In vivo human sock-mapping validation of a simple model that explains unipolar electrogram morphology in relation to conduction-repolarization dynamics

Technical development and feasibility of a reusable vest to integrate cardiovascular magnetic resonance with electrocardiographic imaging

BACKGROUND

Electrocardiographic imaging (ECGI) generates electrophysiological (EP) biomarkers while cardiovascular magnetic resonance (CMR) imaging provides data about myocardial structure, function and tissue substrate. Combining this information in one examination is desirable but requires an affordable, reusable, and high-throughput solution. We therefore developed the CMR-ECGI vest and carried out this technical development study to assess its feasibility and repeatability in vivo.

METHODS

CMR was prospectively performed at 3T on participants after collecting surface potentials using the locally designed and fabricated 256-lead ECGI vest. Epicardial maps were reconstructed to generate local EP parameters such as activation time (AT), repolarization time (RT) and activation recovery intervals (ARI). 20 intra- and inter-observer and 8 scan re-scan repeatability tests.

RESULTS

77 participants were recruited: 27 young healthy volunteers (HV, 38.9 ± 8.5 years, 35% male) and 50 older persons (77.0 ± 0.1 years, 52% male). CMR-ECGI was achieved in all participants using the same reusable, washable vest without complications. Intra- and inter-observer variability was low (correlation coefficients [rs] across unipolar electrograms = 0.99 and 0.98 respectively) and scan re-scan repeatability was high (rs between 0.81 and 0.93). Compared to young HV, older persons had significantly longer RT (296.8 vs 289.3 ms, p = 0.002), ARI (249.8 vs 235.1 ms, p = 0.002) and local gradients of AT, RT and ARI (0.40 vs 0.34 ms/mm, p = 0,01; 0.92 vs 0.77 ms/mm, p = 0.03; and 1.12 vs 0.92 ms/mm, p = 0.01 respectively).

CONCLUSION

Our high-throughput CMR-ECGI solution is feasible and shows good reproducibility in younger and older participants. This new technology is now scalable for high throughput research to provide novel insights into arrhythmogenesis and potentially pave the way for more personalised risk stratification.

CLINICAL TRIAL REGISTRATION

Title: Multimorbidity Life-Course Approach to Myocardial Health-A Cardiac Sub-Study of the MRC National Survey of Health and Development (NSHD) (MyoFit46). National Clinical Trials (NCT) number: NCT05455125. URL: https://clinicaltrials.gov/ct2/show/NCT05455125?term=MyoFit&draw=2&rank=1.

Understanding repolarization in the intracardiac unipolar electrogram: A long-lasting controversy revisited

Background: The optimal way to determine repolarization time (RT) from the intracardiac unipolar electrogram (UEG) has been a topic of debate for decades. RT is typically determined by either the Wyatt method or the "alternative method," which both consider UEG T-wave slope, but differently. Objective: To determine the optimal method to measure RT on the UEG. Methods: Seven pig hearts surrounded by an epicardial sock with 100 electrodes were Langendorff-perfused with selective cannulation of the left anterior descending (LAD) coronary artery and submersed in a torso-shaped tank containing 256 electrodes on the torso surface. Repolarization was prolonged in the non-LAD-regions by infusing dofetilide and shortened in the LAD-region using pinacidil. RT was determined by the Wyatt (t_Wyatt) and alternative (t_Alt) methods, in both invasive (recorded with epicardial electrodes) and in non-invasive UEGs (reconstructed with electrocardiographic imaging). t_Wyatt and t_Alt were compared to local effective refractory period (ERP). Results: With contact mapping, mean absolute error (MAE) of t_Wyatt and t_Alt vs. ERP were 21 ms and 71 ms, respectively. Positive T-waves typically had an earlier ERP than negative T-waves, in line with theory. t_Wyatt -but not t_Alt-shortened by local infusion of pinacidil. Similar results were found for the non-invasive UEGs (MAE of t_Wyatt and t_Alt vs. ERP were 30 ms and 92 ms, respectively). Conclusion: The Wyatt method is the most accurate to determine RT from (non) invasive UEGs, based on novel and historical analyses. Using it to determine RT could unify and facilitate repolarization assessment and amplify its role in cardiac electrophysiology.

