Literature DB >> 25623826

Diffusion-weighted MRI of epithelial ovarian cancers: correlation of apparent diffusion coefficient values with histologic grade and surgical stage.

Ji-Won Oh1, Sung Eun Rha2, Soon Nam Oh3, Michael Yong Park4, Jae Young Byun5, Ahwon Lee6.   

Abstract

OBJECTIVE: The purpose of this article is to correlate the apparent diffusion coefficient (ADC) values of epithelial ovarian cancers with histologic grade and surgical stage.
MATERIALS AND METHODS: We enrolled 43 patients with pathologically proven epithelial ovarian cancers for this retrospective study. All patients underwent preoperative pelvic magnetic resonance imaging (MRI) including diffusion-weighted images with b value of 0 and 1000 s/mm2 at 3.0-T unit. The mean ADC values of the solid portion of the tumor were measured and compared among different histologic grades and surgical stages.
RESULTS: The mean ADC values of epithelial ovarian cancers differed significantly between grade 1 (well-differentiated) and grade 2 (moderately-differentiated) (P=0.013) as well as between grade 1 and grade 3 (poorly-differentiated) (P=0.01); however, no statistically significant difference existed between grade 2 and grade 3 (P=0.737). The receiver-operating characteristic analysis indicated that a cutoff ADC value of less than or equal to 1.09×10(-3)mm2/s was associated with 94.4% sensitivity and 85.7% specificity in distinguishing grade 1 and grade 2/3 cancer. The difference in mean ADC values was statistically significant for early stage (FIGO stage I) and advanced stage (FIGO stage II-IV) cancer (P=0.011). The interobserver agreement for the mean ADC values of epithelial ovarian cancers was excellent.
CONCLUSION: The mean ADC values of the solid portion of epithelial ovarian cancers negatively correlated to histologic grade and surgical stage. The mean ADC values may be useful imaging biomarkers for assessment of tumor grade of epithelial ovarian cancer.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Apparent diffusion coefficient; Diffusion-weighted imaging; Epithelial ovarian cancer; Histologic grade; MRI

Mesh:

Substances:

Year:  2015        PMID: 25623826     DOI: 10.1016/j.ejrad.2015.01.005

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  9 in total

1.  Apparent Diffusion Coefficient Histogram Analysis for Assessing Tumor Staging and Detection of Lymph Node Metastasis in Epithelial Ovarian Cancer: Correlation with p53 and Ki-67 Expression.

Authors:  Feng Wang; Yuxiang Wang; Yan Zhou; Congrong Liu; Dong Liang; Lizhi Xie; Zhihang Yao; Jianyu Liu
Journal:  Mol Imaging Biol       Date:  2019-08       Impact factor: 3.488

2.  Prediction of Clinical Pathologic Prognostic Factors for Rectal Adenocarcinoma: Volumetric Texture Analysis Based on Apparent Diffusion Coefficient Maps.

Authors:  Zhihua Lu; Lei Wang; Kaijian Xia; Heng Jiang; Xiaoyan Weng; Jianlong Jiang; Mei Wu
Journal:  J Med Syst       Date:  2019-11-07       Impact factor: 4.460

3.  Primary and metastatic ovarian cancer: Characterization by 3.0T diffusion-weighted MRI.

Authors:  Auni Lindgren; Maarit Anttila; Suvi Rautiainen; Otso Arponen; Annukka Kivelä; Petri Mäkinen; Kirsi Härmä; Kirsi Hämäläinen; Veli-Matti Kosma; Seppo Ylä-Herttuala; Ritva Vanninen; Hanna Sallinen
Journal:  Eur Radiol       Date:  2017-03-13       Impact factor: 5.315

Review 4.  Diffusion magnetic resonance imaging: A molecular imaging tool caught between hope, hype and the real world of "personalized oncology".

Authors:  Abhishek Mahajan; Sneha S Deshpande; Meenakshi H Thakur
Journal:  World J Radiol       Date:  2017-06-28

5.  The distribution of the apparent diffusion coefficient as an indicator of the response to chemotherapeutics in ovarian tumour xenografts.

Authors:  Monique C Tourell; Ali Shokoohmand; Marietta Landgraf; Nina P Holzapfel; Patrina S P Poh; Daniela Loessner; Konstantin I Momot
Journal:  Sci Rep       Date:  2017-02-21       Impact factor: 4.379

6.  Ependymoma of the broad ligament mimicking an ovarian surface epithelial tumor.

Authors:  Ryo Inukai; Tatsuya Kawai; Ryutaro Nishikawa; Shino Ogawa; Ryuji Kojima; Nozomi Kita; Hideo Hattori; Yuta Shibamoto
Journal:  Radiol Case Rep       Date:  2020-11-20

7.  An Application of Machine Learning That Uses the Magnetic Resonance Imaging Metric, Mean Apparent Diffusion Coefficient, to Differentiate between the Histological Types of Ovarian Cancer.

Authors:  Heekyoung Song; Seongeun Bak; Imhyeon Kim; Jae Yeon Woo; Eui Jin Cho; Youn Jin Choi; Sung Eun Rha; Shin Ah Oh; Seo Yeon Youn; Sung Jong Lee
Journal:  J Clin Med       Date:  2021-12-31       Impact factor: 4.241

Review 8.  [Adnexal Masses: Clinical Application of Multiparametric MR Imaging & O-RADS MRI].

Authors:  So Young Eom; Sung Eun Rha
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2021-09-15

Review 9.  Update on Imaging of Ovarian Cancer.

Authors:  Rosemarie Forstner; Matthias Meissnitzer; Teresa Margarida Cunha
Journal:  Curr Radiol Rep       Date:  2016-04-09
  9 in total

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