Rectification of the Background Potassium Current
A Determinant of Rotor Dynamics in Ventricular Fibrillation
Faramarz H. Samie, Omer Berenfeld, Justus Anumonwo, Sergey F. Mironov, Sharda Udassi,
Jacques Beaumont, Steven Taffet, Arkady M. Pertsov, José Jalife
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Abstract—Ventricular fibrillation (VF) is the leading cause of sudden cardiac death. Yet, the mechanisms of VF remain
elusive. Pixel-by-pixel spectral analysis of optical signals was carried out in video imaging experiments using a
potentiometric dye in the Langendorff-perfused guinea pig heart. Dominant frequencies (peak with maximal power)
were distributed throughout the ventricles in clearly demarcated domains. The fastest domain (25 to 32 Hz) was always
on the anterior left ventricular (LV) wall and was shown to result from persistent rotor activity. Intermittent block and
breakage of wavefronts at specific locations in the periphery of such rotors were responsible for the domain
organization. Patch-clamping of ventricular myocytes from the LV and the right ventricle (RV) demonstrated an
LV-to-RV drop in the amplitude of the outward component of the background rectifier current (IB). Computer
simulations suggested that rotor stability in LV resulted from relatively small rectification of IB (presumably IK1),
whereas instability, termination, and wavebreaks in RV were a consequence of strong rectification. This study provides
new evidence in the isolated guinea pig heart that a persistent high-frequency rotor in the LV maintains VF, and that
spatially distributed gradients in IK1 density represent a robust ionic mechanism for rotor stabilization and wavefront
fragmentation. (Circ Res. 2001;89:1216-1223.)
Key Words: ventricular fibrillation 䡲 rotors 䡲 optical mapping 䡲 inwardly rectifying potassium channels 䡲 IK1
V
entricular fibrillation (VF) is traditionally attributed to
multiple randomly wandering electrical wavelets, ever
changing in direction and number.1 However, a new idea
based on theoretical2 and experimental3 studies postulates
that “rotors” are the major organizing centers of fibrillation.
Thus, two divergent mechanisms for the maintenance of VF
have come to light. Some workers propose that VF results
from the instability of rotors, which ultimately leads to their
breakup.4,5 Alternatively, other investigators hypothesize that
fibrillation is maintained by wavefronts emanating at an
exceedingly high frequency from a relatively stable rotor.6 –9
Accordingly, fibrillatory conduction is the result of the
interaction of such wavefronts with anatomical and functional
obstacles, and not the breakup of the source.
Consistent with the stable source hypothesis, recent studies
demonstrated spatiotemporal periodicities10 and domain-like
distribution of excitation frequencies11 during VF. Such
results suggested that VF may have an underlying organization. Using high-resolution optical mapping, we present new
evidence in the isolated Langendorff-perfused guinea pig
heart that demonstrates that VF may be the result of a highly
periodic reentrant source, which may remain stable for more
than 100 rotations. Moreover, using the patch-clamp technique and computer simulations, we demonstrate for the first
time that regional differences in an inward rectifier current
may provide an ionic mechanism for the localization of the
source and the establishment of a consistent gradient of
excitation frequencies during VF.
Materials and Methods
Detailed descriptions of the approaches used in the experiments,
computer simulations, and analyses are presented in the online
expanded Materials and Methods section, available in the data
supplement at http://www.circresaha.org.
Results
Spatial Distribution of Dominant Frequencies
Figure 1 shows an example of the frequency analysis performed on the optical recordings of the fibrillating heart (see
online Materials and Methods for details). In Figure 1A, the
rapid and irregular ECG is typical of VF. Figure 1B shows the
dominant frequency (DF) map.11 The DFs are clustered in
several distinctive and smooth regions termed “domains.”
