Fibrosis Microstructure Modulates Reentry in Non-ischemic Dilated Cardiomyopathy: Insights From Imaged Guided 2D Computational Modeling

Abstract

Aims: Patients who present with non-ischemic dilated cardiomyopathy (NIDCM) and enhancement on late gadolinium magnetic resonance imaging (LGE-CMR), are at high risk of sudden cardiac death (SCD). Further risk stratification of these patients based on LGE-CMR may be improved through better understanding of fibrosis microstructure. Our aim is to examine variations in fibrosis microstructure based on LGE imaging, and quantify the effect on reentry inducibility and mechanism. Furthermore, we examine the relationship between transmural activation time differences and reentry.Methods and Results: 2D Computational models were created from a single short axis LGE-CMR image, with 401 variations in fibrosis type (interstitial, replacement) and density, as well as presence or absence of reduced conductivity (RC). Transmural activation times (TAT) were measured, as well as reentry incidence and mechanism. Reentries were inducible above specific density thresholds (0.8, 0.6 for interstitial, replacement fibrosis). RC reduced these thresholds (0.3, 0.4 for interstitial, replacement fibrosis) and increased reentry incidence (48 no RC vs. 133 with RC). Reentries were classified as rotor, micro-reentry, or macro-reentry and depended on fibrosis micro-structure. Differences in TAT at coupling intervals 210 and 500ms predicted reentry in the models (sensitivity 89%, specificity 93%). A sensitivity analysis of TAT and reentry incidence showed that these quantities were robust to small changes in the pacing location.Conclusion: Computational models of fibrosis micro-structure underlying areas of LGE in NIDCM provide insight into the mechanisms and inducibility of reentry, and their dependence upon the type and density of fibrosis. Transmural activation times, measured at the central extent of the scar, can potentially differentiate microstructures which support reentry.

Perlin Noise Generation of Physiologically Realistic Patterns of Fibrosis

“…Variability on the microscopic scale has been explored computationally in terms of density of obstruction for diffuse fibrosis [39,40], including the differential effects on excitation propagating in directions longitudinal or transverse to the fibre direction [41]. A recent work incorporated interstitial and diffuse fibrosis into a larger-scale model, using image data to inform density but without an attempt to explicitly capture the precise microfibrotic structure [17]. Our work, however, is the first effort to explicitly consider micro-scale variability using histologicallyverified patterns, and demonstrates a powerful framework for further such research towards understanding the impacts of fibrosis.…”

“…Non-invasive imaging techniques remain unable to fully characterise the nature of fibrosis in the lung [8] and particularly the heart [9], resulting in a reliance upon ex vivo studies [10,11]. This has motivated in silico investigations, seeking to explain both the creation of different fibrotic patternings [12] and in the case of cardiac fibrosis, its pro-arrhythmic consequences [13,14,15,16,17]. Although some in silico investigations have directly used invasively-collected data of cardiac fibrosis localisation to study the electrophysiological impacts of realistic patterns of affliction [10,18,19,20], the reliance on this limited data has meant that the effects of variability in these patterns remains very poorly understood.…”

3D Electrophysiological Modeling of Interstitial Fibrosis Networks and Their Role in Ventricular Arrhythmias in Non-Ischemic Cardiomyopathy

“…We build on our previous image-guided 2D modeling methodology for interstitial fibrosis in NICM [13], based on the efficient discrete finite element (DFE) technique of Mendonça Costa et al [14]. In our 2D simulations, we uncovered relationships between fibrosis density, activation delays and the likelihood of arrhythmia induction.…”

Sudden Cardiac Death Prediction in Non-ischemic Dilated Cardiomyopathy: a Multiparametric and Dynamic Approach

“…Importantly, these patients would not be eligible for a primary prevention ICD under current guidelines yet are likely to derive significant benefit due to a lower competing risk of nonsudden death. Computational modelling techniques have recently been used to further characterize LGE in patients with DCM, demonstrating extensive variation in fibrosis type and density and linking these to re-entry inducibility and arrhythmogenesis [44]. An alternative method evaluating LGE entropy, a measure of scar heterogeneity, was found to have significant independent predictive value for major arrhythmic events in a registry-based study of patients with DCM and primary prevention ICDs [45].…”