Amr Ali, Kayvanpour Elham, Sedaghat-Hamedani Farbod, Passerini Tiziano, Mihalef Viorel, Lai Alan, Neumann Dominik, Georgescu Bogdan, Buss Sebastian, Mereles Derliz, Zitron Edgar, Posch Andreas E, Würstle Maximilian, Mansi Tommaso, Katus Hugo A, Meder Benjamin
Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany.
Siemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA.
Genomics Proteomics Bioinformatics. 2016 Aug;14(4):244-52. doi: 10.1016/j.gpb.2016.04.006. Epub 2016 Jul 29.
The search for a parameter representing left ventricular relaxation from non-invasive and invasive diagnostic tools has been extensive, since heart failure (HF) with preserved ejection fraction (HF-pEF) is a global health problem. We explore here the feasibility using patient-specific cardiac computer modeling to capture diastolic parameters in patients suffering from different degrees of systolic HF. Fifty eight patients with idiopathic dilated cardiomyopathy have undergone thorough clinical evaluation, including cardiac magnetic resonance imaging (MRI), heart catheterization, echocardiography, and cardiac biomarker assessment. A previously-introduced framework for creating multi-scale patient-specific cardiac models has been applied on all these patients. Novel parameters, such as global stiffness factor and maximum left ventricular active stress, representing cardiac active and passive tissue properties have been computed for all patients. Invasive pressure measurements from heart catheterization were then used to evaluate ventricular relaxation using the time constant of isovolumic relaxation Tau (τ). Parameters from heart catheterization and the multi-scale model have been evaluated and compared to patient clinical presentation. The model parameter global stiffness factor, representing diastolic passive tissue properties, is correlated significantly across the patient population with τ. This study shows that multi-modal cardiac models can successfully capture diastolic (dys) function, a prerequisite for future clinical trials on HF-pEF.
由于射血分数保留的心力衰竭(HF-pEF)是一个全球性的健康问题,因此人们广泛地从非侵入性和侵入性诊断工具中寻找代表左心室舒张功能的参数。我们在此探讨使用患者特异性心脏计算机模型来获取不同程度收缩性心力衰竭患者舒张参数的可行性。58例特发性扩张型心肌病患者接受了全面的临床评估,包括心脏磁共振成像(MRI)、心导管检查、超声心动图和心脏生物标志物评估。一个先前引入的用于创建多尺度患者特异性心脏模型的框架已应用于所有这些患者。已为所有患者计算了代表心脏主动和被动组织特性的新参数,如整体僵硬度因子和左心室最大主动应力。然后使用心导管检查的有创压力测量值,通过等容舒张时间常数Tau(τ)来评估心室舒张功能。已对心导管检查和多尺度模型的参数进行了评估,并与患者的临床表现进行了比较。代表舒张期被动组织特性的模型参数整体僵硬度因子在整个人群中与τ显著相关。这项研究表明,多模态心脏模型可以成功捕捉舒张(功能障碍)功能,这是未来HF-pEF临床试验的一个先决条件。