Contrast computed tomography-based radiomics is correlation with COG risk stratification of neuroblastoma

被引:3
作者
Zhang, Yimao [1 ]
Yang, Yuhan [1 ]
Ning, Gang [2 ]
Wu, Xin [3 ]
Yang, Gang [1 ]
Li, Yuan [1 ,4 ]
机构
[1] Sichuan Univ, West China Hosp, Dept Pediat Surg, 37 Guo Xue Xiang, Chengdu, Sichuan, Peoples R China
[2] Sichuan Univ, West China Hosp 2, Dept Radiol, 20,Sect 3,Renmin South Rd, Chengdu, Sichuan, Peoples R China
[3] Sichuan Univ, West China Hosp, Dept Radiol, 37 Guo Xue Xiang, Chengdu, Sichuan, Peoples R China
[4] Sichuan Univ, West China Hosp, Lab Digest Surg, Chengdu, Sichuan, Peoples R China
关键词
Contrast CT; Radiomics; Risk stratification; Neuroblastoma; NEURON-SPECIFIC ENOLASE; MICROVASCULAR INVASION; CHEMOTHERAPY;
D O I
10.1007/s00261-023-03875-4
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
PurposeAlthough a risk stratification strategy for neuroblastoma (NB) has been proposed, precise and convenient clinical risk estimation remains challenging. This study aimed to investigate the correlation of contrast computed tomography (CT)-based radiomics with NB risk stratification.MethodsPatients with NB (n = 289) from two centers (244 and 45 patients in the training/testing and external validation cohorts, respectively) were divided into nonhigh- and high-risk groups. A total of 1648 radiomics features were extracted from the arterial phase, and the radiomics signature was constructed using rad scores, whereas the clinical model was established based on clinical factors. Further, a combined nomogram was developed based on the clinical factors and radiomics signatures. Finally, receiver operating characteristic curve and decision curve analyses (DCA) were used to assess the performance of the established models.ResultsSeventeen radiomics features were used to construct the radiomics signature. A significant difference was observed in the rad score between the two groups in the training (0.540 vs. 0.704, P < 0.001) and testing (0.563 vs. 0.969, P < 0.001) cohorts. The nomogram showed a higher area under the curve (AUC) in the training (AUC = 0.87), testing (AUC = 0.83), and external validation (AUC = 0.84) cohorts than other models. The Hosmer-Lemeshow test and calibration curves indicated that the nomogram fit perfectly. DCA demonstrated that the clinical-radiomics nomogram was more beneficial.ConclusionsContrast CT-based radiomics shows correlation with COG risk stratification of NB. Radiomics features combined with clinical factors showed the best performance, which may improve the management of patients with NB.
引用
收藏
页码:2111 / 2121
页数:11
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