基于CT的影像组学在鉴别脊柱骨肉瘤与软骨肉瘤中的价值
Feature Classification of Spinal Osteosarcoma and Chondrosarcoma Based on CT Radiomics
袁源 1王晨曦 1叶凯 1郎宁 1袁慧书1
作者信息
摘要
目的 探讨基于CT的影像组学在鉴别脊柱骨肉瘤和软骨肉瘤鉴别诊断中的应用价值.方法 回顾性分析经病理证实的10例脊柱骨肉瘤和28例软骨肉瘤患者的CT图像.在联影智能科研平台上对患者CT图像进行肿瘤分割、影像组学特征提取.应用相关系数、最小绝对收缩和选择算子(LASSO)随机重复五折交叉验证20次后,将选择出的特征构建影像组学模型,采用ROC曲线评估其性能.结果 共提取2264个影像组学特征,筛选后得到7个最佳特征构建模型.逻辑回归模型性能最佳,训练组、测试组ROC曲线下面积为0.928(95％CI:0.806～1)、0.912(95％CI:0.802～1).结论 基于CT影像组学在鉴别脊柱骨肉瘤和软骨肉瘤中有一定的应用价值.
Abstract
Objective To explore the CT-based radiomics in the differential diagnosis of spinal osteosarcoma and chon-drosarcoma.Methods 10 patients with spinal osteosarcoma and 28 patients with chondrosarcoma who were admitted were retrospectively analyzed.Image segmentation and feature extraction were performed on CT image with the Research Portal V1.1.Correlation coefficient and the least absolute shrinkage and selection operator(LASSO)algorithm were used to select the radiomics features,a fivefold cross-validation was repeated 20 times with random initialization to reduce bias.The receiv-er operating characteristic curve(ROC)was used to evaluate the performance of the models.Results The 2264 ra-diomics features were selected,and the most significant 7 radiomics features were obtained to construct radiomics model.The logistic model based on CT can yield the the mean area under the ROC curve(AUC)of 0.928(95％CI 0.806-1)in training cohort,and 0.912(95％CI 0.802-1)in test cohort.Conclusion CT-based radiomics models have some poten-tial for differentiating spinal osteosarcoma from chondrosarcoma.
关键词
体层摄影术,X线计算机/影像组学/骨肉瘤/软骨肉瘤Key words
Tomography,X-ray computed/Radiomics/Osteosarcoma/Chondrosarcoma引用本文复制引用
出版年
2024
NETL
NSTL
万方数据