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Diagnostic Accuracy of Ultrasound, Contrast-enhanced CT, and Conventional MRI for Differentiating Leiomyoma From Leiomyosarcoma

Posted Sep 30, 2016 Updated Apr 10, 2023
By Kara Gaetke-Udager MD , Karen McLean MD , Andrew P. Sciallis MD , Timothy Alves MD , Katherine E. Maturen MD , Benjamin M. Mervak MD , Andreea G. Moore MD , Ashish P. Wasnik MD , Jake Erba BS , Matthew S. Davenport MD
9 min read

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.

Introduction

Uterine leiomyosarcoma is a malignant neoplasm of smooth muscle cells, comprising approximately 1% of all uterine malignancies . Prognosis is relatively poor; the National Cancer Institute reports 5-year survival ranges based on the extent of disease from 63% for patients with local disease to 36% for patients with regional disease to 14% for patients with distant disease . Clinical diagnosis is challenging, as symptoms can be indistinguishable from far more common uterine leiomyomas, and many leiomyosarcomas are only found at pathology after surgery to treat presumed leiomyomas . This can further complicate treatment, as morcellation of a leiomyosarcoma resulting in tumor spread has the potential to render a patient incurable , and infarction of leiomyosarcoma during uterine artery embolization can delay diagnosis and management.

Imaging of uterine leiomyosarcomas on ultrasound (US), computed tomography (CT), or magnetic resonance imaging (MRI) typically shows a heterogeneous mass distorting the uterine architecture , which can appear identical to degenerating or cellular leiomyomas. Some studies have examined imaging “markers” that might prospectively help distinguish leiomyosarcomas from leiomyomas, such as necrosis, hemorrhage , ill-defined or nodular margins , calcification , early/heterogeneous postcontrast enhancement , and impeded diffusion on diffusion-weighted imaging (DWI) on MRI . However, imaging characteristics highly predictive of a pathologic diagnosis of malignancy remain to be elucidated. It has been postulated that rapid growth of a uterine mass is suggestive of a diagnosis of leiomyosarcoma, but this remains controversial . Despite these efforts to clarify the imaging features that predict malignancy, there have been few studies in the literature that directly examine radiologists’ accuracy in assigning a diagnosis of either leiomyosarcoma or leiomyoma to a uterine mass, and most prior imaging studies have used small cohorts .

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Materials and Methods

Subjects

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TABLE 1

Study Population

Characteristic Leiomyomas Leiomyosarcomas Number 28 28 Mean age 47 ± 13 years 48 ± 9 years Race ( n ) African American 11%(3/28) 32%(9/28) Asian 4%(1/28) 7%(2/28) Caucasian 79%(22/28) 57%(16/28) Hispanic 0%(0/28) 4%(1/28) Unknown 7%(2/28) 0%(0/28) Mean gravidity 2.1 ± 1.5 2.6 ± 1.9 Mean parity 1.9 ± 1.3 2.0 ± 1.5 Prior uterine artery embolization 0%(0/28) 0%(0/28) Prior hormone therapy 36%(10/28) 18%(5/28) Imaging modality ( n ) CT ( n ) 43%(12/28) 43%(12/28) MRI ( n ) 25%(7/28) 25%(7/28) Ultrasound ( n ) 36%(10/28) 36%(10/28) Mean mass size 11 ± 7 cm 10 ± 5 cm

CT, computed tomography; MRI, magnetic resonance imaging.

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Reference Standard

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Imaging Details

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Image Review

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Clinical Data

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Data Analysis

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Results

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TABLE 2

Areas Under the Receiver Operating Characteristic (ROC) Curves by Reader and Modality (Ultrasound [ n = 20], CT [ n = 22], MRI [ n = 14])

Reader All Examinations

( n = 56)P Ultrasound

( n = 20)P CT

( n = 22)P MRI

( n = 14)P Attending A 0.539 .72 0.405 .61 0.650 .39 0.540 .86 B 0.470 .79 0.520 .91 0.513 .96 0.330 .44 C 0.582 .45 0.685 .30 0.521 .91 0.579 .72 Resident D 0.517 .88 0.610 .55 0.541 .82 0.400 .65 E 0.562 .57 0.440 .75 0.618 .50 0.660 .47 F 0.600 .36 0.585 .65 0.685 .28 0.527 .90

CT, computed tomography; MRI, magnetic resonance imaging.