Here, the right ventricular (RV) DFs range between 10 and 16
Hz, with 14 Hz (light green) constituting the largest domain
on the epicardial surface; the left ventricular (LV) frequencies
range between 14 and 26 Hz. Note that the highest frequency
(26 Hz) is on the anterior LV wall (red). Thus, in contrast to
the complex propagation patterns during VF, the distribution
of DFs is simple. Moreover, the ventricles are activated at
Original received June 11, 2001; revision received October 15, 2001; accepted October 15, 2001.
From SUNY Upstate Medical University, Syracuse, NY.
Correspondence to José Jalife, MD, Department of Pharmacology, SUNY Upstate Medical University, 766 Irving Ave, Syracuse, NY 13210. E-mail
[email protected]
© 2001 American Heart Association, Inc.
Circulation Research is available at http://www.circresaha.org
DOI: 10.1161/hh2401.100818
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Figure 2. Quantification of DF maps. A, Mean DF maps constructed from 9 experiments. Left, Anterior view. Right, Posterior
view. B, Maps of the SD of the DFs. Left, Anterior view. Right,
Posterior view. LAD indicates left anterior descending artery; PD
posterior descending artery. See text for further details.
Figure 1. Frequency analysis of VF. A, ECG trace of VF. B, DF
map. DFs in RV range between 10 and 16 Hz; DFs in LV range
between 14 and 26 Hz. The highest frequency (26 Hz) is found
on the LV anterior free wall. Single pixel recordings and frequency
spectra corroborate the DF map findings. C, Microelectrode recordings. APs recorded from the RV and the LV during VF.
different rates, which results in a gradient of excitation
frequencies.
The presence of rapid frequencies (⬎20 Hz, cycle length
(CL) ⬍50 ms) on the anterior LV wall is intriguing and
implies that the guinea pig action potential (AP) is highly
plastic, since the paced (1 Hz) AP duration is ⬇200 ms.12 To
independently confirm the extremely rapid frequencies during VF in the LV, we recorded electrical activity with an
intracellular floating microelectrode (3 mol/L KCl, 20 M⍀).
Five-second recordings from the RV and the LV, obtained 5
minutes after the initiation of VF, were analyzed. AP CLs
were measured from a 1-second segment chosen at random.
Figure 1C shows representative APs. For this episode, the
mean AP CLs were 38.6 (⬇26 Hz) and 64.12 ms (⬇16 Hz)
for LV and RV, respectively, which correlated well with the
optical data. In 4 microelectrode experiments, CLs on the
anterior LV wall (36.96⫾3.9 ms; mean⫾SD) were significantly briefer than CLs on the RV free wall (63.92⫾17.16
ms; P⫽0.011).
Quantification of Dominant-Frequency Maps
The DF domain configuration (Figure 1B) was consistent
across experiments. To quantify this finding, we constructed
DF maps in nine hearts, which were subsequently aligned,
rescaled, and averaged (see online Materials and Methods for
details). Figure 2A shows the composite DF maps of the
anterior (left) and posterior (right) surfaces. Here, the average
DFs are also organized in domains. Moreover, the locus of
the fastest domain is the anterior LV wall (mean DF⫽26 Hz)
and is much faster than the RV (mean DF⫽15 Hz). To
substantiate the difference, six sites in the RV were compared
with six sites in the fastest domain (marked 1 to 12), across
the nine hearts. Based on post hoc comparisons using Scheffe’s test, no differences (P⬎⬎0.05) were found among DFs
within the RV (eg, 2 versus 5) or within the LV (eg, 8 versus
11). However, DFs at RV sites were significantly different
(10⫺3⬎P⬎10⫺8) from DFs at LV sites (eg, 5 versus 9).
The standard deviation (SD) of the mean DFs for each
pixel was used to construct an SD map (Figure 2B). The SD
is lowest (0 to 2 Hz) in the free walls of the ventricles and is
largest in the periphery and in between the major domains.
Hence, both domain organization and hierarchy of frequency
gradients are preserved among animals.