Assessing Noninvasive Delineation of Low-Voltage Zones Using ECG Imaging in Patients With Structural Heart Disease

OBJECTIVES

This study sought to assess the association between electrocardiographic imaging (ECGI) parameters and voltage from simultaneous electroanatomic mapping (EAM).

BACKGROUND

ECGI offers noninvasive assessment of electrophysiologic features relevant for mapping ventricular arrhythmia and its substrate, but the accuracy of ECGI in the delineation of scar is unclear.

METHODS

Sixteen patients with structural heart disease underwent simultaneous ECGI (CardioInsight, Medtronic) and contact EAM (CARTO, Biosense-Webster) during ventricular tachycardia catheter ablation, with 7 mapped epicardially. ECGI and EAM geometries were coregistered using anatomic landmarks. ECGI points were paired to the closest site on the EAM within 10 mm. The association between EAM voltage and ECGI features from reconstructed epicardial unipolar electrograms was assessed by mixed-effects regression models. The classification of low-voltage regions was performed using receiver-operating characteristic analysis.

RESULTS

A total of 9,541 ECGI points (median: 596; interquartile range: 377-737 across patients) were paired to an EAM site. Epicardial EAM voltage was associated with ECGI features of signal fractionation and local repolarization dispersion (N = 7; P < 0.05), but they poorly classified sites with bipolar voltage of <1.5 mV or <0.5 mV thresholds (median area under the curve across patients: 0.50-0.62). No association was found between bipolar EAM voltage and low-amplitude reconstructed epicardial unipolar electrograms or ECGI-derived bipolar electrograms. Similar results were found in the combined cohort (n = 16), including endocardial EAM voltage compared to epicardial ECGI features (n = 9).

CONCLUSIONS

Despite a statistically significant association between ECGI features and EAM voltage, the accuracy of the delineation of low-voltage zones was modest. This may limit ECGI use for pr-procedural substrate analysis in ventricular tachycardia ablation, but it could provide value in risk assessment for ventricular arrhythmias.

Detailed Assessment of Low-Voltage Zones Localization by Cardiac MRI in Patients With Implantable Devices

OBJECTIVES

The purpose of this study was to assess the performance and limitations of low-voltage zones (LVZ) localization by optimized late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) scar imaging in patients with cardiac implantable electronic devices (CIEDs).

BACKGROUND

Scar evaluation by LGE-CMR can assist ventricular tachycardia (VT) ablation, but challenges with electroanatomical maps coregistration and presence of imaging artefacts from CIED limit accuracy.

METHODS

A total of 10 patients underwent VT ablation and preprocedural LGE-CMR using wideband imaging. Scar was segmented from CMR pixel signal intensity maps using commercial software (ADAS-VT, Galgo Medical) with bespoke tools and compared with detailed electroanatomical maps (CARTO). Coregistration of EP and imaging-derived scar was performed using the aorta as a fiducial marker, and the impact of coregistration was determined by assessing intraobserver/interobserver variability and using computer simulations. Spatial smoothing was applied to assess correlation at different spatial resolutions and to reduce noise.

RESULTS

Pixel signal intensity maps localized low-voltage zones (V <1.5 mV) with area under the receiver-operating characteristic curve: 0.82 (interquartile range [IQR]: 0.76-0.83), sensitivity 74% (IQR: 71%-77%), and specificity 78% (IQR: 73%-83%) and correlated with bipolar voltage (r = -0.57 [IQR: -0.68 to -0.42]) across patients. In simulations, small random shifts and rotations worsened LVZ localization in at least some cases. The use of the full aortic geometry ensured high reproducibility of LVZ localization (r >0.86 for area under the receiver-operating characteristic curve). Spatial smoothing improved localization of LVZ. Results for LVZ with V <0.5 mV were similar.

CONCLUSIONS

In patients with CIEDs, novel wideband CMR sequences and personalized coregistration strategies can localize LVZ with good accuracy and may assist VT ablation procedures.

