The value of radiomics for individualized prophylactic cranial irradiation in limited-stage small cell lung cancer
10.3760/cma.j.cn113030-20220507-00161
- VernacularTitle:影像组学在局限期小细胞肺癌脑预防照射优化中的价值
- Author:
Qing HOU
1
;
Lijuan WEI
;
Ningning YAO
;
Bochen SUN
;
Yu LIANG
;
Xin CAO
;
Yan TAN
;
Jianzhong CAO
Author Information
1. 山西省肿瘤医院/中国医学科学院肿瘤医院山西医院/山西医科大学附属肿瘤医院放射治疗中心，太原 030013
- Keywords:
Small cell lung carcinoma, limited-stage;
Neoplasm metastasis, brain;
Radiomics;
Prophylactic cranial irradiation
- From:
Chinese Journal of Radiation Oncology
2023;32(1):8-14
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the predictive value of enhanced CT-based radiomics for brain metastasis (BM) and selective use of prophylactic cranial irradiation (PCI) in limited-stage small cell lung cancer (LS-SCLC).Methods:Clinical data of 97 patients diagnosed with LS-SCLC confirmed by pathological and imaging examination in Shanxi Provincial Cancer Hospital from January 2012 to December 2018 were retrospectively analyzed. The least absolute shrinkage and selection operator (LASSO) Cox and Spearman correlation tests were used to select the radiomics features significantly associated with the incidence of BM and calculate the radiomics score. The calibration curve, the area under the receiver operating characteristic (ROC) curve (AUC), 5-fold cross-validation, decision curve analysis (DCA), and integrated Brier score (IBS) were employed to evaluate the predictive power and clinical benefits of the radiomics score. Kaplan-Meier method and log-rank test were adopted to draw survival curves and assess differences between two groups.Results:A total of 1272 radiomics features were extracted from enhanced CT. After the LASSO Cox regression and Spearman correlation tests, 8 radiomics features associated with the incidence of BM were used to calculate the radiomics score. The AUCs of radiomics scores to predict 1-year and 2-year BM were 0.845 (95% CI=0.746-0.943) and 0.878 (95% CI=0.774-0.983), respectively. The 5-fold cross validation, calibration curve, DCA and IBS also demonstrated that the radiomics model yielded good predictive performance and net clinical benefit. Patients were divided into the high-risk and low-risk cohorts based on the radiomics score. For patients at high risk, the 1-year and 2-year cumulative incidence rates of BM were 0% and 18.2% in the PCI group, and 61.8% and 75.4% in the non-PCI group, respectively ( P<0.001). In the PCI group, the 1-year and 2-year overall survival rates were 92.9% and 78.6%, and 85.3% and 36.8% in the non-PCI group, respectively ( P=0.023). For patients at low risk, the 1-year and 2-year cumulative incidence rates of BM were 0% and 0% in the PCI group, and 10.0% and 20.2% in the non-PCI group, respectively ( P=0.062). In the PCI group, the 1-year and 2-year overall survival rates were 100% and 77.0%, and 96.7% and 79.3% in the non-PCI group, respectively ( P=0.670). Conclusion:The radiomics model based on enhanced CT images yields excellent performance for predicting BM and individualized PCI.
