Abstract
Purpose
To construct a diagnostic model for differentiating carcinosarcoma from carcinoma of the uterus.
Materials and methods
Twenty-six patients with carcinosarcomas and 26 with uterine corpus carcinomas constituted a derivation cohort. The following nine MRI features of the tumors were evaluated: inhomogeneity, predominant signal intensity, presence of hyper- and hypointense areas, conspicuity of tumor margin, cervical canal extension on T2WI, presence of hyperintense areas on T1WI, contrast defect area volume percentage, and degree of enhancement. Two predictive models—with and without contrast—were constructed using multivariate logistic regression analysis. Fifteen other patients with carcinosarcomas and 30 patients with carcinomas constituted a validation cohort. The sensitivity and specificity of each model for the validation cohort were calculated.
Results
Inhomogeneity, predominant signal intensity on T2WI, and presence of hyperintense areas on T1WI were significant predictors in the unenhanced-MRI-based model. Presence of hyperintensity on T1WI, contrast defect area volume percentage, and degree of enhancement were significant predictors in the enhanced-MRI-based model. The sensitivity/specificity of unenhanced MRI were 87/73 and 87/70% according to reviewer 1 and 2, respectively. The sensitivity/specificity of the enhanced-MRI-based model were 87/70% according to both reviewers.
Conclusions
Our diagnostic models can differentiate carcinosarcoma from carcinoma of the uterus with high sensitivity and moderate specificity.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
D’Angelo E, Prat J. Pathology of mixed Mullerian tumours. Best Pract Res Clin Obstet Gynaecol. 2011;25:705–18.
Barwick KW, LiVolsi VA. Malignant mixed mullerian tumors of the uterus. A clinicopathologic assessment of 34 cases. Am J Surg Pathol. 1979;3:125–35.
Gadducci A, Sartori E, Landoni F, Zola P, Maggino T, Cosio S, et al. The prognostic relevance of histological type in uterine sarcomas: a Cooperation Task Force (CTF) multivariate analysis of 249 cases. Eur J Gynaecol Oncol. 2002;23:295–9.
Koh WJ, Greer BE, Abu-Rustum NR, Apte SM, Campos SM, Chan J, et al. Uterine neoplasms, version 1.2014. J Natl Compr Cancer Netw. 2014;12:248–80.
Homesley HD, Filiaci V, Markman M, Bitterman P, Eaton L, Kilgore LC, et al. Phase III trial of ifosfamide with or without paclitaxel in advanced uterine carcinosarcoma: a gynecologic oncology group study. J Clin Oncol. 2007;25:526–31.
Bansal N, Herzog TJ, Burke W, Cohen CJ, Wright JD. The utility of preoperative endometrial sampling for the detection of uterine sarcomas. Gynecol Oncol. 2008;110:43–8.
Sagae S, Yamashita K, Ishioka S, Nishioka Y, Terasawa K, Mori M, et al. Preoperative diagnosis and treatment results in 106 patients with uterine sarcoma in Hokkaido, Japan. Oncology. 2004;67:33–9.
Yamashita Y, Takahashi M, Miyazaki K, Okamura H. Contrast-enhanced MR imaging of malignant mixed mullerian tumor of the uterus. AJR Am J Roentgenol. 1993;160:1150–1.
Ohguri T, Aoki T, Watanabe H, Nakamura K, Nakata H, Matsuura Y, et al. MRI findings including gadolinium-enhanced dynamic studies of malignant, mixed mesodermal tumors of the uterus: differentiation from endometrial carcinomas. Eur Radiol. 2002;12:2737–42.
Kato H, Kanematsu M, Furui T, Imai A, Hirose Y, Kondo H, et al. Carcinosarcoma of the uterus: radiologic-pathologic correlations with magnetic resonance imaging including diffusion-weighted imaging. Magn Reson Imaging. 2008;26:1446–50.
Tanaka YO, Tsunoda H, Minami R, Yoshikawa H, Minami M. Carcinosarcoma of the uterus: MR findings. J Magn Reson Imaging. 2008;28:434–9.
Teo SY, Babagbemi KT, Peters HE, Mortele KJ. Primary malignant mixed mullerian tumor of the uterus: findings on sonography, CT, and gadolinium-enhanced MRI. AJR Am J Roentgenol. 2008;191:278–83.
Bharwani N, Newland A, Tunariu N, Babar S, Sahdev A, Rockall AG, et al. MRI appearances of uterine malignant mixed mullerian tumors. AJR Am J Roentgenol. 2010;195:1268–75.
Genever AV, Abdi S. Can MRI predict the diagnosis of endometrial carcinosarcoma? Clin Radiol. 2011;66:621–4.
Takeuchi M, Matsuzaki K, Harada M. Carcinosarcoma of the uterus: MRI findings including diffusion-weighted imaging and MR spectroscopy. Acta Radiol. 2016;57:1277–84.
D’Angelo E, Prat J. Uterine sarcomas: a review. Gynecol Oncol. 2010;116:131–9.
Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–74.
Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3:32–5.
Murphey MD, Walker EA, Wilson AJ, Kransdorf MJ, Temple HT, Gannon FH. From the archives of the AFIP: imaging of primary chondrosarcoma: radiologic-pathologic correlation. Radiographics. 2003;23:1245–78.
Takahashi M, Kozawa E, Tanisaka M, Hasegawa K, Yasuda M, Sakai F. Utility of histogram analysis of apparent diffusion coefficient maps obtained using 3.0 T MRI for distinguishing uterine carcinosarcoma from endometrial carcinoma. J Magn Reson Imaging. 2016;43:1301–7.
Amant F, Cadron I, Fuso L, Berteloot P, de Jonge E, Jacomen G, et al. Endometrial carcinosarcomas have a different prognosis and pattern of spread compared to high-risk epithelial endometrial cancer. Gynecol Oncol. 2005;98:274–80.
Acknowledgments
We thank Dr. Kohei Sasaguri for his cooperation during the collection of MRI data on carcinosarcomas and carcinoma of the uterus.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Grant support
No grant support for this study.
Conflict of interest
The authors declare that they have no conflict of interest.
About this article
Cite this article
Kamishima, Y., Takeuchi, M., Kawai, T. et al. A predictive diagnostic model using multiparametric MRI for differentiating uterine carcinosarcoma from carcinoma of the uterine corpus. Jpn J Radiol 35, 472–483 (2017). https://doi.org/10.1007/s11604-017-0655-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11604-017-0655-6