Nature of the Fastest DFs
In Figure 3A, we present the ECG from another heart during
VF. In Figure 3B, the DF map shows the LV-to-RV gradient
of DFs. Further analysis demonstrated that in fact a relatively
stable high-frequency rotor was responsible for the fastest DF
domain in the LV. Figure 3C shows snapshots of the rotor at
4 different times during one rotation. In this example, the
rotor was on the epicardial surface for ⬇150 rotations at 32
Hz (see online data supplement for videoclip of this VF
episode). Thus, the activity of a high-frequency rotor gave
rise to the fastest DF domain in this heart.
To establish the contribution of rotor activity to the fast
frequency domain in the other eight hearts, 11 rotors were
identified. We calculated the frequency of each rotor and
correlated it with the fastest DF. A strong correlation
(R⫽0.95) existed between the two parameters, suggesting
that the rotor was the main contributor to the frequency of the
fastest domain. However, despite the stability of the highest
frequency domain in the LV, and the excellent correlation
between the rotation frequencies and the highest DFs, inspection of the LV epicardium revealed rotors of variable persistence (range, 4 to 150 rotations). Thus, while it is likely that
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Figure 3. High-frequency rotor. A, ECG trace of VF. B, DF map showing the LV-RV gradient in frequencies. C, Snapshots of a longlasting rotor on the anterior LV wall at 4 different times during one rotation. Numbers in panel B are in Hz; numbers in panel C
are in ms.
all dominant rotors remained in the anterior LV wall, some
probably took an intramural position13 and thus were hidden
from view.
Fibrillatory Conduction as a Mechanism for VF
Phase analysis aids in the identification of the center of
rotation and highlights wavebreaks occurring when fronts
collide with refractory tails or other obstacles.7,8,10 Figure 4
shows a series of phase maps (see online Materials and
Methods for technical details) of the anterior wall depicting
the behavior of the same rotor as in Figure 3, for one
complete rotation. Colors reflect phases of the AP: upstroke is
colored green, plateau is blue and violet, and refractory tail is
red and yellow. A phase singularity (PS) point is the location
at which all phases (ie, colors) converge, and the continuous
spatial changes reflect the full cycle of excitation, repolarization, and recovery.7 Numbers identify PSs (eg, PS 1 marks the
center of rotation) and are used to track the activity. The maps
show that PS 1 is stable and that the wavelet it flanks serves
as a source of new wavelets in its surrounding. At t⫽0 ms, 4
PSs are present on the epicardial surface defining 2 distinct
waves; PSs 1 and 2 flank the source wave, and PSs 3 and 4
flank a daughter wavelet. As the source wave continues to
rotate, it breaks in its periphery producing new wavelets. This
is evident at t⫽5 ms when the source wave originally
bounded by PSs 1 and 2 breaks up at PS 5. The source is then
flanked by PSs 1 and 5, and a new wavelet bounded by PSs
2 and 6 is generated. The process continues as the source
wave (now bounded by PSs 1 and 5) undergoes further
breakup at PS 7, giving rise to a new wavelet bounded by PSs
5 and 8 at t⫽10 ms. Some of the wavelets formed undergo
decremental conduction and die. For example, the wavelet
flanked by PSs 2 and 6, which is visibly formed as the result
of the rotation and breakup of the arm of the rotor, dies
between t⫽15 and t⫽20 ms. Others undergo one or more
rotations and then terminate spontaneously by collision with
another wavefront (data not shown). Still others (eg, PSs 5
and 8) exit the field and vanish elsewhere. Clearly, the
Figure 4. Phase maps demonstrating a stable high-frequency rotor producing multiple wavelets. Numbers below frames are time in ms.
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single narrow frequency peak indicate 1:1 activation. In
contrast, at site b, located at the boundary between the fastest
and slowest domains, the optical APs are irregular. The
small-amplitude depolarizations (marked by arrows) reflect
intermittent blockade of impulses initiated within the fastest
domain. Their timing coincided with the presence of PSs.
