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Medical Image Analysis
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Medical Image Analysis
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A rule-based method for predicting the electrical activation of the heart with cardiac resynchronization therapy from non-invasive clinical data

Authors: Kevin Vernooy; Steven A. Niederer; Jonathan M. Behar; Orod Razeghi; Baldeep S. Sidhu; Benjamin Sieniewicz; Angela W.C. Lee; +6 Authors

A rule-based method for predicting the electrical activation of the heart with cardiac resynchronization therapy from non-invasive clinical data

Abstract

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.Patient specific computational models allow the activation pattern following CRT implant to be predicted and this may be used to optimize CRT lead placement.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.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 ± 0.5 mm (CMR data) or (CT data) 7.5 ± 0.7 mm.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.

Keywords

Epicardial Mapping, VENTRICULAR LEAD PLACEMENT, PACING SITE, Radboud University Medical Center, DIFFUSION TENSOR MRI, Magnetic Resonance Imaging, Cine, Article, Cardiac Resynchronization Therapy, Electrocardiography, Radboudumc 16: Vascular damage RIHS: Radboud Institute for Health Sciences, FIBER ARCHITECTURE, Heart Conduction System, Predictive Value of Tests, TRABECULAR MUSCLE, Image Interpretation, Computer-Assisted, Computational models, Humans, OPTIMIZATION, Cardiology - Radboud University Medical Center, Heart Failure, Cardiac resynchronization therapy, HISTOLOGICAL VALIDATION, Patient-specific simulations, Electrophysiology, MODEL, QRS DURATION, Electrophysiologic Techniques, Cardiac, Tomography, X-Ray Computed, CONDUCTION-VELOCITY

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
39
Top 10%
Top 10%
Top 10%
Green
hybrid