Jacques Beaumont

A Mechanism of Transition From Ventricular Fibrillation to Tachycardia Effect of Calcium Channel Blockade on the Dynamics of Rotating Waves

Abbreviation of the action potential duration and/or effective refractory period (ERP) is thought to decrease the cycle length of reentrant arrhythmias. Verapamil, however, paradoxically converts ventricular fibrillation (VF) to ventricular tachycardia (VT), despite reducing the ERP. This mechanism remains unclear. We hypothesize that the size and the dynamics of the core of rotating waves, in addition to the ERP, influence the arrhythmia manifestation (ie, VF or VT). The objectives of this study were (1) to demonstrate functional reentry as a mechanism of VF and VT in the isolated Langendorff-perfused rabbit heart in the absence of an electromechanical uncoupler and (2) to elucidate the mechanism of verapamil-induced conversion of VF to VT. We used high-resolution video imaging with a fluorescent dye, ECG, frequency and 2-dimensional phase analysis, and computer simulations. Activation patterns in 10 hearts were studied during control, verapamil perfusion (2x10(-6) mol/L), and washout. The dominant frequency of VF decreased from 16.2+/-0.7 to 13.5+/-0.6 Hz at 20 minutes of verapamil perfusion (P<0.007). Concomitantly, phase analysis revealed that wavefront fragmentation was reduced, as demonstrated by a 3-fold reduction in the density of phase singularities (PSs) on the ventricular epicardial surface (PS density: control, 1.04+/-0.12 PSs/cm(2); verapamil, 0.32+/-0.06 PSs/cm(2) [P=0.0008]). On washout, the dominant frequency and the PS density increased, and the arrhythmia reverted to VF. The core area of transiently appearing rotors significantly increased during verapamil perfusion (control, 4.5+/-0.6 mm(2); verapamil, 9.2+/-0.5 mm(2) [P=0.0002]). In computer simulations, blockade of slow inward current also caused an increase in the core size. Rotating waves underlie VF and VT in the isolated rabbit heart. Verapamil-induced VF-to-VT conversion is most likely due to a reduction in the frequency of rotors and a decrease in wavefront fragmentation that lessens fibrillatory propagation away from the rotor.

AV nodal function during atrial fibrillation: The role of electrotonic modulation of propagation

AVN Function in Atrial Fibrillation. The irregular ventricular rhythm that accompanies atrial fibrillation (AF) has been explained in terms of concealed conduction within the AV node (AVN). However, the cellular basis of concealed conduction in AF remains poorly understood. Our hypothesis is that electrotonic modulation of AVN propagation by atrial impulses blocked repetitively within the AVN is responsible for changes in function that lead to irregular ventricular rhythms in patients with AF. We have tested this idea using two different simplified computer ionic models of the AVN. The first (“black‐box”) model consisted of three cells: one representing the atrium, another one representing the AVN, and a third one representing the ventricle. The black‐box model was used to establish the rules of behavior and predictions to be tested in a second, more elaborate model of the AVN. The latter (“nine‐cell” model) incorporated a linear array of nine cells separated into three different regions. The first region of two cells represented the atrium; the second region of five cells represented the AV node; and the third region of two cells represented the ventricle. Cells were connected by appropriate coupling resistances. During regular atrial pacing, both models reproduced very closely the frequency dependence of AV conduction and refractoriness seen in patients and experimental animals. In addition, atrial impulses blocked within the AV node led to electrotonic inhibition or facilitation of propagaticm of immediately succeeding impulses. During simulated AF, using the nine‐cell model, random variations in the atrial (A‐A) interval yielded variations in the ventricular (V‐V) interval but there was no scaling, i.e., the V‐V intervals were not multiples of the A‐A intervals. As such, the model simulated the statistical behavior of the ventricles in patients with AF, including: (1) the ventricular rhythm was random; and (2) the coefficient of variation (standard deviation/mean) of the ventricular rhythm was relatively constant at any given mean V‐V interval. Analysis of cell responses revealed that repetitive atrial input at random A‐A intervals resulted in complex patterns of concealment within the AVN cells. Consequently, the effects of electrotonic modulation were also random, which resulted in a smearing of the AV conduction curve over A‐A intervals that were larger than those predicted for 1:1 AV conduction. Hence, during AF, electrotonic modulation acts in concert with the frequency dependence of AVN conduction to result in complex patterns of ventricular activation. Finally, similarly to what was shown in patients, VVI pacing of the ventricle in the nine‐cell model at the appropriate frequency led to blockade of nearly all anterograde (i.e., A‐V) impulses. The essential feature here was that the retrograde impulse invading the AVN cells was followed by refractoriness with slow recovery of excitability, setting the stage for electrotonic inhibition of anterograde impulses. Overall, the results provide insight into the cellular mechanisms underlying AVN function and irregular ventricular response during AF.

Laplace–Dirichlet Energy Field Specification for Deformable Models. An FEM Approach to Active Contour Fitting

The construction of large scale computer models for complex biological systems requires the fitting of curves or surfaces to anatomical data sets. Algorithms recently developed to perform this task are based on the displacement of an initial model contour. There are several problems associated with this approach. Here we present improvements which eliminate the (i) sensitivity to the initial model position and shape; (ii) existence of local minima or maxima in the field used to displace the model; and (iii) presence of multiple solutions in the rules governing model displacement. Key elements of our algorithm are first that both the energy field used to displace the model and the model displacement itself are governed by partial differential equations. Secondly, we approximate the model with a polygonal contour which facilitates accurate displacement. Tests performed against cases that are known to be problematic show that our algorithm can fit complex data sets entirely automatically.

