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BACKGROUND: Heart rate turbulence (HRT) is associated with risk in chronic heart failure (CHF). The objective of this study was to assess the short-term variability of HRT and to compare the diagnostic yield of 7-day (7DH) versus 24-hour (1DH) Holter monitoring for calculating HRT in a CHF population. METHODS AND RESULTS: Forty-nine consecutive patients with CHF were studied. At inclusion, 7DH was performed to evaluate the variability of HRT parameters. For categorized analyses, turbulence onset (TO) >=0% and turbulence slope (TS) <=2.5 ms/RR were defined as abnormal, and patients were classified into subgroups based on the number of abnormal HRT parameters.The cumulative percentage of patients with calculable HRT increased from 69.4% with 1DH to 93.9% with 7DH. The intraclass correlation coefficients across the 7-day monitoring were 0.81 (95% confidence interval [CI] 0.70-0.89) for TO and 0.90 (95% CI 0.84-0.95) for TS. When comparing 2 randomly selected days, TO and TS values were similar (P > .1) and showed a strong correlation (TO: r = 0.79; TS: r = 0.84: P < .001). Bland-Altman plots showed a mean difference of 0.31% (95% CI -0.07 to 0.70) for TO and 0.44 ms/RR (95% CI -1.37 to 0.48) for TS. In contrast, categorized analyses showed that up to 16% of patients changed their HRT subgroup score from day 1 to day 2 of comparison. CONCLUSIONS: In this population, 7DH significantly increased the percentage of patients with calculable HRT parameters. The short-term variability of the quantitative HRT values was good, but when patients were categorized into the established HRT subgroups, the concordance was suboptimal. [ABSTRACT FROM AUTHOR]

Abstract The tilt test is a valuable clinical tool for vasovagal syncope (VVS) diagnostic, and its early prediction from simple ECG and blood pressure-based parameters has widely been studied in the literature. However, no practical system is currently used in the clinical setting for the early prediction of the tilt test outcome. The objectives of this study were (1) to benchmark the early prediction performance of all the previously proposed parameters, when nonlinearly combined; (2) to try to improve this performance with the inclusion of additional information and processing techniques. We analyzed a database of 727 consecutive cases of tilt test. Previously proposed features were measured from heart rate and systolic/diastolic pressure tachograms, in several representative signal segments. We aimed to improve the prediction performance: first, using new nonlinear features (detrended fluctuation analysis and sample entropy); second, using a multivariable nonlinear classifier (support vector machine); and finally, including additional physiological signals (stroke volume). The predictive performance of the nonlinearly combined previously proposed features was limited [area under receiver operating characteristic curve (ROC) 0.57 ± 0.12], especially at the beginning of the test, which is the most clinically relevant period. The improvement with additional available physiological information was limited too. We conclude that the use of a system for tilt test outcome prediction with current knowledge and processing should be considered with caution, and that further effort has to be devoted to understand the mechanisms of VVS.

Electrocardiographic Imaging (ECGI) aims to estimate the intracardiac potentials noninvasively, hence allowing the clinicians to better visualize and understand many arrhythmia mechanisms. Most of the estimators of epicardial potentials use a signal model based on an estimated spatial transfer matrix together with Tikhonov regularization techniques, which works well specially in simulations, but it can give limited accuracy in some real data. Based on the quasielectrostatic potential superposition principle, we propose a simple signal model that supports the implementation of principled out-of-sample algorithms for several of the most widely used regularization criteria in ECGI problems, hence improving the generalization capabilities of several of the current estimation methods. Experiments on simple cases (cylindrical and Gaussian shapes scrutinizing fast and slow changes, respectively) and on real data (examples of torso tank measurements available from Utah University, and an animal torso and epicardium measurements available from Maastricht University, both in the EDGAR public repository) show that the superposition-based out-of-sample tuning of regularization parameters promotes stabilized estimation errors of the unknown source potentials, while slightly increasing the re-estimation error on the measured data, as natural in non-overfitted solutions. The superposition signal model can be used for designing adequate out-of-sample tuning of Tikhonov regularization techniques, and it can be taken into account when using other regularization techniques in current commercial systems and research toolboxes on ECGI.

