Gd-EOB-DTPA-enhanced MRI radiomic features for predicting histological grade of hepatocellular carcinoma  

作　　者：Yingfan Mao Jincheng Wang Yong Zhu Jun Chen Liang Mao Weiwei Kong Yudong Qiu Xiaoyan Wu Yue Guan Jian He 

机构地区：[1]Department of Radiology,Nanjing Drum Tower Hospital,the Affiliated Hospital of Nanjing University Medical School,Nanjing,China [2]Department of Hepatobiliary Surgery,Drum Tower Clinical Medical College,Nanjing Medical University,Nanjing,China [3]Department of Radiology,Jiangsu Province Hospital of Traditional Chinese Medicine,the Affiliated Hospital of Nanjing University of Chinese Medicine,Nanjing,China [4]Department of Pathology,Nanjing Drum Tower Hospital,the Affiliated Hospital of Nanjing University Medical School,Nanjing,China [5]Department of Hepatopancreatobiliary Surgery,Nanjing Drum Tower Hospital,the Affiliated Hospital of Nanjing University Medical School,Nanjing,China [6]Department of Oncology,Nanjing Drum Tower Hospital,the Affiliated Hospital of Nanjing University Medical School,Nanjing,China [7]School of Biomedical Engineering,Shanghai Jiao Tong University,Shanghai,China

出　　处：《Hepatobiliary Surgery and Nutrition》2022年第1期13-24,I0001-I0005,共17页肝胆外科与营养（英文）

基　　金：This study has received funding by Outstanding Youth supported by Medical Science and Technology Development Foundation Nanjing(JQX16022);Jiangsu Province Key Medical Young Talents,“13th Five-Year”Health Promotion Project of Jiangsu Province(QNRC2016041);The study was conducted in accordance with the Declaration of Helsinki(as revised in 2013);The study was approved by local institutional review board(No.2019AE01036);informed consent from patients was waived due to its retrospective nature。

摘　　要：Background:Prediction models for the histological grade of hepatocellular carcinoma(HCC)remain unsatisfactory.The purpose of this study is to develop preoperative models to predict histological grade of HCC based on gadolinium-ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)-enhanced magnetic resonance imaging(MRI)radiomics.And to compare the performance between artificial neural network(ANN)and logistic regression model.Methods:A total of 122 HCCs were randomly assigned to the training set(n=85)and the test set(n=37).There were 242 radiomic features extracted from volumetric of interest(VOI)of arterial and hepatobiliary phases images.The radiomic features and clinical parameters[gender,age,alpha-fetoprotein(AFP),carcinoembryonic antigen(CEA),carbohydrate antigen 19-9(CA19-9),alanine aminotransferase(ALT),aspartate transaminase(AST)]were selected by permutation test and decision tree.ANN of arterial phase(ANN-AP),logistic regression model of arterial phase(LR-AP),ANN of hepatobiliary phase(ANN-HBP),logistic regression mode of hepatobiliary phase(LR-HBP),ANN of combined arterial and hepatobiliary phases(ANN-AP+HBP),and logistic regression model of combined arterial and hepatobiliary phases(LR-AP+HBP)were built to predict HCC histological grade.Those prediction models were assessed and compared.Results:ANN-AP and LR-AP were composed by AST and radiomic features based on arterial phase.ANN-HBP and LR-HBP were composed by AFP and radiomic features based on hepatobiliary phase.ANN-AP+HBP and LR-AP+HBP were composed by AST and radiomic features based on arterial and hepatobiliary phases.The prediction models could distinguish between high-grade tumors[Edmondson-Steiner(E-S)grade III and IV]and low-grade tumors(E-S grade I and II)in both training set and test set.In the test set,the AUCs of ANN-AP,LR-AP,ANN-HBP,LR-HBP,ANN-AP+HBP and LR-AP+HBP were 0.889,0.777,0.941,0.819,0.944 and 0.792 respectively.The ANN-HBP was significantly superior to LR-HBP(P=0.001).And the ANN-AP+HBP was significantly superior to LR

关 键 词：Hepatocellular carcinoma(HCC) histological grade magnetic resonance imaging(MRI) hepatobiliary phase radiomics 

分 类 号：R73[医药卫生—肿瘤]