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Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia.

ABSTRACT: Ventricular tachycardia (VT), which can lead to sudden cardiac death, occurs frequently in patients with myocardial infarction. Catheter-based radiofrequency ablation of cardiac tissue has achieved only modest efficacy, owing to the inaccurate identification of ablation targets by current electrical mapping techniques, which can lead to extensive lesions and to a prolonged, poorly tolerated procedure. Here we show that personalized virtual-heart technology based on cardiac imaging and computational modelling can identify optimal infarct-related VT ablation targets in retrospective animal (5 swine) and human studies (21 patients) and in a prospective feasibility study (5 patients). We first assessed in retrospective studies (one of which included a proportion of clinical images with artifacts) the capability of the technology to determine the minimum-size ablation targets for eradicating all VTs. In the prospective study, VT sites predicted by the technology were targeted directly, without relying on prior electrical mapping. The approach could improve infarct-related VT ablation guidance, where accurate identification of patient-specific optimal targets could be achieved on a personalized virtual heart prior to the clinical procedure.

SUBMITTER: Prakosa A

PROVIDER: S-EPMC6400313 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia.

Prakosa Adityo A Arevalo Hermenegild J HJ Deng Dongdong D Boyle Patrick M PM Nikolov Plamen P PP Ashikaga Hiroshi H Blauer Joshua J E JJE Ghafoori Elyar E Park Carolyn J CJ Blake Robert C RC Han Frederick T FT MacLeod Rob S RS Halperin Henry R HR Callans David J DJ Ranjan Ravi R Chrispin Jonathan J Nazarian Saman S Trayanova Natalia A NA

Nature biomedical engineering 20180903 10

Ventricular tachycardia (VT), which can lead to sudden cardiac death, occurs frequently in patients with myocardial infarction. Catheter-based radiofrequency ablation of cardiac tissue has achieved only modest efficacy, owing to the inaccurate identification of ablation targets by current electrical mapping techniques, which can lead to extensive lesions and to a prolonged, poorly tolerated procedure. Here we show that personalized virtual-heart technology based on cardiac imaging and computatio ...[more]

PMID: 30847259

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Project description:BackgroundInfiltrating adipose tissue (inFAT) is a newly recognized proarrhythmic substrate for postinfarct ventricular tachycardias (VT) identifiable on contrast-enhanced computed tomography. This study presents novel digital-heart technology that incorporates inFAT from contrast-enhanced computed tomography to noninvasively predict VT ablation targets and assesses the capability of the technology by comparing its predictions with VT ablation procedure data from patients with ischemic cardiomyopathy.MethodsDigital-heart models reflecting patient-specific inFAT distributions were reconstructed from contrast-enhanced computed tomography. The digital-heart identification of fat-based ablation targeting (DIFAT) technology evaluated the rapid-pacing-induced VTs in each personalized inFAT-based substrate. DIFAT targets that render the inFAT substrate noninducible to VT, including VTs that arise postablation, were determined. DIFAT predictions were compared with corresponding clinical ablations to assess the capabilities of the technology.ResultsDIFAT was developed and applied retrospectively to 29 ischemic cardiomyopathy patients with contrast-enhanced computed tomography. DIFAT ablation volumes were significantly less than the estimated clinical ablation volumes (1.87±0.35 versus 7.05±0.88 cm3, P<0.0005). DIFAT targets overlapped with clinical ablations in 79% of patients, mostly in the apex (72%) and inferior/inferolateral (74%). In 3 patients, DIFAT targets colocalized with redo ablations delivered years after the index procedure.ConclusionsDIFAT is a novel digital-heart technology for individualized VT ablation guidance designed to eliminate VT inducibility following initial ablation. DIFAT predictions colocalized well with clinical ablation locations but provided significantly smaller lesions. DIFAT also predicted VTs targeted in redo procedures years later. As DIFAT uses widely accessible computed tomography, its integration into clinical workflows may augment therapeutic precision and reduce redo procedures.

Project description:In the chronic stage of myocardial infarction, a significant number of patients develop life-threatening ventricular tachycardias (VT) due to the arrhythmogenic nature of the remodeled myocardium. Radiofrequency ablation (RFA) is a common procedure to isolate reentry pathways across the infarct scar that are responsible for VT. Unfortunately, this strategy show relatively low success rates; up to 50% of patients experience recurrent VT after the procedure. In the last decade, intensive research in the field of computational cardiac electrophysiology (EP) has demonstrated the ability of three-dimensional (3D) cardiac computational models to perform in-silico EP studies. However, the personalization and modeling of certain key components remain challenging, particularly in the case of the infarct border zone (BZ). In this study, we used a clinical dataset from a patient with a history of infarct-related VT to build an image-based 3D ventricular model aimed at computational simulation of cardiac EP, including detailed patient-specific cardiac anatomy and infarct scar geometry. We modeled the BZ in eight different ways by combining the presence or absence of electrical remodeling with four different levels of image-based patchy fibrosis (0, 10, 20, and 30%). A 3D torso model was also constructed to compute the ECG. Patient-specific sinus activation patterns were simulated and validated against the patient's ECG. Subsequently, the pacing protocol used to induce reentrant VTs in the EP laboratory was reproduced in-silico. The clinical VT was induced with different versions of the model and from different pacing points, thus identifying the slow conducting channel responsible for such VT. Finally, the real patient's ECG recorded during VT episodes was used to validate our simulation results and to assess different strategies to model the BZ. Our study showed that reduced conduction velocities and heterogeneity in action potential duration in the BZ are the main factors in promoting reentrant activity. Either electrical remodeling or fibrosis in a degree of at least 30% in the BZ were required to initiate VT. Moreover, this proof-of-concept study confirms the feasibility of developing 3D computational models for cardiac EP able to reproduce cardiac activation in sinus rhythm and during VT, using exclusively non-invasive clinical data.