Introduction: Spatial and temporal processing of intracardiac electrograms provides relevant information to support the arrhythmia ablation during electrophysiological studies. Current cardiac navigation systems (CNS) and electrocardiographic imaging (ECGI) build detailed 3-D electroanatomical maps (EAM), which represent the spatial anatomical distribution of bioelectrical features, such as activation time or voltage., Objective: We present a principled methodology for spectral analysis of both EAM geometry and bioelectrical feature in CNS or ECGI, including their spectral representation, cutoff frequency, or spatial sampling rate (SSR)., Methods: Existing manifold harmonic techniques for spectral mesh analysis are adapted to account for a fourth dimension, corresponding to the EAM bioelectrical feature. Appropriate scaling is required to address different magnitudes and units., Results: With our approach, simulated and real EAM showed strong SSR dependence on both the arrhythmia mechanism and the cardiac anatomical shape. For instance, high frequencies increased significantly the SSR because of the "early-meets-late" in flutter EAM, compared with the sinus rhythm. Besides, higher frequency components were obtained for the left atrium (more complex anatomy) than for the right atrium in sinus rhythm., Conclusion: The proposed manifold harmonics methodology opens the field toward new signal processing tools for principled EAM spatiofeature analysis in CNS and ECGI, and to an improved knowledge on arrhythmia mechanisms.

Objective: Heart rate turbulence (HRT) has been successfully explored for cardiac risk stratification. While HRT is known to be influenced by the heart rate (HR) and the coupling interval (CI), nonconcordant results have been reported on how the CI influences HRT. The purpose of this study is to investigate HRT changes in terms of CI and HR by means of an especially designed protocol., Methods: A dataset was acquired from 11 patients with structurally normal hearts for which CI was altered by different pacing trains and HR by isoproterenol during electrophysiological study (EPS). The protocol was designed so that, first, the effect of HR changes on HRT and, second, the combined effect of HR and CI could be explored. As a complement to the EPS dataset, a database of 24-h Holters from 61 acute myocardial infarction (AMI) patients was studied for the purpose of assessing risk. Data analysis was performed by using different nonlinear ridge regression models, and the relevance of model variables was assessed using resampling methods. The EPS subjects, with and without isoproterenol, were analyzed separately., Results: The proposed nonlinear regression models were found to account for the influence of HR and CI on HRT, both in patients undergoing EPS without isoproterenol and in low-risk AMI patients, whereas this influence was absent in high-risk AMI patients. Moreover, model coefficients related to CI were not statistically significant, p > 0.05, on EPS subjects with isoproterenol., Conclusion: The observed relationship between CI and HRT, being in agreement with the baroreflex hypothesis, was statistically significant ( ), when decoupling the effect of HR and normalizing the CI by the HR., Significance: The results of this study can help to provide new risk indicators that take into account physiological influence on HRT, as well as to model how this influence changes in different cardiac conditions.

The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, little effort has been invested toward feature selection and the features' corresponding medical interpretation. In this study, we focus on the task of early detection of anastomosis leakage (AL), a severe complication after elective surgery for colorectal cancer (CRC) surgery, using free text extracted from EHRs. We use a bag-of-words model to investigate the potential for feature selection strategies. The purpose is earlier detection of AL and prediction of AL with data generated in the EHR before the actual complication occur. Due to the high dimensionality of the data, we derive feature selection strategies using the robust support vector machine linear maximum margin classifier, by investigating: 1) a simple statistical criterion (leave-one-out-based test); 2) an intensive-computation statistical criterion (Bootstrap resampling); and 3) an advanced statistical criterion (kernel entropy). Results reveal a discriminatory power for early detection of complications after CRC (sensitivity 100%; specificity 72%). These results can be used to develop prediction models, based on EHR data, that can support surgeons and patients in the preoperative decision making phase.

