Cardiovascular Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, United States of America.
Department of Computer Science, Technical University of Munich, Munich, Germany.
PLoS One. 2020 Jun 1;15(6):e0233694. doi: 10.1371/journal.pone.0233694. eCollection 2020.
The pattern of myocardial fibrosis differs significantly between different cardiomyopathies. Fibrosis in hypertrophic cardiomyopathy (HCM) is characteristically as patchy and regional but in dilated cardiomyopathy (DCM) as diffuse and global. We sought to investigate if texture analyses on myocardial native T1 mapping can differentiate between fibrosis patterns in patients with HCM and DCM.
We prospectively acquired native myocardial T1 mapping images for 321 subjects (55±15 years, 70% male): 65 control, 116 HCM, and 140 DCM patients. To quantify different fibrosis patterns, four sets of texture descriptors were used to extract 152 texture features from native T1 maps. Seven features were sequentially selected to identify HCM- and DCM-specific patterns in 70% of data (training dataset). Pattern reproducibility and generalizability were tested on the rest of data (testing dataset) using support vector machines (SVM) and regression models.
Pattern-derived texture features were capable to identify subjects in HCM, DCM, and controls cohorts with 202/237(85.2%) accuracy of all subjects in the training dataset using 10-fold cross-validation on SVM (AUC = 0.93, 0.93, and 0.93 for controls, HCM and DCM, respectively), while pattern-independent global native T1 mapping was poorly capable to identify those subjects with 121/237(51.1%) accuracy (AUC = 0.78, 0.51, and 0.74) (P<0.001 for all). The pattern-derived features were reproducible with excellent intra- and inter-observer reliability and generalizable on the testing dataset with 75/84(89.3%) accuracy.
Texture analysis of myocardial native T1 mapping can characterize fibrosis patterns in HCM and DCM patients and provides additional information beyond average native T1 values.
不同心肌病的心肌纤维化模式有很大差异。肥厚型心肌病(HCM)的纤维化特征为局灶性和区域性,而扩张型心肌病(DCM)的纤维化特征为弥漫性和全身性。我们试图研究心肌 native T1 映射的纹理分析是否可以区分 HCM 和 DCM 患者的纤维化模式。
我们前瞻性地采集了 321 名受试者(55±15 岁,70%为男性)的 native 心肌 T1 映射图像:65 名对照组,116 名 HCM 患者和 140 名 DCM 患者。为了量化不同的纤维化模式,我们使用了四组纹理描述符从 native T1 图中提取 152 个纹理特征。使用支持向量机(SVM)和回归模型,在 70%的数据(训练数据集)中,我们依次选择了 7 个特征来识别 HCM 和 DCM 特有的模式。然后,我们在其余数据(测试数据集)上测试了模式的可重复性和泛化性。
使用 10 折交叉验证,基于 SVM 的纹理特征能够以 202/237(85.2%)的准确率识别出训练数据集中所有受试者中的 HCM、DCM 和对照组受试者(AUC 分别为 0.93、0.93 和 0.93),而基于 pattern-independent 的全局 native T1 映射则以 121/237(51.1%)的准确率(AUC 分别为 0.78、0.51 和 0.74)较差地识别出这些受试者(P<0.001)。pattern-derived 特征具有极好的观察者内和观察者间可靠性,在测试数据集中具有 75/84(89.3%)的准确率,可重复性良好。
心肌 native T1 映射的纹理分析可以描述 HCM 和 DCM 患者的纤维化模式,并提供平均 native T1 值之外的附加信息。