Integrative Physiology |
From the Department of Pharmacology (J.C., R.M., O.B. A.S., J.J.) and Pediatrics (Cardiology) (R.M.), State University of New York Health Science Center, Syracuse, NY.
Correspondence to Dr José Jalife, Department of Pharmacology, SUNY Health Science Center at Syracuse, 766 Irving Ave, Syracuse, NY 13210. E-mail jalifej{at}vax.cs.hscsyr.edu
| Abstract |
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Key Words: arrhythmia electrophysiology ventricular fibrillation Fourier analysis mapping
| Introduction |
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300 000 deaths each year in the United States
alone.1 Nevertheless, despite years of intensive research,
its mechanism remains poorly understood. Recent studies from our
laboratory2 3 4 5 and others6 7 8 9 have shown that
VF is not entirely random and that complex spatiotemporal organization
underlies this enigmatic phenomenon. Yet there is still some
controversy as to whether fibrillation in the ventricles is due to (1)
multiple unstable wavelet reentry,10 11 (2) the
destabilization of 3-dimensional scroll waves and their
breakup,12 13 14 15 or (3) the fibrillatory conduction from a
single or a small number of ongoing reentrant
circuits.2 16 Computer simulations have suggested that
single or multiple 3-dimensional rotor(s) (ie, scroll waves) may be the
underlying mechanism of VF.12 13 17 18 In 1995, Gray et
al2 provided direct experimental evidence that at least
some cases of VF can be due to a single rotor moving rapidly throughout
the heart. However, in many studies, rotors are not
consistently observed on the epicardial
surface.15 19 20 We hypothesized that at least some forms of VF are not random and that high-frequency periodic sources of activity manifest themselves as spatiotemporal periodicities, which drive VF. To this end, we used frequency analysis, in conjunction with high-resolution video imaging and phase mapping,4 (1) to demonstrate spatiotemporal periodicity (STP) of wavefronts, (2) to determine its contribution to the frequency content of VF, and (3) to elucidate the relative importance of multiple wavelets in the maintenance of VF. Overall, the results from our study strongly suggest that a single or a small number of sources of periodic activity are responsible for the maintenance of VF and that fibrillatory conduction away from such sources results in multiple short-lived wavelets.
| Terminology |
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| Materials and Methods |
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3
to 4 seconds in duration. An adjustable glass wall was used to gently
compress and restrain the heart, and no electromechanical uncoupling
agents were used.
Electrocardiographic and Frequency Analysis
Global volumeconducted bipolar ECGs were obtained at a
sampling rate of 2400 Hz. Pseudo-ECGs 22 were constructed
from optical recordings by integrating the transmembrane
fluorescence signal over the entire mapped region of the
ventricle. Fast Fourier transformation (FFT) was performed on both the
global bipolar ECGs and pseudo-ECGs using Welchs25
method.
Two-Dimensional Phase Maps
We quantified the patterns of wave propagation during VF using
phase mapping,4 a recently developed technique, which
highlights the formation of wavebreaks and the resulting PSs. In Figure 1A
, the fluorescence (F) changes
recorded by a single camera pixel (asterisk in Figure 1C
)
during VF are presented as a function of time. In Figure 1B
, the fluorescence of this pixel at time t, F(t), was
plotted against the fluorescence of the same pixel offset by a
time interval
=2 frames. A cyclic return map of F(t) versus
F(t
) was constructed. This allowed a new parameter,
the phase
(t), to be defined as the angle of the coordinate [F(t),
F(t
)] around the mean fluorescence for that given pixel,
with values between
and
, represented as a
continuous color scheme from red to purple. After the transformation, a
new phase,
(t), movie was produced including all pixels, whereby the
upstroke of the action potential, and hence the activation wavefront,
corresponded to the color green, whereas the plateau of the action
potential corresponded to the colors blue and purple. The refractory
tail of the action potential corresponded to the colors red and yellow.
