A rule-based method for predicting the electrical activation of the heart with cardiac resynchronization therapy from non-invasive clinical data.
Med Image Anal
; 57: 197-213, 2019 10.
Article
em En
| MEDLINE
| ID: mdl-31326854
ABSTRACT
BACKGROUND:
Cardiac Resynchronization Therapy (CRT) is one of the few effective treatments for heart failure patients with ventricular dyssynchrony. The pacing location of the left ventricle is indicated as a determinant of CRT outcome.OBJECTIVE:
Patient specific computational models allow the activation pattern following CRT implant to be predicted and this may be used to optimize CRT lead placement.METHODS:
In this study, the effects of heterogeneous cardiac substrate (scar, fast endocardial conduction, slow septal conduction, functional block) on accurately predicting the electrical activation of the LV epicardium were tested to determine the minimal detail required to create a rule based model of cardiac electrophysiology. Non-invasive clinical data (CT or CMR images and 12 lead ECG) from eighteen patients from two centers were used to investigate the models.RESULTS:
Validation with invasive electro-anatomical mapping data identified that computer models with fast endocardial conduction were able to predict the electrical activation with a mean distance errors of 9.2⯱â¯0.5â¯mm (CMR data) or (CT data) 7.5⯱â¯0.7â¯mm.CONCLUSION:
This study identified a simple rule-based fast endocardial conduction model, built using non-invasive clinical data that can be used to rapidly and robustly predict the electrical activation of the heart. Pre-procedural prediction of the latest electrically activating region to identify the optimal LV pacing site could potentially be a useful clinical planning tool for CRT procedures.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Interpretação de Imagem Assistida por Computador
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Tomografia Computadorizada por Raios X
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Imagem Cinética por Ressonância Magnética
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Técnicas Eletrofisiológicas Cardíacas
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Terapia de Ressincronização Cardíaca
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Sistema de Condução Cardíaco
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Insuficiência Cardíaca
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Revista:
Med Image Anal
Ano de publicação:
2019
Tipo de documento:
Article