Accuracy of prediction of infarct-related arrhythmic circuits from image-based models reconstructed from low and high resolution MRI

Abstract

Identification of optimal ablation sites in hearts with infarct-related ventricular tachycardia (VT) remains difficult to achieve with the current catheter-based mapping techniques. Limitations arise from the ambiguities in determining the reentrant pathways location(s). The goal of this study was to develop experimentally validated, individualized computer models of infarcted swine hearts, reconstructed from high-resolution ex-vivo MRI and to examine the accuracy of the reentrant circuit location prediction when models of the same hearts are instead reconstructed from low clinical-resolution MRI scans. To achieve this goal, we utilized retrospective data obtained from four pigs ~10 weeks post infarction that underwent VT induction via programmed stimulation and epicardial activation mapping via a multielectrode epicardial sock. After the experiment, high-resolution ex-vivo MRI with late gadolinium enhancement was acquired. The Hi-res images were downsampled into two lower resolutions (Med-res and Low-res) in order to replicate image quality obtainable in the clinic. The images were segmented and models were reconstructed from the three image stacks for each pig heart. VT induction similar to what was performed in the experiment was simulated. Results of the reconstructions showed that the geometry of the ventricles including the infarct could be accurately obtained from Med-res and Low-res images. Simulation results demonstrated that induced VTs in the Med-res and Low-res models were located close to those in Hi-res models. Importantly, all models, regardless of image resolution, accurately predicted the VT morphology and circuit location induced in the experiment. These results demonstrate that MRI-based computer models of hearts with ischemic cardiomyopathy could provide a unique opportunity to predict and analyze VT resulting for from specific infarct architecture, and thus may assist in clinical decisions to identify and ablate the reentrant circuit(s).

Optogenetic defibrillation terminates ventricular arrhythmia in mouse hearts and human simulations

“…As described previously (52), a leapfrogging approach was used to couple the monodomain partial differential equation with the system of ordinary differential equations that modeled cell-level phenomena. Our previous studies have described rigorous validation of this computational framework against experimental measurements (14,34,(54)(55)(56). All simulations were executed on 24 Intel Haswell CPUs (2.5 GHz) on the parallel computing resource at the Maryland Advanced Research Computing Center.…”

“…The modeling approach has been previously validated in infarct-related VT inducibility studies (12,34,35). Our laboratory pipeline for cardiac model reconstruction has been described in detail in previous work (12,(34)(35)(36)(37). Briefly, anatomical landmark points on the epicardial and endocardial walls were identified manually in each LGE-MRI slice.…”

“…We used a computational model of the diseased human ventricles reconstructed from clinical late gadolinium-enhanced MRI (LGE-MRI) scans of a patient with post-myocardial infarction VT (33). The modeling approach has been previously validated in infarct-related VT inducibility studies (12,34,35). Our laboratory pipeline for cardiac model reconstruction has been described in detail in previous work (12,(34)(35)(36)(37).…”

A feasibility study of arrhythmia risk prediction in patients with myocardial infarction and preserved ejection fraction

“…The MRI image stacks were segmented using our recently published segmentation and interpolation method, 12,13 an updated methodology in comparison to what was previously used in the VARP approach.…”

“…The grey-level thresholding method described in our previous paper 13 was used to further segment the myocardium into three tissue types, non-infarcted tissue, border zone (also termed grey zone, because of its intermediate level of signal intensity in the MRI), and scar. The mean and SD of the voxel intensities in the region outside the infarct were calculated.…”