A PS was defined at the point where all phases converged. Figure 1C
is a single snapshot (phase map) of a phase movie with 3
wavelets, each bounded by a PS or a PS and a boundary.
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Data Analysis
In 8 experiments, 24 optical recording episodes were
analyzed for STP. Only 10 randomly chosen episodes were
analyzed for lifespan analysis; all 24 episodes were
analyzed for waves entering and leaving.
Statistical Analysis
Correlation of frequencies was performed using simple linear
regression analysis. Comparisons were also performed using
standard ANOVA. A P<0.05 was considered to be statistically
significant.
An expanded Materials and Methods section is available online at http://www.circresaha.org.
| Results |
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A representative example is shown in Figure 2
, with its corresponding optical data.
The pseudo-ECG (Figure 2A
) shows rapid, irregular activity, and
its FFT (Figure 2B
) has a dominant peak at 12.2 Hz, with a
smaller peak at 10.4 Hz. The global bipolar EG for this same episode is
illustrated in Figure 2C
, with its corresponding FFT shown in
Figure 2D
. In this single example, a DF peak is seen at 12.1 Hz,
and 2 smaller peaks are seen at 11.0 and 13.5 Hz. For the purposes of
this study, the dominant frequencies of the pseudo-ECGs and global
bipolar ECGs can be considered identical, as they are within the given
spectral resolution of our system. Subsequent examination of the
optical recordings from the same episode revealed the source of
this DF in the form of STP (Figure 2E
). Figure 2E
shows 4 sequential isochrone maps of activation for this same
episode of VF over a period of 333 ms (see horizontal bars in Figure 2A
and 2C
). All 4 maps contain a very similar periodic activity,
with a wavefront emerging repetitively and periodically from the upper
left corner. This spatiotemporal periodic activity continued throughout
the entire 4 seconds of recording. The cycle length of these
periodic waves was
83 ms, which corresponded to the DF peak of the
FFT (12.1 Hz) seen in both the pseudo-EGs and global bipolar EGs,
clearly demonstrating that these periodic waves were responsible for
the DF of the arrhythmia in this specific example. As can be
seen in activations 3 and 4 of Figure 2E
, these periodic waves
did not always propagate across the mapping field undisturbed. More
often than not, these waves did not activate the rest of the
mapped region in a 1:1 manner after entering the mapping field but
followed complex pathways with multiple spatially distributed
conduction delays and sites of block (ie, fibrillatory conduction).
Figure 2F
shows a single pixel recording from the region
where the STP enters the mapped region (black asterisk in Figure 2E
). The FFT of this pixel recording (Figure 2G
)
shows a single narrow peak at 12.2 Hz, which corresponds to the DF of
both the optical pseudo-ECG and bipolar ECG, in addition to the cycle
length between this spatiotemporal periodic activity. At a site distant
from this region (white asterisk in Figure 2E
; map at t=249 ms),
fibrillatory conduction results in activity shown in Figure 2H
.
At this pixel location (white asterisk), the DF (Figure 2I
) is
10.3 Hz, with a prominent secondary peak at 12.3 Hz. This spectral
pattern correlates well with patterns of activation at this location,
where an approximate sequence of 6:5 could be demonstrated. Thus, the
representative isochrone map of activation patterns
(Figure 2E
), in conjunction with the 2 peaks seen in Figure 2I
, shows that the faster peak (12.3 Hz) represents the
input frequency and the slower peak represents the output
frequency at that site. Spatial distribution of many such patterns of
complex input:output relations is the hallmark of fibrillatory
conduction. Overall, the data presented strongly suggest the
presence of a periodic source outside the mapping region at 12.1 Hz
that is driving this complex arrhythmia.
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After having demonstrated the direct relationship between the frequency
of periodic activity and the global VF DF, we then proceeded to
quantify such a relationship in all episodes. Figure 3
shows the correlation between the
frequency of the periodic activity (STP) and the DF of the pseudo-EG.
