Quantification of Spatial Repolarization Heterogeneity: Testing the Robustness of a New Technique

Abstract The V-index is a recently-proposed metric related to repolarization heterogeneity (RH) Introduction Spatial heterogeneity of ventricular repolarization is a key quantity for the development of arrhythmias. Despite many methods have been proposed and investigated in the past [1-3], a non-invasive quantification of Repolarization Heterogeneity (RH) is still an open issue We recently proposed an estimator of the standard deviation of RH, which was named "V-index" Although the performances of the method have been deeply investigated in the original paper Method An estimate of repolarization heterogeneity Let us suppose to subdivide the myocardium in "nodes", each node m sharing a common transmembrane potential (TMP), D(t), but having a specific repolarization time given by ρ m =ρ + Δρ m . At each node m, the repolarization delay Δρ m is the deviation from the average repolarization timeρ = 1 M M m=1 ρ m in the given heartbeat. We have recently [5] introduced a simple model to describe the distribution of these delays Δρ m (k) among beats, being k the beat index. In particular we set: where ϑ m models the spatial variability of the repolarization times for a given subject at a given HR, and ϕ m (k) describes difference in repolarization times which are observable among successive beats

A multivariate time-frequency method to characterize the influence of respiration over heart period and arterial pressure

Respiratory activity introduces oscillations both in arterial pressure and heart period, through mechanical and autonomic mechanisms. Respiration, arterial pressure, and heart period are, generally, non-stationary processes and the interactions between them are dynamic. In this study we present a methodology to robustly estimate the time course of cross spectral indices to characterize dynamic interactions between respiratory oscillations of heart period and blood pressure, as well as their interactions with respiratory activity. Time-frequency distributions belonging to Cohen's class are used to estimate time-frequency (TF) representations of coherence, partial coherence and phase difference. The characterization is based on the estimation of the time course of cross spectral indices estimated in specific TF regions around the respiratory frequency. We used this methodology to describe the interactions between respiration, heart period variability (HPV) and systolic arterial pressure variability (SAPV) during tilt table test with both spontaneous and controlled respiratory patterns. The effect of selective autonomic blockade was also studied. Results suggest the presence of common underling mechanisms of regulation between cardiovascular signals, whose interactions are time-varying. SAPV changes followed respiratory flow both in supine and standing positions and even after selective autonomic blockade. During head-up tilt, phase differences between respiration and SAPV increased. Phase differences between respiration and HPV were comparable to those between respiration and SAPV during supine position, and significantly increased during standing. As a result, respiratory oscillations in SAPV preceded respiratory oscillations in HPV during standing. Partial coherence was the most sensitive index to orthostatic stress. Phase difference estimates were consistent among spontaneous and controlled breathing patterns, whereas coherence was higher in spontaneous breathing. Parasympathetic blockade did not affect interactions between respiration and SAPV, reduced the coherence between SAPV and HPV and between respiration and HPV. Our results support the hypothesis that non-autonomic, possibly mechanically mediated, mechanisms also contributes to the respiratory oscillations in HPV. A small contribution of sympathetic activity on HPV-SAPV interactions around the respiratory frequency was also observed

Non-invasive evaluation of the effect of metoprolol on the atrioventricular node during permanent atrial fibrillation.

During atrial fibrillation (AF), conventional electrophysiological techniques for assessment of refractory period or conduction velocity of the atrioventricular (AV) node cannot be used. We aimed at evaluating changes in AV nodal properties during administration of metoprolol from electrocardiogram data, and to support our findings with simulated data based on results from an electrophysiological study

