(Circulation. 2000;101:533.)
© 2000 American Heart Association, Inc.
Basic Science Reports |
Noninvasive ECG Imaging of Electrophysiologically Abnormal Substrates in Infarcted Hearts
A Model Study
From the Cardiac Bioelectricity Research and Training Center and the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (J.E.B., Y.R.), and the Cardiovascular Research and Training Institute, University of Utah, Salt Lake City (B.T., R.S.M.).
Correspondence to Yoram Rudy, Cardiac Bioelectricity Center, 505 Wickenden Bldg, Case Western Reserve University, Cleveland, OH 44106-7207. E-mail yxr{at}po.cwru.edu
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Abstract |
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Background—Myocardial infarction and subsequent remodeling create substrates with altered electrophysiological (EP) properties that are highly arrhythmogenic. Existing ECG methods cannot always detect the existence of such substrates nor provide any detailed information about their EP characteristics. A noninvasive method with such capabilities is greatly needed for identifying patients at risk of arrhythmias and for guidance and evaluation of therapy. Recently, we developed a noninvasive ECG imaging modality that can reconstruct epicardial EP information from body surface potentials. We extended its application to hearts with structural disease and examined its ability to detect and characterize abnormal EP substrates.
Methods and Results—Epicardial potentials were recorded with a 490-electrode sock from an open-chest dog. Recordings were obtained from a normal heart and from the same heart 2 hours after left anterior descending coronary artery occlusion and ethanol injection to create an infarct. Body surface potentials were generated from these epicardial potentials in a human torso model. Realistic geometry errors and measurement noise were added to the torso data, which were then used to noninvasively reconstruct epicardial potentials and electrograms (EGMs), with excellent accuracy. EP characteristics associated with the infarct substrate were reconstructed, including (1) a negative region over the infarct, (2) EGMs with large predominant negative deflections (eg, Q-wave EGMs), (3) Q-wave EGMs with superimposed RS deflections reflecting local activation of surviving myocardium within the infarct border zone, (4) reduced magnitudes of EGM negative derivatives, and (5) negative QRS integrals of EGMs over the infarct.
Conclusions—ECG imaging can noninvasively detect and map abnormal EP substrates associated with infarction and structural heart disease.
Key Words: infarction • electrocardiography • potentials
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Introduction |
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Myocardial infarction and subsequent remodeling creates altered electrophysiological (EP) substrates that are highly arrhythmogenic.1 Experimental and clinical data from infarcted hearts have helped to define measures for identifying abnormal EP substrates2 3 4 5 and for stratifying their arrhythmogenic potential.6 7 Identification of arrhythmogenic substrates before an arrhythmia occurs could reduce the risk of sudden death by indicating the need for device, drug, or ablation therapy. Current noninvasive methods for assessing abnormal EP substrates rely on ECG measurements from the body surface.8 These methods cannot provide detailed EP information about the cardiac substrate. ECG imaging (ECGI) is a noninvasive method for reconstructing EP information on the heart surface from body surface measurements. Studies from our laboratories9 10 11 demonstrated that ECGI can accurately reconstruct epicardial potentials, electrograms (EGMs), and isochrones in normal hearts. The purpose of this study was to evaluate the ability of ECGI to noninvasively locate and characterize abnormal cardiac EP substrates associated with myocardial infarction.