Dominant frequency analysis (DFA) and organization analysis (OA) of cardiac electrograms (EGMs) aims to establish clinical targets for cardiac arrhythmia ablation. However, these previous spectral descriptions of the EGM have often discarded relevant information in the spectrum, such as the harmonic structure or the spectral envelope. We propose a fully automated algorithm for estimating the spectral features in EGM recordings. This approach, called Fourier OA (FOA), accounts jointly for the organization and periodicity in the EGM, in terms of the fundamental frequency instead of dominant frequency. In order to compare the performance of FOA and DFA-OA approaches, we analyzed simulated EGM, obtained in a computer model, as well as two databases of implantable defibrillator-stored EGM. FOA parameters improved the organization measurements with respect to OA, and averaged cycle length and regularity indexes were more accurate when related to the fundamental (instead of dominant) frequency, as estimated by the algorithm (p < 0.05 comparing f(0) estimated by DFA and by FOA). FOA yields a more detailed and robust spectral description of EGM compared to DFA and OA parameters.

The purpose of this study was to compare the diagnostic sensitivity of 1-day Holter monitoring versus 7-day Holter monitoring (7DH) to detect atrial and ventricular arrhythmias in a population of stable patients with chronic heart failure and left ventricular dysfunction. Sixty-three consecutive stable patients with chronic heart failure with left ventricular ejection fractions < or =50% were included. Blood samples were obtained, the Minnesota Living With Heart Failure Questionnaire was administered, and echocardiography, 6-minute walk tests, and 7DH were performed at enrollment. The mean ejection fraction was 35.8 +/- 9.8%, and the mean age was 55.5 +/- 13.9 years. Seven-day Holter monitoring did not significantly increase the detection of nonsustained atrial tachycardia or atrial fibrillation. In contrast, the incidence of nonsustained ventricular tachycardia increased in nonischemic patients from 35.1% on day 1 to 54.1% on day 7 (p = 0.01). In ischemic patients, the sensitivity increased from 11.5% to 46.2% (p = 0.004). Two patients without nonsustained ventricular tachycardia on day 1 had episodes of 13 and 16 beats on days 3 and 6 of monitoring. In patients with left ventricular ejection fractions >35% and N-terminal-pro-brain natriuretic peptide levels <1,000 pg/ml, no episodes of nonsustained ventricular tachycardia were detected on day 1 in nonischemic and ischemic patients, but 7DH detected 3 new patients in each group. In conclusion, 7DH clearly improves the detection and allows a better characterization of ventricular arrhythmic episodes but seems to be less useful for supraventricular events., (2010 Elsevier Inc. All rights reserved.)

Heart rate variability (HRV) markers have been widely used to characterize the autonomous regulation state of the heart from 24-h Holter monitoring, but long-term evolution of HRV indexes is mostly unknown. A dataset of 7-day Holter recordings of 22 patients with congestive heart failure was studied. A rhythmometric procedure was designed to characterize the infradian, circadian, and ultradian components for each patient, as well as circadian and ultradian fluctuations. Furthermore, a bootstrap test yielded automatically the rhythmometric model for each patient. We analyzed the temporal evolution of relevant time-domain (AVNN, SDNN, and NN50), frequency-domain (LF, HF, HFn, and LF/HF), and nonlinear (alpha(1) and SampEn) HRV indexes. Circadian components were the most significant for all HRV indexes, but the infradian ones were also strongly present in NN50, HFn, LF/HF, alpha(1), and SampEn indexes. Among ultradian components that one corresponding to 12 h, was the most relevant. Long-term monitoring of HRV conveys new potentially relevant rhythmometric information, which can be analyzed by using the proposed automatic procedure.