Intermittent block and wavebreaks are also reflected in the
spectrum, which shows two distinct peaks (13 and 32 Hz)
whose similar amplitudes depict the almost equal contribution of both fast and slow domains at that location. A number
of smaller peaks in the power spectrum reflect the contribution of the other neighboring domains, namely those corresponding to 18, 20, and 27 Hz. Similar to site a, at site c,
located within the 13-Hz domain in the RV, the regular
morphology of the APs and the single narrow peak in the
spectrum suggest that this region is activated rhythmically at
the slower frequency. Therefore, the data suggest that spatially distributed wavebreaks and conduction block may be a
mechanism for the formation of DF domains.
Quantification of Spatial Distribution
and PS Lifespan
Figure 5. Spatial distribution of phase singularities. A, Contours
of DF domains shown in Figure 3 superimposed on the spatial
histogram of PSs. Most PSs occur near domain boundaries. B,
Optical APs and their corresponding frequency spectra. At sites
a and c, the morphology of optical APs is regular, which is also
reflected in the single narrow band of the FFT. At site b, the
APs are irregular and the amplitude alternates. The smallamplitude APs, marked by red arrows, reflect blocked beats,
and their timing coincides with a PS. C, Composite spatial distribution of PSs (6 hearts) during VF.
breakup of waves from a stable high-frequency source gives
rise to complex patterns of activation, consistent with VF.
Spatial Distribution of Phase Singularities
From the foregoing, it is evident that a high-frequency
stationary rotor may be a source of PSs and wavelets. To
understand the relation between DF domains and PSs, we
characterized the spatial distribution of PSs by marking their
location for 1 second during VF. Figure 5A outlines the DF
domains (black lines) shown in Figure 3 with a superimposed
spatial histogram of PSs (colored squares). The black circle
marks the center of rotation. Most PSs are located near the
boundaries of the DF domains suggesting that wavebreaks
occur near those boundaries. Close to the source, activation of
the LV is 1:1, but at an intermediate distance, corresponding
to the boundaries of the fastest domain, wavebreaks and
intermittent block develop. Beyond such boundaries, slower
DF domains are created where excitation is again periodic,
albeit at a slower frequency. Figure 5B shows optical APs and
corresponding frequency spectra obtained by fast Fourier
transformation (FFT) of signals from 3 sites marked in panel
Figure 5A (black squares). At site a, located within the 32-Hz
domain, the regular morphology of the optical APs and the
To determine whether wavebreaks constitute a general mechanism for the formation of DF domains, we further identified
the position of PSs in six experiments (see online Materials
and Methods for details). Figure 5C outlines the major DF
domains (black lines) of the anterior composite DF map
(Figure 2A). Superimposed on that image is the composite
spatial histogram of PSs (colored squares). Once again, the
majority of PSs occurred at the boundary of the fastest
domain. We also measured the lifespan of PSs7 and hence
indirectly the lifespan of wavelets. During VF, the mean
lifespan of PSs was 22 ms (range, 3.2 to 100 ms), with 50%
of the PSs lasting ⬍15 ms. Further analysis revealed that the
average lifespan of PSs in the fastest frequency domain was
43.5 ms (range, 3.3 to 275.6 ms), whereas the average
lifespan of PSs elsewhere was significantly briefer at 17.1 ms
(range, 1.7 to 80.2 ms; P⫽0.00016) with 50% of PSs lasting
⬍13.6 ms. Given that the rotation period for the rotors in the
LV is 37.04⫾3.8 ms, the short lifespan and location of the
majority of PSs suggest that they are the result of breakup
from distant periodic sources and, therefore, most likely not
maintaining VF. Overall, the data further support our conclusion that wavebreaks and spatially distributed intermittent
block are responsible for the domain-like distribution of DFs.
