Beyond the tumor region:Peritumoral radiomics enhances prognostic accuracy in locally advanced rectal cancer  

作　　者：Zhi-Ying Liang Mao-Li Yu Hui Yang Hao-Jiang Li Hui Xie Chun-Yan Cui Wei-Jing Zhang Chao Luo Pei-Qiang Cai Xiao-Feng Lin Kun-Feng Liu Lang Xiong Li-Zhi Liu Bi-Yun Chen 

机构地区：[1]Department of Radiology,State Key Laboratory of Oncology in South China,Guangdong Provincial Clinical Research Center for Cancer,Sun Yat-sen University Cancer Center,Guangzhou 510060,Guangdong Province,China [2]Department of Radiology,West China Hospital,Sichuan University,Chengdu 610041,Sichuan Province,China [3]West China School of Medicine,Sichuan University,Chengdu 610041,Sichuan Province,China [4]Department of Medical Imaging,First Affiliated Hospital of Gannan Medical University,Ganzhou 341000,Jiangxi Province,China

出　　处：《World Journal of Gastroenterology》2025年第8期49-65,共17页世界胃肠病学杂志(英文)

摘　　要：BACKGROUND The peritumoral region possesses attributes that promote cancer growth and progression.However,the potential prognostic biomarkers in this region remain relatively underexplored in radiomics.AIM To investigate the prognostic value and importance of peritumoral radiomics in locally advanced rectal cancer(LARC).METHODS This retrospective study included 409 patients with biopsy-confirmed LARC treated with neoadjuvant chemoradiotherapy and surgically.Patients were divided into training(n=273)and validation(n=136)sets.Based on intratumoral and peritumoral radiomic features extracted from pretreatment axial high-resolution small-field-of-view T2-weighted images,multivariate Cox models for progression-free survival(PFS)prediction were developed with or without clinicoradiological features and evaluated with Harrell’s concordance index(C-index),calibration curve,and decision curve analyses.Risk stratification,Kaplan-Meier analysis,and permutation feature importance analysis were performed.RESULTS The comprehensive integrated clinical-radiological-omics model(ModelICRO)integrating seven peritumoral,three intratumoral,and four clinicoradiological features achieved the highest C-indices(0.836 and 0.801 in the training and validation sets,respectively).This model showed robust calibration and better clinical net benefits,effectively distinguished high-risk from low-risk patients(PFS:97.2%vs 67.6%and 95.4%vs 64.8%in the training and validation sets,respectively;both P<0.001).Three most influential predictors in the comprehensive ModelICRO were,in order,a peritumoral,an intratumoral,and a clinicoradiological feature.Notably,the peritumoral model outperformed the intratumoral model(C-index:0.754 vs 0.670;P=0.015);peritumoral features significantly enhanced the performance of models based on clinicoradiological or intratumoral features or their combinations.CONCLUSION Peritumoral radiomics holds greater prognostic value than intratumoral radiomics for predicting PFS in LARC.The comprehensive model may serve as a rel

关 键 词：Rectal cancer Peritumoral radiomics Intratumoral radiomics Prognosis analysis Variable importance analysis Tumor microenvironment 

分 类 号：R735.37[医药卫生—肿瘤]