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Differentiation of uterine low-grade endometrial stromal sarcoma from rare leiomyoma variants by magnetic resonance imaging.

ABSTRACT: The purpose of this study is to evaluate utility of MRI in differentiation of uterine low-grade endometrial stromal sarcoma (LGESS) from rare leiomyoma variants. This multi-center retrospective study included consecutive 25 patients with uterine LGESS and 42 patients with rare leiomyoma variants who had pretreatment MRI. Two radiologists (R1/R2) independently evaluated MRI features, which were analyzed statistically using Fisher's exact test or Student's t-test. Subsequently, using a five-point Likert scale, the two radiologists evaluated the diagnostic performance of a pre-defined MRI system using features reported as characteristics of LGESS in previous case series: uterine tumor with high signal intensity (SI) on diffusion-weighted images and with either worm-like nodular extension, intra-tumoral low SI bands, or low SI rim on T2-weighted images. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of the two readers' Likert scales were analyzed. Intra-tumoral low SI bands (p < 0.001), cystic/necrotic change (p ≤ 0.02), absence of speckled appearance (p < 0.001) on T2-weighted images, and a low apparent diffusion coefficient value (p ≤ 0.02) were significantly associated with LGESS. The pre-defined MRI system showed very good diagnostic performance: AUC 0.86/0.89, sensitivity 0.95/0.95, and specificity 0.67/0.69 for R1/R2. MRI can be useful to differentiate uterine LGESS from rare leiomyoma variants.

SUBMITTER: Himoto Y

PROVIDER: S-EPMC8476551 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI).Materials and methodsA total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC).ResultsMean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10-3 mm²/s vs. 1.23 ± 0.25 10-3 mm²/s; P < 0.001), and the relative contrast ratio was higher in the uterine sarcoma (8.16 ± 2.94 vs. 4.19 ± 2.66; P < 0.001). Selected qualitative MRI features included ill-defined margin (adjusted odds ratio [aOR], 17.9; 95% confidence interval [CI], 1.41-503, P = 0.040), intratumoral hemorrhage (aOR, 27.3; 95% CI, 3.74-596, P = 0.006), and absence of T2 dark area (aOR, 83.5; 95% CI, 12.4-1916, P < 0.001). The classifier that combined qualitative MRI features and DWI-based quantitative parameters showed significantly better performance than without DWI-based parameters in the validation set (AUC, 0.92 vs. 0.78; P < 0.001).ConclusionThe addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.

Project description:The benign tumor uterine leiomyoma (UL) develops from the smooth muscle tissue that constitutes the uterus, whereas malignant tumor uterine sarcoma develops from either the smooth muscle tissue or stroma and is different from UL and endometrial cancer. Uterine sarcoma is broadly classified into three types: uterine leiomyosarcoma, endometrial stromal sarcoma (ESS), and carcinosarcoma. Although uterine leiomyosarcoma and ESS are both classified as uterine sarcoma, they significantly differ in terms of their sites of occurrence, symptoms, and treatment methods. Uterine leiomyosarcoma develops from the muscle tissue constituting the wall of the uterus and accounts for approximately 70% of all uterine sarcoma cases. In contrast, ESS develops from the stromal tissue beneath the endometrium and accounts for approximately 25% of all uterine sarcoma cases. ESS is classified as either low grade (LG) or high grade (HG). This case report aimed to highlight the importance of histopathologic examinations based on surgical specimens. Herein, we reported the case of a 45-year-old woman suspected of having submucosal leiomyoma of the uterus based on imaging results. Transvaginal ultrasonography and endometrial biopsy or partial dilation and curettage were performed. Contrast-enhanced magnetic resonance imaging (MRI) revealed a 32-mm mass projecting from the posterior wall of the uterus into the uterine cavity. T2-weighted imaging revealed a low signal within the mass; thus, submucosal UL was suspected. Histopathologic examination of surgical specimens obtained from a patient suspected of having submucosal UL after contrast-enhanced MRI indicated that the patient had ESS. Despite the remarkable advancements in medical imaging technology, the accuracy of contrast-enhanced MRI for detecting uterine mesenchymal tumors is limited. Therefore, histopathologic diagnosis based on surgical specimens should be performed when medical grounds for diagnosing a benign tumor on contrast-enhanced MRI are lacking.

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Differentiation of uterine low-grade endometrial stromal sarcoma from rare leiomyoma variants by magnetic resonance imaging.

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