Department of Medical Physics, Memorial Sloan Kettering Cancer Center, USA.
Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, USA.
Radiother Oncol. 2024 Jan;190:109983. doi: 10.1016/j.radonc.2023.109983. Epub 2023 Nov 4.
Disease progression after definitive stereotactic body radiation therapy (SBRT) for early-stage non-small cell lung cancer (NSCLC) occurs in 20-40% of patients. Here, we explored published and novel pre-treatment CT and PET radiomics features to identify patients at risk of progression.
MATERIALS/METHODS: Published CT and PET features were identified and explored along with 15 other CT and PET features in 408 consecutively treated early-stage NSCLC patients having CT and PET < 3 months pre-SBRT (training/set-aside validation subsets: n = 286/122). Features were associated with progression-free survival (PFS) using bootstrapped Cox regression (Bonferroni-corrected univariate predictor: p ≤ 0.002) and only non-strongly correlated predictors were retained (|Rs|<0.70) in forward-stepwise multivariate analysis.
Tumor diameter and SUV were the two most frequently reported features associated with progression/survival (in 6/20 and 10/20 identified studies). These two features and 12 of the 15 additional features (CT: 6; PET: 6) were candidate PFS predictors. A re-fitted model including diameter and SUV presented with the best performance (c-index: 0.78; log-rank p-value < 0.0001). A model built with the two best additional features (CT and SUV) had a c-index of 0.75 (log-rank p-value < 0.0001).
A re-fitted pre-treatment model using the two most frequently published features - tumor diameter and SUVmax - successfully stratified early-stage NSCLC patients by PFS after receiving SBRT.
在接受立体定向体放射治疗(SBRT)的早期非小细胞肺癌(NSCLC)患者中,有 20-40%的患者会出现疾病进展。在这里,我们探索了已发表和新的治疗前 CT 和 PET 放射组学特征,以确定有进展风险的患者。
材料/方法:确定并探讨了已发表的 CT 和 PET 特征,以及在 408 例连续接受 SBRT 治疗的早期 NSCLC 患者的 15 个其他 CT 和 PET 特征(训练/预留验证子集:n=286/122)。使用 Bootstrap Cox 回归(Bonferroni 校正的单变量预测因子:p≤0.002)将特征与无进展生存期(PFS)相关联,并且仅保留非强相关的预测因子(|Rs|<0.70)进行正向逐步多变量分析。
肿瘤直径和 SUV 是与进展/生存最相关的两个最常报道的特征(在 6/20 和 10/20 项确定的研究中)。这两个特征和 15 个额外特征中的 12 个(CT:6;PET:6)是 PFS 预测因子的候选者。包括直径和 SUV 的重新拟合模型具有最佳性能(c 指数:0.78;对数秩 p 值<0.0001)。使用两个最佳附加特征(CT 和 SUV)构建的模型的 c 指数为 0.75(对数秩 p 值<0.0001)。
使用最常发表的两个特征 - 肿瘤直径和 SUVmax - 重新拟合的治疗前模型成功地对接受 SBRT 治疗的早期 NSCLC 患者进行了 PFS 分层。