Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing 210029, China.
Department of PET/CT Center, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research and the Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, China.
Acad Radiol. 2024 Dec;31(12):5066-5077. doi: 10.1016/j.acra.2024.05.029. Epub 2024 Jun 6.
The aim of this study was to develop and validate a nomogram, integrating clinical factors and radiomics features, capable of predicting overall survival (OS) in patients diagnosed with esophageal squamous cell carcinoma (ESCC).
In this study, we retrospectively analyzed the case data of 130 patients with ESCC who underwent F-FDG PET/CT before treatment. Radiomics features associated with OS were screened by univariate Cox regression (p < 0.05). Further selection was performed by applying the least absolute shrinkage and selection operator Cox regression to generate the weighted Radiomics-score (Rad-score). Independent clinical risk factors were obtained by multivariate Cox regression, and a nomogram was constructed by combining Rad-score and independent risk factors. The predictive performance of the model for OS was assessed using the time-dependent receiver operating characteristic curve, concordance index (C-index), calibration curve, and decision curve analysis.
Five radiomics features associated with prognosis were finally screened, and a Rad-score was established. Multivariate Cox regression analysis revealed that surgery and clinical M stage were identified as independent risk factors for OS in ESCC. The combined clinical-radiomics nomogram exhibited C-index values of 0.768 (95% CI: 0.699-0.837) and 0.809 (95% CI: 0.695-0.923) in the training and validation cohorts, respectively. Ultimately, calibration curves and decision curves for the 1-, 2-, and 3-year OS demonstrated the satisfactory prognostic prediction and clinical utility of the nomogram.
The developed nomogram, leveraging F-FDG PET/CT radiomics and clinically independent risk factors, demonstrates a reliable prognostic prediction for patients with ESCC, potentially serving as a valuable tool for guiding and optimizing clinical treatment decisions in the future.
本研究旨在开发并验证一种列线图,该列线图综合了临床因素和放射组学特征,可用于预测接受氟代脱氧葡萄糖正电子发射断层扫描/计算机断层扫描(F-FDG PET/CT)检查诊断为食管鳞状细胞癌(ESCC)患者的总生存(OS)。
本研究回顾性分析了 130 例接受治疗前 F-FDG PET/CT 检查的 ESCC 患者的病例数据。通过单因素 Cox 回归(p<0.05)筛选与 OS 相关的放射组学特征。应用最小绝对值收缩和选择算子 Cox 回归进一步选择,生成加权放射组学评分(Rad-score)。采用多因素 Cox 回归获取独立的临床危险因素,并结合 Rad-score 和独立危险因素构建列线图。采用时间依赖性接收器工作特征曲线、一致性指数(C-index)、校准曲线和决策曲线分析评估模型对 OS 的预测性能。
最终筛选出 5 个与预后相关的放射组学特征,建立了 Rad-score。多因素 Cox 回归分析显示,手术和临床 M 分期是 ESCC OS 的独立危险因素。联合临床-放射组学列线图在训练和验证队列中的 C-index 值分别为 0.768(95%CI:0.699-0.837)和 0.809(95%CI:0.695-0.923)。最终,1、2 和 3 年 OS 的校准曲线和决策曲线表明该列线图具有良好的预后预测和临床应用价值。
该研究开发的列线图利用 F-FDG PET/CT 放射组学和临床独立危险因素,为 ESCC 患者提供了可靠的预后预测,有望成为未来指导和优化临床治疗决策的有价值工具。