A method for dynamic subtraction MR imaging of the liver

BACKGROUND: Subtraction of Dynamic Contrast-Enhanced 3D Magnetic Resonance (DCE-MR) volumes can result in images that depict and accurately characterize a variety of liver lesions. However, the diagnostic utility of subtraction images depends on the extent of co-registration between non-enhanced and enhanced volumes. Movement of liver structures during acquisition must be corrected prior to subtraction. Currently available methods are computer intensive. We report a new method for the dynamic subtraction of MR liver images that does not require excessive computer time. METHODS: Nineteen consecutive patients (median age 45 years; range 37–67) were evaluated by VIBE T1-weighted sequences (TR 5.2 ms, TE 2.6 ms, flip angle 20°, slice thickness 1.5 mm) acquired before and 45s after contrast injection. Acquisition parameters were optimized for best portal system enhancement. Pre and post-contrast liver volumes were realigned using our 3D registration method which combines: (a) rigid 3D translation using maximization of normalized mutual information (NMI), and (b) fast 2D non-rigid registration which employs a complex discrete wavelet transform algorithm to maximize pixel phase correlation and perform multiresolution analysis. Registration performance was assessed quantitatively by NMI. RESULTS: The new registration procedure was able to realign liver structures in all 19 patients. NMI increased by about 8% after rigid registration (native vs. rigid registration 0.073 ± 0.031 vs. 0.078 ± 0.031, n.s., paired t-test) and by a further 23% (0.096 ± 0.035 vs. 0.078 ± 0.031, p < 0.001, paired t-test) after non-rigid realignment. The overall average NMI increase was 31%. CONCLUSION: This new method for realigning dynamic contrast-enhanced 3D MR volumes of liver leads to subtraction images that enhance diagnostic possibilities for liver lesions

Assessment of the dynamics of atrial signals and local atrial period series during atrial fibrillation: effects of isoproterenol administration

BACKGROUND: The autonomic nervous system (ANS) plays an important role in the genesis and maintenance of atrial fibrillation (AF), but quantification of its electrophysiologic effects is extremely complex and difficult. Aim of the study was to evaluate the capability of linear and non-linear indexes to capture the fine changing dynamics of atrial signals and local atrial period (LAP) series during adrenergic activation induced by isoproterenol (a sympathomimetic drug) infusion. METHODS: Nine patients with paroxysmal or persistent AF (aged 60 ± 6) underwent electrophysiological study in which isoproterenol was administered to patients. Atrial electrograms were acquired during i) sinus rhythm (SR); ii) sinus rhythm during isoproterenol (SRISO) administration; iii) atrial fibrillation (AF) and iv) atrial fibrillation during isoproterenol (AFISO) administration. The level of organization between two electrograms was assessed by the synchronization index (S), whereas the degree of recurrence of a pattern in a signal was defined by the regularity index (R). In addition, the level of predictability (LP) and regularity of LAP series were computed. RESULTS: LAP series analysis shows a reduction of both LP and R index during isoproterenol infusion in SR and AF (R(SR )= 0.75 ± 0.07 R(SRISO )= 0.69 ± 0.10, p < 0.0001; R(AF )= 0.31 ± 0.08 R(AFISO )= 0.26 ± 0.09, p < 0.0001; LP(SR )= 99.99 ± 0.001 LP(SRISO )= 99.97 ± 0.03, p < 0.0001; LP(AF )= 69.46 ± 21.55 LP(AFISO )= 55 ± 24.75; p < 0.0001). Electrograms analysis shows R index reductions both in SR (R(SR )= 0.49 ± 0.08 R(SRISO )= 0.46 ± 0.09 p < 0.0001) and in AF (R(AF )= 0.29 ± 0.09 R(AFISO )= 0.28 ± 0.08 n.s.). CONCLUSIONS: The proposed parameters succeeded in discriminating the subtle changes due to isoproterenol infusion during both the rhythms especially when considering LAP series analysis. The reduced value of analyzed parameters after isoproterenol administration could reflect an important pro-arrhythmic influence of adrenergic activation on favoring maintenance of AF

Time-variant power spectrum analysis for the detection of transient episodes in HRV signal

A time-variant algorithm of autoregressive (AR) identification is introduced and applied to the heart rate variability (HRV) signal. The power spectrum is calculated from the AR coefficients derived from each single RR interval considered. Time-variant AR coefficients are determined through adaptive parametric identification with a forgetting factor which obtains weighted values on a running temporal window of 50 preceding measurements. Power spectrum density (PSD) is hence obtained at each cardiac cycle, making it possible to follow the dynamics of the spectral parameters on a beat-by-beat basis. These parameters are mainly the LF (low-frequency) and the HF (high-frequency) powers, and their ratio, LF/HF. These together account for the balanced sympatho-vagal control mechanism affecting the heart rate. This method is applied to subjects suffering from transient ischemic attacks. The time variant spectral parameters suggest an early activation of LF component in the HRV power spectrum. It precedes by approximately 1.5-2 min the tachycardia and the ST displacement, generally indicative of the onset of an ischemic episode