Direct in vivo assessment of global and regional mechanoelectric feedback in the intact human heart

Background

Inhomogeneity of ventricular contraction is associated with sudden cardiac death, but the underlying mechanisms are unclear. Alterations in cardiac contraction impact electrophysiological parameters through mechanoelectric feedback. This has been shown to promote arrhythmias in experimental studies, but its effect in the in vivo human heart is unclear.

Objective

The purpose of this study was to quantify the impact of regional myocardial deformation provoked by a sudden increase in ventricular loading (aortic occlusion) on human cardiac electrophysiology.

Methods

In 10 patients undergoing open heart cardiac surgery, left ventricular (LV) afterload was modified by transient aortic occlusion. Simultaneous assessment of whole-heart electrophysiology and LV deformation was performed using an epicardial sock (240 electrodes) and speckle-tracking transesophageal echocardiography. Parameters were matched to 6 American Heart Association LV model segments. The association between changes in regional myocardial segment length and activation-recovery interval (ARI; a conventional surrogate for action potential duration) was studied using mixed-effect models.

Results

Increased ventricular loading reduced longitudinal shortening (P = .01) and shortened ARI (P = .02), but changes were heterogeneous between cardiac segments. Increased regional longitudinal shortening was associated with ARI shortening (effect size 0.20 [0.01–0.38] ms/%; P = .04) and increased local ARI dispersion (effect size –0.13 [–0.23 to –0.03] ms/%; P = .04). At the whole organ level, increased mechanical dispersion translated into increased dispersion of repolarization (correlation coefficient r = 0.81; P = .01).

Conclusion

Mechanoelectric feedback can establish a potentially proarrhythmic substrate in the human heart and should be considered to advance our understanding and prevention of cardiac arrhythmias.

A novel method to correct repolarization time estimation from unipolar electrograms distorted by standard filtering

Reliable patient-specific ventricular repolarization times (RTs) can identify regions of functional block or afterdepolarizations, indicating arrhythmogenic cardiac tissue and the risk of sudden cardiac death. Unipolar electrograms (UEs) record electric potentials, and the Wyatt method has been shown to be accurate for estimating RT from a UE. High-pass filtering is an important step in processing UEs, however, it is known to distort the T-wave phase of the UE, which may compromise the accuracy of the Wyatt method. The aim of this study was to examine the effects of high-pass filtering, and improve RT estimates derived from filtered UEs. We first generated a comprehensive set of UEs, corresponding to early and late activation and repolarization, that were then high-pass filtered with settings that mimicked the CARTO filter. We trained a deep neural network (DNN) to output a probabilistic estimation of RT and a measure of confidence, using the filtered synthetic UEs and their true RTs. Unfiltered ex-vivo human UEs were also filtered and the trained DNN used to estimate RT. Even a modest 2 Hz high-pass filter imposes a significant error on RT estimation using the Wyatt method. The DNN outperformed the Wyatt method in 62.75% of cases, and produced a significantly lower absolute error (p=8.99E-13), with a median of 16.91 ms, on 102 ex-vivo UEs. We also applied the DNN to patient UEs from CARTO, from which an RT map was computed. In conclusion, DNNs trained on synthetic UEs improve the RT estimation from filtered UEs, which leads to more reliable repolarization maps that help to identify patient-specific repolarization abnormalities.

Prolonged action potential duration and dynamic transmural action potential duration heterogeneity underlie vulnerability to ventricular tachycardia in patients undergoing ventricular tachycardia ablation

Aims

Differences of action potential duration (APD) in regions of myocardial scar and their borderzones are poorly defined in the intact human heart. Heterogeneities in APD may play an important role in the generation of ventricular tachycardia (VT) by creating regions of functional block. We aimed to investigate the transmural and planar differences of APD in patients admitted for VT ablation.

