U.S. patent application number 11/527989 was filed with the patent office on 2007-01-25 for method and apparatus for classifying and localizing heart arrhythmias.
Invention is credited to Valmik Bhargava, Sanjiv Mathur Narayan.
Application Number | 20070021679 11/527989 |
Document ID | / |
Family ID | 31996932 |
Filed Date | 2007-01-25 |
United States Patent
Application |
20070021679 |
Kind Code |
A1 |
Narayan; Sanjiv Mathur ; et
al. |
January 25, 2007 |
Method and apparatus for classifying and localizing heart
arrhythmias
Abstract
Analyzes surface electrocardiographic and intracardiac signals
to identify and separate electrical activity corresponding to
distinct but superimposed events in the heart. Assesses the spatial
phase, temporal phase, rate, spectrum and reproducibility of each
event to determine uniformity of activation in all spatial
dimensions. Uses numerical indices derived from these analyses to
diagnose arrhythmias. Uses these indices to determine the location
of an arrhythmia circuit, and to direct the movement of an
electrode catheter to this location for ablation or permanent
catheter positioning. Subsequently, uses these indices to determine
whether ablation has successfully eliminated the circuit. Uses
variability in these indices from the surface electrocardiogram to
indicate subtle beat-to-beat fluctuations which reflect the
tendency towards atrial and ventricular arrhythmias.
Inventors: |
Narayan; Sanjiv Mathur; (San
Diego, CA) ; Bhargava; Valmik; (San Diego,
CA) |
Correspondence
Address: |
STOUT, UXA, BUYAN & MULLINS LLP
4 VENTURE, SUITE 300
IRVINE
CA
92618
US
|
Family ID: |
31996932 |
Appl. No.: |
11/527989 |
Filed: |
September 26, 2006 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
10323423 |
Dec 18, 2002 |
7123954 |
|
|
11527989 |
Sep 26, 2006 |
|
|
|
60412148 |
Sep 19, 2002 |
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Current U.S.
Class: |
600/518 |
Current CPC
Class: |
A61N 1/3625 20130101;
A61B 5/7264 20130101; A61B 5/35 20210101 |
Class at
Publication: |
600/518 |
International
Class: |
A61B 5/04 20060101
A61B005/04 |
Claims
1. A method of analyzing a signal, comprising: providing a digital
template and a digitized signal sufficient to facilitate
identification of atrial fibrillatory components of activity as
originating from a left side or a right side of the heart, the
digitized signal comprising a plurality of amplitudes corresponding
to consecutive time samples; generating a plurality of correlation
values correlating the digital template to successive time samples
of the digitized signal, wherein a plurality of correlation values
are generated sufficient to facilitate discernment of whether
distinct components of activity have origins in the left or right
sides of the heart; mapping the correlation values; and identifying
a treatable condition, based upon the mapping of the correlation
values.
2. The method as set forth in claim 1, wherein the correlation
values are mapped against time.
3. The method as set forth in claim 1, wherein the providing
comprises providing a digital template and a digitized cardiac
signal sufficient to facilitate identification of atrial
fibrillatory components of activity from distinct regions of the
heart, the identification being sufficient to facilitate a
separation of atrial tachycardia, atrial fibrillation, atrial
flutter and ventricular tachycardia.
4. The method as set forth in claim 1, wherein the time samples
span a plurality of cardiac cycles
5. The method as set forth in claim 1, wherein successive time
samples are consecutive time samples.
6. The method as set forth in claim 1, wherein the digitized signal
is an ECG.
7. The method as set forth in claim 1, wherein the digitized signal
is an intracardiac electrogram.
8. The method as set forth in claim 1, wherein the digitized signal
is a digitized cardiac signal and the method further comprises:
comparing correlation values with a threshold value; and
identifying features as correlation values that exceed the
threshold value.
9. The method as set forth in claim 8, wherein the correlation
values are derived from a template having a duration up to that of
the digitized cardiac signal.
10. The method as set forth in claim 9, wherein correlation values
that exceed the threshold value indicate rates of activity in the
digitized cardiac signal.
11. The method as set forth in claim 10, and further comprising
generating a frequency domain representation of the digitized
cardiac signal and of the correlation values.
12. The method as set forth in claim 11, wherein the frequency
domain representation of the digitized cardiac signal comprises a
plot of frequency versus power.
13. The method as set forth in claim 1, and wherein: the digitized
signal is a digitized cardiac signal generated from a plurality of
leads; and the correlation values are plotted, with each plot
comprising a representation of correlation values of two leads from
the plurality of leads, wherein for each plot the correlation
values of one of the two leads is plotted against the correlation
values of the other of the two leads.
14. The method as set forth in claim 13, wherein the plurality of
leads is used to calculate a rate of activity in the digitized
cardiac signal in one or more of the plurality of leads.
15. The method as set forth in claim 13, wherein the plurality of
leads is used to calculate one or more features of a rate of the
digitized cardiac signal.
16. The method as set forth in claim 15, wherein the one or more
features comprise a highest rate of activity of the digitized
cardiac signal.
17. The method as set forth in claim 15, wherein the one or more
features comprise a lowest rate of activity of the digitized
cardiac signal.
18. The method as set forth in claim 15, wherein the one or more
features comprise a range of rates of the digitized cardiac
signal.
19. The method as set forth in claim 15, wherein the one or more
features comprise peak frequencies of the digitized cardiac
signal.
20. The method as set forth in claim 15, wherein the one or more
features comprise a width of the frequency peaks of the digitized
cardiac signal.
21. The method as set forth in claim 1, and whereinat least a part
of the amplitudes represent tracings corresponding to electrical
activity from organs other than the heart.
22. The method as set forth in claim 1, wherein the digitized
signal is a digitized cardiac signal and the providing is preceded
by: a. placing a medical instrument into proximity of a heart; b.
moving the medical instrument in one or more of a direction toward
a lead indicating a highest rate of the digitized cardiac signal, a
direction toward a lead indicating a lowest rate of the digitized
cardiac signal, a direction toward a lead indicating the highest
frequency of the digitized cardiac signal, a direction toward a
lead indicating the lowest frequency of the digitized cardiac
signal, a direction toward a lead indicating the widest frequency
peak of the digitized cardiac signal, and a direction toward a lead
indicating the narrowest frequency peak of the digitized cardiac
signal; and c. using the medical instrument to cause at least one
modification to tissue of the heart.
23. The method as set forth in claim 22, wherein the modification
comprises a reduction of heart function.
24. The method as set forth in claim 22, wherein the modification
comprises a destruction of heart function.
25. The method as set forth in claim 22, wherein the modification
comprises a stimulation of heart function.
26. The method as set forth in claim 22, wherein the modification
comprises a pacing of the heart.
27. The method as set forth in claim 22, wherein the modification
is caused by electromagnetic energy.
28. The method as set forth in claim 22, wherein the modification
is caused by cooling.
29. The method as set forth in claim 22, wherein the modification
is caused by ultrasound energy.
30. The method as set forth in claim 22, wherein the modification
is caused by biochemical alterations.
31. The method as set forth in claim 22, wherein the modification
is caused by gene therapy.
32. The method as set forth in claim 1, wherein the digitized
signal is a biopotential of a cardiac arrhythmia.
33. The method as set forth in claim 32, wherein the distinct
components of activity include atrial and ventricular activity.
34. The method as set forth in claim 32, wherein the distinct
components of activity include activation and repolarization.
35. The method as set forth in claim 1, wherein the amplitudes
represent tracings corresponding to non-electrical activity.
Description
[0001] This application is a continuation of U.S. application Ser.
No. 10/323,423, filed Jun. 3, 2003, which claims the benefit of
U.S. Provisional Application No. 60/412,148, filed Sep. 19, 2002.
The entire contents of both applications are incorporated herein by
reference.
BACKGROUND OF INVENTION
[0002] 1. Field of the Invention
[0003] This invention relates generally to the field of heart
rhythm disorders and more specifically to systems and methods for
analyzing the electrocardiogram, pacing and mapping the heart for
the diagnosis and treatment of cardiac conditions.
[0004] 2. History of Technology
[0005] A normal heartbeat consists of an organized sequence of
conduction and orderly myocardial contraction. Normal (sinus)
rhythm begins when the sinoatrial node (or "SA node") generates a
depolarization wavefront in atrium. The impulse causes adjacent
atrial cells to depolarize in a spreading wavefront, resulting in
the "P-wave" on the Electrocardiogram (ECG), which causes the atria
to contract and empty blood into the ventricles. Next, the impulse
is delivered via the atrioventricular node (or "AV node") and the
bundle of His to myocardial tissue cells of the ventricle.
Depolarization propagates similarly across ventricular cells,
resulting in the "QRS" complex on the ECG, causing the ventricles
to contract and eject blood into the lungs and the systemic
circulation.
[0006] Unfortunately, several important and common diseases result
when aberrant conductive pathways develop and disrupt the normal
paths of atrial or ventricular depolarization. In general, anatomic
barriers (known as "conduction blocks") can develop and disorganize
the electrical impulse into wavelets that circulate around the
barrier. In addition, localized regions of scarred or ischemic
tissue may propagate depolarization slower than normal tissue,
causing "slow conduction zones" (SCZ) which facilitate the wavelets
to create errant, circular propagation patterns. The "reentry" or
"circus motion" resulting from these effects disrupts normal
depolarization and contraction of the atria or ventricles, and can
lead to abnormal rhythms ("arrhythmias").
[0007] Arrhythmias cause significant mortality and morbidity in the
United States. Arrhythmias can include fast rhythms
("tachycardias") and slow rhythms ("bradycardias"). Both can be
life-threatening or cause symptoms such as shortness of breath,
chest pain, dizziness, loss of consciousness or stroke. Ventricular
arrhythmias are the most common cause of sudden death, causing over
300,000 deaths per year. Ventricular arrhythmias include
ventricular tachycardia (VT) and fibrillation (VF). Atrial
arrhythmias are very common and cause many symptoms. They include
atrial fibrillation (AF), the most common arrhythmia in the U.S.,
affecting up to 5% of the population, atrial tachycardia (AT) and
atrial flutter (AFL).
