Abstract:
RATIONALE AND OBJECTIVES: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. MATERIALS AND METHODS: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. RESULTS: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). CONCLUSIONS:Uterine leiomyoma cannot be differentiated accurately from leiomyosarcoma on US, CT, or MRI without diffusion-weighted imaging.
journal_name
Acad Radioljournal_title
Academic radiologyauthors
Gaetke-Udager K,McLean K,Sciallis AP,Alves T,Maturen KE,Mervak BM,Moore AG,Wasnik AP,Erba J,Davenport MSdoi
10.1016/j.acra.2016.06.004subject
Has Abstractpub_date
2016-10-01 00:00:00pages
1290-7issue
10eissn
1076-6332issn
1878-4046pii
S1076-6332(16)30106-4journal_volume
23pub_type
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journal_title:Academic radiology
pub_type: 杂志文章,随机对照试验
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