Elyar Ghafoori

Global Electric Heterogeneity Risk Score for Prediction of Sudden Cardiac Death in the General Population: The Atherosclerosis Risk in Communities (ARIC) and Cardiovascular Health (CHS) Studies.

Background— Asymptomatic individuals account for the majority of sudden cardiac deaths (SCDs). Development of effective, low-cost, and noninvasive SCD risk stratification tools is 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 years; 56% female; 77% white) were followed up for 14.0 years (median). Five ECG markers of global electric 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 electrocardiographic parameters and SCD. An SCD competing risks score was derived from demographics, comorbidities, and GEH parameters. SCD incidence was 1.86 per 1000 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 mellitus, hypertension, coronary heart disease, 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. The net reclassification index was 18.3%. Conclusions— Abnormal electrophysiological substrate quantified by GEH parameters is independently associated with SCD in the general population. The addition of GEH parameters to clinical characteristics improves SCD risk prediction.

Global Electric Heterogeneity Risk Score for Prediction of Sudden Cardiac Death in the General Population

Background— Asymptomatic individuals account for the majority of sudden cardiac deaths (SCDs). Development of effective, low-cost, and noninvasive SCD risk stratification tools is 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 years; 56% female; 77% white) were followed up for 14.0 years (median). Five ECG markers of global electric 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 electrocardiographic parameters and SCD. An SCD competing risks score was derived from demographics, comorbidities, and GEH parameters. SCD incidence was 1.86 per 1000 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 mellitus, hypertension, coronary heart disease, 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. The net reclassification index was 18.3%. Conclusions— Abnormal electrophysiological substrate quantified by GEH parameters is independently associated with SCD in the general population. The addition of GEH parameters to clinical characteristics improves SCD risk prediction.

Electrophysiologic Substrate and Risk of Mortality in Incident Hemodialysis

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/m2.7 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.

Characterization of Gadolinium Contrast Enhancement of Radiofrequency Ablation Lesions in Predicting Edema and Chronic Lesion Size

Background: Magnetic resonance imaging (MRI) has been used to acutely visualize radiofrequency 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 MRI done immediately after ablation to predict acute edema and chronic lesion size. Methods and Results: In a canine model (n=10), ventricular radiofrequency lesions were created using ThermoCool SmartTouch (Biosense Webster) catheter. All animals underwent MRI (late gadolinium enhancement and T2-weighted edema imaging) immediately after ablation and after 1, 2, 4, and 8 weeks. Edema, microvascular obstruction, and enhanced volumes were identified in MRI and normalized to chronic histological volume. Immediately after contrast administration, the microvascular obstruction region was 3.2±1.1 times larger than the chronic lesion volume in acute MRI. Even 60 minutes after contrast administration, edema was 8.7±3.31 times and the enhanced area 6.14±2.74 times the chronic lesion volume. Exponential fit to the microvascular obstruction volume was found to be the best predictor of chronic lesion volume at 26.14 minutes (95% prediction interval, 24.35–28.11 minutes) after contrast injection. The edema volume in late gadolinium enhancement correlated well with edema volume in T2-weighted MRI with an R2 of 0.99. Conclusion: Microvascular obstruction region on acute late gadolinium enhancement images acquired 26.1 minutes 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 radiofrequency ablation.

Electrical dyssynchrony on noninvasive electrocardiographic mapping correlates with SAI QRST on surface ECG

Aim: The goal of this study was to compare associations between clinical and ECG predictors of cardiac resynchronization therapy (CRT) response with electrical dyssynchrony. Methods: Body-surface potentials were recorded using a 120-lead system in 4 patients (age 62 ± 12 y, left ventricular ejection fraction (L VEF) 29 ± 5 %; QRS duration 154 ± 19 ms) with post-myocardial infarction scar and left bundle branch block before CRT implantation. A patient-specific heart-torso model derived from MRi with 291 heart-surface nodes was developed. Electrical dyssynchrony index (EDl) was computed as the standard deviation of activation times on the epicardium while uncoupling index (Ul) was measured as the diference between the activation times. Results: QRS duration correlated with mean activation time (r = 0.977; P = 0.023), but did not correlate with EDl or VI. L VEF inversely correlated with activation time at the lowest 20th percentile (r = - 0.960; P = 0.040). Sum absolute QRST integral (SAl QRST), measured on orthogonal XYZ ECG, correlated with EDl (r = 0.955; P = 0.045), and characterized late-activated area of the left ventricle.

Analysis of speed, curvature, planarity and frequency characteristics of heart vector movement to evaluate the electrophysiological substrate associated with ventricular tachycardia

BACKGROUND We developed a novel method of assessing ventricular conduction using the surface ECG. METHODS Orthogonal ECGs of 81 healthy controls (age 39.0±14.2 y; 51.8% males; 94% white), were compared with iDower-transformed 12-lead ECGs (both 1000Hz), recorded in 8 patients with infarct-cardiomyopathy and sustained monomorphic ventricular tachycardia (VT) (age 68.0±7.8y, 37.5% male, mean LVEF 29±12%). Normalized speed at 10 QRS segments was calculated as the distance traveled by the heart vector along the QRS loop in three-dimensional space, divided by 1/10th of the QRS duration. Curvature was calculated as the magnitude of the derivative of the QRS loop tangent vector divided by speed. Planarity was calculated as the mean of the dihedral angles between 2 consecutive planes for all planes generated for the median beat. Orbital frequency (a scalar measure of rotation rate of the QRS vector) was calculated as a product of speed and curvature. RESULTS Mixed regression analysis showed that speed was slower [6.6 (95%CI 4.4-8.9) vs. 24.6 (95%CI 11.5-37.7)µV/ms; P<0.0001]; orbital frequency was smaller [1.4 (95%CI 1.2-1.6) vs. 6.8 (95%CI 5.4-8.1)ms(-1); P<0.0001], and planarity was larger by 3.6° (95%CI 1.4°-5.8; P=0.002) in VT cases than in healthy controls. ROC AUC for orbital frequency was 0.940 (95%CI 0.935-0.944) across all frequencies and QRS segments. ROC AUC for planarity at 70-249Hz was 0.995 (95%CI 0.985-1.00). ROC AUC for speed at 70-79Hz was 0.979 (95%CI 0.969-0.989). CONCLUSION This novel method reveals characteristic features of an abnormal electrophysiological substrate associated with VT.