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Methods |
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A combination of experimental and modeling methods were used to evaluate ECGI with the use of measured epicardial potentials in an accurate heart-torso model. Figure 1A
shows the strategy used. Epicardial potential maps were recorded
from a single anesthetized dog. The heart was exposed through a
sternotomy, and a sock with 490 unipolar silver electrodes was pulled
over the heart. Unipolar signals were recorded with respect to the
left leg. The system simultaneously sampled 490 electrodes
at 1 kHz with 12-bit resolution and a frequency response of 0.03 to 500
Hz. Potentials were recorded during anterior left
ventricular (LV) epicardial pacing and right atrial (RA)
pacing (simulating sinus rhythm). Stimulation was by 2-ms current
pulses at twice diastolic threshold. A region of
infarcted/necrotic tissue was then created by ligating the left
anterior descending coronary artery (LAD) distal to the first
diagonal branch (Figure 1B). A needle was inserted into the LAD
and 2 mL of a 50:50 ethanol/saline solution was injected. The estimated
area perfused by the LAD is outlined in Figure 1B, showing the
expected region of infarction created by the combined arrest of blood
flow and necrotizing effect of ethanol. This protocol yields a
border-zone infarct similar in dimensions to the 5-day-old LAD
occlusion model.12 A 10- to 20-mV ST elevation was
observed over this region after occlusion-injection, which fell to 3 to
4 mV after 2 hours. The same pacing protocols as in the preinfarction
heart were repeated 2 hours after occlusion-injection, when the infarct
was well developed. As in our previous studies,9 10 11 ECGI
reconstructed potentials were evaluated by direct comparison to
measured epicardial potentials in the same heart.
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The mathematics of ECGI and modeling methods used here have been described previously.9 13 Importantly, computation of epicardial potentials from body surface potentials using the ECGI method only requires information that can be obtained noninvasively. In this study, epicardial potentials at all 490 epicardial points were noninvasively computed at 1-ms increments throughout the cardiac cycle. Potentials were displayed in space for a single instant of time to create epicardial potential maps and in time for a single point in space to create epicardial EGMs. The general quality of reconstructed potential maps and EGMs was evaluated with respect to measured data using absolute error (AE), relative error (RE), and correlation coefficient (CC) (RE and CC were defined previously).13 The AE is an average of absolute differences between measured and reconstructed potentials at each point in space for potential maps and each point in time for EGMs. The average AE, RE, and CC presented for potential maps were averaged over all reconstructed time frames. The average AE, RE, and CC presented for EGMs were averaged over all 490 epicardial points. Epicardial isochrones were created with the use of epicardial activation times determined as the time of maximum negative derivative (-dV/dtmax) in the EGMs. QRS integrals were computed for each EGM by summing the potentials over the QRS window determined using lead II.
Potentials recorded from the open-chest heart were placed on a
digitized 3-D stylized canine heart model and aligned on the basis of
positions of coronary arteries (eg, LAD). The heart model was
mathematically placed in its anatomic position within a homogenous
computer model of the human torso, constructed using 458 nodes.
Potentials on the torso surface were computed from the measured
epicardial potentials (Figure 1A
).13 The reference
of the computed torso surface potentials was converted from the left
leg to a Wilson central terminal. A 12-lead ECG was derived with the
use of torso potentials from the standard surface positions shown in
Figure 1C. Fifty-microvolt peak-to-peak gaussian noise
(typically 0.5% of the signal) was added to the computed torso
potentials and 1 mm-gaussian geometric error was added to the
torso surface points. We based the levels of signal noise and geometric
error on previous, detailed studies13 and our experience
with clinical data acquisition. The clinical ECGI procedure currently
being evaluated at Case Western Reserve University obtains body surface
electrode positions with the use of a 3-D digitizer with better than
1-mm accuracy. Simulations in which added signal and geometric noise
are both doubled result in only modest increases (on the order of 10%)
in RE and AE and minimal reductions in CC, reflecting the effectiveness
of the regularization procedure used in the ECGI
reconstructions.13 The computed torso potentials,
contaminated by measurement noise and position errors, were then used
as inputs to noninvasively compute epicardial potentials with the use
of the ECGI methodology.
The combination of the measured epicardial potentials and the heart-torso model used in this study provides a well-controlled tool for evaluating the ability of ECGI to noninvasively reconstruct epicardial potentials, EGMs, and isochrones in an infarcted heart. The directly measured preinfarction and postinfarction epicardial potential maps provide physiologically realistic data for evaluation of the noninvasively reconstructed epicardial potentials. The use of ethanol results in fast infarct formation, allowing for the infarcted heart to be its own control. These features facilitate a rigorous evaluation of ECGI in the context of electrophysiologically abnormal substrates in the presence of structural heart disease.
