Literature DB >> 18501546

Carcinosarcoma of the uterus: radiologic-pathologic correlations with magnetic resonance imaging including diffusion-weighted imaging.

Hiroki Kato1, Masayuki Kanematsu, Tatsuro Furui, Atsushi Imai, Yoshinobu Hirose, Hiroshi Kondo, Satoshi Goshima, Yusuke Tsuge.   

Abstract

The authors describe the MRI findings, including diffusion-weighted imaging findings, of histopathologically proven uterine carcinosarcoma in four postmenopausal women. In three of four patients, diffusion-weighted images clearly revealed hypointense areas corresponding to hypocellular regions caused by intratumoral necrosis, and apparent diffusion coefficient (ADC) mapping images indicated that necrotic areas had high ADC values. In the remaining patient, diffusion-weighted and ADC mapping images clearly distinguished components of adenocarcinoma from sarcoma. In all patients, diffusion-weighted and ADC mapping images precisely reflected histopathological findings. Diffusion-weighted images were found to demonstrate complicated tissue components in carcinosarcomas of the uterus, and thus, which may be useful for the diagnosis of this disease.

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Year:  2008        PMID: 18501546     DOI: 10.1016/j.mri.2008.04.003

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  3 in total

1.  A predictive diagnostic model using multiparametric MRI for differentiating uterine carcinosarcoma from carcinoma of the uterine corpus.

Authors:  Yuki Kamishima; Mitsuru Takeuchi; Tatsuya Kawai; Takatsune Kawaguchi; Ken Yamaguchi; Naoki Takahashi; Masato Ito; Toshinao Arakawa; Akiko Yamamoto; Kazushi Suzuki; Masaki Ogawa; Moe Takeuchi; Yuta Shibamoto
Journal:  Jpn J Radiol       Date:  2017-06-05       Impact factor: 2.374

Review 2.  Current Status of Magnetic Resonance Imaging in Patients with Malignant Uterine Neoplasms: A Review.

Authors:  Yu-Ting Huang; Yen-Ling Huang; Koon-Kwan Ng; Gigin Lin
Journal:  Korean J Radiol       Date:  2018-12-27       Impact factor: 3.500

3.  Differentiation of carcinosarcoma from endometrial carcinoma on magnetic resonance imaging using deep learning.

Authors:  Tsukasa Saida; Kensaku Mori; Sodai Hoshiai; Masafumi Sakai; Aiko Urushibara; Toshitaka Ishiguro; Toyomi Satoh; Takahito Nakajima
Journal:  Pol J Radiol       Date:  2022-09-21
  3 in total

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