Yuki Kamishima1, Mitsuru Takeuchi2, Tatsuya Kawai1, Takatsune Kawaguchi3, Ken Yamaguchi4, Naoki Takahashi5, Masato Ito6, Toshinao Arakawa7, Akiko Yamamoto8, Kazushi Suzuki1, Masaki Ogawa1, Moe Takeuchi9, Yuta Shibamoto1. 1. Department of Radiology, Nagoya City University Graduate School of Medical Sciences and Medical School, 1 Kawasumi Mizuho-cho, Mizuho-ku, Nagoya, 467-8601, Japan. 2. Department of Radiology, Radiolonet Tokai, 3-86-2 Asaoka-cho, Chikusa-ku, Nagoya, 464-0811, Japan. m2rbimn@gmail.com. 3. Department of Radiology, Kariya Toyota General Hospital, 5-15 Sumiyoshi-cho, Kariya, 448-8505, Japan. 4. Department of Radiology, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga, 849-8501, Japan. 5. Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. 6. Department of Radiology, Japanese Red Cross Nagoya Daini Hospital, 2-9, Myoken-cho, Showa-ku, Nagoya, 466-8650, Japan. 7. Department of Radiology, Okazaki City Hospital, 3-1 Gosyoai, Kouryuji-cho, Okazaki, 444-8553, Japan. 8. Department of Radiology, Aichi Cancer Center Aichi Hospital, 18 Kuriyado, Kake-machi, Okazaki, 444-0011, Japan. 9. Department of Radiology, Nagoya City East Medical Center, 1-2-23 Wakamizu, Chikusa-ku, Nagoya, 464-8547, Japan.
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.
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.
Entities:
Keywords:
Carcinoma; Carcinosarcoma; Endometrial neoplasms; Magnetic resonance imaging; Uterus
Authors: Frederic Amant; Isabelle Cadron; Luca Fuso; Patrick Berteloot; Eric de Jonge; Gerd Jacomen; Johan Van Robaeys; Patrick Neven; Philippe Moerman; Ignace Vergote Journal: Gynecol Oncol Date: 2005-08 Impact factor: 5.482
Authors: Howard D Homesley; Virginia Filiaci; Maurie Markman; Pincas Bitterman; Lynne Eaton; Larry C Kilgore; Bradley J Monk; Frederick R Ueland Journal: J Clin Oncol Date: 2007-02-10 Impact factor: 44.544