Department of Gastrointestinal Surgery, Affiliated Hospital of Qingdao University, Qingdao, China.
Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Shandong First Medical University, Shandong, China.
Med Phys. 2024 Apr;51(4):2563-2577. doi: 10.1002/mp.16827. Epub 2023 Nov 21.
A circumferential resection margin (CRM) is an independent risk factor for local recurrence, distant metastasis, and poor overall survival of rectal cancer. In this study, we developed and validated a radiomics prediction model to predict perioperative surgical margins in patients with middle and low rectal cancer following neoadjuvant treatment and for decisions about treatment plans for patients.
This study retrospectively analyzed 275 patients from center 1(training cohort) and 120 patients from center 2(verification cohort) with rectal cancer diagnosed at two centers from July 2020 to July 2022 who underwent neoadjuvant therapy and had their CRM status confirmed by preoperative high-resolution magnetic resonance imaging (MRI) scans. Radiomics signatures were extracted and screened from MRI images and a radiomics signature was built by the least absolute shrinkage and selection operator (LASSO) logistic regression model, which was combined with clinical signatures to construct a nomogram. The receiver operating characteristic (ROC) curve and area under the curve (AUC) value, sensitivity, specificity, positive predictive value, negative predictive value, and calibration curve were used to evaluate the predictive performance of the model.
In our research, the combined model has the best performance. In the training group, the radiomics model based on high-spatial-resolution T2-weighted imaging (HR-T2WI), clinical model and combined model demonstrated an AUC of 0.819 (0.802-0.833), 0.843 (0.822-0.861), and 0.910 (0.880-0.940), respectively. In the validation group, they demonstrated an AUC of 0.745 (0.715-0.788), 0.827 (0.798-0.850), and 0.848 (0.779-0.917), respectively. The calibration curve confirmed the clinical applicability of the model.
The individualized prediction model established by combining radiomics signatures and clinical signatures can efficiently and objectively predict perioperative margin invasion in patients with middle and low rectal cancer.
环周切缘（CRM）是直肠癌局部复发、远处转移和总体生存不良的独立危险因素。本研究旨在开发和验证一种放射组学预测模型，以预测接受新辅助治疗的中低位直肠癌患者的围手术期切缘，并为患者的治疗计划决策提供依据。
本研究回顾性分析了 2020 年 7 月至 2022 年 7 月在两个中心确诊为直肠癌并接受新辅助治疗的 275 例患者（中心 1，训练队列）和 120 例患者（中心 2，验证队列）的临床资料，这些患者的 CRM 状态均通过术前高分辨率磁共振成像（MRI）扫描得到确认。从 MRI 图像中提取放射组学特征，并采用最小绝对收缩和选择算子（LASSO）逻辑回归模型进行筛选，构建放射组学特征与临床特征相结合的列线图。采用受试者工作特征（ROC）曲线和曲线下面积（AUC）值、灵敏度、特异度、阳性预测值、阴性预测值和校准曲线评估模型的预测性能。
在本研究中，联合模型具有最佳性能。在训练组中，基于高空间分辨率 T2 加权成像（HR-T2WI）的放射组学模型、临床模型和联合模型的 AUC 分别为 0.819（0.802-0.833）、0.843（0.822-0.861）和 0.910（0.880-0.940）。在验证组中，它们的 AUC 分别为 0.745（0.715-0.788）、0.827（0.798-0.850）和 0.848（0.779-0.917）。校准曲线证实了模型的临床适用性。
放射组学特征与临床特征相结合的个体化预测模型可以有效地、客观地预测中低位直肠癌患者的围手术期切缘侵犯情况。