[0008] Accurate and precise diagnosis of the arrhythmia is critical
in customizing medication therapy for the patient, and to provide
accurate advice on the likely outcomes of therapy for that patient.
In addition, many arrhythmias are cured nowadays by precisely
destroying tissue (known as "ablation") responsible for aberrant
conduction using a specialized electrical probe (or "catheter").
For example, typical atrial flutter, in which the circuit involves
the sub-eustachian isthmus of the right atrium, is successfully
cured in this way. However, other rhythms that may appear similar
on the surface ECG, such as atypical AFL, may involve circuits that
vary between successive beats and may not consistently involve the
isthmus. These rhythms are less successfully ablated. The precise
diagnosis and localization of the tissue responsible for an
arrhythmia is clearly important for successful ablation.
1. Diagnosis
[0009] Current techniques for precise heart rhythm diagnosis are
sub optimal and cumbersome. Although the electrocardiogram (ECG)
recorded from the body surface forms the cornerstone of diagnosis,
current interpretation methods often cannot determine the
arrhythmia diagnosis. Invasive electrophysiologic study is then
required to confirm the diagnosis and decide upon treatment,
although this involves discomfort and risk to the patient. For
example, the ECG often cannot separate typical and atypical AFL.
However, this distinction is important since typical AFL is best
treated by ablation while atypical AFL is more difficult to ablate
and is often treated with medications. Thus, invasive
electrophysiologic study may be performed, only to find atypical
AFL and recommend drug treatment. There is a pressing need to
improve upon the prior art and allow accurate diagnosis from the
standard 12-lead body surface ECG of the various forms of AFL,
other atrial arrhythmias and forms of VT.
2. Arrhythmia Localization, Catheter Guidance and Determination of
Ablation Success
[0010] For successful ablation, destructive energy is typically
targeted and delivered using a catheter positioned in contact with
tissue integral to the circuit. The first pass at arrhythmia
localization is made using the ECG. However, current methods of
analyzing the ECG are often inadequate even to determine if the
rhythm originates in the atria or ventricle (such as "wide complex
tachycardias"), or whether it primarily involves the left or right
side of the heart (such as atypical AFL). However, these
distinctions are important since they determine the recommendation
for medical or invasive therapy, and the type of invasive therapy
(including ablation or surgery). There is a real need for methods
to improve arrhythmia localization from the ECG, to help avoid
electrophysiologic study in some patients while guiding the study
in others.
[0011] More precise arrhythmia localization is usually performed
during invasive electrophysiologic study. These methods generally
involve placing a catheter close to the arrhythmia circuit. This is
indicated when the signals after stimulating the heart ("pacing")
match those during the actual arrhythmia. However, this requires
considerable skill and is often cumbersome even for practitioners
skilled in the prior art. All methods require the physician to
assimilate and compare the shape and relative timing of multiple
(often 10-15) complex signals from the ECG and inside the heart
("intracardiac"), during each pacing episode. This is a field in
which numerical and computer processing should have led to
increased precision and efficiency. However, the prior art has yet
to fill this void; most practitioners use their expert knowledge to
process information in much the same way as they did a decade
ago.
[0012] Once a catheter is maneuvered to the located arrhythmia
circuit, it is used to deliver destructive energy ("ablation").
Determining whether ablation is successful is also sub optimal. It
requires the physician to be unable to re-induce the arrhythmia.
However, this is not foolproof since many arrhythmia circuits are
induced on a sporadic basis in the first place. There is clearly a
need for quantitative methods to reproducibly determine if
activation of the arrhythmia circuit has been eliminated by
ablation.
3. Pacemaker and Defibrillator Lead Positioning
[0013] The leads of pacemakers and implantable defibrillators are
required to pace or deliver high-voltage energy to ("defibrillate")
a heart chamber. This purpose is best served by placing leads close
to arrhythmia circuits. However, this customization for each
patient is not performed, and leads are generally placed in
standard anatomic locations. This is because current methods for
arrhythmia localization are difficult to implement when implanting
a lead. Therefore, even though an atrial lead would better
terminate AFL, for example, if placed in the right atrial isthmus,
it is usually placed in the right atrial appendage. Similarly, the
ventricular lead of an implantable cardiac defibrillator is rarely
targeted to a site of VT, even though pacing and defibrillating
rhythms emanating from that site may be the main function of that
device.
[0014] A method to quickly and systematically localize an
arrhythmia circuit during implantation of a pacer or defibrillator
lead would significantly advance the performance of each of these
frequently implanted devices.
4. Arrhythmia Risk Stratification
[0015] The prediction of whether a patient will develop an
arrhythmia in the future is becoming increasingly important. This
is particularly true for VT and VF, where the first occurrence may
cause death, but is also important for AF and other arrhythmias.
However, the current art is sub optimal in this "risk
stratification" since it is rarely able to detect substrates until
the patient has a documented arrhythmia. Although there are several
methods to determine the risk for VT or VF, none are very accurate
and they have not entered routine clinical practice. The prior art
for predicting AF, AFL and other atrial arrhythmias is even more
rudimentary.
[0016] There is a very real need to improve risk stratification for
these arrhythmias. Waiting for VT or VF to occur puts the patient
at an unacceptable risk (a third or more will not survive), but if
identified ahead of time they may receive proven life-saving
treatment such an implantable cardioverter defibrillator.
Similarly, waiting for AF or AFL to occur delays treatment, while
earlier diagnosis and treatment makes them less likely to progress
and reduces the risk for stroke and other complications.
PRIOR TECHNOLOGY
[0017] This section will describe prior technology in each of the
areas covered by the invention.
1. Diagnosis
[0018] The surface ECG is by far the most common technology used by
skilled practitioners to diagnose an arrhythmia. The prior art
describes several methods to use the ECG to broadly classify
rhythms including AF, typical or atypical AFL, VT or VF. However,
these methods are limited when attempting to separate related
rhythms, such as AF or AT from AFL as shown by Horvath et al. [1],
or when more precisely localizing atrial [2] or ventricular
circuits.
[0019] Several methods can improve ECG diagnosis of atrial rhythm
events by enhancing P-wave detection. These include methods to
subtract out the QRS complex including U.S. Pat. No. 4,721,114
issued to DuFault and work by Xue et al. [3]. However, these
methods simply enhance atrial activity. Fast atrial rates are
likely to signify AF. This can be detected via frequency analysis
of the surface ECG, as in U.S. Pat. No. 6,064,906 issued to
Langberg. The shape of the P-wave can also help localize sites of
origin in the atria, such as work by Tang et al. [2], and pulmonary
veins [4]. Recent methods have used high spatial resolution body
surface potential maps to improve the non-invasive detection of
atrial activation and its vector of activation, such as work by
SippensGroenewegen et al. [5].
[0020] Several methods have been used to diagnose ventricular
arrhythmias from the ECG. The most frequently used prior art
includes the criteria of Brugada et al. [6] to separate VT from
types of atrial arrhythmia that appear similar. If a beat is
thought to arise from a ventricular site, ECG vector analysis can
determine the location of that site [7]. Finally, high spatial
resolution ECGs have also been used to better define the direction
of activation in VT, such as work by Peeters et al. [8].
[0021] Currently, when a definitive diagnosis of an arrhythmia is
required, intracardiac signals have to be analyzed. Such signals
are obtained at invasive electrophysiologic study, which introduces
discomfort and potentially serious risks to the patient. At
invasive study, signals are recorded from each chamber of the
heart, enabling their relationship to be easily determined.
Notably, most of the prior art focuses on diagnosis using the ECG
or intracardiac signals, but not both.
[0022] Using intracardiac atrial and ventricular signals, much of
the prior art focuses on detection of high rates. AF has been
diagnosed from high atrial rates in U.S. Pat. No. 5,522,852 issued
to White, U.S. Pat. No. 6,041,251, issued to Kim and U.S. Pat. No.
5,827,197 issued to Bocek. High rates are also analyzed as high
frequencies in U.S. Pat. No. 6,178,347 issued to Olsson. In
particular, work by Stambler et al. [9] showed that, after QRS
subtraction, AF is represented by several frequency components in a
broad bandwidth. U.S. Pat. No. 5,868,680 issued to Steiner reports
that when AF becomes more organized, indicated by distinct
frequency characteristics, it is more likely to terminate. Other
work, such as U.S. Pat. No. 5,366,486 issued to Zipes and U.S. Pat.
No. 5,509,925 issued to Adams, used signal regularity to diagnose
AF and make similar inferences.
[0023] AF and AFL have also been diagnosed using variability in the
size or shape of atrial signals on intracardiac tracings. AF is
associated with a fall in intracardiac atrial signal size in U.S.
Pat. No. 5,720,295 issued to Greenhut, while atrial signal shapes
distinguish AFL (consistent) to AF (variable) in U.S. Pat. No.
5,968,079 issued to Warman. However, much of this work cannot
separate typical from atypical AFL, which have similar rates and
ECG appearances, but different treatments. U.S. Pat. No. 5,782,876
issued to Flammang and other work use rules based on the rate and
regularity of intracardiac atrial signals to separate AF from AFL.
As a means to separate atypical AFL from AF, which can be difficult
from the ECG, U.S. Pat. No. 5,817,134' issued to Greenhut diagnosed
AF when variability between 2 temporally or spatially separated
atrial signals is high. U.S. Pat. No. 5,676,153 issued to Smith
extends this concept by measuring the distance over which atrial
signals are part of the same wavefront ("activation space
constant"), thus separating AFL (most organized) from AF (least
organized).
[0024] Intracardiac diagnosis can also be based on the relationship
between atrial and ventricular activity (atrioventricular
relationship), such as U.S. Pat. No. 5,782,876 issued to Flammang,
while U.S. Pat. No. 5,542,430 issued to Farrugia and other work
describes how this relationship can be analyzed using neural
networks.