Methods and results

Six patients (median age 53 years, five male); (median ejection fraction 35%), were studied. Endocardial (Endo) and epicardial (Epi) 3D electroanatomic mapping was performed. A bipolar voltage of <0.5 mV was defined as dense scar, 0.5–1.5 mV as scar borderzone, and >1.5 mV as normal. Decapolar catheters were positioned transmurally across the scar borderzone to assess differences of APD and repolarization time (RT) during restitution pacing from Endo and Epi. Epi APD was 173 ms in normal tissue vs. 187 ms at scar borderzone and 210 ms in dense scar (P < 0.001). Endocardial APD was 210 ms in normal tissue vs. 222 ms in the scar borderzone and 238 ms in dense scar (P < 0.01). This resulted in significant transmural RT dispersion (ΔRT 22 ms across dense transmural scar vs. 5 ms in normal transmural tissue, P < 0.001), dependent on the scar characteristics in the Endo and Epi, and the pacing site.

Conclusion

Areas of myocardial scar have prolonged APD compared with normal tissue. Heterogeneity of regional transmural and planar APD result in localized dispersion of repolarization, which may play an important role in initiating VT.

Evaluation of ECG Imaging to Map Hemodynamically Stable and Unstable Ventricular Arrhythmias

BACKGROUND

ECG imaging (ECGI) has been used to guide treatment of ventricular ectopy and arrhythmias. However, the accuracy of ECGI in localizing the origin of arrhythmias during catheter ablation of ventricular tachycardia (VT) in structurally abnormal hearts remains to be fully validated.

METHODS

During catheter ablation of VT, simultaneous mapping was performed using electroanatomical mapping (CARTO, Biosense-Webster) and ECGI (CardioInsight, Medtronic) in 18 patients. Sites of entrainment, pace-mapping, and termination during ablation were used to define the VT site of origin (SoO). Distance between SoO and the site of earliest activation on ECGI were measured using co-registered geometries from both systems. The accuracy of ECGI versus a 12-lead surface ECG algorithm was compared.

RESULTS

A total of 29 VTs were available for comparison. Distance between SoO and sites of earliest activation in ECGI was 22.6, 13.9 to 36.2 mm (median, first to third quartile). ECGI mapped VT sites of origin onto the correct AHA segment with higher accuracy than a validated 12-lead ECG algorithm (83.3% versus 38.9%; P=0.015).

CONCLUSIONS

This simultaneous assessment demonstrates that CardioInsight localizes VT circuits with sufficient accuracy to provide a region of interest for targeting mapping for ablation. Resolution is not sufficient to guide discrete radiofrequency lesion delivery via catheter ablation without concomitant use of an electroanatomical mapping system but may be sufficient for segmental ablation with radiotherapy.

Evaluation of the reentry vulnerability index to predict ventricular tachycardia circuits using high-density contact mapping

Background

Identifying arrhythmogenic sites to improve ventricular tachycardia (VT) ablation outcomes remains unresolved. The reentry vulnerability index (RVI) combines activation and repolarization timings to identify sites critical for reentrant arrhythmia initiation without inducing VT.

Objective

The purpose of this study was to provide the first assessment of RVI’s capability to identify VT sites of origin using high-density contact mapping and comparison with other activation-repolarization markers of functional substrate.

Methods

Eighteen VT ablation patients (16 male; 72% ischemic) were studied. Unipolar electrograms were recorded during ventricular pacing and analyzed offline. Activation time (AT), activation–recovery interval (ARI), and repolarization time (RT) were measured. Vulnerability to reentry was mapped based on RVI and spatial distribution of AT, ARI, and RT. The distance from sites identified as vulnerable to reentry to the VT site of origin was measured, with distances <10 mm and >20 mm indicating accurate and inaccurate localization, respectively.

Results

The origins of 18 VTs (6 entrainment, 12 pace-mapping) were identified. RVI maps included 1012 (408–2098) (median, 1st–3rd quartiles) points per patient. RVI accurately localized 72.2% VT sites of origin, with median distance of 5.1 (3.2–10.1) mm. Inaccurate localization was significantly less frequent for RVI than AT (5.6% vs 33.3%; odds ratio 0.12; P = .035). Compared to RVI, distance to VT sites of origin was significantly larger for sites showing prolonged RT and ARI and were nonsignificantly larger for sites showing highest AT and ARI gradients.