The Background Current
Simulations previously demonstrated the importance of the
background inward rectifier current (IK1) in the establishment
of fast and stable reentry.9 Thus, we hypothesized that the
stabilization of the high-frequency rotor in the LV may result
from chamber-specific differences in IK1. We used the wholecell voltage-clamp technique to characterize the background
current in the RV and the LV and relate its spatial distribution
to the excitation frequencies and stability. Figure 6A shows
the I-V relations of the background current, IB, (most likely
IK1, see Technical Limitations) of two different cells from the
LV and the RV in the same heart. The outward conductance
of IB is clearly larger in the LV cell than in the RV cell.
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Figure 6. I-V relations for IB. A, Current-density voltage relation
of IB for sample cells from the RV and LV of the same heart.
Inset, Voltage-clamp protocol. B, Mean I-V relation for IB
(nRV⫽18 and nLV⫽19). Currents were normalized to cell capacitance and averaged. Mean RV and LV capacitances, 165 and
167 pF, respectively.
Similar results were obtained for 19 LV cells and 18 RV cells
from 10 hearts. Figure 6B shows the mean I-V relations.
Clearly, the outward conductance is significantly higher in
the LV than the RV (⫺50 mV: RV 5.3⫾0.4; LV 7.4⫾0.6
pA/pF, P⫽0.009).
Computer Simulations
To understand the effect of the difference in the LV and RV
background currents on VF dynamics, we used the respective
experimental mean IB (Figure 6B), in a 2-dimensional computer model (see online Materials and Methods for details on
the model and its parameters). Figure 7A shows simulated
steady-state I-V relations (IK1) for the LV (solid line) and RV
(broken line), superimposed on the corresponding experimental data (see Figure 6), and the respective simulated singlecell APs obtained at 1 Hz. The reduced outward component
of IK1 in the RV resulted in a longer AP than the LV. Figure
7B shows four snapshots of the simulations (3⫻3-cm2 sheets)
with the inward rectifying properties of the RV (top frames)
and the LV (bottom frames), ie, small and large IK1, respectively. Strong rectification in the RV model resulted in
unstable, ie, self-terminating reentry. In contrast, the smaller
degree of rectification in the LV model resulted in a stable
and persistent high-frequency rotor (33 Hz, CL⫽30 ms).
Hence, the relatively large outward component of the background current may play an important role in stabilizing
reentry in the LV.
To more closely approximate the experimental situation,
we combined the two models. Two representative frames of a
simulation using a 6⫻6-cm2 sheet containing the LV in the
center (2⫻2 cm2), and the RV in the periphery are shown in
Figure 7C. In both frames, the stationary vortex in the LV
gives rise to waves that propagate into the RV. However,
dynamic nonuniformity results in wavefront fragmentation,
decremental conduction, and intermittent block, with occasional formation of short-lived rotors near the edges of the
sheet (see online data supplement for videoclips). Such rotors
are either invaded by incoming waves or they self-terminate
(Figure 7B). To quantify such behavior, we carried out
additional simulations using sheets of three different RV
sizes, in which we documented the formation of 20 randomly
chosen rotors (PSs) and measured their lifespan. The size
(2⫻2 cm2) and central position of the LV were kept constant,
while the total size of the sheet was changed. When the sheet
was 4⫻4 cm2, the lifespan of the PSs in the RV was 73⫾93
ms (mean⫾SD) with a median of 27 ms. When a sheet of
6⫻6 cm2 was used, the lifespan of PSs in the RV was 61⫾83
ms (median⫽34 ms). Finally, when the sheet was 8⫻8 cm2,
the lifespan of PSs in the RV became 109⫾139 ms (median⫽45 ms). In addition, while the LV rotor CL was 30 ms,
the RV rotors that lasted at least one rotation had a CL of 40
to 50 ms. The somewhat longer lifespan of the RV rotors in
the simulations than in the experiments most likely reflects
the proximity of the rotors to the boundaries of the sheet,
which protected them from invasion and annihilation by
incoming wavefronts from the LV. Obviously such boundaries do not exist in the experimental situation. Nevertheless,
these data demonstrate that while rotors did form in the
simulated RV, they were always slower and relatively shortlived, regardless of the size of the sheet.
