity, (5) calcifications, (6) heterogeneity, and (7) likelihood of malignancy (primary end point). Mean suspicion scores were calculated and receiver operating characteristic curves were generated. The ability of individual morphologic features to predict malignancy was assessed with logistic regression.
  
  
  
  Mean suspicion scores were 2.5 ± 1.2 (attendings) and 2.4 ± 1.3 (residents) for leiomyoma, and 2.7 ± 1.3 (attendings) and 2.7 ± 1.4 (residents) for leiomyosarcoma. The areas under the receiver operating characteristic curves (range: 0.330-0.685) were not significantly different from chance, either overall (P = .36-.88) or by any modality (P = .28-.96), for any reader. Reader experience had no effect on diagnostic accuracy. No morphologic parameter was significantly predictive of malignancy (P = .10-.97).
  
  
  
  Uterine leiomyoma cannot be differentiated accurately from leiomyosarcoma on US, CT, or MRI without diffusion-weighted imaging.
authors.affiliation: Department of Radiology, University of Michigan Health System, 1500 E Medical Center Drive, TC 2852B, Ann Arbor, MI 48109. Electronic address: kgaetke@med.umich.edu.
authors.forename: Kara
authors.initials: K
authors.lastname: Gaetke-Udager
authors.affiliation: Department of Gynecologic Oncology, University of Michigan Health System, Ann Arbor, Michigan.
authors.forename: Karen
authors.initials: K
authors.lastname: McLean
authors.affiliation: Department of Pathology, University of Michigan Health System, Ann Arbor, Michigan.
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Sciallis
authors.affiliation: Department of Radiology, University of Michigan Health System, 1500 E Medical Center Drive, TC 2852B, Ann Arbor, MI 48109.
authors.forename: Timothy
authors.initials: T
authors.lastname: Alves
authors.affiliation: Department of Radiology, University of Michigan Health System, 1500 E Medical Center Drive, TC 2852B, Ann Arbor, MI 48109.
authors.forename: Katherine E
authors.initials: KE
authors.lastname: Maturen
authors.affiliation: Department of Radiology, University of Michigan Health System, 1500 E Medical Center Drive, TC 2852B, Ann Arbor, MI 48109.
authors.forename: Benjamin M
authors.initials: BM
authors.lastname: Mervak
authors.affiliation: Department of Radiology, University of Michigan Health System, 1500 E Medical Center Drive, TC 2852B, Ann Arbor, MI 48109.
authors.forename: Andreea G
authors.initials: AG
authors.lastname: Moore
authors.affiliation: Department of Radiology, University of Michigan Health System, 1500 E Medical Center Drive, TC 2852B, Ann Arbor, MI 48109.
authors.forename: Ashish P
authors.initials: AP
authors.lastname: Wasnik
authors.affiliation: University of Michigan Medical School, Ann Arbor, Michigan.
authors.forename: Jake
authors.initials: J
authors.lastname: Erba
authors.affiliation: Department of Radiology, University of Michigan Health System, 1500 E Medical Center Drive, TC 2852B, Ann Arbor, MI 48109; Michigan Radiology Quality Collaborative, Ann Arbor, Michigan.
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Davenport
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003287:Contrast Media; D005260:Female; D006801:Humans; D007889:Leiomyoma / Q000000981:diagnostic imaging* / Q000473:pathology; D007890:Leiomyosarcoma / Q000000981:diagnostic imaging* / Q000473:pathology; D016015:Logistic Models; D008279:Magnetic Resonance Imaging; D008875:Middle Aged; D012372:ROC Curve; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed; D018608:Ultrasonography, Doppler; D014594:Uterine Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology
chemical_list: D003287:Contrast Media
keywords: Leiomyosarcoma; MRI; contrast-enhanced CT; leiomyoma; ultrasound