Literature DB >> 20619566

Diagnostic performance of apparent diffusion coefficient for predicting histological grade of hepatocellular carcinoma.

Akihiro Nishie1, Tsuyoshi Tajima, Yoshiki Asayama, Kousei Ishigami, Daisuke Kakihara, Tomohiro Nakayama, Yukihisa Takayama, Daisuke Okamoto, Nobuhiro Fujita, Akinobu Taketomi, Kengo Yoshimitsu, Hiroshi Honda.   

Abstract

OBJECTIVE: To investigate whether the histological grade of hepatocellular carcinoma (HCC) can be predicted using the apparent diffusion coefficient (ADC).
MATERIALS AND METHODS: This retrospective study group consisted of 80 patients with 85 surgically resected HCCs who underwent preoperative MRI exams including diffusion-weighted imaging. The tumors were histologically classified into five groups as follows: five well (w-), 17 well to moderately (wm-), 37 moderately (m-), 16 moderately to poorly (mp-), and 10 poorly (p-) differentiated HCCs. For ADC measurement of each HCC, the largest possible region of interest was placed on the solid region on the ADC map where ADC was considered to be the lowest. The average ADCs of the five histological grades were compared using Spearman's rank correlation test and Student's t-test, and the diagnostic performance of ADC for mp- and p-HCCs was also evaluated using a receiver operating characteristic-based positive test.
RESULTS: The average ADC of p-HCC (0.76±0.10×10(-3) mm2/s) was significantly lower than those of the other four histological grades. The average ADC of mp-HCCs (0.99±0.20×10(-3) mm2/s) was significantly lower than those of w-, wm- and m-HCCs. The sensitivity, specificity, PPV, NPV, and accuracy, when an ADC of 0.972 or lower was considered an indicator of mp- and p-HCCs, were 73.1%, 72.9%, 54.3%, 86.0% and 72.9%, respectively.
CONCLUSION: ADCs of mp- and p-HCCs were lower than those of w-, wm- and m-HCCs. ADC can contribute to radiological diagnosis of poorly differentiated components in HCCs.
Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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Year:  2010        PMID: 20619566     DOI: 10.1016/j.ejrad.2010.06.019

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


  44 in total

1.  Prediction of the histopathological grade of hepatocellular carcinoma using qualitative diffusion-weighted, dynamic, and hepatobiliary phase MRI.

Authors:  Chansik An; Mi-Suk Park; Hyae-Min Jeon; Yeo-Eun Kim; Woo-Suk Chung; Yong Eun Chung; Myeong-Jin Kim; Ki Whang Kim
Journal:  Eur Radiol       Date:  2012-03-22       Impact factor: 5.315

2.  Predicting the grade of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature.

Authors:  Minghui Wu; Hongna Tan; Fei Gao; Jinjin Hai; Peigang Ning; Jian Chen; Shaocheng Zhu; Meiyun Wang; Shewei Dou; Dapeng Shi
Journal:  Eur Radiol       Date:  2018-11-07       Impact factor: 5.315

3.  Histological grade of hepatocellular carcinoma predicted by quantitative diffusion-weighted imaging.

Authors:  Weihua Guo; Suhong Zhao; Yuhai Yang; Guangrui Shao
Journal:  Int J Clin Exp Med       Date:  2015-03-15

4.  Distinguishing intrahepatic cholangiocarcinoma from poorly differentiated hepatocellular carcinoma using precontrast and gadoxetic acid-enhanced MRI.

Authors:  Yoshiki Asayama; Akihiro Nishie; Kousei Ishigami; Yasuhiro Ushijima; Yukihisa Takayama; Nobuhiro Fujita; Yuichiro Kubo; Shinichi Aishima; Ken Shirabe; Takashi Yoshiura; Hiroshi Honda
Journal:  Diagn Interv Radiol       Date:  2015 Mar-Apr       Impact factor: 2.630

5.  Intravoxel incoherent motion diffusion-weighted imaging for assessment of histologic grade of hepatocellular carcinoma: comparison of three methods for positioning region of interest.

Authors:  Yi Wei; Feifei Gao; Min Wang; Zixing Huang; Hehan Tang; Jiaxing Li; Yi Wang; Tong Zhang; Xiaocheng Wei; Dandan Zheng; Bin Song
Journal:  Eur Radiol       Date:  2018-07-19       Impact factor: 5.315

Review 6.  Current status of imaging biomarkers predicting the biological nature of hepatocellular carcinoma.

Authors:  Norihide Yoneda; Osamu Matsui; Satoshi Kobayashi; Azusa Kitao; Kazuto Kozaka; Dai Inoue; Kotaro Yoshida; Tetsuya Minami; Wataru Koda; Toshifumi Gabata
Journal:  Jpn J Radiol       Date:  2019-02-02       Impact factor: 2.374

Review 7.  Diffusion-weighted MRI of the liver: challenges and some solutions for the quantification of apparent diffusion coefficient and intravoxel incoherent motion.

Authors:  Yi Xiang J Wang; Hua Huang; Cun-Jing Zheng; Ben-Heng Xiao; Olivier Chevallier; Wei Wang
Journal:  Am J Nucl Med Mol Imaging       Date:  2021-04-15

8.  Prediction of histological grade of hepatocellular carcinoma using quantitative diffusion-weighted MRI: a retrospective multivendor study.

Authors:  Yusuke Ogihara; Yoshio Kitazume; Yoshihiro Iwasa; Shinichi Taura; Yoshiro Himeno; Tomo Kimura; Seishi Sawano; Shigehiko Terada; Minoru Tanabe; Yukihisa Saida; Ukihide Tateishi
Journal:  Br J Radiol       Date:  2018-02-05       Impact factor: 3.039

Review 9.  Topics on quantitative liver magnetic resonance imaging.

Authors:  Yì Xiáng J Wáng; Xiaoqi Wang; Peng Wu; Yajie Wang; Weibo Chen; Huijun Chen; Jianqi Li
Journal:  Quant Imaging Med Surg       Date:  2019-11

Review 10.  Multiparametric MR Imaging in Abdominal Malignancies.

Authors:  Antonio Luna; Shivani Pahwa; Claudio Bonini; Lidia Alcalá-Mata; Katherine L Wright; Vikas Gulani
Journal:  Magn Reson Imaging Clin N Am       Date:  2016-02       Impact factor: 2.266

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