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Results |
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Standard 12-Lead ECG
Figure 2
shows a standard 12-lead
ECG derived from the computed torso potentials. The 12-lead ECG from
the preinfarction heart (top panel) serves as control and illustrates
that the model generates clinically realistic data on the torso
surface. The ECG is consistent with that of a normal subject,
as characterized by several properties such as the progression from
negative in V1 and V2 to
isoelectric in V3 to positive in
V4 to V6. Precordial
lead V3 exhibits a notch that reflects a similar
notch in the epicardial EGM near the site of right
ventricular breakthrough (RVBT, arrival of the activation
front at the epicardium and beginning of epicardial activation). The
12-lead ECG generated by the infarcted heart (bottom panel) shows the
presence of myocardial infarction when compared with the control ECG in
panel A. ECG features indicating infarction include the appearance of a
Q wave in lead II and deep pathologic Q waves in
V3 and V4. Close
examination of the computed ECGs reveals minor differences compared
with ECGs observed in humans (eg, the positivity in aVR). These
differences can be explained by differences in anatomy between
the human and canine hearts and their different orientation within the
torso.
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Epicardial and Torso Potential Maps During LV Pacing
Figure 3 (top row) shows torso
potentials, measured epicardial potentials, and noninvasively
reconstructed epicardial potentials for the preinfarction heart at 30
ms and 200 ms after pacing. The bottom row shows corresponding
potential maps from the infarcted heart. Paced activation in the
control heart (30 ms) produces the expected elliptical region of
large-magnitude negative potentials (white) around the pacing site.
This elliptical pattern is aligned with the local epicardial fiber
direction.14 A similar pattern (light gray) is observed in
the measured potentials from the infarcted heart. However, although the
potential pattern is similar to that observed in the control heart, the
magnitudes of the potentials are reduced by >50% in the presence of
the infarction in the underlying myocardium. The
noninvasively reconstructed epicardial potentials (obtained with the
use of the ECGI methodology) closely approximate the directly measured
potentials in both the control and infarcted hearts. The
ECGI-reconstructed potentials capture the elliptical negative region
around the pacing site and its orientation along the direction of
epicardial fibers. The 50% reduction of potential magnitudes over the
infarct is also captured noninvasively by ECGI. Potential maps measured
during repolarization (200 ms) show the expected pattern of an
elliptical positive region (dark gray) in about the same position as
the initial negative elliptical region associated with early activation
(30 ms, white). This polarity reversal is characteristic of excitation
during ventricular pacing. Repolarization potentials from
the same time frame in the infarcted heart show a pattern similar to
the control heart, but with reduced magnitudes associated with the
presence of the infarct. The noninvasively reconstructed epicardial
potentials for both the control and infarcted hearts during
repolarization clearly show similar patterns to the directly measured
epicardial potentials, including magnitude reduction in the presence of
the infarct. Errors for the 250 reconstructed time frames in the
control and infarcted hearts are presented in the
Table. Consistent with
previous results from our laboratory,11 the average error
observed throughout depolarization is similar to the error observed
throughout repolarization. This raises the possibility of using ECGI to
investigate repolarization properties such as activation recovery
intervals.
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Epicardial EGMs and Isochrones During LV Pacing
Epicardial EGMs at 4 selected sites are presented in
Figure 4. Site A is located on the right
ventricle (RV), sites B and C are over the infarcted region of the LV,
and site D is over a necrosis free region of the basal LV. Directly
measured and noninvasively reconstructed EGMs are shown for the control
(left panels) and infarcted (right panels) heart. EGMs at sites A and D
show little change after infarct formation because they lie outside the
region perfused by the LAD. The EGM from site B (located over the
region of infarction) shows a 58% reduction in negative peak magnitude
after infarction. The LV EGM at site C, also located directly over the
infarcted tissue, has an RS morphology in the control heart that is
altered to a Q-wave morphology by the presence of the infarct. All EGM
morphologies are reconstructed correctly in both the control and
infarcted heart. The Table summarizes average errors for the 490
reconstructed EGMs in the control and infarcted hearts. In general, all
EGMs around the heart are accurately reconstructed, with anterior EGMs
having slightly higher CCs than posterior EGMs.