It has been previously documented that the main features and sensing performance of electrograms (EGMs) recorded in implantable cardioverter defibrillators (ICDs) depend on lead configuration. Although this dependence has been ascribed to differences in lead sensitivity and spatial resolution, the quantification of these two properties on ICD has not yet been attempted. In this paper, an operative framework to study the spatial resolution of ICD transvenous leads is presented. We propose to quantify the spatial resolution of ICD transvenous leads based on a new characterization called lead resolution volume (ResV). We analyzed the sensitivity distribution and the ResV of two unipolar (tip-can and coil-can ) and two bipolar (true or tip-ring and integrated or tip-coil) ICD transvenous lead configurations. A detailed 3-D model of the human thorax based on the visible human man dataset was used to compute the lead sensitivity and computer simulations of simple cardiac dynamics were used to quantify the ResV. Differences in the sensitivity distribution throughout the ventricular myocardium (VM) were observed for each lead configuration. In our computer model of the human thorax, the ResV was found to comprise 7%, 35%, 45%, and 70% of the VM for true bipolar, integrated bipolar, tip-can unipolar, and coil-can unipolar ICD leads, respectively. Furthermore, our analysis shows that the spatial resolution depends on both lead sensitivity and cardiac dynamics, and therefore, it can vary for different heart rhythms.

The mechanisms responsible for the maintenance and termination of ventricular fibrillation (VF) are poorly understood. The aim of this study was to compare the spectral characteristics of the electrical signal during sustained and non-sustained VF in patients with an implantable cardioverter-defibrillator. The study included 51 patients who had had at least one episode of sustained VF (i.e., duration >5 s and requiring shock administration) and non-sustained VF (i.e., duration >3 s and spontaneously terminated) that were recorded by the device set in a unipolar configuration. Spectral analysis of the first 3 s of each episode was performed. The dominant frequency was higher in sustained VF (4.6+/-0.7 Hz) than in non-sustained VF (4.3+/-0.6 Hz; P=.01), while the other parameters were similar. Although the spectral characteristics of sustained and non-sustained VF were similar, differences were observed during the first 3 s that could be used in algorithms for the early detection of non-sustained VF.

Aims: Very limited data are available on the differences between spontaneous and induced episodes of ventricular fibrillation (VF) in humans. The aim of the study was to compare the spectral characteristics of the electrical signal recorded by an implantable cardioverter defibrillator (ICD) during both types of episodes., Methods and Results: Thirteen ICD patients with at least one spontaneous and one induced VF recorded by the device were included in the study. A spectral representation was obtained for the first 3 s of the intracardiac unipolar electrogram during VF. The dominant frequency (f(d)), the peak power at f(d), an organization index (OI), a bandwidth measurement, and an estimate of the correlation with a sinusoidal wave (leakage) were estimated for each episode. The f(d) was higher in induced episodes (4.75 +/- 0.57 vs. 3.95 +/- 0.59 Hz for the spontaneous episodes, P = 0.002), as well as the degree of organization assessed by the OI, bandwidth, and leakage parameters., Conclusion: Clinical and induced VF episodes in humans have different spectral characteristics. Changes in the electrophysiological substrate or in the location of the arrhythmia wavefront at onset could play a role to explain the observed differences.

Heart rate turbulence (HRT) is a transient acceleration and subsequent deceleration of the heart rate after a premature ventricular complex (PVC), and it has been shown to be a strong risk stratification criterion in patients with cardiac disease. In order to reduce the noise level of the HRT signal, conventional measurements of HRT use a patient-averaged template of post-PVC tachogram (PPT), hence providing with long-term HRT indexes. We hypothesize that the reduction of the noise level at each isolated PPT, using signal processing techniques, will allow us to estimate short-term HRT indexes. Accordingly, its application could be extended to patients with reduced number of available PPT. In this paper, several HRT denoising procedures are proposed and tested, with special attention to support vector machine (SVM) estimation, as this is a robust algorithm that allows us to deal with few available time samples in the PPT. Pacing-stimulated HRT during electrophysiological study are used as a low-noise gold standard. Measurements in a 24-h Holter patient database reveal a significant reduction in the bias and the variance of HRT measurements. We conclude that SVM denoising yields short-term HRT measurements and improves the signal-to-noise level of long-term HRT measurements.

