Evidence map›Paper›PMID 42859213›Full record

ArticleAbdominal radiology (New York)2026

CT radiomics and topology-based intratumoral heterogeneity for preoperative prediction of nuclear β-catenin expression in hepatocellular carcinoma.

Yongming Tan, Siya Xu, Xiaofang Liu, Weiwei Liao, Ru Zhu, Minghui Shen, Weijia Wang, Meng Liu, Jianwei Liu

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Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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9 authors.

Yongming TanDepartment of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.ORCID http://orcid.org/0009-0000-7867-3246
Siya XuDepartment of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Xiaofang LiuDepartment of Radiology, Xinyu People's Hospital, Xinyu, China.
Weiwei LiaoDepartment of Radiology, Ganzhou People's Hospital, Ganzhou, China.ORCID https://orcid.org/0009-0006-8537-7924
Ru ZhuDepartment of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Minghui ShenDepartment of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Weijia WangDepartment of Pathology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Meng LiuDepartment of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Jianwei LiuDepartment of stomatology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China. ndyfy05875@ncu.edu.cn.

Funding

Clinical Medical Research Center Project of Jiangxi Province Grant No. 20223BCG74001the Key Laboratory of Precision Pathology and Intelligent Diagnosis of Jiangxi Province Grant No. 2024SSY06281the Project of Jiangxi Provincial Health Commission Grant No. 202610023the Science and Technology Research Project of the Education Department of Jiangxi Province Grant No. GJJ2200110
6 · The paper itself

Abstract

backgroundNuclear β-catenin accumulation reflects activation of the Wnt/β-catenin pathway in hepatocellular carcinoma (HCC), but noninvasive preoperative prediction of this immunohistochemical phenotype remains incompletely established. PURPOSE: To develop and externally validate CT radiomics and topology-based intratumoral heterogeneity (ITH) models for preoperative prediction of nuclear β-catenin expression in HCC. MATERIALS AND

methodsThis multicenter retrospective study included 1029 patients with histopathologically confirmed HCC. Patients from two participating institutions formed the development cohort and were split into training (n=620; nuclear β-catenin-positive, 293) and internal validation (n=267; nuclear β-catenin-positive, 126) sets. Patients from an independent third institution formed the external validation cohort (n=142; nuclear β-catenin-positive, 43). Whole-tumor portal venous phase CT radiomics features and topology-based ITH features were extracted from the audited image-mask cohort. Model discrimination, calibration, and clinical utility were evaluated using AUC, bootstrap 95% confidence intervals, calibration summaries, Brier scores, and decision curve analysis.

resultsIn external validation, AUCs were 0.677 for the clinical model, 0.862 for the radiomics model, 0.857 for the ITH model, 0.831 for the core ITH model, 0.863 for the radiomics-ITH model, and 0.886 for the stacking model. Compared with radiomics alone, stacking showed a numerical ΔAUC of 0.024 (95% CI, -0.010 to 0.060; P=0.180).

conclusionCT radiomics and topology-based ITH features showed external predictive value for nuclear β-catenin expression in HCC. The stacking model had the highest external AUC, but its improvement over radiomics alone was not statistically significant. If prospectively validated, these CT-based approaches could complement tissue assessment for pretreatment biological stratification.

Indexed as

Beta-cateninHepatocellular carcinomaRadiomicsTomographyTumor heterogeneityX-ray computed

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PMID42859213

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