Arterial phase contrast-enhanced CT radiomics model for predicting progression-free survival of patients with small cell lung cancer
10.13929/j.issn.1003-3289.2024.11.014
- VernacularTitle:基于动脉期增强CT影像组学模型预测小细胞肺癌无进展生存期
- Author:
Jie LEI
1
;
Yang YANG
;
Xiaohui QIU
Author Information
1. 亳州市人民医院放射科,安徽 亳州 236000
- Keywords:
carcinoma,non-small-cell lung;
tomography,X-ray computed;
radiomics;
disease-free survival
- From:
Chinese Journal of Medical Imaging Technology
2024;40(11):1698-1703
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of arterial phase contrast-enhanced CT radiomics model for predicting progression-free survival(PFS)of patients with small cell lung cancer(SCLC).Methods A total of 210 patients with pathology confirmed SCLC were retrospectively enrolled and randomly divided into training set(n=147)and test set(n=63)at the ratio of 7∶3.Clinical independent influence factors of PFS rate were selected with Cox proportional hazards regression.The radiomics features of tumors were extracted from arterial phase contrast-enhanced CT,and those being most relevant to PFS rate selected in training set were used to construct the radiomics model.Then Radscores were calculated,and the risks of disease progression were stratified,and PFS rates of patients with different risks were compared.A clinical-radiomics model was constructed combining clinical independent influence factors and radiomics features.The differentiation,calibration,and net benefit of each model for predicting PFS rates of SCLC patients were evaluated and compared in test set.Results Extensive stage was an independent risk factor for shorter PFS of SCLC patients(HR=1.841,95％CI[1.288,2.633],P=0.001).Five radiomics features which relevant to PFS rate were selected based on training set.The patients were categorized as low-risk(Radscore＜0.235)or high-risk(Radscore 0.235)for disease progression,and those with high-risk had lower PFS rates than the low-risk ones(P＜0.001).In test set,the area under the curve(AUC)of receiver operating characteristic curves of the clinical model,radiomics model and clinical-radiomics model for predicting PFS rate within 6 months was 0.646,0.920 and 0.931,respectively,while within 12 months was 0.591,0.917 and 0.919,respectively.The concordance index(C-index)of the radiomics model was 0.878,of the clinical-radiomics model was 0.884,both higher than that of the clinical model(C-index=0.595).Compared with clinical model,the radiomics model had net reclassification index(NRI)of 75.82％(P＜0.001)and integrated discrimination index(IDI)of 59.76％(P＜0.001),clinical-radiomics model had NRI of 78.94％(P＜0.001)and IDI of 61.13％(P＜0.001),which were not statistically different between the latter two models(both P＞0.05).DCA showed that both radiomics model and clinical-radiomics model had higher net benefit than clinical model.Conclusion Arterial phase contrast-enhanced CT radiomics model was helpful to predicting PFS rate of patients with SCLC,providing incremental information for individualized treatment.