[0025] Analogous prior art pertains to ventricular rhythm
diagnosis. For the surface ECG, VT and VF can be detected from a
rapid rate, from wide QRS complexes in U.S. Pat. No. 5,400,795
issued to Murphy, and via measures of ECG complexity in work by
Zhang et al. [10]. Using intracardiac signals, VT and VF have been
detected from rapid ventricular signals in U.S. Pat. No. 5,891,170
issued to Nitzsche, signal shapes in U.S. Pat. No. 4,552,154 issued
to Hartlaub, and systems that integrate many such criteria such as
U.S. Pat. No. 5,542,430 issued to Farrugia.
2. Arrhythmia Localization and Ablation
[0026] Two major concepts in the prior art help localize an
electrode close to the arrhythmia circuit, to enable ablation or
termination of the rhythm via pacing. First, pacing from the site
of the arrhythmia will produce a theoretically identical ECG to the
tachycardia. This "pace mapping" is used at invasive
electrophysiologic study when the patient is not in the arrhythmia
[11], and is described in the section entitled Detailed Description
of the Invention. Second, a catheter placed at the arrhythmia site
will record identically timed intracardiac signals and ECGs during
tachycardia and when pacing. This "entrainment with concealed
fusion" is used when the patient is in arrhythmia and works for
both atrial [12] and ventricular [13] rhythms, and is also
described further in the Detailed Description of the Invention.
Although this approach is the standard of care, it accurately
identifies the site to ablate in only 25% of ventricular [13] and
50% of atrial [12] rhythms. This shows the obvious difficulty for
even the most skilled practitioners to compare differences between
10-15 waveforms from multiple catheter sites using just visual
analysis.
3. Assessment of Ablation or Termination Effectiveness
[0027] There are very few methods in the prior art to determine if
an arrhythmia has been ablated successfully. In the case of
isthmus-dependent AFL, there are a few examples. First, work by
Hamdan et al. [14] show that P-wave develops a specific shape and
vector during isthmus pacing if ablation was successful. Second, a
positive unipolar intracardiac signal on the opposite side of the
ablation line to the pacing site [15] and, third, showing double
potentials along the ablation line [16] indicate successful
ablation. However, these methods are cumbersome and not always
accurate, and practitioners often use the inability to re-start an
arrhythmia to indicate that it has been eliminated; as discussed,
this may be inaccurate if arrhythmia induction is sporadic.
4. Pacemaker and Defibrillator lead Positioning
[0028] Placing a lead close to an arrhythmia site will make it
easier to terminate that arrhythmia by pacing or defibrillation.
The opposite is also true, and studies by Stevenson et al. [13] and
Morton et al. [12] have shown that arrhythmias like AFL or VT are
less easily terminated from a remote location. However, the prior
methods for locating an arrhythmia (mentioned above) are lengthy
and difficult to perform during permanent pacemaker or
defibrillator lead implantation. However, targeting a specific lead
position is increasingly felt to be important, and is already being
done to improve the strength of heart contraction, such as work by
Leclercq et al. [17], and possibly to reduce arrhythmias, in work
by Zagrodzky et al. [18].
5. Arrhythmia Risk Stratification
[0029] There are several prior art methods to stratify the risk for
arrhythmias non-invasively from the ECG. However, they can have
limitations and are rarely used except for research. To predict AF,
work by Steinberg et al. [19] and others show that prolonged atrial
activity indicates slow conduction and may predict AF, while recent
work by Narayan et al. [20] suggests that an alternation of the
timing, shape or amplitude of the intracardiac atrial signals may
predict AF. In the ventricle, Kleiger et al. [21] showed that
reduced variability over 24 hours in the interval between heart
beats ("heart rate variability") predicts VT or VF. Slow conduction
through ventricular scar has been detected as "late potentials" at
the end of ventricular depolarization, and may predict the risk for
ventricular arrhythmias [22]. U.S. Pat. No. 4,802,481 issued to
Cohen, and work by others, describe techniques for using
fluctuations in the size of T-waves ("T-wave alternans") to predict
VT or VF. Newer methods, such as U.S. Pat. No. 5,555,888 issued to
Brewer use altered ventricular activation after sub-threshold
current to assess the risk for VT or VF.
Deficiencies in Prior Technology
[0030] The prior art can have several significant deficiencies in
each of the areas addressed by the current invention. Most prior
art in the field of arrhythmias has limited scope. Thus, methods
exist that can use either the surface ECG or intracardiac signals,
but few that can use both. Similarly, there are several methods
that apply for either atrial or ventricular arrhythmias, but few
that apply to either. Furthermore, there are several methods that
can examine the timing, spectra, spatial pattern or shape of ECG or
intracardiac signals, but few that incorporate all four. This lack
of integration has arisen since methods focus on the manifestations
of arrhythmia substrates, rather than on the substrates themselves.
This has slowed technical advances in arrhythmia management, since
ECG diagnosis, arrhythmia localization and catheter guidance have
had to be separated. In contrast, the current invention studies
temporal, spatial phase and spectral relationships that are true
for surface ECG and intracardiac signals, and for atrial as well as
ventricular arrhythmias.
1. Diagnosis
[0031] Several specific deficiencies can be identified in the prior
art. In general, the prior art focuses on arrhythmia diagnosis for
implanted pacemakers and defibrillators, rather than on bedside
clinical diagnosis.
[0032] First, the prior art does not help very much in separate
rhythms of similar rate and regularity from the ECG. This remains a
major dilemma since, for example, typical and atypical atrial
flutter (AFL) may co-exist as described by Horvath et al. [1].
Ablation of typical AFL in these cases is less successful. If
co-existence was known in advance, invasive study and its attendant
risks may be avoidable. Another example is the diagnosis of a wide
complex tachycardia as either VT or SVT, despite the rules proposed
by Brugada et al. [6].
[0033] Second, the prior art has limited methods for analyzing
superimposed activity. The method of QRS subtraction is frequently
applied to `uncover` P-wave activity, yet it introduces errors
since the average QRS used for subtraction will differ from the
actual QRS complex. These errors are often compounded if frequency
analysis is subsequently performed.
[0034] Third, the prior art is poor at localizing an arrhythmia
site from the surface ECG. The work by Tang et al. [2] and Yamane
et al. [4] for atrial, and Callans et al. [7] for ventricular,
arrhythmias provide very general locations. For example, they
cannot determine if an atypical AFL circuit is in the right or left
atria, which require significantly different invasive
approaches.
[0035] Fourth, the prior art does not fully exploit functional
information, such as whether atrioventricular relationships are
likely physiologic. Thus, although methods have recently begun to
focus on atrial versus ventricular rate, they usually ignore
additional information used by experts, such as the precise timing
of ventricular to atrial activity (for example, in atrial flutter
with 4:1 ventricular conduction, does ventricular activity arise at
the same point in each preceding atrial activity?)
[0036] Clearly, there is a need to improve the accuracy of ECG
diagnosis of complex rhythms. Some of the uses of this improvement
would be to improve the diagnosis and treatment of patients by
physicians, improvements in the diagnostic algorithm of modern ECG
machines, and a more solid foundation for invasive
electrophysiologic studies in those patients who still require
them.
2. Arrhythmia Localization and Catheter Guidance
[0037] Despite the current focus on ablation (destroying) many
arrhythmia circuits using precisely targeted energy delivery,
localization of the delivery site requires several manual
measurements and comparisons by the practitioner. Very few methods
have been described to automate or simplify this process. Ablation
therefore remains time-consuming and laborious, even for the most
skilled practitioners of the art.
[0038] From the ECG, the prior art for localization is limited. In
the atrium, certain rhythms have characteristic ECG patterns, and
ablation is successful using a stereotypical approach in most
patients. Once the diagnosis of typical isthmus dependent AFL has
been made, ablation in the isthmus of the right atrium is
successful in the vast majority of cases as shown by Feld et al.
[23]. Similarly, once the diagnosis of atrioventricular nodal
reentry tachycardia is made, ablation in the region of Koch's
triangle is almost universally effective as shown by Jackman et al.
[24]. However, problems still arise when ECG patterns are not
typical, such as atypical AFL masquerading as typical [1], or when
another rhythm event mimics these ECG patterns. Ventricular
arrhythmias are somewhat better localized from the ECG, but methods
are still limited. First, certain ventricular rhythms have
stereotypical ECG patterns, such as VT arising from the outflow
tracts of the right or left ventricles as described by Callans et
al. [7]. Second, vector analysis of ventricular complexes localizes
the arrhythmia more easily than for atrial arrhythmias, where low
voltages obfuscate this analysis. However, precise localization
remains difficult and there are few tools enabling this task to be
automated in modern ECG machines or laboratory electrophysiology
systems.
[0039] In other rhythms, intracardiac localization must be
customized to the patient using pace mapping or entrainment with
concealed fusion. There is little prior art to aid or automate this
cognitive process. This is true despite the widespread adoption of
digital laboratory electrophysiologic machines, which therefore
remain little more than digital monitors and recorders, annotation
pads, measurement systems and storage devices.
[0040] Using catheters inside the heart, an arrhythmia circuit is
located by finding the region which activates first, or from where
pacing produces electrograms similar in shape to the tachycardia in
all channels, known as pace mapping [11]. Methods have begun to
numerically analyze beat similarity by storing a template (of
native or paced rhythm), as described by Watanabe [25] and Saba
[26], then performing a correlation of this beat to an aligned
paced beat. However, these methods are limited. First, many
different paced beats may produce the same numerical correlation
against template, and therefore be indistinguishable. Prior methods
do not identify which of these pacing sites is most likely to lead
to successful ablation. Second, most strategies rely on a "lead
count" of successful ECG lead matches (typically, "pacing matches
tachycardia in 11/12 leads"). However, quite distinct pacing sites
may produce matches in the same proportion of leads. The prior art
does not identify which site is likely closest to a successful
ablation site. Third, the prior art usually analyzes very few paced
beats (often one), as discussed by Saba [26], which may be subject
to "impurities". For example, this beat may be fused with native
activation, making the pace maps appear better than they are. By
way of another example, the beats analyzed may not adequately
represent normal beat-to-beat variability, leading to the
mis-classification of beats. Fourth, the prior art superimposes the
paced and native beat to compute correlation at one "optimal"
alignment. This single analysis for each beat ignores variabilities
along the duration of the ECG beat. Fifth, the prior art
correlation methods are greatly affected by amplitude or temporal
scaling. In other words, paced and native beats of the same shape,
but differing either in magnitude or "stretched" relative to the
other, will not match well. As a corollary, the prior art is not
effective when comparing rhythms of different rates, from different
recording sessions or from different equipment. This prevents
comparison of one rhythm to a previously stored rhythm in that
patient or another patient. Sixth, the prior art provides little
aid in guiding a catheter from its current position to move closer
to the putative ablation site.