Background: The location of the myocardial infarction (MI) might modify the spectral characteristics of ventricular fibrillation (VF) in humans., Objective: To evaluate the effect of the location of the infarcted area on the spectral parameters of VF., Methods: Patients with chronic MI (29 anterior, 32 inferior) and induced VF during cardioverter defibrillator implant were retrospectively studied. Dominant frequency (f(d)), organization index (OI), and power of the harmonic peaks were calculated in the device-stored electrograms (EGM) during sinus rhythm (SR) and VF., Results: The f(d) of the VF was not affected by the left ventricular ejection fraction (LVEF) or the MI location (anterior: 4.54 +/- 0.74 Hz, inferior: 4.77 +/- 0.48 Hz, n.s.). The OI was also similar in both groups. However, in patients with inferior MIs, normalized peak power at f(d) was higher (118.3 +/- 18.5 vs 100.6 +/- 28.2, P < 0.01) and the normalized peak power of the harmonics was lower than in the anterior MI group. The analysis of EGM during SR showed similar results. The size of the necrotic area and its distance to the recording electrode might partially explain these results., Conclusion: In our series, the spectral characteristics of the EGMs during VF showed significant differences depending on the MI localization. A higher fraction of energy (in the low-frequency region) was seen in inferior MIs, whereas the peak power at the harmonics increased in anterior MIs. A similar effect was seen during SR and VF, suggesting that it is caused by local electrophysiology abnormalities induced by the MI rather than by different intrinsic characteristics of the VF.

Quantitative processing of color-Doppler echocardiographic images has substantially improved noninvasive assessment of cardiac physiology. Many indices are computed from the velocity fields derived either from color-Doppler tissue imaging (DTI), such as acceleration, strain and strain-rate, or from blood-flow color-Doppler, such as intracardiac pressure gradients (ICPG). All of these indices are dependent on the finite resolution of the ultrasound scanner. Therefore, we developed an image-dependent method for assessing the influence of temporal, spatial, and velocity resolutions, on cardiovascular parameters derived from velocity images. In order to focus our study on the spatial, temporal, and velocity resolutions of the digital image, we did not consider the effect of other sources of noise such as the interaction between ultrasound and tissue. A simple first-order Taylor's expansion was used to establish the functional relationship between the acquired image velocity and the calculated cardiac index. Resolutions were studied on: (a) myocardial acceleration, strain, and strain-rate from DTI, and (b) ICPG from blood-flow color-Doppler. The performance of Taylor's-based error bounds (TBEB) was demonstrated on simulated models and illustrated on clinical images. Velocity and temporal resolution were highly relevant for the accuracy of DTI-derived parameters and ICPGs. TBEB allow to assess the effects of ideal digital image resolution on quantitative cardiovascular indices derived from velocity measurements obtained by cardiac imaging techniques.

The long QT syndrome type-3 (LQT3) is an inherited cardiac disorder caused by mutations in the sodium channel gene SCN5A. LQT3 has been associated with ventricular arrhythmias and sudden cardiac death, specially at low heart rates. Based on computer simulations and experimental investigations, analysis of the morphology of the Action Potential (AP) has shown that it undergoes early afterdepolarizations (EADs) and spontaneous discharges, which are thought to be the trigger for reentry like-activity. However, dynamic characteristics of cardiac tissue are also important factors of arrhythmia mechanisms. In this work, we propose a dynamical analysis of the LQT3 at cellular level. We use a detailed Markovian model of the DeltaKPQ mutation, which is associated with LQT3, and we study beat-to-beat AP Duration (APD) variations by using a long-term stimulation protocol. Compared to wild-type (WT) cells, DeltaKPQ mutant cells are found to develop APD alternans over a narrow range of stimulation frequencies. Moreover, the interval of frequency dependence of APD alternans is related to the degree of severity of the EADs present in the AP. In conclusion, dynamical analysis of paced cells is a useful approach to understand the mechanisms of rate dependent arrhythmias.

