Literature DB >> 26605502

Utility of histogram analysis of apparent diffusion coefficient maps obtained using 3.0T MRI for distinguishing uterine carcinosarcoma from endometrial carcinoma.

Masahiro Takahashi1, Eito Kozawa1, Megumi Tanisaka1, Kousei Hasegawa2, Masanori Yasuda3, Fumikazu Sakai1.   

Abstract

PURPOSE: We explored the role of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating uterine carcinosarcoma and endometrial carcinoma.
MATERIALS AND METHODS: We retrospectively evaluated findings in 13 patients with uterine carcinosarcoma and 50 patients with endometrial carcinoma who underwent diffusion-weighted imaging (b = 0, 500, 1000 s/mm(2) ) at 3T with acquisition of corresponding ADC maps. We derived histogram data from regions of interest drawn on all slices of the ADC maps in which tumor was visualized, excluding areas of necrosis and hemorrhage in the tumor. We used the Mann-Whitney test to evaluate the capacity of histogram parameters (mean ADC value, 5th to 95th percentiles, skewness, kurtosis) to discriminate uterine carcinosarcoma and endometrial carcinoma and analyzed the receiver operating characteristic (ROC) curve to determine the optimum threshold value for each parameter and its corresponding sensitivity and specificity.
RESULTS: Carcinosarcomas demonstrated significantly higher mean vales of ADC, 95th, 90th, 75th, 50th, 25th percentiles and kurtosis than endometrial carcinomas (P < 0.05). ROC curve analysis of the 75th percentile yielded the best area under the ROC curve (AUC; 0.904), sensitivity of 100%, and specificity of 78.0%, with a cutoff value of 1.034 × 10(-3) mm(2) /s.
CONCLUSION: Histogram analysis of ADC maps might be helpful for discriminating uterine carcinosarcomas and endometrial carcinomas. J. Magn. Reson. Imaging 2016;43:1301-1307.
© 2015 Wiley Periodicals, Inc.

Entities:  

Keywords:  ADC; MR; apparent diffusion coefficient; histogram analysis; uterine carcinosarcoma

Mesh:

Year:  2015        PMID: 26605502     DOI: 10.1002/jmri.25103

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  12 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

2.  Volumetric apparent diffusion coefficient histogram analysis of the testes in nonobstructive azoospermia: a noninvasive fingerprint of impaired spermatogenesis?

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Review 4.  Endometrial Cancer MRI staging: Updated Guidelines of the European Society of Urogenital Radiology.

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7.  Differentiation of orbital lymphoma and idiopathic orbital inflammatory pseudotumor: combined diagnostic value of conventional MRI and histogram analysis of ADC maps.

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8.  Histogram Analysis Parameters Apparent Diffusion Coefficient for Distinguishing High and Low-Grade Meningiomas: A Multicenter Study.

Authors:  Alexey Surov; Daniel T Ginat; Tchoyoson Lim; Teresa Cabada; Ozdil Baskan; Stefan Schob; Hans Jonas Meyer; Georg Alexander Gihr; Diana Horvath-Rizea; Gordian Hamerla; Karl Titus Hoffmann; Andreas Wienke
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9.  The value of clinical parameters combined with magnetic resonance imaging (MRI) features for preoperatively distinguishing different subtypes of uterine sarcomas: An observational study (STROBE compliant).

Authors:  Qiu Bi; Kunhua Wu; Fajin Lv; Zhibo Xiao; Yulin Xiong; Yiqing Shen
Journal:  Medicine (Baltimore)       Date:  2020-04       Impact factor: 1.817

10.  Rectal Cancer Invasiveness: Whole-Lesion Diffusion-Weighted Imaging (DWI) Histogram Analysis by Comparison of Reduced Field-of-View and Conventional DWI Techniques.

Authors:  Yang Peng; Hao Tang; Xuemei Hu; Yaqi Shen; Ihab Kamel; Zhen Li; Daoyu Hu
Journal:  Sci Rep       Date:  2019-12-10       Impact factor: 4.379

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