[0041] "Entrainment with concealed fusion" is used to confirm the
diagnosis of re-entry and that an intracardiac catheter is located
close to the circuit, as described by the prior art of Waldo [27,
28], Stevenson [13] and others. During tachycardia, several
criteria must be met while pacing from the intracardiac catheter.
First, the interval separating the intracardiac signal at the
catheter from its ECG activity must be identical during pacing or
tachycardia. Second, the ECG resulting from pacing (pace maps)
should be identical to those during tachycardia. Third, after the
cessation of pacing, the tachycardia should resume at its prior
rate without an intervening delay. Fourth, progressively faster
pacing should cause a progression in ECG and intracardiac signal
shape from the tachycardia (when matched by the pacing rate) to
that of pacing (when faster rates). Finally, the time interval
between the pacing stimulus at the site and the ECG wave is
characteristic.
[0042] However, the application of this method requires
improvement. Although experts routinely apply these criteria for
atrial [12] and ventricular [13] rhythms, their success in locating
ablation sites is only 50% of atrial [12] and 25% of ventricular
[13] rhythms. This highlights the difficulties for a human operator
to compare subtle changes in the relative timing and shape of 12
surface ECG and additional intracardiac signals for each of several
catheter positions, then select the set that matches the above
criteria. Recently, concealed entrainmentfor a single beat was
implemented by cross-correlation in U.S. Pat. No. 5,792,064 issued
to Panescu. This prior art examined two criteria of concealed
entrainment: whether intracardiac electrogram timing and shape were
similar between one paced beat at the catheter location and the
extra beat which initiates AF. However, this method was not
described for continuous tachycardia. In addition, it did not
analyze the surface ECG, nor did it assess the other criteria of
concealed entrainment. Clearly, there is a need for numeric methods
to implement this method and help to automate it.
3. Pacemaker and Defibrillator Lead Positioning
[0043] As mentioned above, positioning a pacemaker or defibrillator
lead close to an arrhythmia circuit requires pace mapping or
concealed entrainment. The current rules for these methods make
them unwieldy to apply while placing a poorly steerable lead. There
is a need to develop ECG methods, confirmed using intracardiac
signals, to position a lead in an individualized location where it
can later facilitate the termination of an arrhythmia by pacing
(stimulating) or defibrillating (providing an electrical shock) the
tissue.
4. Assessment of the Effectiveness of Ablation
[0044] There are few prior art methods to measure the effectiveness
of ablation in eradicating the substrate for an arrhythmia.
Although markers of success exist for certain arrhythmias, such as
P-wave shape change and double potentials along the ablation line
in AFL, most of the prior art does not probe the arrhythmia circuit
and cannot therefore detect its absence after ablation. This may
partly explain the recurrence rate after the ablation of AFL (up to
15%) and other rhythms. There is a need to accurately measure the
continued presence of substrates for the arrhythmia.
5. Arrhythmia Risk Stratification
[0045] Risk stratification for arrhythmias from the surface ECG is
an attractive but largely elusive task. Predicting the risk for AF
remains difficult. There has been somewhat more success in
predicting the occurrence of VT and VF. However, the "heart rate
variability" method of Kleiger et al. [21] requires a long
recording period, assesses only long-term risk, and cannot be
performed in many patients with pre-existing arrhythmias such as
AF. Late potentials cannot be examined if patients have AF or
bundle branch block, and their predictive accuracy for VT or VF has
also been seriously questioned. The "T-wave altemans" method of
Cohen in U.S. Pat. No. 4,802,481 has sub optimal predictive
accuracy and requires considerable experience in interpretation,
yet still often produces uninterpretable results (see, for example,
Bloomfield et al. [29]) and also cannot be performed if the patient
has AF or bundle-branch block. The success of other, newer methods
has yet to be determined. None have entered routine clinical
practice as none improve upon assessments of the strength of
ventricular contraction and other non-arrhythmic factors. There is
clearly a need to improve the risk stratification for both atrial
and ventricular cardiac rhythm events from the ECG.
BRIEF DESCRIPTION OF THE DRAWINGS
[0046] FIG. 1a is a general schematic of a system in accordance
with the present invention;
[0047] FIG. 1b is a detailed schematic of the system of the present
invention;
[0048] FIG. 2 is a diagram of sensing/pacing a catheter in
accordance with the present invention;
[0049] FIG. 3 is a diagram of sensing/pacing an ablation catheter
in accordance with the present invention;
[0050] FIG. 4 is a chart integrating modes of operation in
accordance with the present invention;
[0051] FIG. 5 is a flowchart of an analysis engine in accordance
with the present invention;
[0052] FIG. 6 is a schematic diagram of a method for computing
temporal spatial correlation in accordance with the present
invention;
[0053] FIG. 7 is a schematic diagram comparing prior-art
vectorcardiography with the invention;
[0054] FIG. 8A is a schematic diagram of the invention diagnosing
typical atrial flutter;
[0055] FIG. 8B is schematic of the invention diagnosing atrial
tachycardia;
[0056] FIG. 8C is a schematic of the invention diagnosing atypical
atrial flutter;
[0057] FIG. 8D is a schematic of the invention diagnosing atrial
fibrillation;
[0058] FIG. 8E is a schematic of the invention diagnosing
monomorphic ventricular tachycardia;
[0059] FIG. 8F is a schematic of the invention diagnosing
polymorphic ventricular tachycardia; and
[0060] FIG. 9 is a schematic explaining reentry arrhythmias.
DETAILED DESCRIPTION OF THE INVENTION
[0061] FIG. 1A shows an overview of the general components of a
system 5 for analyzing the timing and shape ("morphology") of body
tissue biopotentials in three spatial dimensions over time, for
diagnostic and therapeutic purposes. The heart is shown
diagrammatically and not in an anatomically accurate form. The
illustrated and preferred embodiment shows the system being used to
analyze the activation ("depolarization") and recovery
("repolarization") of heart tissue experiencing an arrhythmia.
[0062] A strength of this invention is that it has the option of
integrating the analysis of shape, distribution, reproducibility
and timing of biopotentials from inside the heart as well as from
the body surface. From the surface ECG, the invention can analyze a
cardiac signal which corresponds to the activation wavefront on the
heart, and which can be measured using several ECG leads. The
invention can diagnose subtly different rhythm abnormalities
("arrhythmias") in the atria and/or ventricles from the traditional
12-lead ECG. This includes a very accurate separation between
typical and atypical forms of atrial flutter (described above).
Using spectral, temporal and spatial ECG morphology analysis, the
invention can precisely compare pace-maps taken from different
locations and times in a single patient, or compare them to
previously stored ECG maps of known arrhythmias from this or
different patients. Pacing can be performed using a medical
instrument including, but not limited to devices inside the heart,
e.g., pacing catheters, pacemaker leads and defibrillator leads, or
devices external to the heart. The invention also performs
non-invasive prediction of the presence of substrates for
arrhythmias by detecting variations in the above analysis from beat
to beat.
[0063] From signals inside the heart ("intracardiac"), the
invention quantifies the measurement of entrainment with concealed
fusion [12, 13]. This enables it to confirm an ECG diagnosis, and
to help automate the diagnosis of an arrhythmia mechanism and its
localization, to enable a catheter to be placed close to the
circuit for therapeutic ablation. The invention provides a spatial
relationship comparator function, enabling it to guide the
physician in moving a catheter towards the arrhythmia circuit for
optimum ablation. The invention can also be used for the optimal
placement of a pacemaker or defibrillator lead. Finally, the
invention can assess whether ablation was successful by detecting
whether substrates for the arrhythmia circuit are still
present.
[0064] The invention is well suited for use in performing
electrical diagnosis and therapy of the heart. However, it should
be appreciated that the invention is applicable for use in other
regions of the body where tissue biopotential morphologies can be
ascertained by analyzing electrical events in that tissue. For
example, the various diagnostic aspects of the invention have
application in analyzing electroencephalograms in the brain or
neurologic tissue, or electrograms in the gastro-intestinal tract.
Many aspects of the invention have potential applicability for
invasive surgical techniques on the heart, brain or other organs.
Furthermore, it should be appreciated that the invention can
analyze any biopotential and could be applied, for example, to the
detection of atrial and ventricular timing and hence the analysis
of rhythm disturbances using hemodynamic recordings.
[0065] Furthermore, the principal analysis of this invention has
potential applicability in the field of electrical engineering,
such as to assess frequency variability ("jitter") from an
oscillating waveform, such as may arise from analogue circuits.
This will be discussed again later.
[0066] Turning in more detail to FIG. 1A, one can see the system 5
for analyzing electrical events in the heart 10 using a combination
of electrodes. These electrodes may be standard body surface ECG
electrodes 25, or electrode catheters placed within the chambers or
vasculature of the heart, labeled 15, 18, 20. An ablation catheter
20 can be placed within the heart or its vasculature to destroy
tissue responsible for a cardiac event. From a general point of
view, it can be seen that the electrodes interface with an
electrode controller 30, interfaced to a process controller 70. The
ablation catheter 20 interfaces with an energy generator 40. The
process controller 70 interfaces to modules for signal processing
50, pacing 60 and the energy generator 40. The process controller
70 also receives input from an input module 80 and controls a
display module 90.
