Arrhythmogenic cardiomyopathy is characterized by apex-to-base heterogeneity of right ventricular myocardial contractility, stiffness, and mechanical delay: a patient-specific modeling study
Authors: Van Osta N , Kirkels F , Lyon A , Koopsen T , Van Loon TAM , Cramer MJ , Delhaas T , Teske AJ , Lumens J 
Published: February 2021

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NWO-ZonMw, VIDI grant 016.176.340 Dutch Heart Foundation (2015T082)

Introduction

Arrhythmogenic Cardiomyopathy (AC) is an inherited cardiac disease, characterized by life-threatening ventricular arrhythmias and progressive cardiac dysfunction. Geno-positive subjects with and without symptoms may suffer from sudden cardiac death. Therefore, early disease detection and risk stratification is important. Right ventricular (RV) longitudinal deformation abnormalities in early stages of disease have been shown to be of prognostic value. We propose an imaging-based patient-specific computer modelling approach for non-invasive quantification of regional ventricular tissue abnormalities.

Purpose

To non-invasively reveal the individual patient’s myocardial tissue substrates underlying the regional RV deformation abnormalities in AC mutation carriers.

Methods

In 65 individuals carrying a plakophilin-2 or desmoglein-2 mutation and 20 control subjects, regional longitudinal deformation patterns of the RV free wall (RVfw), interventricular septum (IVS) and left ventricular free wall (LVfw) were obtained using speckle-tracking echocardiography (Figure: left). This cohort was subdivided into 3 consecutive clinical stages i.e. subclinical (concealed, n = 18) with no abnormalities, electrical stage (n = 13) with only electrocardiographic abnormalities, and structural stage (n = 34) with both electrical and structural abnormalities defined by the 2010 Task Force AC criteria. We developed and used a patient-specific parameter estimation protocol based on the multi-scale CircAdapt cardiovascular system model to create virtual AC subjects (Figure: middle). Using the individuals’ RVfw, IVS, and LVfw strain patterns as model input, this protocol automatically estimated regional RV and global IVS and LVfw tissue properties, such as myocardial contractility, stiffness, and activation delay.

Results

The computational model was able to reproduce the regional deformation patterns as measured clinically. Patient-specific parameter estimation results (Figure: right) revealed that clinical AC disease progression is characterized by a decrease in contractility and an increase in stiffness and mechanical delay of the RV myocardial tissue in the basal segment compared to the apex. The subclinical stage subjects showed tissue properties comparable to the control group, including a small apex-to-base heterogeneity in tissue properties.

Conclusion

Our patient-specific modelling approach is able to reveal individual myocardial substrates underlying the regional RV deformation abnormalities. Early abnormalities in RV longitudinal strain are most likely caused by increased heterogeneity in local tissue properties, such as an apex-to-base decrease of contractility, increased of myocardial stiffness, and time to peak stress. Abnormalities in tissue properties may be found already in the subclinical stage. In future studies, this artificial intelligence approach will be used to investigate how these abnormalities relate to disease progression and arrhythmogenic risk.

Abstract Figure. Characterization of AC Disease Substrate