Outcome prediction after resection of colorectal cancer liver metastases: out with the old, in with the new?

作     者：Iakovos Amygdalos Daniel Truhn Florian W.R.Vondran 

作者机构：Department of GeneralVisceralPediatric and Transplantation SurgeryUniversity Hospital RWTH AachenAachenGermany Department of Diagnostic and Interventional RadiologyUniversity Hospital RWTH AachenAachenGermany 

出 版 物：《Hepatobiliary Surgery and Nutrition》 (肝胆外科与营养（英文）)

年 卷 期：2024年第13卷第4期

页      面：732-735页

核心收录：

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主　　题：Machine learning(ML) artificial intelligence(AI) colorectal liver metastases hepatobiliary 

摘      要：Colorectal cancer remains one of the commonest and most lethal malignancies worldwide(1).Up to 80%of patients with colorectal cancer develop liver metastases(CRLM),which are the main factor limiting survival(1,2).Despite advances in systemic therapy and the emergence of multimodal treatment concepts,curative surgical resection remains the best therapeutic option and provides the highest chance of long-term survival(1,2).However,liver resection is associated with perioperative morbidity and mortality,while multiple factors affect long-term prognosis(3,4).As a result,various predictive models have been developed over time,to improve preoperative patient selection and foresee unfavourable outcomes.