[0067] FIG. 1B presents a detailed schematic of a preferred
embodiment of the invention. The system analyzes electrical events
in regions of the heart 110. Signals may be recorded from standard
body surface ECG electrodes 130, catheters 134' percutaneously
inserted into a vein or artery (typically the femoral vein or
artery) into the right or left side of the heart, or inserted into
the coronary arteries (not shown) via the aorta 116 by passing
retrograde from a peripheral artery, or through the coronary sinus
112 into the cardiac veins 114. An electrode 136 can also be placed
within the esophagus 120, where it lies in close proximity to the
heart without the need to directly access the vasculature. An
important component is the connection of one or more ablation
catheters 138. One of the above catheters, denoted ROVE, is moved
within the heart to localize an arrhythmia circuit. In the
preferred embodiment, ROVE is the ablation catheter 138, which is
typically steerable and therefore easily directed within the heart
110 or its vasculature 114, but any catheter may serve this
purpose. A series of signals recorded at ROVE during the cardiac
diagnosis are labeled S.sub.i, and during pacing are labeled
P.sub.i, where I=1, 2, 3 or greater. These signals S1, S2, S3 or
P1, P2, P3 may represent signals obtained from one site at
different timepoints, or from separate and distinct sites at one
timepoint. In the preferred embodiment, these signals are unipolar
recordings, obtained between ROVE catheter electrodes and a distant
electrode in the inferior vena cava or another indifferent
electrode (not shown). However, these and other signals may also be
recorded in bipolar, monophasic action potential or other
configurations as desired.
[0068] The electrodes are connected to an electrode control 140
allowing electrical stimulation of the heart from a menu of
electrodes 144, at user-selectable current, voltage, waveform
shape, rate and pattern of stimulation. This can be implemented
using commercially available digital-to-analog processor boards and
associated software such as those from National Instruments Inc.,
Austin, Tex. Signals from the electrode controller 140 pass through
a conditioning unit 150 that includes an anti-aliasing filter,
analog-to-digital converter and line frequency filter. A cardiac
signal should first be digitized using this conditioning unit 150.
The conditioning unit can also effectively removes pacing stimuli
from the input waveform using smoothing, low-pass filtering,
interpolation or other methods in a window centered on the stimulus
artifact. The electrograms may or may not be filtered before
analysis. Typically, a 0.05-300 Hz bandpass filter is used for
filtering. If a filter is used to reduce the noise, the same
filters must be employed for all subsequent analysis since
filtering may alter electrogram morphology. In addition, magnitude
clipping or clamping is made available to diminish the effect of
large or outlying magnitudes on subsequent analyses. The ablation
electrode 138, is connected to an energy generator 172. Typically,
this provides radiofrequency energy such as that from EP
Technologies Inc., Sunnyvale, Calif., but could alternatively
provide electrical, ultrasound, infrared or other energy types.
[0069] For recording, conditioned signals are transferred to a
recording system 158 comprising electromagnetic, magneto-optical or
other technology. Signals are then processed on the host processor
195, such as a personal computer, using a menu 155. This menu
includes mathematical processing for correlation, slope and
intercept, and power spectral analyses, as well as additional
filters such as high, low and band pass and notch. A pacing module
160 provides energy pulses to the electrode control system 140 to
electrically stimulate the heart. A defibrillating energy source
180, such as that by Medtronic Physio-Control, Redmond, Wash., is
used to cardiovert or defibrillate the heart using connections to
the electrode controller 140 via catheters 134',136 or 138 or
surface paddles. An ablation module 170 interfaces with the energy
generator 172 interfaced to the ablation catheter 138.
[0070] To accomplish an important goal of the invention, a master
process controller 190 integrates the abovementioned modules for
recording 158, pacing 160, ablation 170 and defibrillation 180. The
process controller 190 is electrically coupled by a bus to the host
processor 195, that is adequately implemented as a Pentium II,
Maclntosh G-series or newer computer. The process controller 190
interfaces to a database system 197 for storage of electrograms and
analyzed information, to alternative ECG sources 198, an input
module 200 and a display module 230.
[0071] In an alternative embodiment, ECG and electrogram data can
be uploaded from the database 197 for analysis in a completely
analogous fashion to the real-time mode of operation described
below. Data from the database 197 can be from the same or different
patients, recorded at any time and using any acquisition system. In
yet another embodiment, the process controller 190 can upload for
analysis electrograms from a mapping system, that may be computed
("virtual"), such as in the system by Endocardial Solutions, Inc.
(St. Paul, Minn.), or real, such as in the system by Biosense
Webster, Inc. In these cases, the mapping system provides
additional location information for these electrograms, which is
used for subsequent catheter electrode localization.
[0072] The input module 200 allows selection of the mode of
operation and other functions of the invention. In the preferred
embodiment, a menu of Modes of Operation 220 includes A. Signal
Sampling; B. Surface ECG Diagnosis and Localization, C.
Intracardiac Diagnosis and Arrhythmia Localization, D. Catheter
Guidance System to target the placement of a diagnostic, ablation,
pacemaker or defibrillator electrode, E. Determination of Ablation
Success after delivery of ablation energy, and F. Arrhythmia
Prediction by detecting arrhythmia substrates prior to arrhythmia
onset. In an alternative embodiment, these and related modes can be
selected using a neural network or other type of expert system.
[0073] Analysis actions may be selected from a menu 210, either
automatically or interactively by the user, and underlie each mode
of operation. These analyses are described briefly now, and in more
detail later in the specification. The first action includes
further signal conditioning such as bandpass filtering. The primary
analysis of this invention is the temporospatial correlation of
electrogram morphology. This analyzes the reproducibility of
electrogram morphology over time for each electrode, and then
between electrodes. A strength of this method is that it can
integrate analyses of the shape, distribution, reproducibility and
timing of many types of biopotential. From the surface ECG, the
analysis can diagnose regular versus irregular tachycardias,
compare pace-maps, provide timing information similar to those from
intracardiac signals and non-invasively determine the presence of
arrhythmia substrates. From intracardiac signals, the system
implements a quantitative measurement of entrainment with concealed
entrainment including the matching of electrogram shapes. This
enables it to make the diagnosis of reentry, place an electrode
catheter close to an arrhythmia circuit for ablation or for
pacemaker or defibrillator lead positioning, and to assess whether
ablation was successful. Menu 210 provides additional analyses
including Timing analyses, Spatial Magnitude comparator, Spatial
relationship comparator, Spectral processing and other numerical
methods including the computation of Eigen vectors, morphology
cross-correlation, and magnitude clipping or clamping (which
diminish the effects of large or outlying magnitudes).
[0074] The process controller 190 connects to a display module 230
to display user-selectable screens. Typically, information relevant
to the current mode of operation is displayed, including real-time
electrograms on all catheters including ROVE (mode A), the computed
arrhythmia diagnosis (mode B) or intracardiac signals (mode C). The
display also indicates the plane in which ROVE signals least match
the arrhythmia under consideration. It therefore graphically
displays the direction in which to move the ROVE catheter to reach
the circuit (mode D). The display indicates if the ROVE catheter is
close to a site where ablation is likely to terminate the
arrhythmia, based on entrainment analysis, which is text labeled
SITE (mode D). After ablation, the display indicates if ablation
was likely to have been successful (mode E). Separately (mode F),
the display indicates the presence of substrates for the arrhythmia
for risk stratification. These display elements are enumerated by
way of example, and several other items may be selected.
[0075] Although analysis actions 210 have been described as
user-selectable choices, it must be stressed that the preferred
embodiment is `automated`. It suggests an optimal sequence of
actions based on the current rhythm, and in this way integrates
several of the above modes. The preferred embodiment therefore
enables a complete and efficient arrhythmia diagnosis and
therapeutic procedure for a patient. In a partly-automated fashion
driven by user prompts and confirmations, the invention makes a
diagnosis from the ECG and intracardiac signals, localizes the
arrhythmia to facilitate ablation, then confirms its success.
[0076] FIG. 2 shows an electrode catheter (labeled 134' or 136 in
FIG. 1B) with a flexible body 320. Its distal end carries a three
dimensional multiple electrode structure 310. In one preferred
embodiment of the invention, structure 310 takes the form of a
linear array of electrodes. The shaft is approximately 100-125 cm
in length, has an external diameter of 1-3 millimeters (3 to 9
"French"), and its terminal end may be straight or curved in
various configurations. In another embodiment, structure 310 takes
the form of a basket defining an open interior space. It should be
appreciated that alternative one, two or three dimensional
structures could also be used. A signal wire (not shown) is
electrically coupled to each electrode in the multipole structure
310. The wires run through the flexible shaft 320 into a handle
300, and then to an external multiple pin connector 330. The
connector 330 electrically couples the electrodes to the electrode
controller 140 in FIG. 1B.
[0077] FIG. 3 shows an ablation probe that features a long narrow
flexible catheter body 380. For the sake of illustration, FIG. 3
shows a single ablation electrode 360 at the distal tip of the
catheter body 380. Of course, other configurations employing
multiple ablation electrodes are possible. The ablation electrodes
can be used to emit signals to pace the heart structure 110 (in
FIG. 1B). A handle 370 attached to the proximal end of the catheter
body 380 controls a steering mechanism that runs the length of the
catheter, and bends or flexes the distal portion of the catheter
body 380 along its length. This is shown in two positions 350. In
the preferred embodiment, the tip can curve through an angle of
curvature of approximately 180 degrees in each plane. The actual
steering mechanism can vary, such as that described in U.S. Pat.
No. 5,254,088 issued to Lundquist, which is incorporated herein by
reference. A wire (not shown) electrically couples the ablation
electrode 360 to a connector 390. Connector 390 interfaces the
electrode to an energy generator (172 in FIG. 1B) to provide
varying types of energy to the electrode 360. Typically, the
generator 172 supplies radio frequency energy, such as Model
EPT-1000 from EP Technologies Inc., Sunnyvale, Calif. In use, the
physician places the catheter 138 in contact with heart tissue at
the site identified for ablation. The ablation electrode 360 emits
energy to thermally destroy the tissue. Alternatively, a
piezoelectric crystal-based catheter could generate ultrasound
energy, while cells or genes could be injected to improve or worsen
conduction.
