Improving electrocardiographic imaging solutions: A comprehensive study on regularization parameter selection in L-curve optimization in the Atria.

BACKGROUND: In electrocardiographic imaging (ECGI), selecting an optimal regularization parameter (λ) is crucial for obtaining accurate inverse electrograms. The effects of signal and geometry uncertainties on the inverse problem regularization have not been thoroughly quantified, and there is no established methodology to identify when λ is sub-optimal due to these uncertainties. This study introduces a novel approach to λ selection using Tikhonov regularization and L-curve optimization, specifically addressing the impact of electrical noise in body surface potential map (BSPM) signals and geometrical inaccuracies in the cardiac mesh. METHODS: Nineteen atrial simulations (5 of regular rhythms and 14 of atrial fibrillation) ensuring variability in substrate complexity and activation patterns were used for computing the ECGI with added white Gaussian noise from 40 dB to -3dB. Cardiac mesh displacements (1-3 cm) were applied to simulate the uncertainty of atrial positioning and study its impact on the L-curve shape. The regularization parameter, the maximum curvature, and the most horizontal angle of the L-curve (ß) were quantified. In addition, BSPM signals from real patients were used to validate our findings. RESULTS: The maximum curvature of the L-curve was found to be inversely related to signal-to-noise ratio and atrial positioning errors. In contrast, the ß angle is directly related to electrical noise and remains unaffected by geometrical errors. Our proposed adjustment of λ, based on the ß angle, provides a more reliable ECGI solution than traditional corner-based methods. Our findings have been validated with simulations and real patient data, demonstrating practical applicability. CONCLUSION: Adjusting λ based on the amount of noise in the data (or on the ß angle) allows finding optimal ECGI solutions than a λ purely found at the corner of the L-curve. It was observed that the relevant information in ECGI activation maps is preserved even under the presence of uncertainties when the regularization parameter is correctly selected. The proposed criteria for regularization parameter selection have the potential to enhance the accuracy and reliability of ECGI solutions.

Substrate Mapping for Ventricular Tachycardia Ablation Through High-Density Whole-Chamber Double Extra Stimuli: The S3 Protocol.

BACKGROUND: A partial delineation of targets for ablation of ventricular tachycardia (VT) during a stable rhythm is likely responsible for a suboptimal success rate. The abnormal low-voltage near-field functional components may be hidden within the high-amplitude far-field signal. OBJECTIVES: The aim of this study was to evaluate the benefit and feasibility of functional substrate mapping using a full-ventricle S3 protocol and to assess its colocalization with arrhythmogenic conducting channels (CCs) on late gadolinium enhancement cardiac magnetic resonance. METHODS: An S3 mapping protocol with a drive train of S1 followed by S2 (effective refractory period + 30 ms) and S3 (effective refractory period + 50 ms) from the right ventricular apex was performed in 40 consecutive patients undergoing scar-related VT ablation. Deceleration zones (DZs) and areas of late potentials (LPs) were identified for all maps. A preprocedural noninvasive substrate assessment was done using late gadolinium enhancement cardiac magnetic resonance and postprocessing with automated CC identification. RESULTS: The S3 protocol was completed in 34 of the 40 procedures (85.0%). The S3 protocol enhanced the identification of VT isthmus on the basis of DZ (89% vs 62%; P < 0.01) and LP (93% vs 78%; P = 0.04) assessment. The percentage of CCs unmasked by DZs and LPs using S3 maps was significantly higher than the ones using S2 and S1 maps (78%, 65%, and 48% [P < 0.001] and 88%, 81%, and 68% [P < 0.01], respectively). The functional substrate identified during S3 activation mapping was significantly more extensive than the one identified using S2 and S1, including a greater number of DZs (2.94, 2.47, and 1.82, respectively; P < 0.001) and a wider area of LPs (44.1, 38.2, and 29.4 cm2, respectively; P < 0.001). After VT ablation, 77.9% of patients have been VT free during a median follow-up period of 13.6 months. CONCLUSIONS: The S3 protocol was feasible in 85% of patients, allows a better identification of targets for ablation, and might improve VT ablation results.

Regional conduction velocities determined by noninvasive mapping are associated with arrhythmia-free survival after atrial fibrillation ablation.

BACKGROUND: Atrial arrhythmogenic substrate is a key determinant of atrial fibrillation (AF) recurrence after pulmonary vein isolation (PVI), and reduced conduction velocities have been linked to adverse outcome. However, a noninvasive method to assess such electrophysiologic substrate is not available to date. OBJECTIVE: This study aimed to noninvasively assess regional conduction velocities and their association with arrhythmia-free survival after PVI. METHODS: A consecutive 52 patients scheduled for AF ablation (PVI only) and 19 healthy controls were prospectively included and received electrocardiographic imaging (ECGi) to noninvasively determine regional atrial conduction velocities in sinus rhythm. A novel ECGi technology obviating the need of additional computed tomography or cardiac magnetic resonance imaging was applied and validated by invasive mapping. RESULTS: Mean ECGi-determined atrial conduction velocities were significantly lower in AF patients than in healthy controls (1.45 ± 0.15 m/s vs 1.64 ± 0.15 m/s; P < .0001). Differences were particularly pronounced in a regional analysis considering only the segment with the lowest average conduction velocity in each patient (0.8 ± 0.22 m/s vs 1.08 ± 0.26 m/s; P < .0001). This average conduction velocity of the "slowest" segment was independently associated with arrhythmia recurrence and better discriminated between PVI responders and nonresponders than previously proposed predictors, including left atrial size and late gadolinium enhancement (magnetic resonance imaging). Patients without slow-conduction areas (mean conduction velocity <0.78 m/s) showed significantly higher 12-month arrhythmia-free survival than those with 1 or more slow-conduction areas (88.9% vs 48.0%; P = .002). CONCLUSION: This is the first study to investigate regional atrial conduction velocities noninvasively. The absence of ECGi-determined slow-conduction areas well discriminates PVI responders from nonresponders. Such noninvasive assessment of electrical arrhythmogenic substrate may guide treatment strategies and be a step toward personalized AF therapy.