磁共振成像2025，Vol.16Issue(3)：51-57,7.DOI:10.12015/issn.1674-8034.2025.03.008
基于CEMRI瘤内瘤周影像组学预测肝细胞癌分化程度的研究
CEMRI-based intratumoral and peritumoral radiomics for predicting the degree of pathological differentiation of hepatocellular carcinoma
摘要
Abstract
Objective:To develop and validate intratumoral and multiregion peritumoral radiomics models based on contrast-enhanced magnetic resonance imaging(CEMRI)for predicting pathological differentiation in hepatocellular carcinoma(HCC)patients.Materials and Methods:A total of 213 HCC patients diagnosed between January 2020 and July 2023 at the Third Affiliated Hospital of Soochow University was included in the retrospective study,comprising 62 poorly differentiated HCC(pHCC)and 161 non-poorly differentiated HCCs(npHCC).The HCCs were randomly divided into training(149 patients,156 HCCs)and validation(64 patients,67 HCCs)cohorts at a 7∶3 ratio.The ITK-SNAP software delineated the region of interest(ROI)on arterial,portal vein,and delayed phase images,while PyRadiomics software extracted 3045 radiomic features.Feature selection was carried out using Spearman rank correlation,least absolute shrinkage and selection operator(LASSO),and maximum relevance-minimum redundancy(mRMR)approaches,followed by support vector machine algorithm to build Intratumoral,5 mm peritumoral(Peri_5mm),10 mm peritumoral(Peri_10mm),and Intratumoral+10 mm peritumoral(IntraPeri)models.The predictive performance of these models was assessed using the area under the curve(AUC)of receiver operating characteristic and decision curve analysis(DCA).Results:The Intratumoral,Peri_5mm,Peri_10mm,and IntraPeri models consisted of 10,17,11,and 12 features,respectively.In the Intratumoral model,the AUC values for predicting pHCC in the training and validation cohorts were 0.92 and 0.93,respectively.The Peri_10mm model exhibited higher AUCs compared to the Peri_5mm model:0.88 versus 0.82 in the training cohort and 0.90 versus 0.85 in the validation cohort.The IntraPeri model demonstrated superior performance with AUC values of 0.95 and 0.95 in the training and validation cohorts,respectively.DCA suggested that the Intratumoral,Peri_5mm,and Peri_10mm models provided notable clinical benefits,with the IntraPeri model being the most optimal.Conclusions:The IntraPeri model based on CEMRI can accurately predict HCC differentiation and has good clinical benefits.关键词
肝细胞癌/分化程度/磁共振成像/瘤内/瘤周/影像组学Key words
hepatocellular carcinoma/pathological differentiation/magnetic resonance imaging/intratumoral/peritumoral/radiomics分类
医药卫生引用本文复制引用
陆煜杰,顾文豪,许大波,刘海峰,邢伟..基于CEMRI瘤内瘤周影像组学预测肝细胞癌分化程度的研究[J].磁共振成像,2025,16(3):51-57,7.基金项目
The Clinical Research Project of the First People's Hospital of Changzhou(No.2024-14) （No.2024-14）
2024 Suzhou Applied Basic Research(Medical and Health)Science and Technology(Second Batch)Innovation Guidance Projec(No.SYWD2024020). 2024年常州市第一人民医院临床研究专项(编号:2024-14) （Medical and Health）
2024年度苏州市应用基础研究(医疗卫生)科技创新(第二批)指导性项目(编号:SYWD2024020) （医疗卫生）