[0078] In a preferred embodiment, the invention automatically runs
a sequence of six modes that can be modified interactively by the
user. The mode menu 220 can have different, fewer or greater number
of modes. By way of example, a user can select Mode A, signal
sampling, from the mode menu 220 on display 230 so that this mode
is operated first. Upon completion of the mode, the user is
prompted to either automatically enter Mode B or, for example, to
return to the mode menu 220. While in Mode A, if a rapid arrhythmia
("tachycardia") is detected by the process controller 190, it thus
prompts the user to initiate mode B: Surface ECG Diagnosis and
Localization, that suggests the most likely diagnoses and possible
locations within the heart. If intracardiac catheters 134', 136 or
138 are connected, the process controller 190 can then prompt the
user to initiate mode C: Intracardiac Diagnosis and Arrhythmia
Localization. This interactive mode will quantify entrainment with
concealed fusion to help the physician confirm the diagnosis and
location of the arrhythmia circuit. Upon completion of Mode C, the
user can then be prompted to enter Mode D: Catheter Guidance to
help direct the catheter to an appropriate ablation site. Upon
completion of this mode, the user may then be prompted to return to
the mode menu.
[0079] In the illustrated embodiment, the user can terminate any
mode manually if desired. Modes C and D can be further enhanced if
the ROVE catheter is connected to an intracardiac mapping system
(such as by Endocardial Solutions, Inc., or Biosense Webster,
Inc.). After ablation, the process controller 190 can suggest the
use of mode E: Determination of Ablation Success, or, as with any
of the modes, the user can enter mode E directly from the mode menu
220. Upon direct entry into a mode, if the required information has
not yet been obtained, the user can be prompted to enter or
designate a source for such information. As an alternative example,
if the patient starts in a regular rhythm, the process controller
190 will offer the option of enabling mode F: Arrhythmia
Prediction, or of inducing the cardiac event by pacing from module
160.
Modes of Operation
[0080] As previously mentioned, the display 230 shows a menu of six
user-selectable modes of operation 220. FIG. 4 provides an overview
of the six modes (corresponding to the below headings A-F) of
operation of the invention in the preferred embodiment. FIG. 5
expands upon process blocks 614, 655 and 720 of FIG. 4.
A. Signal Sampling
[0081] In the illustrated and preferred embodiment, Signal Sampling
is performed during an arrhythmia that the physician seeks to
diagnose or treat, for example, ventricular tachycardia (VT),
atrial tachycardia (AT), atrial flutter (AFL) or atrial
fibrillation (AF). This is shown in FIG. 4, process 605. The
invention requires digital ECG and electrogram data. However, in
cases where these cannot be provided directly, analog sources of
these signals can be digitized prior to processing by the
invention. In a preferred embodiment, the ECG or electrogram data
should comprise at least one cardiac cycle (which generally
represents a heart beat). In modified circumstances, a cardiac
cycle may include at least one instance of portion of the interval
between two instances of the rhythm under consideration. This will
include portions of atrial and ventricular activity in sinus
rhythm, or simply ventricular activity in ventricular tachycardia,
for example.
[0082] In one embodiment, the signal sampling mode requires that
either ECG electrodes are connected to the body surface 130, and/or
that other electrodes are connected such as catheters 134' or an
ablation catheter 138 or an electrode 136 in the esophagus 120.
During sampling, it is important that the various intracardiac
electrodes remain stationary relative to the heart 110, and that
the surface ECG electrodes 130 are not re-positioned. In an
alternative embodiment, signal sampling can be performed without
connecting any catheters, by uploading already-stored electrograms
from the database 197 to the process controller 190. In a third
embodiment, the process controller 190 interfaces to different
acquisition systems 198 to upload electrograms. In this embodiment,
the sampled signals can be traditional as well as virtual (or
computed) electrograms from a mapping system such as that by
Endocardial Solutions, Inc. (St. Paul, Minn.). Electrograms are
analyzed in an analogous fashion for all embodiments.
[0083] To ensure that adequate contact is made in the desired
region of the heart 110 with an electrode catheter 134', 136 or
138, the physician may have to move, rotate, curve or straighten
the catheter. The degree of contact can be monitored by the process
controller 190 in various ways. For example, the process controller
190 can ascertain contact by comparing the amplitude of the sensed
signals during the cardiac event to a predetermined threshold.
Alternatively, the process controller 190 can condition the pacing
module 160 to emit pacing signals through catheters 134', 136 or
138. The process controller 190 conditions the processing module
150 and sensing electrodes 130, 134', 136 or 138 to detect the
pacing stimuli or paced electrograms and use their amplitude to
ascertain effective contact. As a third alternative, the processing
module 190 can also ascertain the desired degree of contact by
measuring tissue impedance.
[0084] Once the multiple electrode system is properly positioned,
the process controller 190 conditions the electrodes 130, 134', 136
or 138, conditioning module 150 and recording module 158 to record
electrogram samples during the selected cardiac event at a given
gain and paper sweep speed. The processor controller 190 then
records and saves electrogram samples in the host processor 195. In
an alternative mode of operation, the user uses module 200 to input
instructions to upload previously stored electrograms from the
database 197. Other acquisition, recording or archival systems can
be interfaced 198 from a 12-lead ECG machine, event recorder,
Holter monitor or other systems. This invention can use any user
selected data sample rate (such as 1 ms sampling, 4 ms sampling and
so on). When data is imported from these systems, the data sample
rate will be matched to that of the invention using linear and
other interpolation methods. Parts of this process can be performed
before acquiring any real-time data. All signals are subsequently
analyzed in an analogous fashion.
B. Surface ECG Diagnosis and Localization
[0085] The Surface ECG Diagnosis and Localization mode uses ECG
signals from electrodes 130 in the standard 12-lead or the Frank
X,Y,Z configurations, and is summarized in FIG. 4, processes 610 to
618. The algorithms selected from the menu of actions 210 in FIG.
1B can be relatively easily implemented in software by a
practitioner skilled in the art, operate relatively quickly and are
suitable for real-time as well as off-line analysis. For example,
in one implementation of the algorithm in the Labview programming
language running under Windows 2000 on a Pentium 3 PC at 1.2 GHz
processor speed, analysis of a full ECG took under one second.
[0086] FIG. 5 illustrates a flowchart detailing the primary
analysis of this invention of temporospatial morphology
correlation. This algorithm comprises several computational steps,
described below.
1. Temporospatial Morphology Correlation
[0087] Temporospatial morphology correlation is the major analysis
of the present invention and a significant advance over prior art
methods. It involves correlating the electrographic signal shape
("morphology") to a template over time, then assessing these
temporal correlations simultaneously in multiple spatial planes
(based on the X, Y and Z directions). It is generally performed
after baseline correction (processes 420-500). These processes are
designed to compute a baseline voltage, even if this is obscured by
continuous atrial activity such as in atrial flutter. The
processes, which can be useful for example in Eigen vector
calculation, and which can be omitted in modified embodiments, will
be discussed later.
[0088] In FIG. 5, process 520 commences the algorithm, which can be
made on electrographic data or derived signals. Process 530 selects
an atrial or ventricular template, typically selected for atrial or
ventricular rhythms, respectively.
[0089] In a preferred embodiment, the physician will initially
(e.g., at step 600) focus his or her attention on a region of
abnormality on the patient's ECG. This focus will typically be the
atrial signal (P-wave) for atrial rhythm problems. For example, the
physician may observe abnormalities (e.g., abnormal shape or
vector) in the atrial portion of the ECG. The focus can also be the
ventricular portion of the ECG reflecting ventricular
depolarization (QRS complex) or ventricular repolarization (the
T-wave). The physician may then select a template that primarily
includes the activity of interest (e.g., F wave in atrial flutter
or QRS complex in ventricular tachycardia). In a preferred
embodiment, the invention will provide an automatic selection of
template that the user may accept. Typically, the template duration
is 70-400 milliseconds, but the selection incorporates the duration
of electrical activity and the inter-beat interval to shorten the
template at faster rates. Templates have no theoretical upper limit
on duration, are typically 50-200% of the duration of activity. The
duration of activity may span the entire cycle (for example, atrial
flutter or monomorphic ventricular tachycardia), or be shorter (for
example, focal atrial or ventricular tachycardias) or longer (such
as where altemans arises since atrial or ventricular activation
exceeds cycle length). As the template lengthens to span more of
the cycle or multiple cycles, such as F-waves (a variant of P-waves
seen in AFL) or ventricular cycles in VT, analysis will be more
specific for reproducibility but less sensitive since it will be
less tolerant of variations in shape or rate.
[0090] In an alternative mode of operation, the host processor 190
searches for, locates and uploads a previously stored template from
the database 197. This mode allows the current event to be compared
against a template of a previous rhythm in this or another patient.
Indeed, a particular strength of this method, which will be
expanded upon later, is that any signal shape can be used to assess
correlation, including a generic template unrelated to the ECG
channel in question.
[0091] FIG. 6 summarizes the main correlation engine for the
invention. In a preferred embodiment illustrated in FIG. 6, the ECG
signal should comprise at least one cardiac cycle. A cardiac cycle
is defined as a heart beat. However, in modified circumstances, it
may be defined to encompass a portion of the interval between two
instances of the rhythm under consideration. Processes 440, 450 and
460 (and FIG. 6) summarize correlation of the template against a
window of the same duration from the ECG. This yields one
correlation value. The next correlation is calculated by `sliding`
the template one point (for example, 1 ms) along the digital or
digitized ECG. Alternatively, the template can slide more rapidly
across the ECG by using steps of 2 or more milliseconds, so that
the template is slid more than 1 point per step. The template is
then correlated against this ECG. This process is repeated for the
entire ECG duration as shown in FIG. 6 (process loop 440 to 460),
then repeated for each ECG channel (process loop 420 to 470).
Correlation can proceed using Pearson, Fischer or other functions.