As shown in Figure 3A
, in 24 episodes from 8 hearts, we obtained
a strong correlation of R2=0.75
between these 2 variables. In Figure 3B
, a similar
correlation for the DF of the global bipolar EG and the frequency of
the STP region produced an R2 value of
0.79. In many cases (52%), the frequency of the STP region was higher
than the DF of the pseudo-ECG but was still represented as
a significant peak in the frequency spectra. As seen in Figure 2
, this is most likely reflective of the fact that activity from
the periodic site was not propagating in a 1:1 fashion to the majority
of the mapping field, thus representing breakup of periodic
activity and fibrillatory conduction. Overall, the high correlation
between the periodic sources and the global DF strongly suggests that
these spatiotemporal periodic wavefronts are the source for the
majority of the frequency content of VF.
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Sources and Nature of Periodic Activity
In 21 of 24 episodes, STP was found. In many cases, however,
sources (ie, rotors and/or breakthroughs) alternated with STP occurring
from the edge of the mapping field. That is, a source would persist for
several activations and either drift out of the mapped region or
terminate, in which case STP from the edge would occur. These sources
would reappear later on in the movies with the concomitant termination
of STP from the edge. For those select episodes (n=16) in which the
source of STP was clearly identified, 12.5% of the time (2 episodes)
this source occurred exclusively in the form of a rotor (Figure 4
), 81.25% of the time (13
episodes) it occurred exclusively in the form of a breakthrough (Figure 5
), and 6.25% of the time (1 episode),
the source was seen to alternate between a periodic breakthrough and a
rotor (Figure 6
). In specific cases,
these sources were seen to persist during the entire episode. As can be
seen in Figure 4B
, a rotor acted as a source of 2 distinct
periodic waves. This rotor persisted for 52 rotations, and both waves
emanating from it were seen to exit the field of view in a spatially
and temporally similar fashion throughout the episode. As seen in the
series of 2-dimensional phase maps illustrated in Figure 4A
, this mother rotor (represented by PS 1) gave rise to
multiple short-lived wavelets, in addition to the 2 broad wavelets that
eventually left the field of view. Two-dimensional phase mapping better
enabled us to study the generation of multiple wavelets. At t=0 ms,
this source wave, bounded by PS 1 and PS 2, is clearly seen as a
reentrant phenomenon on the ventricular epicardium. At t=8
ms, wavelet 1-2 breaks up into wavelets 1-3 and 4-2, each bounded by a
PS. At t=16 ms, wavelet 4-2 persists, and wavelet 1-3 breaks up into
wavelets 3-6 and 1-5. At t=24 ms, wavelet 4-2 continues to move toward
the left ventricular free wall, whereas wavelet 6-3
extinguishes itself on refractory tissue (red). Wavelet 1-5 breaks up
into 2 distinct wavelets (not shown, as it is outside of the mapping
field), appropriately named wavelet 1-boundary and wavelet 5-boundary.
Finally, at t=32 ms, wavelet 4-2 moves upward and to the right, and
wavelet 5-boundary moves downward and to the left. Both waves
eventually exit the mapping region. Wavelet 1-boundary, also
characterized as mother rotor PS 1, continues to rotate, acting as a
source of new wavelets for the remainder of the movie. In Figure 4B
, the isochrone map for this activation sequence (ie,
three fourths of a rotation) depicted in the phase maps t=0 through
t=32 ms is shown.
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High-frequency periodic sources were also observed to occur in the form
of a breakthrough (Figure 5
). Two-dimensional phase maps are
shown illustrating one such source that persists throughout the movie.
At t=0 ms, no depolarization wavefront is seen on the
ventricular epicardial surface. At t=4 ms, wavelet 1 to 2,
bounded on each side by PS 1 and PS 2, creeps into the mapping region
from the midmyocardial or endocardial muscle layers of the right
ventricle. Four milliseconds later, the full wavelet emerges and begins
to propagate toward the left ventricle. At t=20 ms and t=28 ms, wavelet
1 to 2 now moves toward the apex and the left ventricular
free wall. At t=36 ms, wavelet 1 to 2 breaks up into wavelets 2 to 3
and 1 to 4. Eventually wavelets 2 to 3 and 1 to 4 exit the mapping
field (not shown).