In Figure 7D, we present a DF map of the 6⫻6-cm2 LV-RV
model, to allow for quantitative comparison with the experimental results. As in the experiments, there is a sharp drop in DF
from 33 Hz in the LV to 17 to 20 Hz in the RV. Overall, these
data support the idea that the amplitude of the outward component of the background current plays a role in establishing the
maximum allowable rate of local activation during VF.
Discussion
The major finding of this study is that VF in the isolated
guinea pig heart is characterized by a consistent gradient in
dominant activation frequency from the LV to the RV. Such
a gradient may result from a significant difference in the
density of the background current, presumably IK1, between
the two ventricles. Further, the high-frequency activity found
in the LV is likely to result from persistent rotors that sustain
VF. The finding of chamber-specific differences in the
background current was demonstrated numerically to represent a possible ionic mechanism for the stabilization of the
high-frequency rotors in the LV, along with wavefront
fragmentation in their periphery, and for the relative lowfrequency activity elsewhere, including the RV.
Mechanisms of VF
Previously, Rogers et al14 found reentry in ⬇30% of VF cases
in pig hearts; it was mostly short-lived, and tended to cluster,
although in different regions across animals. Although other
potential mechanisms cannot be ruled out, such results are
Samie et al
Potassium Current as a Determinant of VF Dynamics
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Figure 7. Computer simulations. A, Formulation of IK1 used in the model (solid and
broken lines) with corresponding APs. Mean
experimental data from Figure 6B (circles)
are superimposed. B, Snapshots of numerical data; 3⫻3-cm2 sheets simulating the RV
(top) and LV (bottom). C, Snapshots of
numerical data in the combined RV-LV
model of 6⫻6 cm2. D, DF map obtained
from the model in panel C. Values in panels
B and C are in ms; in panel D, in Hz. Broken lines in panels C and D show the
perimeter of the LV model (area, 2⫻2 cm2).
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consistent with the idea that VF is maintained by stable
source(s), with fibrillatory conduction of the waves that
emanate from them. Indeed, recent data showed that fibrillatory conduction is present during VF in the rabbit heart7,8 and
in the isolated sheep ventricular preparations.11 Those studies
demonstrated that rapidly emanating wavefronts from reentrant sources propagate throughout the ventricles and intermittently block, giving rise to wavelets, and DF domains.
Consequently, fibrillatory conduction from a stable source
may account for the complex patterns of wavefront propagation, together with the organization that is documented in
VF.14,15 Our analysis of the lifespan of PSs, which result from
fibrillatory conduction and reflect the lifespan of wavelets,
suggests that they are too brief (mean lifespan ⬇17 ms) to
maintain VF. Additionally, their location in the periphery of
the fastest domain (see Figures 2 and 5) is consistent with
wavebreaks and block of waves emanating from a highfrequency source.
Gradients of excitation frequency have been shown to exist
both during atrial fibrillation in sheep16,17and dogs18 and VF
in swine.19 Our study in the guinea pig heart is the first to
show a highly consistent localization of a stable highfrequency source in the LV. Moreover, this study is the first
to describe the maintenance of fibrillation with a correlation
to its stationary properties, namely, the LV-to-RV gradient of
excitation frequencies. The finding that ionic current differences between the RV and the LV are also highly consistent
suggests an ionic mechanism for the formation of a relatively
stable high-frequency source in the LV and for the establishment of an LV-to-RV frequency gradient.