Quantitative Assessment of Vectorcardiographic Loop Morphology.

Vectorcardiography (VCG), developed 100years ago, characterizes clinically important electrophysiological properties of the heart. In this study, VCG QRS loop roundness, planarity, thickness, rotational angle, and dihedral angle were measured in 81 healthy control subjects (39.0±14.2y; 51.8% male; 94% white), and 8 patients with infarct-cardiomyopathy and sustained monomorphic ventricular tachycardia (VT) (68.0±7.8y, 37.5% male). The angle between two consecutive QRS vectors was defined as the rotational angle, while dihedral angle quantified planar alteration over the QRS loop. In VT subjects, planarity index decreased (0.63±0.22 vs. 0.88±0.10; P=0.014), and dihedral angle was significantly more variable (variance of dihedral angle, median (IQR): 897(575-1450) vs. 542(343-773); P=0.029; rMSSD: 47.7±12.7 vs. 35.1±13.1; P=0.027). Abnormal electrophysiological substrate in VT patients is characterized by the appearance of QRS loop folding, likely due to local conduction block. The presence of fragmented QRS complexes on the 12-lead ECG had low sensitivity (31%) for detecting QRS loop folding on the VCG.

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

Ventricular tachycardia (VT), which can lead to sudden cardiac death, occurs frequently in patients with myocardial infarction. Catheter-based radio-frequency 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 (five swine) and human studies (21 patients), as well as in a prospective feasibility study (five patients). We first assessed, using retrospective studies (one of which included a proportion of clinical images with artefacts), 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 before the clinical procedure.A personalized virtual-heart model that determines optimal radio-frequency ablation targets for infarct-related tachycardia is validated in retrospective large-animal and patient studies, and in a prospective study in patients.

Construction of intracardiac vectorcardiogram from implantable cardioverter-defibrillator intracardiac electrograms ☆,☆☆,★

We constructed an intracardiac vectorcardiogram from 3 configurations of intracardiac cardiovertor defibrilator (ICD) electrograms (EGMs). Six distinctive 3 lead combinations were selected out of five leads: can to right ventricular coil (RVC); RVC to superior vena cava coil (SVC); atrial lead tip (A-tip) to right ventricular (RV)-ring; can to RV-ring; RV-tip to RVC, in a patient with dual chamber ICD. Surface spatial QRS-T angle (119.8°) was similar to intracardiac spatial QRS-T angle derived from ICD EGMs combination A (101.3°), B (96.1°), C (92.8°), D (95.2), E (99.0), F (96.2) and median (101.5). Future validation of the novel method is needed.

Atrial fibrillation observed on surface ECG can be atrial flutter or atrial tachycardia

BACKGROUND Differentiating between atrial fibrillation (AF) and atrial tachycardia (AT) or atrial flutter (AFL) on surface ECG can be challenging. The same problem arises in animal models of AF, in which atrial arrhythmias are induced by pacing or pharmacological intervention with the goal of making mechanistic determinations. Some of these induced arrhythmias can be AFL or AT, even though it might appear as AF on the body-surface ECG based on irregular R-R intervals. We hypothesize that a dominant frequency (DF) analysis of the ECG can differentiate between the two distinct arrhythmias, even when it is not evident by the presence of flutter waves or beat-to-beat regularity when looking at brief recordings. METHODS Canine model (n = 15, 10 controls and 5 Persistent AF animals with >6 months of AF) was used to test the hypothesis. Atrial arrhythmia was induced by rapid atrial pacing. Five blinded observers evaluated the 3‑lead surface ECGs recorded during atrial arrhythmia and classified the rhythm as AFL/AT or AF. The 64-electrode Constellation (Boston Scientific) catheter was used to acquire left (entire group) and right (7 of 10 controls) atrial intracardiac electrograms. For the surface ECG and the intracardiac electrograms, Welch method with a hamming window and 50% overlap was used to calculate DF of two-minute segments. Mean of standard deviations of the DF values were calculated for both ECGs and intracardiac EGMs. Ground truth came from activations maps and DF analysis derived from the intracardiac electrograms recorded in the two chambers. RESULTS Rapid pacing induced atrial arrhythmias in all the control animals. The ECG in 8 of the 10 control cases was read as AF by at least 80% percent of observers even though the EGMs from the Constellation showed organized activation and consistent DF (STD of DF < 0.001) in all the electrodes confirming the arrhythmia as AFL in 10/10 cases. In the persistent AF group, the DF from the three lead ECGs were significantly different (Mean of STDs = 2.65 ± 0.99) whereas the DF in the control animals with AFL was consistent across all ECG channels (Mean of STDs < 0.001), and the DF in the control animals ECGs was in agreement with the DF of the intracardiac electrograms. CONCLUSION Surface ECG recordings can mimic AF even when the underlying atrial arrhythmia is AFL in control canine models. DF variation of the signals from multiple surface ECG leads can help differentiate between the AF and AFL.