Liang Zhi-Ying, Yu Mao-Li, Yang Hui, Li Hao-Jiang, Xie Hui, Cui Chun-Yan, Zhang Wei-Jing, Luo Chao, Cai Pei-Qiang, Lin Xiao-Feng, Liu Kun-Feng, Xiong Lang, Liu Li-Zhi, Chen Bi-Yun
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.
Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
World J Gastroenterol. 2025 Feb 28;31(8):99036. doi: 10.3748/wjg.v31.i8.99036.
The peritumoral region possesses attributes that promote cancer growth and progression. However, the potential prognostic biomarkers in this region remain relatively underexplored in radiomics.
To investigate the prognostic value and importance of peritumoral radiomics in locally advanced rectal cancer (LARC).
This retrospective study included 409 patients with biopsy-confirmed LARC treated with neoadjuvant chemoradiotherapy and surgically. Patients were divided into training ( = 273) and validation ( = 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.
The comprehensive integrated clinical-radiological-omics model (Model) 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% 67.6% and 95.4% 64.8% in the training and validation sets, respectively; both < 0.001). Three most influential predictors in the comprehensive Model were, in order, a peritumoral, an intratumoral, and a clinicoradiological feature. Notably, the peritumoral model outperformed the intratumoral model (C-index: 0.754 0.670; = 0.015); peritumoral features significantly enhanced the performance of models based on clinicoradiological or intratumoral features or their combinations.
Peritumoral radiomics holds greater prognostic value than intratumoral radiomics for predicting PFS in LARC. The comprehensive model may serve as a reliable tool for better stratification and management postoperatively.
肿瘤周围区域具有促进癌症生长和进展的特性。然而，该区域潜在的预后生物标志物在放射组学中仍未得到充分探索。
探讨肿瘤周围放射组学在局部晚期直肠癌（LARC）中的预后价值和重要性。
这项回顾性研究纳入了409例经活检确诊的LARC患者，这些患者接受了新辅助放化疗和手术治疗。患者被分为训练组（n = 273）和验证组（n = 136）。基于从治疗前轴向高分辨率小视野T2加权图像中提取的肿瘤内和肿瘤周围放射组学特征，建立了有无临床放射学特征的无进展生存（PFS）预测多变量Cox模型，并通过Harrell一致性指数（C指数）、校准曲线和决策曲线分析进行评估。进行了风险分层、Kaplan-Meier分析和排列特征重要性分析。
整合了七个肿瘤周围、三个肿瘤内和四个临床放射学特征的综合临床-放射学-组学模型（模型）取得了最高的C指数（训练组和验证组分别为0.836和0.801）。该模型显示出稳健的校准和更好的临床净效益，有效地区分了高风险和低风险患者（PFS：训练组和验证组分别为97.2%对67.6%和95.4%对64.8%；P均<0.001）。综合模型中三个最有影响力的预测因子依次为一个肿瘤周围、一个肿瘤内和一个临床放射学特征。值得注意的是，肿瘤周围模型优于肿瘤内模型（C指数：0.754对0.670；P = 0.015）；肿瘤周围特征显著提高了基于临床放射学或肿瘤内特征或其组合的模型的性能。
对于预测LARC的PFS，肿瘤周围放射组学比肿瘤内放射组学具有更大的预后价值。综合模型可作为术后更好分层和管理的可靠工具。