The isochrone maps depicted in Figure 6A
illustrate an
example in which the source alternated between a breakthrough and a
rotor. In Figure 6B
and 6C
, respectively, the pseudo-EG
from the same episode and its FFT are shown. At t=1.483 seconds (first
dashed line from left in Figure 6B
), a periodic breakthrough is
shown that persisted for 43 activations acting as a source of new
wavelets. The frequency of activation of this source accelerated and
decelerated. Most commonly, however, the cycle length at the
breakthrough site was
61 ms, which corresponded highly to the DF of
the FFT (16.4 Hz; Figure 6C
). The cycle length of this
breakthrough varied from
50 to
69 ms, corresponding to peaks in
the range of 14.5 to 20.2 Hz. At t=3.554 seconds (second dashed line
from left in Figure 6B
), the breakthrough transformed into a
rotor, which persisted for 10 rotations and meandered in a cycloid
fashion, finally ending up in the location depicted at t=3.912 seconds.
The rotation period at t=3.554 seconds (
50 ms) showed a small
increase to 54 ms at t=3.912 seconds. Both of these rotation periods
are represented by major peaks in the FFT at 20.2 and 18.5
Hz, respectively. At t=3.912 seconds, the rotor continued for 2 more
activations before finally transforming back to a breakthrough at
t=4.096 seconds. A reasonable interpretation of these results is that
the overall arrhythmia resulted from high-frequency activation
by a single nonstationary scroll wave, of which the filament changed
orientation repeatedly with respect to the ventricular
epicardium, and most likely resulted in the source alternating between
a rotor and a breakthrough.
Figure 7
illustrates STP from the edge of
the mapping region alternating with STP in the form of a breakthrough.
In the isochrone map shown in Figure 7A
, at t=1.708 seconds
(first dashed line from left in Figure 7B
), a wavefront
activates the apex of the left ventricle and proceeds toward
the base. This activity occurred in a spatially and temporally similar
fashion for 14 activations. The cycle length of this activity was
100 ms, which was equal to the DF of the FFT (9.9 Hz; Figure 7C
) of the optical pseudo-EG (Figure 7B
). At t=3.108
seconds (second dashed line from left in Figure 7B
), STP from
the edge stopped, and STP was then seen to occur in the form of a
breakthrough. This source persisted for 7 activations at a cycle length
of
100 ms and gradually drifted toward the upper right corner of the
mapped region. Finally, at t=3.808 seconds (third dashed line from left
in Figure 8B
), the breakthrough drifted
out of the field of view, and STP (cycle length
100 ms) occurred
once again from the edge.
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Analysis of Wavelet Lifespan During Sustained VF
To investigate the role of multiple wavelets in the sustenance of
this complex arrhythmia, we measured the lifespan of PSs and
hence indirectly measured the lifespan of wavelets during VF. Figure 8
shows the lifespan of PSs in milliseconds and rotations. The
lifespan distribution was skewed to the left, with 51% of PSs lasting
only 8 ms or less. The mean lifespan of PSs was short, 14.7±14.4 ms,
with a range that varied from 4.17 (1 frame) to 100 ms. Because the
average rotation period of a rotor was
80 ms, 98% of PSs were found
to exist for <1 rotation. The majority of these short-lived PSs were
seen to be the result of breakup from broad spatiotemporal periodic
waves (ie, fibrillatory conduction; see Figure 4
).