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Epicardial isochrones from the LV paced control heart (Figure 5A, top) show the elliptical activation
pattern aligned with the epicardial fibers that is typical of
epicardially paced beats. Isochrones from the infarcted heart
(Figure 5A, bottom) have the same elliptical pattern and
orientation as in the control heart, only with a lower density of
isochrones, indicating an increased propagation velocity away from
the pacing site. The faster conduction could be due to reduced electric
load from intramural myocardium on the epicardial wave
front in the infarcted heart. Isochrones constructed from
noninvasively reconstructed epicardial potentials, in both the control
and infarcted hearts, closely match the directly measured
isochrones. The general activation patterns and the increased
conduction velocity observed in the infarcted heart are accurately
reproduced.
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Epicardial and Torso Potential Maps During RA Pacing
The ability to noninvasively detect, locate, and characterize an
abnormal EP substrate during sinus rhythm is of important clinical
significance because the information can be used to identify patients
at risk of developing life-threatening arrhythmias and to guide
strategies for treatment. Results during RA pacing are
presented in detail below to demonstrate the ability of ECGI to
noninvasively reconstruct abnormal infarct-related EP properties during
simulated sinus rhythm. Figure 6 shows
potential maps from 48 ms (left panels) and 65 ms (right panels) after
pacing. The 48-ms map shows the localized minimum (white) on the RV
associated with RVBT. RVBT occurs in both the control and infarcted
hearts because LAD occlusion leaves the tissue and activation sequences
of the RV unaltered. Comparison of the LV epicardial potentials from
the control heart with those measured from the infarcted heart at 48 ms
shows the formation of a large region of negative potentials over the
infarcted LV (light gray). These negative potentials are a result of
the underlying electrically inactive necrotic tissue, which cannot
support normal spread of activation from endocardium to epicardium.
Activation fronts associated with such spread generate positive
potentials on the overlying epicardium.15 In their
absence, a major positive component is subtracted from the potentials
over the infarct, shifting the balance of potentials in the negative
direction. The contribution of negative potentials is probably from
more remote ("far-field") activation fronts propagating away from
the infarct. The large negative area over the infarct is reflected in
the corresponding torso potentials as an anterior region of negativity.
Notice how the torso surface RVBT minimum is completely hidden in this
negative region despite its presence on the RV epicardium (48 ms,
infarct, measured). Despite this lack of spatial resolution on the
torso surface, ECGI successfully reconstructs from the torso potentials
both the extensive negative potential region over the LV infarct and
the RVBT epicardial minimum (48 ms, infarct, reconstructed). The
zero-potential line that delineates the LV negative and positive
regions closely resembles the directly measured maps. The RVBT
epicardial minimum is also successfully reconstructed for the control
heart, in the absence of infarction (48 ms, control,
reconstructed).
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At 65 ms, the LV epicardial potential map of the control heart shows an
island of large positive potentials, probably reflecting late
activation of this LV free wall region. In contrast, the region of
positive potentials does not form over the infarcted LV, which remains
negative. Note that the torso potentials reflect the negative
epicardial potentials associated with the infarcted heart (65 ms,
infarct), whereas in the control maps, they contain a positive
pseudopod that reflects the positive epicardial region (arrow in torso,
control). However, the torso potentials are smooth and low in
resolution, they do not reflect details of the epicardial potentials,
nor do they provide information regarding the location of potential
features on the heart. ECGI accurately reconstructs the positive region
over the control heart LV and the negative region over the infarcted
heart LV. The Table summarizes errors from RA-paced epicardial
potential map reconstructions.
