A Novel Clinical-Radiomics Model Based on Sarcopenia and Radiomics for Predicting the Prognosis of Intrahepatic Cholangiocarcinoma After Radical Hepatectomy

Liming Deng; Bo Chen; Chenyi Zhan; Haitao Yu; Jiuyi Zheng; Wenming Bao; Tuo Deng; Chongming Zheng; Lijun Wu; Yunjun Yang; Zhengping Yu; Yi Wang; Gang Chen

doi:10.3389/fonc.2021.744311

A Novel Clinical-Radiomics Model Based on Sarcopenia and Radiomics for Predicting the Prognosis of Intrahepatic Cholangiocarcinoma After Radical Hepatectomy

Front Oncol. 2021 Nov 19:11:744311. doi: 10.3389/fonc.2021.744311. eCollection 2021.

Authors

Liming Deng^{1

2}, Bo Chen^{1

2}, Chenyi Zhan³, Haitao Yu^{1

2}, Jiuyi Zheng^{1

2}, Wenming Bao^{1

2}, Tuo Deng^{1

2}, Chongming Zheng^{1

2}, Lijun Wu^{1

2}, Yunjun Yang³, Zhengping Yu^{1

2}, Yi Wang⁴, Gang Chen^{1

2}

Affiliations

¹ Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
² Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
³ Department of Medical Imaging, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
⁴ Department of Epidemiology and Biostatistics, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China.

Abstract

Background: Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive malignant tumor with a poor prognosis. This study aimed to establish a novel clinical-radiomics model for predicting the prognosis of ICC after radical hepatectomy.

Methods: A clinical-radiomics model was established for 82 cases of ICC treated with radical hepatectomy in our hospital from May 2011 to December 2020. Radiomics features were extracted from venous-phase and arterial-phase images of computed tomography. Kaplan-Meier survival analysis was generated to compare overall survival (OS) between different groups. The independent factors were identified by univariate and multivariate Cox regression analyses. Nomogram performance was evaluated regarding discrimination, calibration, and clinical utility. C-index and area under the curve (AUC) were utilized to compare the predictive performance between the clinical-radiomics model and conventional staging systems.

Results: The radiomics model included five features. The AUC of the radiomics model was 0.817 in the training cohort, and 0.684 in the validation cohort. The clinical-radiomics model included psoas muscle index, radiomics score, hepatolithiasis, carcinoembryonic antigen, and neutrophil/lymphocyte ratio. The reliable C-index of the model was 0.768, which was higher than that of other models. The AUC of the model for predicting OS at 1, and 3 years was 0.809 and 0.886, which was significantly higher than that of the American Joint Committee on Cancer 8^th staging system (0.594 and 0.619), radiomics model (0.743 and 0.770), and tumor differentiation (0.645 and 0.628). After stratification according to the constructed model, the median OS was 59.8 months for low-risk ICC patients and 10.1 months for high-risk patients (p < 0.0001).

Conclusion: The clinical-radiomics model integrating sarcopenia, clinical features, and radiomics score was accurate for prognostic prediction for mass-forming ICC patients. It provided an individualized prognostic evaluation in patients with mass-forming ICC and could helped surgeons with clinical decision-making.

Keywords: clinical-radiomics model; intrahepatic cholangiocarcinoma; nomogram; radical hepatectomy; sarcopenia.