The present paper describes a study where effects of anterior myocardium on body surface potentials were investigated. The study combines numerical lead field analysis combined with cardiac automata model. Electric fields are calculated with finite difference method in a 3-D model of male thorax. The cardiac activation applied in the study is an ectopic beat originating in the apex. The correlations and mean differences between signal generated by anterior segments of left ventricle and signal generated by both ventricles were analysed for 117 leads. The results show that there are leads which have high correlation (>0.9) with low the relative mean difference (<0.2) between the signals generated by anterior segments and signals generated by whole ventricles. These electrode locations would be optimal to monitor the activation of anterior segments when ectopic beats originate in apex.

The analysis of intracardiac Electrograms (EGM) recorded by transvenous lead systems in Implantable Cardioverter Defibrillators (ICD) often entails assumptions on the scope of the lead system. Based on bioelectric signal modeling and on numerical analysis, we studied quantitatively the scope of unipolar and bipolar lead configurations in ICD. We defined the scope in terms of the Mean Square Difference (MSD) between EGM generated by the whole myocardium, and EGM generated by different families of regions within the myocardium. For unipolar and bipolar lead systems, simulations showed that the smallest myocardial region involving a given value of MSD is characterized by the highest measurement sensitivity. Furthermore, the scope in the ventricles was found to be an order of magnitude smaller for bipolar leads than for unipolar leads. Bioelectric signal modeling combined with numerical analysis constitutes a powerful method to study quantitatively the scope of transvenous lead systems.

Reliable noninvasive estimators of global left ventricular (LV) chamber function remain unavailable. We have previously demonstrated a potential relationship between color-Doppler M-mode (CDMM) images and two basic indices of LV function: peak-systolic elastance (Emax) and the time-constant of LV relaxation (tau). Thus, we hypothesized that these two indices could be estimated noninvasively by adequate postprocessing of CDMM recordings. A semiparametric regression (SR) version of support vector machine (SVM) is here proposed for building a blind model, capable of analyzing CDMM images automatically, as well as complementary clinical information. Simultaneous invasive and Doppler tracings were obtained in nine mini-pigs in a high-fidelity experimental setup. The model was developed using a test and validation leave-one-out design. Reasonably acceptable prediction accuracy was obtained for both Emax (intraclass correlation coefficient Ric, = 0.81) and tau (Ric, = 0.61). For the first time, a quantitative, noninvasive estimation of cardiovascular indices is addressed by processing Doppler-echocardiography recordings using a learning-from-samples method.

We conducted a systematic review of the literature for assessing the value of home monitoring for heart failure (HF) patients. The abstracts of 383 articles were read. We excluded those in which either no home monitoring was done or only the technical aspects of the telemedicine application were described. Forty-two studies met the selection criteria. We classified the results into feasibility (technical and institutional) and impact (on the clinical process, on patient health, on accessibility and acceptability of the health system, and on the economy). Evaluating the articles showed that home monitoring in HF patients is viable, given that: (1) it appears to be technically effective for following the patient remotely; (2) it appears to be easy to use, and it is widely accepted by patients and health professionals; and (3) it appears to be economically viable. Furthermore, home monitoring of HF patients has been shown to have a positive impact on: (1) the clinical process, supported by a significant improvement of patient follow-up by adjustment of treatment, diet or behaviour, as well as hospital readmissions and emergency visits reduction; (2) the patient's health, supported by a relevant improvement in quality of life, a reduction of days in hospital, and a decrease in mortality; and (3) costs resulting from the use of health resources.

Introduction and Objectives: The magnitude of the change in heart rate during the first few minutes of the head-up tilt test has been used to predict the test's result. The aim of this study was to investigate whether the heart rate increase during the head-up tilt test potentiated with nitroglycerin is related to the development of syncope., Patients and Method: The study included 158 consecutive patients with syncope, with stable sinus rhythm, and without structural cardiac disease who were undergoing a head-up tilt test with nitroglycerin. The heart rate increment induced by the tilt maneuver and by nitroglycerin administration was calculated, and its relationship to clinical variables and to the test's results was analyzed., Results: The head-up tilt test gave positive results in 117 patients (74%). The heart rate was 68.7 (11.3) bpm in the decubitus position and 85.1 (15.4) bpm during the first 6 min of tilting. There was strong inverse correlation between the heart rate increase induced by tilting and age (r=--0.63; P<.001), but the increase (16.8 [9.3] bpm in patients with syncope versus 14.9 [11.3] bpm in those without; P=.3) did not predict the result of the test. The heart rate increase induced by nitroglycerin was also similar for patients with and without syncope during the pharmacologic phase of the test (27.3 [12.6] bpm and 26.7 (13.4) bpm, respectively; P=.8)., Conclusions: The magnitude of the heart rate increase during the first few minutes of tilt-testing and after nitroglycerin administration is inversely related to age but does not predict the result of the head-up tilt test with nitroglycerin.