Epicardial Electrograms During RA Pacing
Figure 7 illustrates EGMs from 4
representative sites. Site A is located on the RV,
sites B and C are located over the infarcted region of the LV, and site
D is over the necrosis-free region of the anterior basal LV. EGMs from
the control heart (column 1) show the expected RS morphology associated
with a sinus beat in a normal heart and contain a sharp intrinsic
deflection (down slope, arrow in A), which indicates local activation
at the electrode site. These EGMs are noninvasively reconstructed with
the same RS morphologies and sharp intrinsic deflections as with
noninvasive ECGI (column 2). The -dV/dtmax of
the intrinsic deflection at site C is -6.5 mV/ms (measured) and -6.0
mV/ms (noninvasively reconstructed). The EGMs recorded from the
infarcted heart (column 3) show changes from control EGMs in regions
overlying the infarct. The EGM recorded at site B is drastically
altered by the presence of the infarct, with the disappearance of the R
wave and appearance of a large Q wave with a superimposed sharp RS
wave. EGMs with large Q waves are known to be associated with
recordings over necrotic tissue and can generally be explained
by the necrotic tissue interfering with the spread of the wave front
toward the recording electrode (a process that generates the
positive R-wave deflection), thereby leaving the electrode to
record mostly far-field activity of wave fronts spreading away from
the infarct. The superimposed RS wave reflects local activation of a
small region of surviving myocardium within the infarct
substrate, close to the recording electrode. Notice that the
noninvasively reconstructed EGM in column 4 reproduces the measured
Q-wave EGM morphology with the superimposed local RS deflection,
demonstrating that ECGI can noninvasively detect local activation of
surviving tissue within the infarcted substrate. The morphology of the
EGM recorded at site C reflects its location at the border of the
infarcted myocardium. The small initial R wave can be
attributed to viable tissue bordering the infarct. After the small R
wave is a large-magnitude, slow negative deflection
(-dV/dtmax=-1.5 mV/ms), indicating reflection
of far-field activity rather than of local activation. The small sharp
downstroke observed near the negative peak may reflect local activation
of local viable tissue within the infarct border zone. This EGM
is noninvasively reconstructed with the use of ECGI, including the slow
downward deflection (-dV/dtmax=-1.8
mV/ms) and the small sharp deflection caused by local activation.
Sites A and D show no change in EGM morphology or amplitude as a result
of the infarct development because they are situated over regions of
the heart that were not affected by LAD occlusion and ethanol
injection. These EGMs are noninvasively reconstructed (column 4) to
have the same RS morphology and amplitude as the directly measured
EGMs. The Table summarizes errors associated with reconstructed
EGMs during RA pacing.
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Noninvasive Localization of
Electrophysiologically Abnormal
Substrate
The ability of ECGI to noninvasively identify the region of
electrically altered myocardium caused by infarction was
evaluated during RA pacing (simulating sinus rhythm) through the use of
several EP properties associated with infarcted hearts. Laxer et
al2 proposed a method for determining infarct location
that uses EGMs with Q-wave magnitudes >2 mV to indicate the presence
of infarcted myocardium below the recording
electrode. Application of this criterion and its extension to include
EGMs containing a predominant slow negative deflection after a small
R-wave yield the regions shown in Figure 8A, marked for both measured (gray lines)
and noninvasively reconstructed (black lines) data. Note how the
regions estimated using the measured and noninvasively reconstructed
data closely resemble each other. A second method for estimating the
location and extent of abnormal substrate is based on the observation
that during RA paced beats, negative epicardial potentials cover the
infarcted region during most of the cycle. The regions outlined in
Figure 8B show areas where the potential was mostly negative,
with maximum positive potential <5 mV. Again, the measured and
noninvasively reconstructed regions closely resemble each other. A
third criterion for estimating the region of altered substrate is a
large negative QRS integral (<-200 mV · ms) in EGMs overlying
the infarct. The QRS integral (unlike the large Q-wave criterion)
considers not only the Q wave but also the superimposed RS deflection
caused by local activation when it is present. Figure 8C
demonstrates close agreement between the noninvasively (black line) and
invasively (gray line) estimated region. Importantly, comparison of the
anatomically estimated region of infarction in Figure 1B to the
regions of abnormal EP substrate estimated with the use of the 3
different criteria of Figure 8, A through C, shows good
correlation.
