[Show abstract][Hide abstract] ABSTRACT: The identification of suitable markers for critical patterns during atrial fibrillation (AF) may be crucial to guide an effective ablation treatment. Single parameter maps, based on dominant frequency and complex fractionated electrograms, have been proposed as a tool for electrogram-guided ablation, however the specificity of these markers is debated. Experimental studies suggest that AF critical patterns may be identified on the basis of specific rate and organization features, where rapid organized and rapid fragmented activities characterize respectively localized sources and critical substrates. In this paper we introduce the logical operator map, a novel mapping tool for a point-by-point identification and localization of AF critical sites. Based on advanced signal and image processing techniques, the approach combines in a single map electrogram-derived rate and organization features with tomographic anatomical detail. The construction of the anatomically-detailed logical operator map is based on the time-domain estimation of atrial rate and organization in terms of cycle length and wave-similarity, the logical combination of these indexes to obtain suitable markers of critical sites, and the multimodal integration of electrophysiological and anatomical information by segmentation and registration techniques. Logical operator maps were constructed in 14 patients with persistent AF, showing the capability of the combined rate and organization markers to identify with high selectivity the subset of electrograms associated with localized sources and critical substrates. The precise anatomical localization of these critical sites revealed the confinement of rapid organized sources in the left atrium with organization and rate gradients towards the surrounding tissue, and the presence of rapid fragmented electrograms in proximity of the sources. By merging in a single map the most relevant electrophysiological and anatomical features of the AF process, the logical operator map may have significant clinical impact as a direct, comprehensive tool to understand arrhythmia mechanisms in the single patient and guide more conservative, step-wise ablation.
Progress in Biophysics and Molecular Biology 07/2014; · 3.38 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Atrial fibrillation (AF) is the most common complication of cardiac surgery interventions. Several mechanisms are involved in the occurrence of this complex arrhythmia, which include electrical and structural remodeling. In particular, it has been shown that atrial fibrosis, which consists in the massive accumulation of the extracellular matrix (ECM) components between cardiomyocytes, may interfere with the electrical impulse propagation creating a substrate for AF. As well, microRNAs (miRNAs), a broad class of small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level, have been recently indicated as regulators of diverse cardiovascular functions, which may potentially affect arrhythmia occurrence. This study investigates the molecular and structural features of atrial tissue biopsies obtained from patients undergoing cardiac surgery, aiming to identify potential correlations with the occurrence of AF. Specifically, the total RNA was extracted from small biopsies of the right atrial appendage, and the expression of a set of miRNAs, known to regulate structural proteins / ion channels, was evaluated by qRT-PCR. Concurrently, the total collagen content was assessed by applying histological techniques and polarized microscopy to Picro Sirius Red stained tissue slices. The analysis revealed specific profiles of fibrosis-related microRNAs and intramural fibrosis distribution in AF patients, suggesting the potential role of post-transcriptional regulation mechanisms in the creation of a pro-arrhythmic substrate.
SIBBM 2014 - Frontiers in Molecular Biology; "Emerging Arenas in Molecular Biology: from basic mechanisms to personalized medicine", Trento - Italy; 06/2014
[Show abstract][Hide abstract] ABSTRACT: This article discusses the latest development in computational mapping for the identification and localization of critical sources in patients with atrial fibrillation (AF). It focuses on the contribution of electrogram-derived anatomical maps, obtained by applying innovative signal and image processing methodologies, to the investigation of the mechanisms underlying the arrhythmia and to the planning of new target ablation strategies. Reviewed are the experimental studies which allowed to infer the peculiar rate and regularity features of critical sources, the signal processing methods for the quantification of these parameters from atrial electrograms, and the clinical studies mapping rate and organization in AF patients. Finally, we present a novel methodological framework, based on the construction of the logic operation map, designed to merge in a single map the most relevant electrophysiological and anatomical features of the AF process, which may guide the selective identification of critical sources.
[Show abstract][Hide abstract] ABSTRACT: The mechanisms underlying the onset of postoperative atrial fibrillation (POAF) are still poorly understood. Enhanced atrial automaticity and alterations in autonomic tone following surgery have been suggested as critical predisposing factors. This paper proposes an unified framework for the combined analysis of ectopic activity and autonomic function preceding POAF. Atrial intervals series were automatically extracted from long-term atrial signal recordings in postoperative patients, and processed with an adaptive filter to separate normal from abnormal beats. Normal intervals were addressed to classical frequency-domain heart rate variability analysis, while ectopic beats were further processed to characterize their occurrence, coupling interval distribution and type. Preliminary application of the analysis showed concurrent changes in autonomic function and ectopic activity in the three hours preceding POAF onset. These results suggest the potential of the combined analysis to disclose interaction patterns between autonomic tone and automaticity leading to the onset of post-operative arrhythmias.
