An Interpretable Radiomics Model Based on Two-Dimensional Shear Wave Elastography for Predicting Symptomatic Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma

被引：1

作者：

Zhong, Xian ^{[1
,2
]}

Salahuddin, Zohaib ^{[2
]}

Chen, Yi ^{[2
,3
]}

Woodruff, Henry C. ^{[2
,4
]}

Long, Haiyi ^{[1
]}

Peng, Jianyun ^{[1
]}

Xie, Xiaoyan ^{[1
]}

Lin, Manxia ^{[1
]}

Lambin, Philippe ^{[2
,4
]}

机构：

[1] Sun Yat sen Univ, Affiliated Hosp 1, Inst Diagnost & Intervent Ultrasound, Dept Med Ultrason, Guangzhou 510080, Peoples R China

[2] Maastricht Univ, GROW Sch Oncol & Reprod, Dept Precis Med, D Lab, NL-6220 MD Maastricht, Netherlands

[3] Guizhou Univ, Coll Comp Sci & Technol, Key Lab Intelligent Med Image Anal & Precise Diag, Guiyang 550025, Peoples R China

[4] Maastricht Univ, GROW Sch Oncol & Reprod, Dept Radiol & Nucl Med, Med Ctr, NL-6229 HX Maastricht, Netherlands

来源：

CANCERS | 2023年 / 15卷 / 21期

基金：

中国国家自然科学基金;

关键词：

hepatocellular carcinoma; post-hepatectomy liver failure; two-dimensional shear wave elastography; radiomics; interpretability; ALBUMIN-BILIRUBIN SCORE; CHILD-PUGH SCORE; DISEASE; CLASSIFICATION; FIBROSIS; RISK;

D O I：

10.3390/cancers15215303

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Objective: The aim of this study was to develop and validate an interpretable radiomics model based on two-dimensional shear wave elastography (2D-SWE) for symptomatic post-hepatectomy liver failure (PHLF) prediction in patients undergoing liver resection for hepatocellular carcinoma (HCC). Methods: A total of 345 consecutive patients were enrolled. A five-fold cross-validation was performed during training, and the models were evaluated in the independent test cohort. A multi-patch radiomics model was established based on the 2D-SWE images for predicting symptomatic PHLF. Clinical features were incorporated into the models to train the clinical-radiomics model. The radiomics model and the clinical-radiomics model were compared with the clinical model comprising clinical variables and other clinical predictive indices, including the model for end-stage liver disease (MELD) score and albumin-bilirubin (ALBI) score. Shapley Additive exPlanations (SHAP) was used for post hoc interpretability of the radiomics model. Results: The clinical-radiomics model achieved an AUC of 0.867 (95% CI 0.787-0.947) in the five-fold cross-validation, and this score was higher than that of the clinical model (AUC: 0.809; 95% CI: 0.715-0.902) and the radiomics model (AUC: 0.746; 95% CI: 0.681-0.811). The clinical-radiomics model showed an AUC of 0.822 in the test cohort, higher than that of the clinical model (AUC: 0.684, p = 0.007), radiomics model (AUC: 0.784, p = 0.415), MELD score (AUC: 0.529, p < 0.001), and ALBI score (AUC: 0.644, p = 0.016). The SHAP analysis showed that the first-order radiomics features, including first-order maximum 64 x 64, first-order 90th percentile 64 x 64, and first-order 10th percentile 32 x 32, were the most important features for PHLF prediction. Conclusion: An interpretable clinical-radiomics model based on 2D-SWE and clinical variables can help in predicting symptomatic PHLF in HCC.

引用

页数：15

共 34 条

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