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Discussion |
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This study is our first demonstration of the application of ECGI in the presence of structural heart disease. Although the model used here is that of myocardial infarction, a similar approach can be applied in the more general context of altered EP substrate caused by EP remodeling. Myocardial infarction (and other remodeling processes) produces a substrate that can be highly arrhythmogenic.1 It is extremely important to identify the existence of such EP substrate in patients before they have a major arrhythmic event that can lead to sudden cardiac death. ECG late potentials,8 presumably reflecting slow conduction in such a substrate, have been suggested as a noninvasive identifier of patients at risk. Unfortunately, this measure found very limited application because of low sensitivity and specificity and difficulties in interpretation of such low level signals that are measured far away from the heart.
The results demonstrate the ability of ECGI to noninvasively
reconstruct, from body surface potentials, characteristics of
epicardial potentials, EGMs, and isochrones that are associated
with abnormal EP substrates. Through these reconstructions, the
existence of such a substrate can be identified and its location and
extent can be determined (Figure 8). The characteristics include
(1) a large region of negative epicardial potentials over the infarct,
(2) EGMs with large predominant negative deflections (eg, Q-wave
EGMs),2 6 (3) Q-wave EGMs with superimposed RS deflections
reflecting local activation of surviving
myocardium,2 6 (4) reduced magnitude of the
EGM maximum negative derivatives, and (5) large negative QRS integrals.
The ability of ECGI to noninvasively provide detailed EP information on
the epicardial surface could be extremely helpful to clinical
electrocardiographers who currently rely on interpretation of the body
surface ECG for noninvasive diagnosis. The quantitative inverse
solution provided by ECGI will permit identification and localization
of arrhythmogenic substrates in the heart.
The ability of ECGI to noninvasively reconstruct small RS deflections
on Q-wave EGMs over the infarct during sinus rhythm (Figure 7)
has important clinical and mechanistic implications. The small, sharp
RS deflection reflects local activation of an island of surviving
tissue in the infarct border zone. Healing or healed infarcts tend to
be patchy and nonuniform, with necrotic regions separating surviving
myocardium. The structural nonuniformities create local
mismatches of electrical properties, such as abrupt increases in
electrical loading, where narrow myocardial strands merge into larger
islands of surviving tissue. Such structures are highly susceptible to
the development of unidirectional block and reentry. Page et
al6 have shown that VT inducibility is correlated with the
presence of islands with pure Q-wave EGMs bridged by regions of EGMs
with late local deflections. These observations are consistent
with the importance of surviving cardiac fibers traversing the infarct
to the development of VT in the infarcted, Langendorff-perfused human
heart.4 The demonstrated ability of ECGI to reconstruct
Q-wave EGMs with superimposed local RS deflections and EGMs with small
R-waves followed by predominant slow negative deflections (Figure 7) suggests the possibility of noninvasive characterization and
mapping of regions with different EP properties within the infarct
border zone. The degree of EP heterogeneity and
"patchiness" of the substrate could provide a measure of the
vulnerability to arrhythmias and help stratify patients at
risk. Other potential applications associated with the capability of
ECGI to noninvasively map the abnormal substrate could include (1)
optimization of implantable cardioverter-defibrillator lead
placement, (2) identification of potential sites for ablation, and
(3) evaluation of drug therapy through noninvasive examination of its
effects on the EP substrate.