The preferred embodiment uses the Pearson function, which can be
calculated on M pairs of data {X.sub.k, Y.sub.m}, where X.sub.k and
Y.sub.m are samples of fixed duration from the original ECG
sequence, as follows: r j = M .function. ( k , m .times. X k
.times. Y m ) - k .times. X k .times. m .times. Y m [ M .times. k
.times. X k 2 - ( k .times. X k ) 2 ] .function. [ M .times. m
.times. Y m 2 - ( m .times. Y m ) 2 ] ##EQU1## where the index in
X.sub.k, L.ltoreq.k.ltoreq.L+M-1; and the index in Y.sub.m,
j.ltoreq.m.ltoreq.j+M-1; j=1, . . . , Q-M (where Q is the last
sample point for analysis in the ECG); and
1.ltoreq.L.ltoreq.Q-M.
[0092] Process 460 performs this repetitive correlation for
successive timepoints as shown in FIG. 6. This generates a
correlation time series, i.e., a mapping of correlation values
against time, for this signal (e.g., an ECG signal in one preferred
embodiment). FIG. 6 shows analysis for a digitized cardiac signal,
derived from the conditioning unit 150. First, in this case of
atrial flutter the upper part of the figure shows clearly separate
ventricular activity (QRS complexes) and intervening segments,
which include atrial activity and ventricular repolarization
(T-waves). These latter two components are difficult to separate
visually. An atrial signal template is selected (and labeled) just
prior to a QRS complex, to reduce the inclusion of T-wave activity.
The invention cross-correlates this template to the original ECG at
progressive timepoints, as indicated, generating a series of
correlation ("r.sub.j") values. The lower part of the figure plots
these correlations across time. Periodic r-values oscillate with
atrial (and ventricular) cycles over time, reflecting each atrial
cycle (correlations approach 1) and superimposition of a QRS
complex on alternate atrial cycles (reducing maximum correlation to
approximately 0.7). The largest positive excursion of the
correlation function is therefore close to 1.0, and the largest
negative excursion approaches -1.0.
[0093] In general, a "feature" can be identified whenever
correlation values exceed a predetermined threshold. A "feature"
may comprise atrial depolarization (the P-wave) or repolarization,
or ventricular depolarization (QRS complex) or repolarization (the
T-wave). In FIG. 6, the clearly evident P-waves (or F-waves of
atrial flutter) are identified by correlation values (labeled
"atrial peak correlations"). In addition, FIG. 6 also illustrates a
"feature extraction" aspect of the invention, wherein atrial
activity that is masked by ventricular activity, and therefore not
clearly evident in the ECG, is also unmasked by the correlation
method. These unmasked P-waves are labeled "masked atrial peak
correlations" and overlap with a QRS complex or T wave. Both the
"atrial peak correlations" and "masked atrial peak correlations"
occur at precisely the same time as signals measured from inside
the atria of the heart (depicted by the vertical lines and arrows
labeled "atrial activity inside the heart" in FIG. 6, e.g., using a
catheter inside the heart). The use of temporospatial correlation
frequencies, as described below, can further enhance this function
in other cases. The present example illustrates the strength of
feature extraction in this invention. This represents a significant
improvement over the prior art and is also of benefit in
identifying atrial activity for baseline correction as will be
discussed later.
[0094] Temporospatial correlation also offers significant
advantages over vectorcardiograms (VCG). In the prior art VCG of
atrial flutter in FIG. 7B, although the ventricular loops are large
their similarity to each other is blurred by small voltage
fluctuations from gain and noise effects. Furthermore, the
regularity of atrial loops is completely lost in this way, since
similar levels of noise overwhelm the smaller atrial signals. This
remains even when the VCG is magnified over the atrial portion
(FIG. 7B). The temporospatial correlation plot is shown for
comparison in FIG. 7A.
[0095] Process loop 520 to 570 in FIG. 5 repeats the above
correlation analysis for each ECG lead. This generates a
correlation time series, i.e., a mapping of correlation values
against time, for each ECG lead. Process loop 540 to 560 repeats
temporal correlation analysis for successive timepoints, in an
analogous fashion to process loop 440 to 460. Process 550 uses
separate templates for atrial activity, ventricular depolarization
and repolarization. The preferred embodiment computes Pearson
correlation, although Fischer or other coefficients can be
used.
[0096] Process 580 shows temporal correlations plotted for 2 leads
to generate a spatial correlation loop for several defined planes
(displayed on component 230 in FIG. 1B) using leads V5, aVF and V1
as semi-orthogonal leads X, Y and Z. By way of example, FIGS. 8A-F
show the resulting temporospatial correlation loops. A digitized
cardiac signal is shown in panel 1 of FIG. 8A-F. This digitized
cardiac signal is represented by ECG leads V5, aVF and V1. Panel 2
shows correlation time series, i.e., mappings of correlation values
against time, for each ECG lead. Panel 3 shows the plots of these
temporal time series for one lead against another. Specifically,
plots are shown for lead V5 versus aVF (XY plane), lead aVF versus
V1 (YZ) and lead V5 versus V1 (XZ). Frank orthogonal X, Y, Z leads,
or other leads, could be used just as easily.
[0097] The distinct atrial and ventricular correlations (in panel 2
of FIG. 8A) give rise to separate loops (FIG. 6 and panel 3, FIG.
8A). First, atrial correlation loops, labeled in panel 3 FIG. 8A,
reflect correlations of the atrial template to the atrial portion
of the ECG over time. "Atrial correlation loops," generated from
successive cycles of atrial activity, are labeled in panel 3' of
FIG. 8A. Each atrial correlation loop reaches the (1,1) coordinate
(labeled `atrial peak correlation`) signifying that the ECG closely
correlates to the atrial template at this time. Each atrial loop
also lies roughly parallel to the identity line joining (1,1) with
(-1,-1), signifying that activity remains in-phase along each axis
of this plane over time. Second, when atrial activity is masked by
ventricular activity, the temporospatial correlation method is
still able to extract atrial activity and generate loops reflecting
this ventricular influence. "Masked atrial correlation loop"
indicates these loops in panel 3', FIG. 8A. Since these loops
reflect correlations influenced by ventricular activity, they
approach but do not reach the (1,1) correlation, at which point
they are labeled "masked atrial peak correlations" in FIG. 6 and
panel 3, FIG. 8A. The points where atrial correlation loops and
masked atrial correlation loops join are labeled `vent. take off`
in panel 3 of FIG. 8A. By analogy, using a ventricular template
would result in "ventricular" and "masked ventricular correlation"
loops (not shown). In the illustrated embodiment used to generate
FIGS. 6 and 8, template duration was 80-200 ms, and the data
sampling rate was every 4 ms. However, the number of sampled data
points and the data sampling frequency can be varied by the
user.
[0098] Other applications of this method will be described later.
For example, in Mode F: Arrhythmia Prediction described later,
temporospatial correlation can measure alternans of the P-wave, QRS
complex or the T-wave. In these cases the invention will determine
the slope and intercept of the best-fit line joining all of the
correlation points. Parameters of these lines such as their
variability, or dispersion, patterns of alternans and abrupt
changes or discontinuities, may indicate patterns of alternation or
alternans between successive cycles.
2. Rationale for Temporospatial Correlation
[0099] The current invention exploits the concept that regular
activation within the heart will produce repeatable electrical
wavefronts on the surface ECG. These wavefronts should retain a
consistent relationship between each spatial axis, or remain
spatially in-phase, and should be reproducible between successive
cycles. Variable activation wavefronts, including the "functional
reentry" of atypical AFL or AF, will have additional directions of
activation and therefore deviate from this temporal and spatial
reproducibility. Temporospatial correlation has been designed to
exploit this concept.
[0100] By way of example, typical (isthmus-dependent) atrial
flutter is characterized by a re-entrant activation wave that
follows a very reproducible three-dimensional spatial path in the
atria. This involves continuous activation in a counter-clockwise
or clockwise direction around a region known as the tricuspid
annulus in the right atrium. All other atrial regions are activated
passively and secondarily. The resulting atrial activation exhibits
a "saw-tooth" appearance in the inferior ECG leads (II, III, aVF),
with discrete signals in lead V1 (see FIG. 8A panel 1). However,
atrial activity is of low amplitude, easily obscured by the T-wave
and noise including baseline wander, line frequency noise,
respiratory and muscle artifacts, and other sources. It is readily
seen, in FIG. 8A, how the QRS and T waves can obscure it.
Therefore, the diagnosis of typical AFL from the ECG is often
difficult. Although AFL has been described by way of example, this
regularity also applies to regular monomorphic VT, while variable
activation applies to polymorphic VT or ventricular
fibrillation.
[0101] Temporospatial correlation is supplemented by additional
analyses to improve the diagnostic ability of the invention. First,
Eigen vectors are computed in process 590 in FIG. 5, for the
correlation timeplots, the original ECG signals and derived Eigen
leads. These analyses assess the plane of maximum energy for the
correlation plots and the ECG, each of which identifies the plane
in which the arrhythmia circuit is most likely to lie. This
information is used in Mode D: Catheter Guidance System, described
fully later. In process 595, the additional computation of
frequency and power spectra for original electrograms and
correlation values provides another means for assessing regularity.
Notably, since correlations equally weight atrial and ventricular
activity, frequency analysis of these signals will identify their
relative rates of activation, and de-emphasize the frequencies that
contribute to the different shapes and amplitudes of each
complex.
3. Advantages of Temporospatial Correlation Analysis
[0102] The significant advantages of temporospatial morphology
correlation over methods of the prior art are that it assesses
several attributes concurrently, in a computationally efficient
manner. Referring to FIGS. 6, 7 and 8A-F, the method assesses and
provides: [0103] 1. Similarity of the ECG event to the template,
signified by a cross-correlation approaching 1. The electrogram
events are typically complex signals, and their detailed shape is
reflected in the morphology cross-correlation analysis. Thus, each
atrial or ventricular wavefront will be assessed against its
relevant sampled wavefront. [0104] 2. Amplification of
low-magnitude signals of interest. For example, this allows
analysis of atrial activity which is small and therefore very
sensitive to noise. Atrial activity is poorly represented during
arrhythmias in the traditional method of vectorcardiography, shown
for comparison in FIG. 7B.
