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.

Background Asymptomatic individuals account for a majority of sudden cardiac deaths (SCDs). Development of effective, low-cost, and non-invasive SCD risk stratification tools are necessary. Methods and Results Participants from the Atherosclerosis Risk in Communities study and Cardiovascular Health Study (n=20,177; age 59.3±10.1 years; age range 44–100; 56% female; 77% white) were followed for 14.0 years (median). Five ECG markers of global electrical heterogeneity (GEH) (sum absolute QRST integral, spatial QRST angle, spatial ventricular gradient (SVG) magnitude, SVG elevation, and SVG azimuth) were measured on standard 12-lead ECGs. Cox proportional hazards and competing risks models evaluated associations between GEH ECG parameters and SCD. A SCD competing risks score was derived using demographics, comorbidities, and GEH parameters. SCD incidence was 1.86 per 1,000 person-years. After multivariable adjustment, baseline GEH parameters and large increases in GEH parameters over time were independently associated with SCD. Final SCD risk scores included age, sex, race, diabetes, hypertension, coronary heart disease, and stroke, and GEH parameters as continuous variables. When GEH parameters were added to clinical/demographic factors, the C-statistic increased from 0.777 to 0.790 (p=0.008), the risk score classified 10-year SCD risk as high (>5%) in 7.2% of participants, 10% of SCD victims were appropriately reclassified into a high-risk category, and only 1.4% of SCD victims were inappropriately reclassified from high- to intermediate-risk. Net reclassification index was 18.3%. Conclusions Abnormal electrophysiological substrate quantified by GEH parameters is independently associated with SCD in the general population. Addition of GEH parameters to clinical characteristics improves SCD risk prediction.

Background MRI has been used to acutely visualize radiofrequency (RF) ablation lesions but its accuracy in predicting chronic lesion size is unknown. The main goal of this study was to characterize different areas of enhancement in late gadolinium enhancement (LGE) MRI done immediately after ablation to predict acute edema and chronic lesion size. Methods and Results In a canine model (n=10), ventricular RF lesions were created, using ThermoCool SmartTouch (Biosense Webster) catheter. All animals underwent MRI (LGE and T2-weighted (T2w) edema imaging), immediately after ablation and after 1, 2, 4 and 8 weeks. Edema, microvascular obstruction (MVO) and enhanced volumes were identified in MRI and normalized to chronic histological volume. Immediately after contrast administration, the MVO region was 3.2 +/− 1.1 times larger than the chronic lesion volume in acute MRI. Even 60 mins after contrast administration, edema was 8.73 +/− 3.31 times and the enhanced area 6.14 +/− 2.74 times the chronic lesion volume. Exponential fit to the MVO volume was found to be the best predictor of chronic lesion volume at 26.14 (95% prediction interval 24.35 – 28.11) mins after contrast injection. The edema volume in LGE correlated well with edema volume in T2w MRI with an R2 of 0.99. Conclusion MVO region on acute LGE images acquired 26.1 min after contrast administration can accurately predict the chronic lesion volume. We also show that T1-weighted MRI images acquired immediately after contrast injection accurately shows edema resulting from RF ablation.

The single leading cause of mortality on hemodialysis is sudden cardiac death. Whether measures of electrophysiologic substrate independently associate with mortality is unknown. We examined measures of electrophysiologic substrate in a prospective cohort of 571 patients on incident hemodialysis enrolled in the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease Study. A total of 358 participants completed both baseline 5-minute and 12-lead electrocardiogram recordings on a nondialysis day. Measures of electrophysiologic substrate included ventricular late potentials by the signal-averaged electrocardiogram and spatial mean QRS-T angle measured on the averaged beat recorded within a median of 106 days (interquartile range, 78-151 days) from dialysis initiation. The cohort was 59% men, and 73% were black, with a mean±SD age of 55±13 years. Transthoracic echocardiography revealed a mean±SD ejection fraction of 65.5%±12.0% and a mean±SD left ventricular mass index of 66.6±22.3 g/m During 864.6 person-years of follow-up, 77 patients died; 35 died from cardiovascular causes, of which 15 were sudden cardiac deaths. By Cox regression analysis, QRS-T angle ≥75° significantly associated with increased risk of cardiovascular mortality (hazard ratio, 2.99; 95% confidence interval, 1.31 to 6.82) and sudden cardiac death (hazard ratio, 4.52; 95% confidence interval, 1.17 to 17.40) after multivariable adjustment for demographic, cardiovascular, and dialysis factors. Abnormal signal-averaged electrocardiogram measures did not associate with mortality. In conclusion, spatial QRS-T angle but not abnormal signal-averaged electrocardiogram significantly associates with cardiovascular mortality and sudden cardiac death independent of traditional risk factors in patients starting hemodialysis.

BACKGROUND Antitachycardia pacing (ATP) success rates as low as 50% for fast ventricular tachycardias (VTs) have been reported providing an opportunity for improved ATP to decrease shocks.OBJECTIVE The purpose of this study was to determine how a new automated antitachycardia pacing (AATP) therapy would perform compared with traditional burst ATP using computer modeling to conduct a virtual study.METHODS Virtual patient scenarios were constructed from magnetic resonance imaging and electrophysiological (EP) data. Cardiac EP simulation software (CARPEntry) was used to generate reentrant VT. Simulated VT exit sites were physician adjudicated against corresponding clinical 12-lead electrocardiograms. Burst ATP comprised 3 sequences of 8 pulses at 88% of VT cycle length, with each sequence decremented by 10 ms. AATP was limited to 3 sequences, with each sequence learning from the previous sequences.RESULTS Two hundred fifty-nine unique ATP scenarios were generated from 7 unique scarred hearts. Burst ATP terminated 145 of 259 VTs (56%) and accelerated 2.0%. AATP terminated 189 of 259 VTs (73%) with the same acceleration rate. The 2 dominant ATP failure mechanisms were identified as (1) insufficient prematurity to close the excitable gap; and (2) failure to reach the critical isthmus of the VT. AATP reduced failures in these categories from 101 to 63 (44% reduction) without increasing acceleration.CONCLUSION AATP successfully adapted ATP sequences to terminate VT episodes that burst ATP failed to terminate. AATP was successful with complex scar geometries and EP heterogeneity as seen in the real world.