Shu Shenglei, Wang Cheng, Hong Ziming, Zhou Xiaoyue, Zhang Tianjng, Peng Qinmu, Wang Jing, Zheng Chuansheng
Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
Front Cardiovasc Med. 2021 Dec 17;8:766423. doi: 10.3389/fcvm.2021.766423. eCollection 2021.
Late enhanced cardiac magnetic resonance (CMR) images of the left ventricular myocardium contain an enormous amount of information that could provide prognostic value beyond that of late gadolinium enhancements (LGEs). With computational postprocessing and analysis, the heterogeneities and variations of myocardial signal intensities can be interpreted and measured as texture features. This study aimed to evaluate the value of texture features extracted from late enhanced CMR images of the myocardium to predict adverse outcomes in patients with dilated cardiomyopathy (DCM) and severe systolic dysfunction. This single-center study retrospectively enrolled patients with DCM with severely reduced left ventricular ejection fractions (LVEFs < 35%). Texture features were extracted from enhanced late scanning images, and the presence and extent of LGEs were also measured. Patients were followed-up for clinical endpoints composed of all-cause deaths and cardiac transplantation. Cox proportional hazard regression and Kaplan-Meier analyses were used to evaluate the prognostic value of texture features and conventional CMR parameters with event-free survival. A total of 114 patients (37 women, median age 47.5 years old) with severely impaired systolic function (median LVEF, 14.0%) were followed-up for a median of 504.5 days. Twenty-nine patients experienced endpoint events, 12 died, and 17 underwent cardiac transplantations. Three texture features from a gray-level co-occurrence matrix (GLCM) (GLCM_contrast, GLCM_difference average, and GLCM_difference entropy) showed good prognostic value for adverse events when analyzed using univariable Cox hazard ratio regression ( = 0.007, = 0.011, and = 0.007, retrospectively). When each of the three features was analyzed using a multivariable Cox regression model that included the clinical parameter (systolic blood pressure) and LGE extent, they were found to be independently associated with adverse outcomes. Texture features related LGE heterogeneities and variations (GLCM_contrast, GLCM_difference average, and GLCM_difference entropy) are novel markers for risk stratification toward adverse events in DCM patients with severe systolic dysfunction.
左心室心肌的延迟强化心脏磁共振成像（CMR）包含大量信息，其提供的预后价值可能超过钆延迟强化（LGE）。通过计算后处理和分析，心肌信号强度的异质性和变化可以被解释并测量为纹理特征。本研究旨在评估从心肌延迟强化CMR图像中提取的纹理特征对预测扩张型心肌病（DCM）和严重收缩功能障碍患者不良结局的价值。这项单中心研究回顾性纳入了左心室射血分数严重降低（LVEF<35%）的DCM患者。从延迟强化扫描图像中提取纹理特征，并测量LGE的存在和范围。对患者进行随访，观察由全因死亡和心脏移植组成的临床终点。采用Cox比例风险回归和Kaplan-Meier分析评估纹理特征和传统CMR参数对无事件生存的预后价值。共有114例收缩功能严重受损（中位LVEF为14.0%）的患者（37例女性，中位年龄47.5岁）接受了中位504.5天的随访。29例患者发生终点事件，12例死亡，17例接受心脏移植。当使用单变量Cox风险比回归分析时，灰度共生矩阵（GLCM）的三个纹理特征（GLCM_对比度、GLCM_差异平均值和GLCM_差异熵）对不良事件显示出良好的预后价值（回顾性分析，P分别为0.007、0.011和0.007）。当使用包含临床参数（收缩压）和LGE范围的多变量Cox回归模型对这三个特征分别进行分析时，发现它们与不良结局独立相关。与LGE异质性和变化相关的纹理特征（GLCM_对比度、GLCM_差异平均值和GLCM_差异熵）是严重收缩功能障碍的DCM患者不良事件风险分层的新标志物。
