Literature DB >> 35111631

Histogram peritumoral enhanced features on MRI arterial phase with extracellular contrast agent can improve prediction of microvascular invasion of hepatocellular carcinoma.

Xinxin Wang1, Yunfeng Sun1, Xueyan Zhou2, Zhiwei Shen3, Hongxia Zhang1, Jiqing Xing4, Yang Zhou1.   

Abstract

BACKGROUND: Preoperative microvascular invasion (MVI) prediction plays an important role in therapeutic decision-making of hepatocellular carcinoma (HCC). This study aimed to investigate the value of histogram based on the arterial phase (AP) of magnetic resonance imaging (MRI) with extracellular contrast agent compared with radiological features for predicting MVI of solitary HCC.
METHODS: In total, 113 patients with pathologically proven solitary HCC were retrospectively enrolled who received surgical resection and underwent preoperative abdominal MRI. The patients were divided into the ≤3 cm [small HCC (sHCC)] cohort and the >3 cm cohort. Based on pathological analysis of surgical specimens, the patients were classified into MVI negative (MVI-) and MVI positive (MVI+) groups. Peritumoral and intratumoral histogram features [mean, median, standard deviation (Std), coefficient of variation (CV), skewness, kurtosis] were acquired on AP subtraction images and radiological features [size, capsule, corona enhancement, corona enhancement thickness (CET), CET group]. Receiver operating characteristic (ROC) curve was constructed to assess predictive capability. Subgroup analysis of patients with a visible corona enhancement based on the CET cut-off value was performed.
RESULTS: None of the features extracted from the intratumor area were significantly different between the MVI+ and MVI- groups in both cohorts. Histogram defined peritumoral (peri-) mean, median, kurtosis, and radiological features including CET and CET group were associated with MVI in sHCCs. Peri-mean, median, Std and radiological features including incomplete capsule, CET, and CET group were associated with MVI in HCC >3 cm. In multivariate logistic regression analysis, the CET group and peri-mean were independent predictors for HCC >3 cm with an area under the curve (AUC) of 0.741. Peri-mean was an independent predictor for sHCC (AUC =0.798). Subgroup analysis of the corona enhancement using 8 mm as a cut-off value showed 100% sensitivity and negative predictive value (NPV).
CONCLUSIONS: Peritumoral AP enhanced degree on MRI showed an encouraging predictive performance for preoperative prediction of MVI, especially in sHCCs. CET ≤8 mm could be used as a negative predictive marker for MVI. 2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Microvascular invasion (MVI); contrast enhancement; hepatocellular carcinoma (HCC); magnetic resonance imaging (MRI); quantitative analysis

Year:  2022        PMID: 35111631      PMCID: PMC8739130          DOI: 10.21037/qims-21-499

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  29 in total

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Authors:  Alejandro Forner; María Reig; Jordi Bruix
Journal:  Lancet       Date:  2018-01-05       Impact factor: 79.321

2.  Surgical resection for hepatocellular carcinoma: Moving from what can be done to what is worth doing.

Authors:  Renato Romagnoli; Vincenzo Mazzaferro; Jordi Bruix
Journal:  Hepatology       Date:  2015-05-29       Impact factor: 17.425

Review 3.  Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma: a 2017 update.

Authors:  Masao Omata; Ann-Lii Cheng; Norihiro Kokudo; Masatoshi Kudo; Jeong Min Lee; Jidong Jia; Ryosuke Tateishi; Kwang-Hyub Han; Yoghesh K Chawla; Shuichiro Shiina; Wasim Jafri; Diana Alcantara Payawal; Takamasa Ohki; Sadahisa Ogasawara; Pei-Jer Chen; Cosmas Rinaldi A Lesmana; Laurentius A Lesmana; Rino A Gani; Shuntaro Obi; A Kadir Dokmeci; Shiv Kumar Sarin
Journal:  Hepatol Int       Date:  2017-06-15       Impact factor: 6.047

4.  Whole-tumor MRI histogram analyses of hepatocellular carcinoma: Correlations with Ki-67 labeling index.

Authors:  Xin-Xing Hu; Zhao-Xia Yang; He-Yue Liang; Ying Ding; Robert Grimm; Cai-Xia Fu; Hui Liu; Xu Yan; Yuan Ji; Meng-Su Zeng; Sheng-Xiang Rao
Journal:  J Magn Reson Imaging       Date:  2016-11-10       Impact factor: 4.813

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Authors:  Hong Wei; Hanyu Jiang; Xijiao Liu; Yun Qin; Tianying Zheng; Siyun Liu; Xin Zhang; Bin Song
Journal:  Eur J Radiol       Date:  2020-09-28       Impact factor: 3.528

Review 6.  Liver Imaging Reporting and Data System (LI-RADS) Version 2018: Imaging of Hepatocellular Carcinoma in At-Risk Patients.

Authors:  Victoria Chernyak; Kathryn J Fowler; Aya Kamaya; Ania Z Kielar; Khaled M Elsayes; Mustafa R Bashir; Yuko Kono; Richard K Do; Donald G Mitchell; Amit G Singal; An Tang; Claude B Sirlin
Journal:  Radiology       Date:  2018-09-25       Impact factor: 11.105

7.  Microvascular invasion in patients with hepatocellular carcinoma and its predictable clinicopathological factors.

Authors:  Shuji Sumie; Ryoko Kuromatsu; Koji Okuda; Eiji Ando; Akio Takata; Nobuyoshi Fukushima; Yasutomo Watanabe; Masamichi Kojiro; Michio Sata
Journal:  Ann Surg Oncol       Date:  2008-03-07       Impact factor: 5.344

8.  Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma.

Authors:  Xiaohong Ma; Han Ouyang; Shuang Wang; Meng Wang; Chunwu Zhou; Xinming Zhao
Journal:  Chin J Cancer Res       Date:  2019-04       Impact factor: 5.087

9.  Considerable effects of imaging sequences, feature extraction, feature selection, and classifiers on radiomics-based prediction of microvascular invasion in hepatocellular carcinoma using magnetic resonance imaging.

Authors:  Houjiao Dai; Minhua Lu; Bingsheng Huang; Mimi Tang; Tiantian Pang; Bing Liao; Huasong Cai; Mengqi Huang; Yongjin Zhou; Xin Chen; Huijun Ding; Shi-Ting Feng
Journal:  Quant Imaging Med Surg       Date:  2021-05

10.  Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma.

Authors:  Ya-Qin Huang; He-Yue Liang; Zhao-Xia Yang; Ying Ding; Meng-Su Zeng; Sheng-Xiang Rao
Journal:  Medicine (Baltimore)       Date:  2016-06       Impact factor: 1.889

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