Automatic reconstruction of the left atrium activation from sparse intracardiac contact recordings by inverse estimate of fibre structure and anisotropic conduction in a patient-specific model. (4th March 2021)

• Record Type: Journal Article
• Authors: Lubrecht, Jolijn M; Grandits, Thomas; Gharaviri, Ali; Schotten, Ulrich; Pock, Thomas; Plank, Gernot; Krause, Rolf; Auricchio, Angelo; Conte, Giulio; Pezzuto, Simone
• Is Part Of: Europace. Volume 23:Supplement 1(2021)
• Page Start: i63
• Page End: i70
• Publication Date: 2021-03-04
• Subjects: Patient-specific modelling -- Conduction velocity -- Atrial fibres -- Electro-anatomic mapping -- Conductivity tensor; Arrhythmia -- Treatment -- Periodicals; Cardiac pacing -- Periodicals; Catheter ablation -- Periodicals; Heart -- Physiology -- Periodicals; Electrophysiology -- Periodicals; 617.4120645
• DOI: 10.1093/europace/euaa392
• Languages: English
• ISSNs: 1099-5129

Abstract

Abstract: Aims: Electric conduction in the atria is direction-dependent, being faster in fibre direction, and possibly heterogeneous due to structural remodelling. Intracardiac recordings of atrial activation may convey such information, but only with high-quality data. The aim of this study was to apply a patient-specific approach to enable such assessment even when data are scarce, noisy, and incomplete. Methods and results: Contact intracardiac recordings in the left atrium from nine patients who underwent ablation therapy were collected before pulmonary veins isolation and retrospectively included in the study. The Personalized Inverse Eikonal Model from cardiac Electro-Anatomical Maps (PIEMAP), previously developed, has been used to reconstruct the conductivity tensor from sparse recordings of the activation. Regional fibre direction and conduction velocity were estimated from the fitted conductivity tensor and extensively cross-validated by clustered and sparse data removal. Electrical conductivity was successfully reconstructed in all patients. Cross-validation with respect to the measurements was excellent in seven patients (Pearson correlation r > 0.93) and modest in two patients ( r = 0.62 and r = 0.74). Bland–Altman analysis showed a neglectable bias with respect to the measurements and the limit-of-agreement at –22.2 and 23.0 ms. Conduction velocity in the fibre direction was 82 ± 25 cm/s, whereas cross-fibre velocity was 46 ± 7 cm/s. Anisotropic ratio was 1.91±0.16. No significant inter-patient variability was observed. Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps correctly predicted activation times in late regions in all patients ( r = 0.88) and was robust to a sparser dataset ( r = 0.95). Conclusion: Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps offers a novel approach to extrapolate the activation in unmapped regions and to assess conduction properties of the atria. It could be seamlessly integrated into existing electro-anatomic mapping systems. Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps also enables personalization of cardiac electrophysiology models.