Computed tomography-based multi-organ radiomics nomogram model for predicting the risk of esophagogastric variceal bleeding in cirrhosis  

作　　者：Yu-Jie Peng Xin Liu Ying Liu Xue Tang Qi-Peng Zhao Yong Du 

机构地区：[1]Department of Radiology,The Affiliated Hospital of North Sichuan Medical College,Nanchong 637000,Sichuan Province,China [2]Department of Radiology,The People’s Hospital of Chongqing Liang Jiang New Area,Chongqing 401121,China

出　　处：《World Journal of Gastroenterology》2024年第36期4044-4056,共13页世界胃肠病学杂志（英文版）

摘　　要：BACKGROUND Radiomics has been used in the diagnosis of cirrhosis and prediction of its associated complications.However,most current studies predict the risk of esophageal variceal bleeding(EVB)based on image features at a single level,which results in incomplete data.Few studies have explored the use of global multi-organ radiomics for non-invasive prediction of EVB secondary to cirrhosis.AIM To develop a model based on clinical and multi-organ radiomic features to predict the risk of first-instance secondary EVB in patients with cirrhosis.METHODS In this study,208 patients with cirrhosis were retrospectively evaluated and randomly split into training(n=145)and validation(n=63)cohorts.Three areas were chosen as regions of interest for extraction of multi-organ radiomic features:The whole liver,whole spleen,and lower esophagus–gastric fundus region.In the training cohort,radiomic score(Rad-score)was created by screening radiomic features using the inter-observer and intra-observer correlation coefficients and the least absolute shrinkage and selection operator method.Independent clinical risk factors were selected using multivariate logistic regression analyses.The radiomic features and clinical risk variables were combined to create a new radiomics-clinical model(RC model).The established models were validated using the validation cohort.BACKGROUND Radiomics has been used in the diagnosis of cirrhosis and prediction of its associated complications.However,most current studies predict the risk of esophageal variceal bleeding(EVB)based on image features at a single level,which results in incomplete data.Few studies have explored the use of global multi-organ radiomics for non-invasive prediction of EVB secondary to cirrhosis.AIM To develop a model based on clinical and multi-organ radiomic features to predict the risk of first-instance secondary EVB in patients with cirrhosis.METHODS In this study,208 patients with cirrhosis were retrospectively evaluated and randomly split into training(n=145)and validation(n=6

关 键 词：Artificial intelligence CIRRHOSIS Radiomics Esophagogastric variceal bleeding 

分 类 号：R575.2[医药卫生—消化系统]