Whole-tumor radiomics analysis of T2-weighted imaging in differentiating neuroblastoma from ganglioneuroblastoma/ ganglioneuroma in children: an exploratory study

作者全名："Wang, Haoru; Chen, Xin; Yu, Wenqing; Xie, Mingye; Zhang, Li; Ding, Hao; Li, Ting; Qin, Jinjie; He, Ling"

作者地址："[Wang, Haoru; Chen, Xin; Yu, Wenqing; Xie, Mingye; Zhang, Li; Ding, Hao; Li, Ting; Qin, Jinjie; He, Ling] Chongqing Med Univ, Natl Clin Res Ctr Child Hlth & Disorders, Dept Radiol, Minist Educ,Key Lab Child Dev & Disorders,Children, 136 Zhongshan Rd 2, Chongqing 400014, Peoples R China"

通信作者："He, L (通讯作者)，Chongqing Med Univ, Natl Clin Res Ctr Child Hlth & Disorders, Dept Radiol, Minist Educ,Key Lab Child Dev & Disorders,Children, 136 Zhongshan Rd 2, Chongqing 400014, Peoples R China."

来源：ABDOMINAL RADIOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:000955952200001

JCR分区：Q2

影响因子：2.3

年份：2023

卷号：　

期号：　

开始页：　

结束页：　

文献类型：Article; Early Access

关键词：Peripheral neuroblastic tumors; Neuroblastoma; Magnetic resonance imaging; Radiomics

摘要："Purpose To examine the potential of whole-tumor radiomics analysis of T2-weighted imaging (T2WI) in differentiating neuroblastoma (NB) from ganglioneuroblastoma/ganglioneuroma (GNB/GN) in children. Materials and methods This study included 102 children with peripheral neuroblastic tumors, comprising 47 NB patients and 55 GNB/ GN patients, which were randomly divided into a training group (n = 72) and a test group (n = 30). Radiomics features were extracted from T2WI images, and feature dimensionality reduction was applied. Linear discriminant analysis was used to construct radiomics models, and one-standard error role combined with leave-one-out cross-validation was used to choose the optimal radiomics model with the least predictive error. Subsequently, the patient age at initial diagnosis and the selected radiomics features were incorporated to construct a combined model. The receiver operator characteristic (ROC) curve, decision curve analysis (DCA) and clinical impact curve (CIC) were applied to evaluate the diagnostic performance and clinical utility of the models. Results Fifteen radiomics features were eventually chosen to construct the optimal radiomics model. The area under the curve (AUC) of the radiomics model in the training group and test group was 0.940 [95% confidence interval (CI) 0.886, 0.995] and 0.799 (95%CI 0.632, 0.966), respectively. The combined model, which incorporated patient age and radiomics features, achieved an AUC of 0.963 (95%CI 0.925, 1.000) in the training group and 0.871 (95%CI 0.744, 0.997) in the test group. DCA and CIC demonstrated that the radiomics model and combined model could provide benefits at various thresholds, with the combined model being superior to the radiomics model. Conclusion Radiomics features derived from T2WI, in combination with the age of the patient at initial diagnosis, may offer a quantitative method for distinguishing NB from GNB/GN, thus aiding in the pathological differentiation of peripheral neuroblastic tumors in children."

基金机构："Basic Research and Frontier Exploration Project (Yuzhong District, Chongqing, China) [20200155]"

基金资助正文："The project was funded by Basic Research and Frontier Exploration Project (Yuzhong District, Chongqing, China) (Grant No.20200155)."