Mechanisms of Rapid Reentry and Rotor Stability
During VF, the activation rate is significantly faster than that
achievable by either pacemaker activity or rapid pacing.20
Similarly, in our experiments, rotors have significantly
briefer CLs (⬇30 to 40 ms) than expected from the guinea pig
heart whose action potential duration (APD) is ⬇200 ms
during sinus rhythm.12 Computer simulations suggest that
extremely fast rotors may be the result of the strong repolarizing influence exerted by their core, which activates IK1 and
leads to extreme abbreviation of the APD in its proximity.21
However, with increasing distance from the core, this influence weakens and APD progressively increases. Consequently, the tissue close to the core achieves very brief CLs,
whereas far from the core the myocardium cannot conduct at
the rate of the rotor and nonuniform (ie, other than 1:1)
conduction develops. In theory, this effect may provide a
basis for the results shown in Figure 5 demonstrating that
propagation near the rotor was 1:1, and that, at a certain
distance from the rotor, intermittent block and wavebreaks
developed and slower DF domains were formed. Nevertheless, this mechanism does not explain the consistent localization of the rotors to the anterior free wall of the LV.
Regional differences in currents,22 influencing repolarization, may influence the dynamic behavior of rotors and thus
arrhythmias.23 We focused on differences in IK1 density in the
LV and the RV because, in addition to controlling the APD,
a large IK1 stabilizes the rotor.21 This reasoning is further
supported by our current simulations. Upon the incorporation
of the experimental I-V relation of IB into our ionic model, the
large outward conductance in the LV produced both the
necessary abbreviation of the APD for the establishment of
high-frequency activity and stability in terms of persistence
of the rotor. In contrast, the model with small outward
conductance of IB, simulating the RV, was unable to sustain
stable reentry. These results confirm previously published
computer simulations, which demonstrated that when the
outward component of IB is small, the wavetail close to the
core propagates more slowly than the wavefront.21 Consequently, wavefront-wavetail interactions develop, producing
meandering and eventual termination due to collision with the
edges of the sheet (Figure 7B). When the LV and RV models
were coupled (Figure 7C), the LV sustained stable reentry. In
contrast, wavefront fragmentation, decremental conduction,
and intermittent block were most notable in the RV.
These data suggest that the larger amplitude of the LV
background conductance may stabilize the rotor in the LV by
reducing the APD near the core, thus leading to a decrease in
the degree of wavefront-wavetail interactions. On the other
hand, the stronger rectification of IB in the RV should prolong
APD. Consequently, the RV will be unable to conduct at the
frequency of the stable source in the LV (see Figure 1). This
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does not imply, however, that the RV is incapable of
undergoing reentry. Rather, the large difference in the outward component of IK1 suggests that, if rotors are formed in
the RV, their frequency will be relatively slow and they will
be less stable than in the LV.
Structural Mechanisms of Rotor Stabilization
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Kim et al24 suggested that source-sink mismatch between a
papillary muscle and the ventricular wall may serve to anchor
the rotor. Thus, the two papillary muscles in the LV of the
guinea pig heart, which insert in the LV apex and anterior LV
wall, may conceivably help to stabilize the rotor. However, in
contrast to the experiments of Kim et al24 in which reentry
was often terminated by the other wavelets that existed during
VF, we observed that the reentrant source remains stable
within the field of view as long as 150 rotations, at least in
one case (Figure 3). Nevertheless, as 3-dimensional scroll
waves are predicted to align their filaments according to the
myocardial fibers,13 we cannot rule out the possibility that
structures in the LV may somehow stabilize the reentrant
circuit.
Other Ion Channels and VF
The demonstration of differences in IK1 density in the LV and
the RV myocytes seemed sufficient to account for many
aspects of VF dynamics and allowed us to reproduce very
closely the experimental results using computer models in
which other channels are uniformly distributed. Nevertheless,
Beaumont et al9 demonstrated that INa has a major role in the
stabilization of spiral-wave reentry and modulates the transition from VF to monomorphic ventricular tachycardia
(MVT). Thus, we cannot exclude a role of INa characteristics
in the dynamics observed. Similarly, ICa blockade was demonstrated to stabilize reentry and convert VF to MVT by
reducing rotor frequency and wavefront fragmentation.8 Consequently, we cannot discount the involvement of ICa in the
observed phenomena. Moreover, while we focused on structurally normal hearts, in diseased hearts, other currents (eg,
IKATP) may play an important role in the manifestation of the
arrhythmia.25
Fibrillation in Other Species
In the present study, we clearly supported the hypotheses that,
in the structurally normal guinea pig heart, a stable reentrant
source is the underlying mechanism of VF, and that the
stabilization of the source and complexity seen in VF may be
the result of regional differences in potassium currents.