The experimental strategy in this study is to use epicardial potentials recorded in situ to compute torso potentials, which, after contamination by realistic measurement and geometrical errors, serve as the input data for ECGI reconstructions. This approach has advantages and limitations. In this preparation, the preinfarction and postinfarction epicardial potentials are measured from a working heart subject to autonomic innervation and is therefore physiologically realistic. The high-density, 490-electrode epicardial sock provides high spatial resolution for capturing spatial variations such as regions with or without local RS EGM deflections. The high-density measured epicardial potentials also serve as high-resolution data for a direct detailed evaluation of ECGI performance. The use of ethanol injection to create the infarction allows the heart to serve as its own control. This approach provides preinfarction and postinfarction potentials from the same heart during the same experiment, revealing the pathological EP changes associated with infarction. A limitation of the in situ approach is that the torso and epicardial potentials were not simultaneously recorded as was done in our previous torso tank studies.9 10 11 In fact, the epicardial potentials were recorded in an open-chest dog and then used to compute potentials in a human torso model. It should be pointed out, however, that this model is self-consistent. In other words, the computed torso potentials are the same as those that would have been generated in a human torso by a heart with the same epicardial potentials. The difference is that the computed torso potentials, unlike their measured counterpart, are not contaminated by noise and measurement error. The addition of signal and geometric gaussian noise to all torso points overcomes this limitation. It should also be added that the use of a homogenous torso volume (eg, no lungs) does not affect the conclusions of this study. Previous studies have demonstrated that torso inhomogeneities affect epicardial potential magnitudes but have a minimal effect on epicardial potential patterns, EGM waveforms, or isochrones.15 16
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Acknowledgments |
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This study was supported by NIH-NHLBI grants R37-HL-33343, R01-HL-49054 (Y.R.), and R01-HL-43276 (B.T.). Additional support was provided by awards from the Whitaker Foundation (Y.R.), the Nora Eccles Treadwell Foundation, and the Richard A. and Nora Eccles Harrison Fund for Cardiovascular Research (B.T., R.S.M.).
Received March 31, 1999; revision received August 9, 1999; accepted August 16, 1999.
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  K. Gima and Y. Rudy Ionic Current Basis of Electrocardiographic Waveforms: A Model Study Circ. Res., May 3, 2002; 90(8): 889 - 896. [Abstract] [Full Text] [PDF]
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 J. E. Burnes, B. Taccardi, P. R. Ershler, and Y. Rudy Noninvasive electrocardiogram imaging of substrate and intramural ventricular tachycardia in infarcted hearts J. Am. Coll. Cardiol., December 1, 2001; 38(7): 2071 - 2078. [Abstract] [Full Text] [PDF]
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 J. E. Burnes, R. N. Ghanem, A. L. Waldo, and Y. Rudy Imaging Dispersion of Myocardial Repolarization, I: Comparison of Body-Surface and Epicardial Measures Circulation, September 11, 2001; 104(11): 1299 - 1305. [Abstract] [Full Text] [PDF]
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R. N. Ghanem, J. E. Burnes, A. L. Waldo, and Y. Rudy Imaging Dispersion of Myocardial Repolarization, II: Noninvasive Reconstruction of Epicardial Measures Circulation, September 11, 2001; 104(11): 1306 - 1312. [Abstract] [Full Text] [PDF]
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H. E. Botker, J. F. Lassen, F. Hermansen, H. Wiggers, P. Sogaard, W. Y. Kim, M. Bottcher, L. Thuesen, and A. K. Pedersen Electromechanical Mapping for Detection of Myocardial Viability in Patients With Ischemic Cardiomyopathy Circulation, March 27, 2001; 103(12): 1631 - 1637. [Abstract] [Full Text] [PDF]
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J. E. Burnes, B. Taccardi, and Y. Rudy A Noninvasive Imaging Modality for Cardiac Arrhythmias Circulation, October 24, 2000; 102(17): 2152 - 2158. [Abstract] [Full Text] [PDF]
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K. Gima and Y. Rudy Ionic Current Basis of Electrocardiographic Waveforms: A Model Study Circ. Res., May 3, 2002; 90(8): 889 - 896. [Abstract] [Full Text] [PDF]
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