A Novel Clinical-Radiomics Model Based on Sarcopenia and Radiomics for Predicting the Prognosis of Intrahepatic Cholangiocarcinoma After Radical Hepatectomy
| العنوان: | A Novel Clinical-Radiomics Model Based on Sarcopenia and Radiomics for Predicting the Prognosis of Intrahepatic Cholangiocarcinoma After Radical Hepatectomy |
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| المؤلفون: | 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 |
| المصدر: | Frontiers in Oncology Frontiers in Oncology, Vol 11 (2021) |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Oncology, Cancer Research, medicine.medical_specialty, medicine.medical_treatment, clinical-radiomics model, sarcopenia, nomogram, Carcinoembryonic antigen, radical hepatectomy, intrahepatic cholangiocarcinoma, Internal medicine, medicine, RC254-282, Survival analysis, Intrahepatic Cholangiocarcinoma, Original Research, biology, Proportional hazards model, business.industry, Area under the curve, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Cancer, Nomogram, medicine.disease, biology.protein, Hepatectomy, business |
| الوصف: | BackgroundIntrahepatic 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.MethodsA 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.ResultsThe 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 8th 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).ConclusionThe 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. |
| تدمد: | 2234-943X |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79ae1b9ea150b07b8046171c1a7e25a3Test https://pubmed.ncbi.nlm.nih.gov/34868941Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....79ae1b9ea150b07b8046171c1a7e25a3 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 2234943X |
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