Waves Entering and Leaving the Field of View
We hypothesized that if wavebreaks and their resulting wavelets
were not maintaining this arrhythmia, the number of waves
entering the mapping field should exceed or be equal to the number of
waves leaving it. In Figure 9A
, the mean
number of waves entering the mapping region was 6.50±0.69, whereas the
mean number of waves leaving was 4.25±0.56 (P<0.05) for
all experiments. In Figure 9B
, the ratio of entering to leaving
waves (E:L ratio) for each episode varied from 0.6 to 5.0 with a mean
of 1.92±1.03 (hatched bar). In 21 of 24 episodes (85.0%), the E:L
ratio was >1; 3 episodes (15.0%) had an E:L ratio <1. In 2 of the 3
cases in which the E:L ratio was <1, periodic breakthroughs were
observed. In the other example, an ongoing rotor was seen acting as a
source of new wavelets. It is important to note that in all cases in
which a periodic source of wavelets (ie, a rotor or breakthrough) was
present, the number of wavelets leaving the mapping region exceeded
those entering. However, as only the last 50 frames (
200 ms) of each
episode were analyzed because of the laborious time of
analysis, periodic sources were not always present. Hence,
during this time frame, the number of wavelets leaving did not always
exceed those entering. In those episodes in which we could see a
periodic source of activity (n=16), this source was often intermittent
in nature, alternating with STP from the edge (Figure 7
).
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| Discussion |
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Technical Considerations
Two-dimensional phase mapping is a powerful technique to
analyze wave propagation in VF. However, certain constraints
need to be considered. Irregularities in small-amplitude
fluorescence signals near the phase singularity may cause limit
cycle trajectories in the return map, which do not envelop the center
of the map (Figure 3B
online; see http://www.circresaha.org).
Arbitrarily choosing the mean fluorescence as the center of the
map minimized the occurrence of such trajectories. On the basis of
sample recordings (not shown), we have estimated the error in
localizing the PSs to be
0.5 mm. Therefore, owing to the highly
coupled nature of the cardiac tissue, it is difficult to conceive of
erroneous PSs produced as a result of this phenomenon. Rarely, wavelets
can survive annihilation of their PSs during failed vortex
shedding,26 and therefore some wavelets may have gone
undetected by our analysis. We only mapped 40% of the
epicardial surface of the ventricles and thus have no information about
the midmyocardial and the endocardial muscle layers. The high
preponderance of epicardial breakthroughs in our experiments, in
addition to recent computer simulations performed on a realistic
3-dimensional representation of the
heart,12 13 17 18 strongly suggest that intramural reentry
may be the source for VF, but the hypothesis requires experimental
validation. As a whole, we do not believe these limitations in our
technique affected the results of this study. Lastly, our experiments
were performed on an isolated Langendorff-perfused rabbit heart. The
relevance of these data to human VF remains to be determined.
Previous Studies on VF
Several theories regarding the underlying mechanisms of VF have
been proposed, as follows: (1) multiple unstable wavelet reentry, where
multiple wavelets were thought to move randomly throughout cardiac
tissue and a critical number of wavelets was required for the
sustenance of this arrhythmia10 11 ; (2)
3-dimensional scroll waves and their destabilization and
breakup12 13 14 15 ; and (3) uninterrupted periodic activity of
discrete reentrant sites with the subsequent breakup of waves, ie,
fibrillatory conduction.2 16 One important factor that is
unaccounted for by the first 2 hypotheses is the presence of organized
activity in the form of persistent STP, as demonstrated in most of our
episodes of VF. In fact, some recent studies have also demonstrated
spatial organization during VF. Bayly et al8 showed a
correlation between recordings obtained by closely spaced
unipolar electrodes. Furthermore, Damle et al7 previously
showed spatial and temporal linking of epicardial activation patterns
in a canine model of VF. More recently, elegant studies by Huang et
al27 and Rogers et al20 quantified
organization during VF using a concept very similar to STP. They used a
parameter termed "multiplicity," which measures the
number of different pathways in an overall activation. Altogether,
these studies provide strong evidence that VF is not an entirely random
phenomenon. Our study is the first to demonstrate organization during
VF in the form of STP and to relate such activity to the frequency
content of VF.