Three-dimensional reconstruction of large tissue volumes from scanning laser confocal microscopy

Phase correlation is applied to the mosaicing of confocal scanning laser microscopy data. A large specimen (i.e., a murine heart) is cut into a number of individual sections with appropriate thickness. The sections are scanned horizontally and vertically to produce tiles of a 3D volume. Image processing based on phase correlation is used to rebuild the 3D volume and stitch the tiles together. Specifically, 2D registration of in-plane tiles and 3D alignment of optical slices within a given physical section are performed. The approach and performance are presented in this paper along with examples.

Development of ultrafast detector for advanced time-of-flight brain PET

Purpose: Time-of-flight (TOF) been successfully implemented in whole body PET, significantly improving clinical performance. However, TOF has not been a priority in development of dedicated brain PET systems due the relatively small size of the human head, where coincidence timing resolution (CTR) below 200 ps is necessary to arrive at substantial performance improvements. The Brain PET (BET) consortium is developing a PET detector block with ultrafast CTR, high sensitivity and high spatial resolution (X, Y, depth of interaction, DOI) that provides a pathway to significantly improved brain PET. Methods: We have implemented analytical and Monte Carlo models of scintillation photons transport in scintillator segments with the trans-axial cross-section equal or smaller than 3x3 mm2 . Results: The signal amplitude and timing of W mm x W mm x L mm scintillators (1 mm<W<3 mm, 5 mm <L< 30 mm) are strongly influenced by sidewall surface polish and external reflector. Highly polished surfaces provide nearly perfect total internal reflection (TIR), enabling the ultrafast timing performance to be relatively independent of scintillator crosssection. The signal amplitude in such a configuration does not depend on DOI. However, the differential signal from top and bottom SiPM in the dual-ended readout can be used to determine DOI. Using TIR alone, the average of the photon detection times at the top and bottom SiPMs provides a good estimation of the gamma ray absorption time. Averaging ~10 photons starting from 3rd photon produces the shortest CTR for SPTR=50 ps. Conclusions: We established that the advanced silicon photomultiplier designs with high single photon detection efficiency (QE=60%) and high single photon timing resolution (SPTR =50 ps) are critical for achieving ultrafast TOF-PET performance with CTR ~50 ps and ~4 mm DOI resolution.

Determining the light scattering and absorption parameters from forward-directed flux measurements in cardiac tissue

Abstract. We describe a method to accurately measure the light scattering model parameters from forward-directed flux (FDF) measurements carried out with a fiber-optic probe (optrode). Improved determination of light scattering parameters will, in turn, permit better modeling and interpretation of optical mapping in the heart using voltage-sensitive dyes. Using our optrode-based system, we carried out high spatial resolution measurements of FDF in intact and homogenized cardiac tissue, as well as in intralipid-based tissue phantoms. The samples were illuminated with a broad collimated beam at 660 and 532 nm. Measurements were performed with a plunge fiber-optic probe (NA=0.22) at a spatial resolution of up to 10  μm. In the vicinity of the illuminated surface, the FDF consistently manifested a fast decaying exponent with a space constant comparable with the decay rate of ballistic photons. Using a Monte Carlo model, we obtained a simple empirical formula linking the rate of the fast exponent to the scattering coefficient, the anisotropy parameter g, and the numerical aperture of the probe. The estimates of scattering coefficient based on this formula were validated in tissue phantoms. Potential applications of optical fiber-based FDF measurements for the evaluation of optical parameters in turbid media are discussed.

Fitting C² continuous parametric surfaces to frontiers delimiting physiologic structures.

We present a technique to fit C 2 continuous parametric surfaces to scattered geometric data points forming frontiers delimiting physiologic structures in segmented images. Such mathematical representation is interesting because it facilitates a large number of operations in modeling. While the fitting of C 2 continuous parametric curves to scattered geometric data points is quite trivial, the fitting of C 2 continuous parametric surfaces is not. The difficulty comes from the fact that each scattered data point should be assigned a unique parametric coordinate, and the fit is quite sensitive to their distribution on the parametric plane. We present a new approach where a polygonal (quadrilateral or triangular) surface is extracted from the segmented image. This surface is subsequently projected onto a parametric plane in a manner to ensure a one-to-one mapping. The resulting polygonal mesh is then regularized for area and edge length. Finally, from this point, surface fitting is relatively trivial. The novelty of our approach lies in the regularization of the polygonal mesh. Process performance is assessed with the reconstruction of a geometric model of mouse heart ventricles from a computerized tomography scan. Our results show an excellent reproduction of the geometric data with surfaces that are C 2 continuous.

Computational identification of RNA motifs in genome sequences

One of the difficulties of using Artificial Neural Networks (ANNs) to estimate atmospheric temperature is the large number of potential input variables available. In this study, four different feature extraction methods were used to reduce the input vector to train four networks to estimate temperature at different atmospheric levels. The four techniques used were: genetic algorithms (GA), coefficient of determination (CoD), mutual information (MI) and simple neural analysis (SNA). The results demonstrate that of the four methods used for this data set, mutual information and simple neural analysis can generate networks that have a smaller input parameter set, while still maintaining a high degree of accuracy.