Unsupervised k-Mean Classification of Atrial Electrograms From Human Persistent Atrial Fibrillation

Author(s)

Almeida, Tiago P. ; Soriano, Diogo C. ; Li, Xin ; Chu, Gavin S. ; Salinet, Joao L. ; Schlindwein, Fernando S. ; Stafford, Peter J. ; Ng, G. Andre ; Yoneyama, Takashi ; IEEE

• Document type: Journal article
• Source: 2018 COMPUTING IN CARDIOLOGY CONFERENCE (CINC); v. 45, p. 4-pg., 2018-01-01.

Abstract

The dichotomous criterion for atrial electrogram (AEG) classification as proposed by commercial systems (normal/fractionated) to guide ablation has been shown insufficient for persistent atrial fibrillation (persAF) therapy. In this study, we used unsupervised classification to investigate possible sub-groups of persAF AEGs. 3745 bipolar AEGs were collected from 14 persAF patients after pulmonary vein isolation. Automated AEG classification (normal/fractionated) was performed using the CARTO criterion (Biosense Webster). The CARTO attributes (ICL, ACI and SCI) were used to create a 3D space distribution. K-mean with five groups was implemented. Group 1 (43%) represents normal AEGs with low ICL, high ACI and SCI. Groups 2 (9%) and 3 (9%) have shown similar low ICL, but Group 3 has shown AEGs with short activation intervals, as opposed to Group 2. Group 4 (23%) suggests moderated fractionation, with high ACI but low SCI. Group 5 (15%) has shown highly fractionated AEGs with high ICL, low ACI and SCI. The three attributes were significantly different among the five groups (P<0.0001), except ICL between Groups 3 and 4 (P>0.999) and SCI between Groups 3 and 5 (P>0.999). The five sub-groups of AEGs found by the k-mean have shown distinct characteristics, which could provide a more detailed characterization of the atrial substrate during ablation. (AU)

• FAPESP's process: 18/02251-4 - Characterizing persistent atrial fibrillation dynamics using computational models and recurrence quantification analysis - towards novel biomarkers for guiding therapy
• Grantee: Tiago Paggi de Almeida
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• FAPESP's process: 17/00319-8 - Atrial substrate identification in patients with chronic atrial fibrillation using multivariate statistical models and multiple attributes from atrial electrograms
• Grantee: Tiago Paggi de Almeida
• Support Opportunities: Scholarships in Brazil - Post-Doctoral