Department of Radiology, West China Hospital, Sichuan University, 37# Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Road Hai Dian District, Beijing, 100142, China.
BMC Cardiovasc Disord. 2021 Mar 25;21(1):152. doi: 10.1186/s12872-021-01961-3.
Cardiac myxomas (CMs) and thrombi are associated with high morbidity and mortality. These two conditions need totally different treatments. However, they are difficult to distinguish using naked eye. In clinical, misdiagnoses occur now and then. This study aimed to compare the characteristics of CMs and cardiac thrombi and investigate the value of a radiomics signature in distinguishing CMs from cardiac thrombi, based on cardiovascular contrast-enhanced computed tomography (CECT) images.
A total of 109 patients who had CMs (n = 59) and cardiac thrombi (n = 50) were enrolled in this retrospective study from 2009 to 2019. First, the lesion characteristics of cardiovascular CECT images were documented and compared by two radiologists. Then all patients were randomly allotted to either a primary group or a validation group according to a 7:3 ratio. Univariate analysis and the least absolute shrinkage and selection operator were used to select robust features. The best radiomics signature was constructed and validated using multivariate logistic regression. An independent clinical model was created for comparison.
The best radiomics signature was developed using eight selected radiomics. The classification accuracies of the radiomics signature were 90.8% and 90.9%, and the area under the receiver operating characteristic curves were 0.969 and 0.926 in the training and testing cohorts, respectively. Cardiovascular CECT images showed that the two diseases had significant differences in location, surface, Hydrothorax, pericardial effusion and heart enlargement. The naked eye findings were used to create the clinical model. All metrics of the radiomics signature were higher than those of clinical model.
Compared with clinical model, the radiomics signature based on cardiovascular CECT performed better in differentiating CMs and thrombi, suggesting that it could help improving the diagnostic efficiency.
心脏黏液瘤（CMs）和血栓与高发病率和死亡率相关。这两种情况需要完全不同的治疗方法。然而，肉眼很难区分它们。目前临床上时常发生误诊。本研究旨在比较 CMs 和心脏血栓的特征，并基于心血管增强 CT（CECT）图像探讨放射组学特征在区分 CMs 和心脏血栓中的价值。
本回顾性研究纳入了 2009 年至 2019 年期间共 109 名患有 CMs（n=59）和心脏血栓（n=50）的患者。首先，两位放射科医生记录并比较了心血管 CECT 图像的病变特征。然后，根据 7:3 的比例将所有患者随机分为主要组或验证组。采用单变量分析和最小绝对值收缩和选择算子（LASSO）选择稳健特征。使用多变量逻辑回归构建和验证最佳放射组学特征，并创建独立的临床模型进行比较。
使用 8 个选定的放射组学特征构建了最佳放射组学特征。放射组学特征在训练和测试队列中的分类准确率分别为 90.8%和 90.9%，受试者工作特征曲线下面积分别为 0.969 和 0.926。心血管 CECT 图像显示，两种疾病在位置、表面、胸腔积液、心包积液和心脏扩大方面存在显著差异。肉眼观察结果用于创建临床模型。放射组学特征的所有指标均高于临床模型。
与临床模型相比，基于心血管 CECT 的放射组学特征在区分 CMs 和血栓方面表现更好，表明它有助于提高诊断效率。
