The relationship between contrast-enhanced computed tomography radiomics features and mitosis karyorrhexis index in neuroblastoma

作者全名：Chen, Xin; Wang, Haoru; Xia, Yuwei; Shi, Feng; He, Ling; Liu, Enmei

作者地址：[Chen, Xin; Wang, Haoru; He, Ling] Chongqing Med Univ, Natl Clin Res Ctr Child Hlth & Disorders, Dept Radiol,Childrens Hosp,Chongqing Key Lab Child, Minist Educ Key Lab Child Dev & Disorders, Chongqing 400014, Peoples R China; [Xia, Yuwei; Shi, Feng] Shanghai United Imaging Intelligence Co Ltd, Shanghai 200030, Peoples R China; [Liu, Enmei] Chongqing Med Univ, Natl Clin Res Ctr Child Hlth & Disorders, Dept Resp Med,Childrens Hosp,Chongqing Key Lab Chi, Minist Educ Key Lab Child Dev & Disorders, 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,Childrens Hosp,Chongqing Key Lab Child, Minist Educ Key Lab Child Dev & Disorders, Chongqing 400014, Peoples R China.; Liu, EM (通讯作者)，Chongqing Med Univ, Natl Clin Res Ctr Child Hlth & Disorders, Dept Resp Med,Childrens Hosp,Chongqing Key Lab Chi, Minist Educ Key Lab Child Dev & Disorders, Chongqing 400014, Peoples R China.

来源：DISCOVER ONCOLOGY

ESI学科分类：　

WOS号：WOS:001236551100002

JCR分区：Q2

影响因子：2.8

年份：2024

卷号：15

期号：1

开始页：　

结束页：　

文献类型：Article

关键词：Neuroblastoma; Computed tomography; Radiomics; Mitosis karyorrhexis index

摘要：Objective Mitosis karyorrhexis index (MKI) can reflect the proliferation status of neuroblastoma cells. This study aimed to investigate the contrast-enhanced computed tomography (CECT) radiomics features associated with the MKI status in neuroblastoma.Materials and methods 246 neuroblastoma patients were retrospectively included and divided into three groups: low-MKI, intermediate-MKI, and high-MKI. They were randomly stratified into a training set and a testing set at a ratio of 8:2. Tumor regions of interest were delineated on arterial-phase CECT images, and radiomics features were extracted. After reducing the dimensionality of the radiomics features, a random forest algorithm was employed to establish a three-class classification model to predict MKI status.Results The classification model consisted of 5 radiomics features. The mean area under the curve (AUC) of the classification model was 0.916 (95% confidence interval (CI) 0.913-0.921) in the training set and 0.858 (95% CI 0.841-0.864) in the testing set. Specifically, the classification model achieved AUCs of 0.928 (95% CI 0.927-0.934), 0.915 (95% CI 0.912-0.919), and 0.901 (95% CI 0.900-0.909) for predicting low-MKI, intermediate-MKI, and high-MKI, respectively, in the training set. In the testing set, the classification model achieved AUCs of 0.873 (95% CI 0.859-0.882), 0.860 (95% CI 0.852-0.872), and 0.820 (95% CI 0.813-0.839) for predicting low-MKI, intermediate-MKI, and high-MKI, respectively.Conclusions CECT radiomics features were found to be correlated with MKI status and are helpful for reflecting the proliferation status of neuroblastoma cells.

基金机构：Natural Science Foundation of Chongqing

基金资助正文：Not applicable.