Department of Diagnostic and Interventional Oncologic Imaging, Institut Bergonié, 33076 Bordeaux, France; Department of Radiology, Pellegrin University Hospital, 33000 Bordeaux, France.
Department of Medical Oncology, Institut Bergonié, 33076 Bordeaux, France.
Diagn Interv Imaging. 2024 Nov;105(11):439-452. doi: 10.1016/j.diii.2024.07.005. Epub 2024 Aug 26.
The purpose of this study was to assess whether single-site and multi-site radiomics could improve the prediction of overall survival (OS) of patients with metastatic lung adenocarcinoma compared to clinicopathological model.
Adults with metastatic lung adenocarcinoma, pretreatment whole-body contrast-enhanced computed tomography examinations, and performance status (WHO-PS) ≤ 2 were included in this retrospective single-center study, and randomly assigned to training and testing cohorts. Radiomics features (RFs) were extracted from all measurable lesions with volume ≥ 1 cm. Radiomics prognostic scores based on the largest tumor (RPS) and the average RF values across all tumors per patient (RPS) were developed in the training cohort using 5-fold cross-validated LASSO-penalized Cox regression. Intra-patient inter-tumor heterogeneity (IPITH) metrics were calculated to quantify the radiophenotypic dissimilarities among all tumors within each patient. A clinicopathological model was built in the training cohort using stepwise Cox regression and enriched with combinations of RPS, RPS and IPITH. Models were compared with the concordance index in the independent testing cohort.
A total of 300 patients (median age: 63.7 years; 40.7% women; median OS, 16.3 months) with 1359 lesions were included (200 and 100 patients in the training and testing cohorts, respectively). The clinicopathological model included WHO-PS = 2 (hazard ratio [HR] = 3.26; P < 0.0001), EGFR, ALK, ROS1 or RET mutations (HR = 0.57; P = 0.0347), IVB stage (HR = 1.65; P = 0.0211), and liver metastases (HR = 1.47; P = 0.0670). In the testing cohort, RPS, RPS and IPITH were associated with OS (HR = 85.50, P = 0.0038; HR = 18.83, P = 0.0082 and HR = 8.00, P = 0.0327, respectively). The highest concordance index was achieved with the combination of clinicopathological variables and RPS, significantly better than that of the clinicopathological model (concordance index = 0.7150 vs. 0.695, respectively; P = 0.0049) CONCLUSION: Single-site and multi-site radiomics-based scores are associated with OS in patients with metastatic lung adenocarcinoma. RPS improves the clinicopathological model.
本研究旨在评估单站点和多站点放射组学是否能比临床病理模型提高转移性肺腺癌患者的总生存期(OS)预测能力。
本回顾性单中心研究纳入了患有转移性肺腺癌、治疗前全身增强 CT 检查和表现状态(WHO-PS)≤2 的成年人,并将其随机分配到训练和测试队列中。从所有可测量的病灶中提取体积≥1cm 的放射组学特征(RFs)。在训练队列中,使用 5 折交叉验证 LASSO 惩罚 Cox 回归,基于最大肿瘤(RPS)和每位患者所有肿瘤的平均 RF 值(RPS),开发放射组学预后评分。计算每个患者内所有肿瘤之间的肿瘤内异质性(IPITH)指标,以量化每个患者内所有肿瘤的放射表型差异。在训练队列中,使用逐步 Cox 回归构建临床病理模型,并通过 RPS、RPS 和 IPITH 的组合进行富集。在独立测试队列中,通过一致性指数比较模型。
共纳入 300 例患者(中位年龄:63.7 岁;40.7%为女性;中位 OS 为 16.3 个月),共 1359 个病灶(训练队列和测试队列分别为 200 例和 100 例)。临床病理模型包括 WHO-PS=2(风险比[HR]=3.26;P<0.0001)、EGFR、ALK、ROS1 或 RET 突变(HR=0.57;P=0.0347)、IVB 期(HR=1.65;P=0.0211)和肝转移(HR=1.47;P=0.0670)。在测试队列中,RPS、RPS 和 IPITH 与 OS 相关(HR=85.50,P=0.0038;HR=18.83,P=0.0082 和 HR=8.00,P=0.0327)。最高的一致性指数是在临床病理变量和 RPS 的组合中实现的,明显优于临床病理模型(一致性指数=0.7150 与 0.695,分别;P=0.0049)。
基于单站点和多站点放射组学的评分与转移性肺腺癌患者的 OS 相关。RPS 可改善临床病理模型。