Imaging technologies for cardiac fiber and heart failure: a review

Abstract

There has been an increasing interest in studying cardiac fibers in order to improve the current knowledge regarding the mechanical and physiological properties of the heart during heart failure (HF), particularly early HF. Having a thorough understanding of the changes in cardiac fiber orientation may provide new insight into the mechanisms behind the progression of left ventricular (LV) remodeling and HF. We conducted a systematic review on various technologies for imaging cardiac fibers and its link to HF. This review covers literature reports from 1900 to 2017. PubMed and Google Scholar databases were searched using the keywords “cardiac fiber” and “heart failure” or “myofiber” and “heart failure.” This review highlights imaging methodologies, including magnetic resonance diffusion tensor imaging (MR-DTI), ultrasound, and other imaging technologies as well as their potential applications in basic and translational research on the development and progression of HF. MR-DTI and ultrasound have been most useful and significant in evaluating cardiac fibers and HF. New imaging technologies that have the ability to measure cardiac fiber orientations and identify structural and functional information of the heart will advance basic research and clinical diagnoses of HF.

Characterization of Myocardial Microstructure and Function in an Experimental Model of Isolated Subendocardial Damage

“…10,14,29 Despite the growing wealth of cardiac DT-MRI studies, however, there is a lack of data regarding changes that occur during early disease states and investigation of layer-specific alterations. 30 Additionally, the sequential morphological and functional changes during transition from initial subendocardial damage to transmural affection are largely unclear. To our knowledge, this is the first application of DT-MRI to characterize the impact of subendocardial damage on myocardial microstructure.…”

A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations

“…For the sheet direction, we used -65˚at the endocardium and 25˚at the epicardium [38]. Although myocardial microstructure was reported to change in heart failure [40], this was not accounted for by the used rule-based method. The fibre and sheet directions represent those of a healthy human heart.…”

An Introductory Overview of Image-Based Computational Modeling in Personalized Cardiovascular Medicine

“…Most of the published cardiovascular modeling reviews are typically oriented at an expert audience, which makes it difficult for the outsiders to understand the full medical potential of these methods. One of the barriers to penetrating the field is that these works tend to focus on just one or two specific aspects of the simulation approach at a time: such as imaging ( Weese et al, 2013 ; Lamata et al, 2014 ; Watson et al, 2018 ), electrophysiology ( Lopez-Perez et al, 2015 ; Rodriguez et al, 2015 ; Beheshti et al, 2016 ; Gray and Pathmanathan, 2018 ; Ni et al, 2018 ), biomechanics ( Wang et al, 2015 ; Chabiniok et al, 2016 ), hemodynamics ( Zhong et al, 2018 ), electro-biomechanical coupling ( Trayanova, 2011 , 2012 ; Tobon-Gomez et al, 2013 ; Niederer et al, 2019b ), biomechanics-hemodynamics coupling ( Tang et al, 2010 ; Sun et al, 2014 ), etc. In contrast, our manuscript provides a “big picture” overview of the components that these models are built from; their mechanisms, inputs, outputs and connecting pipelines; the underlying physiological processes that they represent; their image-based personalization to the individual patient’s unique anatomy; and their applications to the different cardiovascular disease understanding and treatments.…”

“…are harder to resolve due to their small size. Yet, they strongly determine the electrophysiological and biomechanical properties of cardiac tissue (Watson et al, 2018). Consequently, there are three main methods for accounting for these fine details:…”

“…Although many excellent reviews already exist in the image-based heart-modeling area, most of them are focused on just one or two specific aspects: for example, image acquisition and processing ( Weese et al, 2013 ; Lamata et al, 2014 ; Wang et al, 2015 ; Watson et al, 2018 ), hemodynamic flow simulations ( Tang et al, 2010 ; Mittal et al, 2016 ; Quarteroni et al, 2017 ; Zhong et al, 2018 ); electrical conduction and stimulation modeling ( Trayanova, 2011 , 2012 ; Tobon-Gomez et al, 2013 ; Lopez-Perez et al, 2015 ; Rodriguez et al, 2015 ; Beheshti et al, 2016 ; Gray and Pathmanathan, 2018 ; Ni et al, 2018 ); tissue mechanics computations ( Trayanova, 2011 , 2012 ; Sun et al, 2014 ; Wang et al, 2015 ; Chabiniok et al, 2016 ; Niederer et al, 2019a , b ), ventricular thrombosis ( Mittal et al, 2016 ) and the use of models in diagnostic procedures ( Tang et al, 2010 ; Trayanova, 2012 ). Whereas, the goal of this manuscript is to provide a brief introductory overview of the entire cardiovascular IBM for a non-expert audience, in order to increase the broader exposure of this exciting topic and its numerous potential applications: CAD, Arrhythmias, Heart Failure (HF), Left-Ventricular Assist Devices (LVAD) and Pathogenic Thrombosis/Embolism.…”