Conclusion

RVI identifies vulnerable regions closest to VT sites of origin. Activation-repolarization metrics may improve VT substrate delineation and inform novel ablation strategies.

Noninvasive Mapping of the Electrophysiological Substrate in Cardiac Amyloidosis and Its Relationship to Structural Abnormalities

Background

The relationship between structural pathology and electrophysiological substrate in cardiac amyloidosis is unclear. Differences between light‐chain (AL) and transthyretin (ATTR) cardiac amyloidosis may have prognostic implications.

Methods and Results

ECG imaging and cardiac magnetic resonance studies were conducted in 21 cardiac amyloidosis patients (11 AL and 10 ATTR). Healthy volunteers were included as controls. With respect to ATTR, AL patients had lower amyloid volume (51.0/37.7 versus 73.7/16.4 mL, P=0.04), lower myocardial cell volume (42.6/19.1 versus 58.5/17.2 mL, P=0.021), and higher T1 (1172/64 versus 1109/80 ms, P=0.022) and T2 (53.4/2.9 versus 50.0/3.1 ms, P=0.003). ECG imaging revealed differences between cardiac amyloidosis and control patients in virtually all conduction‐repolarization parameters. With respect to ATTR, AL patients had lower epicardial signal amplitude (1.07/0.46 versus 1.83/1.26 mV, P=0.026), greater epicardial signal fractionation (P=0.019), and slightly higher dispersion of repolarization (187.6/65 versus 158.3/40 ms, P=0.062). No significant difference between AL and ATTR patients was found using the standard 12‐lead ECG. T1 correlated with epicardial signal amplitude (cc=−0.78), and extracellular volume with epicardial signal fractionation (cc=0.48) and repolarization time (cc=0.43). Univariate models based on single features from both cardiac magnetic resonance and ECG imaging classified AL and ATTR patients with an accuracy of 70% to 80%.

Conclusions

In this exploratory study cardiac amyloidosis was associated with ventricular conduction and repolarization abnormalities, which were more pronounced in AL than in ATTR. Combined ECG imaging–cardiac magnetic resonance analysis supports the hypothesis that additional mechanisms beyond infiltration may contribute to myocardial damage in AL amyloidosis. Further studies are needed to assess the clinical impact of this approach.

In vivo human sock-mapping validation of a simple model that explains unipolar electrogram morphology in relation to conduction-repolarization dynamics

INTRODUCTION

The unipolar electrogram (UEG) provides local measures of cardiac activation and repolarization and is an important translational link between patient and laboratory. A simple theoretical model of the UEG was previously proposed and tested in silico.

METHOD AND RESULTS

The aim of this study was to use epicardial sock-mapping data to validate the simple model's predictions of unipolar electrogram morphology in the in vivo human heart. The simple model conceptualizes the UEG as the difference between a local cardiac action potential and a position-independent component representing remote activity, which is defined as the average of all action potentials. UEGs were recorded in 18 patients using a multielectrode sock containing 240 electrodes and activation (AT) and repolarization time (RT) were measured using standard definitions. For each cardiac site, a simulated local action potential was generated by adjusting a stylized action potential to fit AT and RT measured in vivo. The correlation coefficient (cc) measuring the morphological similarity between 13,637 recorded and simulated UEGs was cc  =  0.89 (0.72-0.95), median (Q₁ -Q₃ ), for the entire UEG, cc  =  0.90 (0.76-0.95) for QRS complexes, and cc  =  0.83 (0.58-0.92) for T-waves. QRS and T-wave areas from recorded and simulated UEGs showed cc> 0.89 and cc> 0.84, respectively, indicating good agreement between voltage isochrones maps. Simulated UEGs accurately reproduced the interaction between AT and QRS morphology and between RT and T-wave morphology observed in vivo.

CONCLUSIONS

Human in vivo whole heart data support the validity of the simple model, which provides a framework for improving the understanding of the UEG and its clinical utility.