International Journal of Radiation Research

en Integrating MR imaging and clinical features to differentiate uterine carcinosarcoma from endometrial carcinoma Radiation Biology Radiation Biology تحقيق بديع Original Research <div style="text-align: justify;">Background: This study aimed to investigate the clinical and MRI features of uterine carcinosarcoma (UCS) and endometrial carcinoma (EC), and to explore how integrating these characteristics could help distinguish UCS from EC. Materials and Methods: A total of 33 UCS patients and 114 EC patients were included in this study. Mann-Whitney U test was used to compare clinical-pathological characteristics and MR features between UCS and EC groups. Univariate and multivariate logistic regression analyses were conducted to identify the factors differentiating UCS from EC. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate diagnostic ability to distinguish UCS from EC. Results: UCS patients exhibited higher median age and elevated levels of carbohydrate antigen12-5 (CA 12-5) than EC patients. Compared to EC, UCS showed a greater propensity for ill-defined boundary, tumor prolapse, heterogeneous T2WI signals, hemorrhage, cystic degeneration, and more advanced stage than EC. The tumor size, anterior-posterior (AP) dimension, the ratio of the endometrial thickness (ET) to AP, and apparent diffusion coefficient (ADC) value of UCS were significantly larger than those of EC. Multivariate analysis identified independent factors for differentiating UCS from EC, including ill-defined tumor boundary, heterogenous T2WI signal intensity, heterogenous enhancement pattern, larger tumor volume, greater AP dimension, and higher ADC value. The AUC of the multivariate analysis for differentiating UCS from EC was 0.935, with 87.88% sensitivity and 94.74% specificity. Conclusion: Combining clinical characteristics with MRI features may significantly enhance the differentiation of UCS from EC.</div> Uterine carcinosarcoma, endometrial neoplasms, magnetic resonance imaging, diffusion magnetic resonance imaging, gynecological malignancy. 473 480 http://ijrr.com/browse.php?a_code=A-10-1-1519&slc_lang=en&sid=1 Z. Huang 7900319475328460033567 7900319475328460033567 No Radiology Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, Guangdong, China Y. Jiang 7900319475328460033568 7900319475328460033568 No Radiology Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, Guangdong, China L. Wan 7900319475328460033569 7900319475328460033569 No Guangzhou Cadre and Talent Health Management Center, Guangzhou, 510530, Guangdong, China W. Chen 7900319475328460033570 7900319475328460033570 No Radiology Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, Guangdong, China J. Zhao 453606904@qq.com 7900319475328460033571 7900319475328460033571 Yes Radiology Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, Guangdong, China