Mechanism Underlying the Periodicity
It has generally been accepted that the mechanisms underlying the
maintenance of VF are reentrant in nature.28 For
those select episodes (n=16) in which the source of STP was observed
within our field of view, 12.5% of the time (2 episodes) this source
occurred exclusively in the form of a rotor (Figure 4
), 81.25%
of the time (13 episodes) it occurred exclusively in the form of a
breakthrough (Figure 5
), and 6.25% of the time (1 episode) the
source was seen to alternate between a rotor and a periodic
breakthrough (Figure 6
). These results are compatible with the
idea that complex 3-dimensional vortex-like reentry17 (ie,
scroll waves) is the most likely underlying mechanism of VF in this
model. According to contemporary hypotheses, 3-dimensional reentry is
organized around a central filament that forms the rotation axis of
reentry. The evolution of the filament influences the dynamics of the
arrhythmia, and the filament orientation determines the nature
of the epicardial activation patterns. Our results do not provide
information about activity inside the ventricular wall.
However, as breakthrough patterns were the most common form of periodic
activity seen, we speculate that, more often than not, the filament was
probably not aligned perpendicularly to the epicardial surface. Using
plunge electrodes, Chen et al14 were the first to
demonstrate pairs of mirror-image scroll waves, of which the filaments
were aligned perpendicularly to the ventricular epicardial
surface (ie, transmural reentry). In such a case, the 2-dimensional
manifestation of the scroll wave on the epicardial surface would be a
spiral wave. On the other hand, it is not difficult to perceive
instances in which the filament is not aligned perpendicularly to the
epicardial surface (ie, intramural reentry). Recent work by Berenfeld
and Pertsov17 has provided a mechanistic explanation for
the greater prevalence of intramural reentry over transmural reentry,
whereby the scroll wave filament shows a tendency to align along the
local myocardial fiber orientation and thus is not perpendicular to the
epicardial surface. According to that study,17 stable
intramural reentry would be manifest as periodic breakthroughs of
activity on the epicardial surface, thus providing an explanation for
the predominance of breakthroughs over rotors as a source of STP.
Duration of Spatiotemporal Patterns and Number of Apparent
Sources
In certain episodes, STP could be seen throughout the entire 3- to
4-second recording. However, in most episodes it was transient
(4 to 51 activations). In all cases, when the wavefront entered the
mapping field, breakup of activity occurred, with independent
short-lived wavelets being produced. In the vast majority of episodes,
periodic activity would last for 4 or more activations, thereafter it
would stop, and then it would return later on at the same location and
with the same frequency (ie, intermittent STP). This could reflect
propagation from a single rotor with intermittent block. In addition,
it was noted that in some episodes there was spatiotemporal periodic
activity that stopped, propagated into our mapping field from a
different spatial orientation, and then once again returned to its
original spatiotemporal pattern of propagation. This phenomenon could
be explained by epicardial activation patterns from a single source via
multiple select routes of ongoing 1:1 propagation or propagation from a
rotor that is drifting back and forth. Alternatively, it could also be
explained by 2 distinct independent sources of activity at a similar
frequency; yet the first 2 scenarios seem more plausible in this
case.
It is important to note that the frequency of periodic activity was not
always the same. As clearly demonstrated in Figure 6
, the
rotation period of the source (ie, rotor in this case) may change as it
meanders, and thus periodic activity emanating from this source may
exit the mapped region with slight changes in frequency. In the faster
and more complex episodes of VF, such a phenomenon was not uncommon.
However, in the slower and more organized episodes of VF, such an
occurrence was never found (Figure 7
). Nevertheless, in the rare
case in which there was more than one distinct site of STP in the same
episode, the frequency of these spatiotemporal periodic regions was
usually the same (Figure 7
), which might reflect sites of
activation in a 1:1 manner from a mother source. Finally, as the
rotation period of a mother rotor may accelerate or decelerate,
multiple peaks may be seen in the FFT (Figure 6C
), thus
representing different rotation periods of that rotor at
different points in time. Varying degrees of intermittent block of
waves propagating from the periodic sources (Figure 2
) resulting
in spatially distributed input:output frequency relations (eg, 6:5,
4:3) is also a mechanism for the multiple distinct peaks seen in the
frequency spectra of VF.