Project description:OBJECTIVES:This study sought to characterize ventricular tachycardia (VT) ablation outcomes across nonischemic cardiomyopathy (NICM) etiologies and adjust these outcomes by patient-related comorbidities that could explain differences in arrhythmia recurrence rates. BACKGROUND:Outcomes of catheter ablation of VT in patients with NICM could be related to etiology of NICM. METHODS:Data from 2,075 patients with structural heart disease referred for catheter ablation of VT from 12 international centers was retrospectively analyzed. Patient characteristics and outcomes were noted for the 6 most common NICM etiologies. Multivariable Cox proportional hazards modeling was used to adjust for potential confounders. RESULTS:Of 780 NICM patients (57 ± 14 years of age, 18% women, left ventricular ejection fraction 37 ± 13%), underlying prevalence was 66% for dilated idiopathic cardiomyopathy (DICM), 13% for arrhythmogenic right ventricular cardiomyopathy (ARVC), 6% for valvular cardiomyopathy, 6% for myocarditis, 4% for hypertrophic cardiomyopathy, and 3% for sarcoidosis. One-year freedom from VT was 69%, and freedom from VT, heart transplantation, and death was 62%. On unadjusted competing risk analysis, VT ablation in ARVC demonstrated superior VT-free survival (82%) versus DICM (p ? 0.01). Valvular cardiomyopathy had the poorest unadjusted VT-free survival, at 47% (p < 0.01). After adjusting for comorbidities, including age, heart failure severity, ejection fraction, prior ablation, and antiarrhythmic medication use, myocarditis, ARVC, and DICM demonstrated similar outcomes, whereas hypertrophic cardiomyopathy, valvular cardiomyopathy, and sarcoidosis had the highest risk of VT recurrence. CONCLUSIONS:Catheter ablation of VT in NICM is effective. Etiology of NICM is a significant predictor of outcomes, with ARVC, myocarditis, and DICM having similar but superior outcomes to hypertrophic cardiomyopathy, valvular cardiomyopathy, and sarcoidosis, after adjusting for potential covariates.

Project description:BackgroundDynamic functional substrate mapping of scar-related ventricular tachycardia offers better identification of ablation targets with limited ablation lesions. Several functional substrate mapping approaches have been proposed, including decrement-evoked potential (DEEP) mapping. The aim of our study was to compare the short- and long-term efficacy of a DEEP-guided versus a fixed-substrate-guided strategy for the ablation of scar-related ventricular tachycardia (VT).ResultsForty consecutive patients presenting for ablation of scar-related VT were randomized to either DEEP-guided or substrate-guided ablation. Late potentials were tagged and ablated in the non-DEEP group, while those in the DEEP group were subjected to RV extrastimulation after a drive train. Only potentials showing significant delay were ablated. Patients were followed for a median duration of 12 months. Twenty patients were allocated to the DEEP group, while the other 20 were allocated to the non-DEEP group. Twelve patients (60%) in the DEEP group had ischemic cardiomyopathy versus 10 patients (50%) in the non-DEEP group (P-value 0.525). Intraoperatively, the median percentage of points with LPs was 19% in the DEEP group and 20.6% in the non-DEEP group. The procedural time was longer in the DEEP group, approaching but missing statistical significance (P-value 0.059). VT non-inducibility was successfully accomplished in 16 patients (80%) in the DEEP group versus 17 patients (85%) in the non-DEEP group (P value 0.597). After a median follow-up duration of 12 months, the VT recurrence rate was 65% in both groups (P value 0.311), with a dropout rate of 10% in the DEEP group. As for the secondary endpoints, all-cause mortality rates were 20% and 25% in the DEEP and non-DEEP groups, respectively (P-value 0.342).ConclusionsDEEP-assisted ablation of scar-related ventricular tachycardia is a feasible strategy with comparable short- and long-term outcomes to a fixed-substrate-based strategy with more specific ablation targets, albeit relatively longer but non-significant procedural times and higher procedural deaths. The imbalance between the study groups in terms of epicardial versus endocardial mapping, although non-significant, warrants the prudent interpretation of our results. Further large-scale randomized trials are recommended.Trial registrationclinicaltrials.gov, registration number: NCT05086510, registered on 28th September 2021, record https://classic.Clinicaltrialsgov/ct2/show/NCT05086510.

Dataset Information

Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia.

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Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia.

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