Nevertheless, fibrillation may span a spectrum of mechanisms. For example, Gray et al10 demonstrated that theoretically each rotor occupies a minimum area. Thus, small hearts,
eg, guinea pig and rabbit, can accommodate only a few (1 or
2) rotors, whereas in larger hearts, eg, sheep, dogs, and
humans, a greater number of rotors may exist during VF.
Moreover, the electrophysiological properties of myocytes of
different species vary greatly,22 and such heterogeneity across
species again may influence rotor behavior and arrhythmia
manifestation. Therefore, the frequencies observed here,
which are significantly faster in comparison to the DF
frequencies reported in other species,8,10,19 may be due to the
unique ionic makeup of the guinea pig myocytes. Finally, in
particular hearts, a single drifting rotor may produce fibrillatory dynamics, whereas in other hearts, a stable source within
the ventricles may be responsible for VF, and still in other
hearts, larger numbers of stable or drifting rotors may coexist,
with each dominating a region of the ventricle and thus
producing fibrillation. These alternatives are not mutually
exclusive in that vortex-like reentry is most likely underlying
fibrillation.
Technical Limitations
The limitations of optical mapping and signal analysis have
been discussed at length elsewhere.7,8,26 The current densityvoltage relationship of IB recorded here shows a reversal
potential of ⫺84 mV and inward rectification, which suggests
that IB is predominantly IK1.27 However, potential contaminants may be present (eg, INa). However, this is very unlikely
since IB was activated by a slow ramp (1.6 mV/s), which
probably inactivated fast inward sodium channels. In addition, in a subset of experiments (5 cells), there was no
significant difference in the current before and after administration of tetrodotoxin (30 ␮mol/L). Further, the use of
nifedipine (2 ␮mol/L) eliminates contamination by the L-type
calcium current. Because no sodium ions were included in the
pipette solution, the activity of the Na⫹-K⫹ pump was
minimal.27 Finally, because the pipette solution contained
5 mmol/L of EGTA and no calcium ions, the activity of the
Na⫹-Ca2⫹ exchanger should also be minimal.27 We therefore
believe that the background current IB is mostly IK1. However,
it will be necessary to carry out single-channel studies with
the appropriate pharmacological treatments to firmly establish this. Finally, the limitations of the computer model are
described elsewhere.9 However, please note that sarcolemmal
currents, such as inactivation of the calcium current, the
sodium-calcium exchanger, and the calcium pump, although
important in the regulation of APD, were not incorporated
here because when there are too many parameters, the model
becomes underdetermined with respect to the experimental
data.9
Acknowledgments
This work was supported by grants PO1 HL39707 and HL60843
from the NHLBI and grants from the NIH (1S10RR12917) and the
Whitaker Foundation (to J.B.). We thank Jiang Jiang, Fan Yang,
Robert Morton, Matthew Brunson, and Ploy Siripornsawan for
assistance; Janet Jackson for secretarial support; and Dr Eduardo
Solessio for insightful discussions. Simulations were performed at
supercomputer centers of Boston University, UC San Diego, and on
a Sun E6500 at SUNY Upstate Medical University.
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Rectification of the Background Potassium Current: A Determinant of Rotor Dynamics in
Ventricular Fibrillation
Faramarz H. Samie, Omer Berenfeld, Justus Anumonwo, Sergey F. Mironov, Sharda Udassi,
Jacques Beaumont, Steven Taffet, Arkady M. Pertsov and José Jalife
Circ Res. 2001;89:1216-1223; originally published online October 25, 2001;
doi: 10.1161/hh2401.100818
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