2014 8th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO); 05/2014
[Show abstract][Hide abstract] ABSTRACT: Experimental and clinical evidence suggests the role of fibrosis in the formation of a pro-arrhythmic substrate for atrial fibrillation (AF). This work presents a simulation model to investigate the interactions between excitation wavefronts and fibrosis. The Courtemanche-Ramirez-Nattel model of the human atrial potential was implemented on a sphere monolayer, and fibrosis was included replacing mesh nodes with non-excitable elements with no-flux boundary conditions. A stochastic algorithm was used to generate spatial patterns of fibrosis with specific density, patch dimension and orientation. Simulations run at different model parameters showed that the presence and spatial pattern of fibrosis could significantly alter the dynamics of propagating wavefronts, favoring the occurrence of reentrant activity and self-sustained propagation. Combined with more realistic atrial geometry, this simulation model may help to clarify the determinants of AF multifactorial substrate.
2014 8th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO); 05/2014
[Show abstract][Hide abstract] ABSTRACT: IntroductionAlthough atrial arrhythmias may have genetic causes, very few data are available on evaluation of the arrhythmic substrate in genetic atrial diseases in humans. In the present study, we evaluate the nature and evolution of the atrial arrhythmic substrate in a genetic atrial cardiomyopathy.Methods and ResultsRepeated electroanatomic mapping and tomographic evaluations were used to investigate the evolving arrhythmic substrate in 5 patients with isolated arrhythmogenic atrial cardiomyopathy, caused by Natriuretic Peptide Precursor A (NPPA) gene mutation. Atrial fibrosis was assessed using late gadolinium enhancement magnetic resonance imaging (LGE-MRI). The substrate of atrial tachycardia (AT) and atrial fibrillation (AF) was bi-atrial dilatation with patchy areas of low voltage and atrial wall scarring (in the right atrium: 68.5±6.0% and 22.2±10.2%, respectively). The evolution of the arrhythmic patterns to sinus node disease with atrial standstill (AS) was associated with giant atria with extensive low voltage and atrial scarring areas (in the right atrium: 99.5±0.7% and 57.5±33.2%, respectively). LGE-MRI-proven bi-atrial fibrosis (Utah stage IV) was associated with AS. Atrial conduction was slow and heterogeneous, with lines of conduction blocks. The progressive extension and spatial distribution of the scarring/fibrosis were strictly associated with the different types of arrhythmias.Conclusion
The evolution of the amount and distribution of atrial scarring/fibrosis constitutes the structural substrate for the different types of atrial arrhythmias in a pure genetic model of arrhythmogenic atrial cardiomyopathy.This article is protected by copyright. All rights reserved.
Journal of Cardiovascular Electrophysiology 04/2014; 25(9). · 3.48 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Despite the growing interest in cardiac miRNA expression profiling, having high quality and yield in RNA extraction from cardiac tissue is still challenging. We compared different methods of tissue homogenization and total RNA extraction from pig cardiac tissue aimed at miRNAs expression profiling. Small biopsies of right atrial appendages were obtained from pig hearts and treated according to four different protocols: no homogenization (P1) and homogenization by manual (P2) or automatic (P3 and P4) methods, followed by Proteinase K digestion (PKD) except in P4. Total RNA was extracted using miRNeasy mini kit, assessing
RNA yield and quality by Nanodrop. cDNA synthesis and qRT-PCR were performed using TaqMan MicroRNA Assay. Homogenization was crucial to obtain high yield of pure total RNA. Automatic methods displayed higher yield (0.27 μg RNA/mg tissue in P3) than manual (0.06 μg RNA/mg tissue in P2), with better performance without PKD step (0.38μg RNA/mg tissue in P4). RNA from P4 was suitable for miRNA expression profiling, as demonstrated by qRT-PCR on miRNA 21 and 29.
These results suggest the efficacy of an automatic homogenization to extract RNA suitable for miRNA expression profiling.