Introduction and Objectives: Mathematical models of cardiac electrical activity may help to elucidate the electrophysiological mechanisms involved in the genesis of arrhythmias. The most realistic simulations are based on reaction-diffusion models and involve a considerable computational burden. The aim of this study was to develop a computer model of cardiac electrical activity able to simulate complex electrophysiological phenomena but free of the large computational demands required by other commonly used models., Material and Method: A cellular automata system was used to model the cardiac tissue. Each individual unit had several discrete states that changed according to simple rules as a function of the previous state and the state of the neighboring cells. Activation was considered as a probabilistic process and was adjusted using restitution curves. In contrast, repolarization was modeled as a deterministic phenomenon. Cell currents in the model were calculated with a prototypical action potential that allowed virtual monopolar and bipolar electrograms to be simulated at any point in space., Results: Reproducible flat activation fronts, propagation from a focal stimulus, and reentry processes that were stable and unstable in two dimensions (with their corresponding electrograms) were obtained. The model was particularly suitable for the simulation of the effects observed in curvilinear activation fronts. Fibrillatory conduction and stable rotors in two- and three-dimensional substrates were also obtained., Conclusions: The probabilistic cellular automata model was simple to implement and was not associated with a high computational burden. It provided a realistic simulation of complex phenomena of interest in electrophysiology.

Background: All indices of aortic stenosis (AS) rely on measurements of mean transvalvular pressure gradient (DeltaP) and flow rate. Because the gradient is reversed during late ejection, the late systolic left ventricular (LV)-aortic pressure crossover may be an erroneous landmark of end-ejection. The aortic incisura should be a better reference to calculate indices of AS invasively., Methods and Results: The accuracy of the pressure crossover and the incisura to define end-ejection was assessed in a chronic AS experimental model (9 dogs) with the use of an implantable flowmeter and Doppler echocardiography as reference. In 288 hemodynamic recordings analyzed (aortic valve area [AVA]: 0.74+/-0.46 cm2), ejection ended 37+/-29 ms after the pressure crossover but almost simultaneously with the incisura (2+/-17 ms). Pressure crossover error accounted for significant errors in the measurement of DeltaP (95% limits of agreement, +0 to +7 mm Hg) and AVA (-0.1 to +0.2 cm2). These errors were reduced to less than half with the use of the incisura to define end-ejection. Additionally, the agreement with Doppler-derived AS indices was best with use of the incisura. Pressure crossover error was maximal in situations of higher output, moderate orifice narrowing, higher arterial compliance, and lower vascular resistance. In 32 consecutive patients undergoing cardiac catheterization for AS, the pressure crossover induced a clinically important overestimation of the DeltaP from +22 to +50%. Errors in AVA estimation were considerably smaller (-2% to +6%) because of simultaneous and offsetting errors in the measurements of DeltaP and flow., Conclusions: The aortic incisura and not the second pressure crossover should be used to obtain invasive indices of AS.