Figure 1, (a) Receiver operating characteristic (ROC) curves for attending and resident radiologists. ROC curves reflect discriminatory ability between leiomyoma and leiomyosarcoma for ultrasound ( n = 20), computed tomography (CT) ( n = 22), and magnetic resonance imaging (MRI) ( n = 14) examinations combined. (b) ROC curves for attending and resident radiologists. ROC curves reflect discriminatory ability between leiomyoma and leiomyosarcoma for ultrasound examinations ( n = 20). (c) ROC curves for attending and resident radiologists. ROC curves reflect discriminatory ability between leiomyoma and leiomyosarcoma for CT examinations ( n = 22). (d) ROC curves for attending and resident radiologists. ROC curves reflect discriminatory ability between leiomyoma and leiomyosarcoma for MRI examinations ( n = 14).

Figure 2, 37-year-old woman with leiomyoma that was mischaracterized by most readers as a leiomyosarcoma (mean suspicion score: 2.8). Ultrasound images ( a , longitudinal; b , transverse) show a heterogeneous uterine mass ( arrowheads ) with mixed echogenicity.

Figure 3, 48-year-old woman with leiomyosarcoma that was mischaracterized by most readers as a leiomyoma (mean suspicion score: 1.7). Ultrasound images ( a , longitudinal; b , transverse) show a heterogeneous mass with mixed echogenicity denoted by overlying measurement calipers.

Figure 4, 45-year-old woman with leiomyoma mischaracterized by most readers as a leiomyosarcoma (mean suspicion score: 3.3). T2-weighted fast spin echo magnetic resonance (MR) images of a leiomyoma shown in ( a ) (sagittal); the arrow points to a predominantly high-signal–intensity mass arising from the posterior wall of the uterus with internal heterogeneity. In ( b ) (coronal), the arrow points to the high-signal–intensity mass causing mass effect on the endometrial cavity ( arrowhead ), which is adjacent to a small, low-signal–intensity submucosal leiomyoma.

Figure 5, 49-year-old woman with leiomyosarcoma mischaracterized by most readers as a leiomyoma (mean suspicion score: 1.5). Magnetic resonance (MR) images shown in ( a ) (T2-weighted short axis); the arrow pointing to a low-signal–intensity mass in the right uterine fundus, and in ( b ) (sagittal T1-weighted, fat-suppressed, postcontrast); the arrow indicating the enhancing uterine mass.

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TABLE 3

Mean Attending Radiologist Imaging Characteristic Scores (Scale: 1–5) Stratified by Histology

Characteristic Leiomyoma Leiomyosarcoma_P_ Margins 2.2 ± 0.8 2.5 ± 0.9 .26 Necrosis 2.1 ± 1.1 2.2 ± 1.1 .79 Hemorrhage 1.6 ± 1.1 1.2 ± 0.5 .10 Vascularity 2.9 ± 0.9 2.9 ± 0.6 .74 Calcifications 1.3 ± 0.6 1.3 ± 0.7 .97 Heterogeneity 3.4 ± 0.9 3.3 ± 1.0 .96

P values refer to univariate logistic regression analyses evaluating mean characteristic scores relative to the probability of malignancy within a uterine mass. Higher numbers indicate more of the stated characteristic, with the exception of “margins,” for which a higher score indicates more ill-defined margins.

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Discussion

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Compliance with Ethical Standards

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Academic Radiology, Volume 23, Issue 10
Journals General Radiology
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