Unsupervised Classification of Atrial Electrograms for Electroanatomic Mapping of Human Persistent Atrial Fibrillation

Autor(es):Mostrar menos -

Almeida, Tiago P. ^{[1, 2, 3]} ; Soriano, Diogo C. ^[4] ; Mase, Michela ^{[5, 6]} ; Ravelli, Flavia ^[7] ; Bezerra, Arthur S. ^[8] ; Li, Xin ^{[9, 3]} ; Chu, Gavin S. ^{[9, 10]} ; Salinet, Joao ^[4] ; Stafford, Peter J. ^[10] ; Ng, G. Andre ^{[9, 10, 11]} ; Schlindwein, Fernando S. ^{[3, 11]} ; Yoneyama, Takashi ^[8]

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^[1] Aeronaut Inst Technol, BR-12228900 Sao Jose Dos Campos, SP - Brazil

^[2] Univ Leicester, Glenfield Hosp, Dept Cardiovasc Sci, Leicester LE3 90P, Leics - England

^[3] Univ Leicester, Sch Engn, Leicester LE1 7RH, Leics - England

^[4] Fed Univ ABC, Santo Andre, SP - Brazil

^[5] Univ Trento, Bruno Kessler Fdn FBK, Healthcare Res & Innovat Program, IRCS HTA, Trento, TN - Italy

^[6] Eurac Res, Inst Mt Emergency Med, Bolzano - Italy

^[7] Univ Trento, Trento, TN - Italy

^[8] Aeronaut Inst Technol, Tokyo - Japan

^[9] Univ Leicester, Dept Cardiovasc Sci, Leicester, Leics - England

^[10] Univ Hosp Leicester NHS Trust, Leicester, Leics - England

^[11] Glenfield Hosp, Leicester Cardiovasc Biomed Res Ctr, Natl Inst Hlth Res, Leicester, Leics - England

• Tipo de documento: Artigo Científico
• Fonte: IEEE Transactions on Biomedical Engineering; v. 68, n. 4, p. 1131-1141, APR 2021.
• Citações Web of Science: 1

Resumo

Objective: Ablation treatment for persistent atrial fibrillation (persAF) remains challenging due to the absence of a `ground truth' for atrial substrate characterization and the presence of multiple mechanisms driving the arrhythmia. We implemented an unsupervised classification to identify clusters of atrial electrograms (AEGs) with similar patterns, which were then validated by AEG-derived markers. Methods: 956 bipolar AEGs were collected from 11 persAF patients. CARTO variables (Biosense Webster; ICL, ACI and SCI) were used to create a 3D space, and subsequently used to perform an unsupervised classification with k-means. The characteristics of the identified groups were investigated using nine AEG-derived markers: sample entropy (SampEn), dominant frequency, organization index (OI), determinism, laminarity, recurrence rate (RR), peak-to-peak (PP) amplitude, cycle length (CL), and wave similarity (WS). Results: Five AEG classes with distinct characteristics were identified (F = 582, P<0.0001). The presence of fractionation increased from class 1 to 5, as reflected by the nine markers. Class 1 (25%) included organized AEGs with high WS, determinism, laminarity, and RR, and low SampEn. Class 5 (20%) comprised fractionated AEGs with in low WS, OI, determinism, laminarity, and RR, and in high SampEn. Classes 2 (12%), 3 (13%) and 4 (30%) suggested different degrees of AEG organization. Conclusions: Our results expand and reinterpret the criteria used for automated AEG classification. The nine markers highlighted electrophysiological differences among the five classes found by the k-means, which could provide a more complete characterization of persAF substrate during ablation target identification in future clinical studies. (AU)

• Processo FAPESP: 18/02251-4 - Estudo da dinâmica da fibrilação atrial crônica utilizando modelos computacionais e análise de quantificação de recorrência
• Beneficiário: Tiago Paggi de Almeida
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Pós-Doutorado
• Processo FAPESP: 15/12799-9 - 42th annual scientific meeting of Computing in Cardiology
• Beneficiário: João Loures Salinet Júnior
• Modalidade de apoio: Auxílio à Pesquisa - Reunião - Exterior
• Processo FAPESP: 17/00319-8 - Identificação do substrato atrial em pacientes com fibrilação atrial crônica utilizando modelos estatísticos multivariados e múltiplos atributos de eletrogramas atriais
• Beneficiário: Tiago Paggi de Almeida
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 19/05192-1 - Classificação multivariável do substrato atrial durante fibrilação atrial crônica
• Beneficiário: Arthur Santos Bezerra
• Modalidade de apoio: Bolsas no Brasil - Mestrado