Are Multiple Wavelets Important in the Maintenance of
VF?
To answer this question, we measured the lifespan of PSs, and
hence indirectly that of wavelets. The lifespan of PSs was short; 98%
of them lasted <1 rotation. According to the multiple wavelet
hypothesis, cardiac fibrillation is maintained by spontaneous
wavebreaks that constantly generate randomly wandering daughter
wavelets.10 11 If the lifespan of wavelets is very short,
then these wavelets will have a decreased chance to give rise to new
wavelets, in a dynamic equilibrium that maintains fibrillation, as
originally postulated by Moe et al10 in 1964. In fact, if
we had sampled at a rate faster than 240 Hz (
4 ms), it is quite
probable that the lifespan of many wavelets would have been even
shorter, giving further credence to our hypothesis.
To test the relevance of the multiple wavelet hypothesis to VF in our model, we measured the number of wavelets entering and leaving our mapping field as an estimate of the number of new wavelets produced. If multiple randomly occurring wavelets are the "engine" that maintains fibrillation, there should be an equal/neutral or positive balance between the number of wavelets created and the number destroyed so that a critical number of wavelets still remains. In such a schema, the number of wavelets leaving our mapping field should be equal to or greater than the number of wavelets entering that field. In our experiments, despite a large number of wavebreaks, multiple wavelets were in general constrained to the mapping field (E:L ratio >1), except when a periodic source of activity (ie, rotor or breakthrough) was found. This suggests that the breaking of waves, although effective in producing large numbers of wavelets in the mapping region, was not a robust mechanism of new wavelet production for the ventricle as a whole.
The question then becomes, if multiple wavelets are not maintaining this complex arrhythmia, then what is? Our data are the first to show that spatiotemporally periodic waves are important contributors to the frequency content of VF and hence are important for the maintenance of VF. Moreover, these spatiotemporal periodic sources were always cycling at the fastest frequency so that the rest of the tissue could not keep up in a 1:1 manner. The coexistence of short-lived wavelets with periodic activity mostly in the form of breakthroughs strongly suggests that fibrillatory conduction away from relatively stable intramural scroll waves17 underlies VF in our experimental model.
| Acknowledgments |
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Received August 5, 1999; accepted October 13, 1999.
| References |
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M. P. Nash, A. Mourad, R. H. Clayton, P. M. Sutton, C. P. Bradley, M. Hayward, D. J. Paterson, and P. Taggart Evidence for Multiple Mechanisms in Human Ventricular Fibrillation Circulation, August 8, 2006; 114(6): 536 - 542. [Abstract] [Full Text] [PDF] |
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J. P. Daubert, W. Zareba, W. J. Hall, C. Schuger, A. Corsello, A. R. Leon, M. L. Andrews, S. McNitt, D. T. Huang, A. J. Moss, et al. Predictive Value of Ventricular Arrhythmia Inducibility for Subsequent Ventricular Tachycardia or Ventricular Fibrillation in Multicenter Automatic Defibrillator Implantation Trial (MADIT) II Patients J. Am. Coll. Cardiol., January 3, 2006; 47(1): 98 - 107. [Abstract] [Full Text] [PDF] |
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Z. Qu and J. N. Weiss Effects of Na+ and K+ channel blockade on vulnerability to and termination of fibrillation in simulated normal cardiac tissue Am J Physiol Heart Circ Physiol, October 1, 2005; 289(4): H1692 - H1701. [Abstract] [Full Text] [PDF] |
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T. H. Everett IV, E. E. Wilson, S. Foreman, and J. E. Olgin Mechanisms of Ventricular Fibrillation in Canine Models of Congestive Heart Failure and Ischemia Assessed by In Vivo Noncontact Mapping |