Objectives: The study was designed to validate in vivo a new method to measure ejection intraventricular pressure gradients (IVPGs) by processing color M-mode Doppler data and to assess the effects of inotropic interventions on IVPGs in the clinical setting., Background: In the absence of obstruction, ejection IVPGs cannot be estimated by Doppler using the simplified Bernoulli equation., Methods: High-fidelity micromanometers were placed in the left ventricle of eight minipigs, and synchronic Doppler images and pressure signals were obtained during different hemodynamic conditions. Twenty healthy volunteers and 20 dilated cardiomyopathy patients were studied at baseline and during esmolol, dobutamine, and atropine infusion (only dobutamine in patients)., Results: Excellent agreement was observed between micromanometer and Doppler methods for measuring instantaneous pressure differences among the apex, the mid-cavity, and the outflow tract (R(intraclass) = 0.98, 0.81, 0.76, and 0.98 for the peak, time-to-peak, peak reverse, and time-to-peak reverse values, respectively; n = 810 beats). Error of the noninvasive method was -0.05 +/- 0.25 mm Hg for the peak pressure difference. Parametrical images demonstrated that IVPGs originate mainly in the mid-ventricle and then propagate to the outflow tract. Both the magnitude and the temporal course of IVPGs were different among volunteers and patients. Inotropic interventions induced significant changes in the apex-outflow tract pressure differences in both populations, whereas atropine had no effect on IVPGs., Conclusions: For the first time, ejection IVPGs can be accurately visualized and measured by Doppler-echocardiography. Important aspects of the dynamic interaction among myocardial performance, load mechanics, and ejection dynamics can be assessed in the clinical setting using this method.

Aims: Ventricular activation onset is faster in supraventricular beats than in ventricular rhythms. The aim of this study was to evaluate a criterion to differentiate supraventricular (SVT) from ventricular tachycardia (VT) based on the analysis of the initial voltage changes in ICD-stored morphology electrograms., Methods: Far field ICD-stored EGMs were obtained from 68 VT and 38 SVT episodes in 16 patients. The first EGM peak was detected, three consecutive time epochs were defined within the preceding 80 ms window and the voltage changes with respect to a sinus template were analysed during each time period and combined into a single parameter for rhythm discrimination., Results: The algorithm was tested in an independent validation group of 442 VT and 97 SVT spontaneous episodes obtained from 22 patients with a dual chamber ICD. The area under the receiver-operator characteristics (ROC) curve indicated that the arrhythmia separability with this method was 0.95 (tolerance interval: 0.85-0.99) and 0.98 (0.87-0.99) for the control and validation groups respectively. A specificity of 0.91 was obtained at 95% sensitivity in the validation group., Conclusion: The analysis of voltage changes during the initial ventricular activation process is feasible using the far field stored electrograms of an ICD system and yields a high sensitivity and specificity for arrhythmia discrimination., (Copyright 2003 The European Society of Cardiology.)

The morphological analysis of implantable cardioverter defibrillator (ICD) stored electrograms (EGM) using a multilayer perceptron (MLP) has been proposed for discrimination between supraventricular and ventricular arrhythmias. However, a reliable estimation of the accuracy of MLP methods is lacking. The aim of the study was to compare the morphology and spectrum-based MLP with more conventional morphology-based algorithms in a large series of ICD-stored episodes of arrhythmia. One set of ICD-stored electrograms was used for control and training purposes and a second one, consisting of spontaneous episodes in patients with dual chamber ICDs, for validation of the MLP performance. The correlation waveform analysis (CWA) and the EGM width criterion were compared with MLP methods. Bootstrap resampling techniques were used to extract the relevant information in the MLP training. The morphology-based MLP achieved better discrimination than any other method, with areas under the receiver operating characteristic (ROC) curve (tolerance intervals): 0.96 (0.81, 0.96) for MLP, 0.91 (0.77, 0.94) for CWA, and 0.68 (0.49, 0.78) for EGM width in the validation set. A specificity of 73.0% was obtained at 95% sensitivity, compared with 38.1% and 55.1% using CWA and EGM width criteria, respectively. In contrast, the generalization capabilities of spectral-based MLP methods are poor, showing a lower area under the ROC curve in the validation set. Time-domain MLP techniques may be useful for the morphological analysis of the intracardiac EGM signal stored by ICD devices. When properly trained and validated, these methods perform better than other commonly used morphological criteria for discrimination between supraventricular and ventricular arrhythmias.