9th European Biophysics Congress, Lisbon, Portugal 13-17 July 2013; 07/2013
[Show abstract][Hide abstract] ABSTRACT: Biophysically-detailed and anatomically-realistic atrial models are emerging as a valuable tool in the study of atrial arrhythmias, nevertheless clinical use of these models would be favored by a reduction of computational times. This paper introduces a novel adaptive mesh algorithm, based on multiresolution representation (MR), for the efficient integration of cardiac ODE-PDE systems on unstructured triangle meshes. The algorithm applies a dynamically-adapted node-centered FVM scheme for integration of diffusion. The method accuracy and efficiency were evaluated by simulating propagation scenarios of increasing complexity levels (pacing, stable spirals, atrial fibrillation) on tomography-derived 3D monolayer atrial models, based on a monodomain reaction-diffusion formulation coupled with the Courtemanche atrial ionic model. All simulated propagation patterns were accurately reproduced with substantially reduced computational times (10 - 30% of the fullresolution simulation time). The proposed algorithm, combining the MR computational efficiency with the geometrical flexibility of unstructured meshes, may favor the development of patientspecific multiscale models of atrial arrhythmias and their application in the clinical setting.
IEEE transactions on bio-medical engineering 05/2013; · 2.15 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: BACKGROUND: -Atrial dilatation and atrial standstill are etiologically heterogeneous phenotypes with poorly defined nosology. In 1983 we described 8-years follow-up of idiopathic atrial dilatation with standstill evolution in 8 patients from 3 families. We later identified 5 additional patients with identical phenotypes: 1 member of the largest original family and 4 unrelated to the 3 original families. All families are from a same geographic area in the North-East Italy. METHODS AND RESULTS: -We followed-up the 13 patients for up to 37 years, extended the clinical investigation and monitoring to living relatives and investigated the genetic basis of the disease. The disease was characterized by: 1) clinical onset in adulthood; 2) bi-atrial dilatation up to giant size; 3) early supraventricular arrhythmias with progressive loss of atrial electrical activity to atrial standstill; 4) thromboembolic complications; 5) stable, normal left ventricular function and NYHA functional class during the long-term course of the disease. By linkage analysis we mapped a locus at 1p36.22 containing the natriuretic precursor A (NPPA) gene. By sequencing NPPA we identified a homozygous missense mutation (p.Arg150Gln) in all living affected individuals of the 6 families. All patients showed low serum levels of Atrial Natriuretic Peptide (ANP). Heterozygous mutation carriers were healthy and demonstrated normal levels of ANP. CONCLUSIONS: -Autosomal recessive Atrial Dilated Cardiomyopathy is a rare disease associated with homozygous mutation of the NPPA gene and characterized by extreme atrial dilatation with standstill evolution, thromboembolic risk, preserved left ventricular function and severely decreased levels of ANP.
[Show abstract][Hide abstract] ABSTRACT: The aim of this study was to investigate the anatomic distribution of critical sources in patients with atrial fibrillation (AF) by fusion of biatrial computed tomography (CT) images with cycle length (CL) and wave similarity (WS) maps.
Experimental and clinical studies show that atrial fibrillation (AF) may originate from rapid and repetitive (RR) sources of activation. Localization of RR sources may be crucial for an effective ablation treatment. Atrial electrograms showing rapid and repetitive activations can be identified by combining WS and CL analysis.
Patients with persistent AF underwent biatrial electroanatomic mapping and pre-procedural CT cardiac imaging. WS and CL maps were constructed in 17 patients by calculating the degree of repetitiveness of activation waveforms (similarity index [S]) and the cycle length at each atrial site. WS/CL maps were then integrated with biatrial 3-dimensional CT reconstructions by a stochastic approach.
Repetitive sources of activation (S ≥0.5) were present in most patients with persistent AF (94%) and were mainly located at the pulmonary veins (82% of patients), at the superior caval vein (41%), on the anterior wall of the right atrium (23%), and at the left atrial appendage (23%). Potential driver sources showing both rapid and repetitive activations (CL = 140.7 ± 25.1 ms, S = 0.65 ± 0.15) were present only in a subset of patients (65%) and were confined to the pulmonary vein region (47% of patients) and left atrial appendage (12%). Differently, the repetitive activity of the superior caval vein was characterized by a slow activation rate (CL = 184.7 ± 14.6 ms).
