0000000000276868
AUTHOR
Jose J. Rieta
Reliable Paroxysmal Atrial Fibrillation Substrate Assessment During Sinus Rhythm Through Optimal Estimation of Local Activation Waves Dynamics
[EN] The analysis of coronary sinus (CS) electrograms (EGMs) during catheter ablation (CA) of atrial fibrillation (AF) is highly important for AF substrate evaluation. However, channels of the CS catheter may be affected by vigorous cardiac movement and bad contact. This work investigates the most reliable channels in preserving the AF dynamics during sinus rhythm (SR). Local activation waves (LAWs) were detected in 44 bipolar CS recordings of 60-300 seconds duration in 28 paroxysmal AF patients undergoing CA. Recordings consisted of five channels: distal, mid-distal, medial, mid-proximal and proximal. LAW duration, amplitude, area and correlation between dominant morphologies of each chann…
Atrial activity extraction for atrial fibrillation analysis using blind source separation.
This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA …
Bioelectric model of atrial fibrillation: Applicability of blind source separation techniques for atrial activity estimation in atrial fibrillation episodes
In this contribution, we present the theoretical justification that give support to the suitability of blind signal separation (BSS) techniques for the estimation of the atrial activity (AA) present in ECGs of persistent atrial fibrillation (AF). The application of BSS methods to this problem needs the fulfillment of several conditions regarding AA, ventricular activity (VA) and the fashion in which both activities arise on the body surface, that will be justified along the paper. To empirically validate the model, an ICA method is applied to 10 real 12-lead recordings of AF. The identification of AA is put forward based on kurtosis and spectral analysis. The kurtosis value of the estimated…
Comparative analysis in terms of computational cost for different discrimination algorithms in implantable defibrillators
Implantable defibrillators (ICDs) use very low computational cost criteria (rate, stability and onset) offering good sensitivity for arrhythmia detection. Although, the specificity of these combined criteria decreases in difficult arrhythmia discrimination as in case of discrimination between ventricular tachycardia (VT) and supraventricular tachycardia (SVT). Several morphological published algorithms enhance arrhythmia discrimination but most algorithms are developed in personal computers and cannot be used in ICDs because of computational cost requirements compared with limited ICD capabilities. A general method to determine the possibility of ICD implementation for a discrimination algo…
Assisting Electrophysiological Substrate Quantification in Atrial Fibrillation Ablation
[EN] Catheter ablation (CA) is the most popular treatment of atrial fibrillation (AF) with good results in paroxysmal AF, while its efficiency is significantly reduced in persistent AF. With the equipment used for CA strongly depending on electro-gram (EGM) fractionation quantification, the use of a reliable fractionation estimator is crucial to reduce the high recurrence rates in persistent AF. This work introduces a non-linear EGM fractionation quantification technique, which is based on coarse-grained correlation dimension (CGCD) computed over epochs of 1 second. Recordings were firstly normalized, denoised and lowpass filtered. The final CGCD value was calculated by the median CGCD valu…
Automatic segmentation and 3D reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies.
Abstract Intravascular ultrasound (IVUS) imaging is used along with X-ray coronary angiography to detect vessel pathologies. Manual analysis of IVUS images is slow and time-consuming and it is not feasible for clinical purposes. A semi-automated method is proposed to generate 3D reconstructions from IVUS video sequences, so that a fast diagnose can be easily done, quantifying plaque length and severity as well as plaque volume of the vessels under study. The methodology described in this work has four steps: a pre-processing of IVUS images, a segmentation of media–adventitia contour, a detection of intima and plaque and a 3D reconstruction of the vessel. Preprocessing is intended to remove …
Reliability of Local Activation Waves Features to Characterize Paroxysmal Atrial Fibrillation Substrate During Sinus Rhythm
[EN] Analysis of coronary sinus (CS) electrograms (EGMs) is vastly used for the assessment of the atrial fibrillation (AF) substrate. As a catheter consists of five dipoles (distal, mid-distal, medial, mid-proximal, proximal), results may vary upon the employed channel: myocardial contraction and bad contact are unavoidable factors affecting the recording. This work aims to specify the most reliable channels in catching AF dynamics, using 44 multichannel bipolar CS recordings in sinus rhythm (SR) of paroxysmal AF with 1-5 minutes duration. Local activation waves (LAWs) were detected and main features obtained: duration, amplitude, area and correlation between dominant morphologies of each c…