The identification and localization of RR sources is feasible by fusion of biatrial anatomic images with WS/CL maps. Potential driver sources are present only in a subset of patients with persistent AF and are mainly located in the pulmonary vein region.
[Show abstract][Hide abstract] ABSTRACT: In this study, sparse modeling is introduced for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence function, derived from fitting a multivariate autoregressive model to the observed signal using least-squares (LS) estimation. The propagation pattern analysis incorporates prior information on sparse coupling as well as the distance between the recording sites. Two optimization methods are employed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO), and a novel method named the distance-adaptive group LASSO (dLASSO). Using simulated data, both optimization methods were superior to LS estimation with respect to detection and estimation performance. The normalized error between the true and estimated model parameters dropped from 0.20 ± 0.04 for LS estimation to 0.03 ± 0.01 for both aLASSO and dLASSO when the number of available data samples exceeded the number of model parameters by a factor of 5. For shorter data segments, the error reduction was more pronounced and information on the distance gained in importance. Propagation pattern analysis was also studied on intracardiac AF data, the results showing that the identification of propagation patterns is substantially simplified by the sparsity assumption.
[Show abstract][Hide abstract] ABSTRACT: The genesis of complex ventricular rhythms during atrial tachyarrhythmias in humans is not fully understood. To clarify the dynamics of atrioventricular (AV) conduction in response to a regular high-rate atrial activation, 29 episodes of spontaneous or pacing-induced atrial flutter (AFL), covering a wide range of atrial rates (cycle lengths from 145 to 270 ms), were analyzed in 10 patients. AV patterns were identified by applying firing sequence and surrogate data analysis to atrial and ventricular activation series, whereas modular simulation with a difference-equation AV node model was used to correlate the patterns with specific nodal properties. AV node response at high atrial rate was characterized by 1) AV patterns of decreasing conduction ratios at the shortening of atrial cycle length (from 236.3 ± 32.4 to 172.6 ± 17.8 ms) according to a Farey sequence ordering (conduction ratio from 0.34 ± 0.12 to 0.23 ± 0.06; P < 0.01); 2) the appearance of high-order alternating Wenckebach rhythms, such as 6:2, 10:2, and 12:2, associated with ventricular interval oscillations of large amplitude (407.7 ± 150.4 ms); and 3) the deterioration of pattern stability at advanced levels of block, with the percentage of stable patterns decreasing from 64.3 ± 35.2% to 28.3 ± 34.5% (P < 0.01). Simulations suggested these patterns to originate from the combined effect of nodal recovery, dual pathway physiology, and concealed conduction. These results indicate that intrinsic nodal properties may account for the wide spectrum of AV block patterns occurring during regular atrial tachyarrhythmias. The characterization of AV nodal function during different AFL forms constitutes an intermediate step toward the understanding of complex ventricular rhythms during atrial fibrillation.
[Show abstract][Hide abstract] ABSTRACT: The localization of atrial fibrillation (AF) driver sources, characterized by rapid and regular electrical activity, is crucial for an effective ablation treatment. This work proposes a double-criteria approach for the identification of AF drivers based on a time-domain evaluation of atrial rate and AF organization. These two features are quantified by the measurement of atrial cycle length (ACL) and wave-similarity (WS). Based on ACL/WS formalism, AF drivers can be operatively defined as sites displaying electrical activity with high-rate and high-similarity (HR AND HS). The capability of ACL/WS analysis to identify AF driver sites and distinguish them from non-critical areas is shown in representative examples. The double-criteria evaluation for the identification of AF drivers, provided by our time-domain approach, might open new perspectives for the development of electrogram-guided ablation strategies in the single patient.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:5527-30.
[Show abstract][Hide abstract] ABSTRACT: The present study introduces sparse modeling for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence (PDC) function, derived from fitting a multivariate autoregressive model to the observed signals. A sparse optimization method is proposed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO). In simulations aLASSO was found superior to the commonly used least-squares (LS) estimation with respect to estimation performance. The normalized error between the true and estimated model parameters dropped from 0.20 ± 0.04 for LS estimation to 0.03 ± 0.01 for aLASSO when the number of available data samples exceeded the number of model parameters by a factor of 5. The error reduction was more pronounced for short data segments. Propagation patterns were also studied on intracardiac AF data, the results showing that the identification of propagation patterns is substantially simplified by the sparsity assumption.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:5535-8.