[0105] 3. Detection and extraction of superimposed atrial and
ventricular activity. Using cross-correlations to selected atrial
(or ventricular) activity, the method accurately feature extracts
each atrial cycle and its timing during AFL even if superimposed on
a QRS complex (see FIG. 6). This method is also very effective in
separating distinct activity when superimposed on electrograms
recorded from inside the heart. [0106] 4. Maintenance of the same
spatial activation sequence from cycle to cycle. This is measured
by the spatial phase and, when coherent (in-phase), indicates that
activation (correlations) are high or low between leads
simultaneously for multiple cycles. Such loops of correlations
between spatial planes are shown in FIG. 8A-F, panel 3. First,
correlation loops for reproducible activation will approach the
correlation coordinate (1,1) per cycle. Second, spatial coherence
is seen when the entire loop, or a significant portion of it, lies
predominantly parallel to the identity line from (1,1) to (-1,-1).
Third, if a template is selected from a different set of ECG data
or even another patient (from one of the alternative embodiments
described above), correlation loops should still be reproducible
yet may no longer follow the line of identity. [0107] 5. Spatial
reproducibility of activity, such that temporospatial correlation
loops (FIG. 8A) are almost superimposable for successive cycles.
[0108] 6. Variations in rate of the same rhythm--signified by
correlations approaching 1 at different times from cycle to cycle
(FIG. 8A-F panel 2), or reproducible loops that have differing
periods (durations) across cycles (see FIG. 8A-C, panels 3). [0109]
7. Alterations in the rhythm--signified by a sudden change in the
shape of the temporospatial correlation loop at some point in the
ECG. [0110] 8. Accurate spectral assessment of electrical activity
for each chamber. Since temporal correlations are of normalized
amplitude, their frequency analysis more accurately assesses the
rate of activation than the analysis of raw electrograms, which are
influenced by frequencies contributing to the shape of the
(largest) QRS component. This is seen clearly by comparing spectra
from electrograms (panel 4) and correlations (panel 5) of FIG. 8C
of atypical atrial flutter. [0111] 9. Accurate assessment of
atrial-to-ventricular relationships, represented by the number of
atrial to ventricular loops, and also the time within the atrial
loop at which the ventricular loop arises. This analysis identifies
whether ventricular and atrial activity are related (as in FIG.
8A), variable (as in FIG. 8C) or independent (FIG. 8F). [0112] 10.
Detection of isoelectric intervals in the ECG as a clustering of
low correlation values centered on zero (0,0). This is seen in
sinus rhythm and some atrial tachycardias. Alternatively, a
featureless template sample may give rise to extreme correlation
values that are unchanging over a period of time. This "temporal
invariance" is illustrated in FIG. 8B for a case of atrial
tachycardia. [0113] 11. Insensitivity of the analysis to factors
including baseline wander and electrographic signal gain. This
provides a significant advantage of this method over the prior art
vectorcardiography. Traditional vector loops (FIG. 7B) are degraded
significantly by baseline wander, variable gain and lack of
isoelectric definition. The present invention overcomes these
shortcomings.
[0114] These attributes give extremely high sensitivity and
specificity for atrial and ventricular arrhythmias, including their
atrioventricular relationships. A major strength of the current
invention is that it significantly improves the diagnosis of subtly
different arrhythmias, such as typical AFL versus atypical AFL or
typical AFL versus combined AFL/AF, from the standard surface ECG.
These distinctions can be important since these distinct entities
often require quite different therapies.
[0115] It must be noted at this point that this analysis also has
potential applicability in the field of electrical engineering,
such as to assess frequency variability ("jitter") in oscillating
waveforms, such as those in analogue circuits. In this application,
frequency variations would be manifest as amplitude modulations
(below a perfect correlation magnitude of 1.0) from cycle to cycle.
These differences may be enhanced for discrimination purposes by
the use of linear, logarithmic or other scaling methods.
4. Examples of ECG Diagnosis
[0116] FIG. 4 shows a flowchart outlining the modes of operation of
the invention. Processes 612 to 618 summarizes the diagnostic part
of the invention and illustrates how the algorithm components shown
in FIG. 5 and described above work together. In process 612, ECGs
are selected for analysis then analyzed for temporospatial
correlation and frequency analysis, as mentioned above (process
614), to result in correlation loops for each plane
(lead-pair).
[0117] The invention can diagnose atrial or ventricular arrhythmias
although it is particularly effective for atrial arrhythmias, which
are generally more difficult to diagnose since atrial signals have
lower signal to noise ratios. Examples will shortly be provided but
should not be seen as limiting the applicability of the invention
in any way. FIG. 8 shows analysis by the invention for A. Typical
isthmus-dependent atrial flutter, B. Focal atrial tachycardia, C.
Atypical atrial flutter, D. Atrial fibrillation, E. Monomorphic VT,
and F. Polymorphic VT. Each of FIG. 8A-F has the following
components. Panel 1: Orthogonal ECG leads (V5, aVF, V1), with
templates illustrated. Panel 2: Correlation values over time for
each lead. Panel 3: Temporospatial correlation plots for the planes
given by lead pairs V5 and aVF (XY), leads aVF and V1 (YZ), and
leads V5 and V1 (XZ). Panels 1, 2 and 3 represent 4 seconds of
data. Panel 4: Power spectra for each ECG lead in panel 1. Panel 5:
Power spectra for each correlation plot in panel 2. Panels 4 and 5
are computed over 8.2 seconds of data. In each case below, the
diagnostic steps are outlined one at a time from the perspective of
a human user. However, these components could easily be analyzed
using neural networks, or a deterministic or other expert
system.
[0118] FIG. 6, which has already been discussed above, shows the
temporal correlation method for typical atrial flutter. Briefly,
processes 510 to 530 (FIG. 5) identify atrial activity and select a
template (upper panel; labeled), just prior to a QRS complex to
minimize T-wave inclusion. Processes 540 to 560 (FIG. 5)
cross-correlates the template to the ECG at successive timepoints
to produce plots of correlation (labeled "r-value for each point")
against time. A periodicity in r-values is clearly seen, with
values approaching 1 for each repetition of the template (clean
F-wave), and distinct values when the template slides across the
QRS complex. Peak correlations correspond precisely to intra-atrial
activity, as shown in the FIG. 6.
Isthmus Dependent (Typical) Atrial Flutter
[0119] Now turn to FIG. 8A. This provides, by way of example, the
preferred mode of operation analyzing typical isthmus-dependent
atrial flutter. This rhythm is characterized by a re-entrant
wavefront of activation that follows a very reproducible
three-dimensional spatial path in the atrial tissue. This involves
continuous counter-clockwise or clockwise activation in the right
atrium, parallel to the plane of the tricuspid valve. Left atrial
activation then follows secondarily along stereotypical paths
involving the coronary sinus musculature and tissue known as
"Bachmann's bundle". The resulting atrial activation exhibits a
"saw-tooth" appearance in the inferior ECG leads (aVF, II, III),
with discrete signals in lead V1. However, these F-waves are of low
amplitude, easily obscured by the T-wave and noise such as baseline
wander, line frequency noise, respiratory and muscle artifacts, and
other sources. Therefore, atypical forms of atrial flutter with
different F-waves are often mistaken for typical AFL.
[0120] The present specification exploits the temporal and spatial
regularity of this activation by determining whether correlations
remain in-phase in all spatial dimensions simultaneously. In FIG.
8A, panel 3 shows that the invention compares temporal correlations
for pairs of ECG leads defining each spatial plane. Only 4 seconds
of data are presented for clarity. In practice, any duration may be
analyzed although 8-10 seconds are typical and sufficient. The
correlation loops formed by sliding this template across the ECG
results in the temporal correlations shown below the ECG (process
loop 540 to 560 in FIG. 5).
[0121] Repeating this for all ECG leads (FIG. 8A panel 3 and FIG. 5
process loop 520 to 580), results in spatial correlation loops for
planes XY (V5 versus aVF; coronal), YZ (aVF versus V1; sagittal)
and XZ (V5 versus V1; axial) for simultaneous timepoints. Atrial
and ventricular correlation loops are readily identified and are
labeled. The point of ventricular takeoff from each atrial loop is
also labeled.
[0122] It can be seen that atrial (and ventricular) loops are
reproducible in each spatial plane. In addition, each atrial loop
approaches the (1,1) coordinate and is spatially in-phase {lies
roughly parallel to the identity line joining (1,1) with (-1,-1)}.
In particular: [0123] 1. Panel 2 confirms continuously varying
atrial activity, with correlations that vary continuously over
time, without a clear isoelectric, which is reflected by a period
of unchanging correlations. This finding is more supportive of the
diagnosis of atrial flutter than of atrial tachycardia (where
isoelectric TP, PR and other segments may be seen). [0124] 2. In
panel 3, a determination can be made as to whether each atrial peak
correlation passes beyond a predetermined threshold coordinate (x,
y). When this occurs, it can be determined that the atrial template
(in this case the flutter wave) is occurring repeatedly, i.e. at
both atrial peak and masked atrial peak correlation points (in
FIGS. 6 and 8A). Therein lies the basis for feature extraction in
the invention. In a preferred embodiment, x=0.8, y=0.8. This
similarity to the original template (wavefront sample) in three
dimensions excludes atrial fibrillation and atypical forms of
atrial flutter. [0125] 3. Panel 3 also shows that the principal
axis of atrial correlation loops lie almost parallel to the line of
identity. This indicates spatial phase coherence, or that the
correlations are simultaneously high or low in each axis. [0126] 4.
Panel 3 shows reproducibility of successive correlation plots,
showing that successive atrial cycles are reproducible over their
entire duration. [0127] 5. Panel 3 also shows very similar areas of
atrial correlation loops. These areas can be computed since the
loops are essentially "closed" per cycle. In cases where the loops
do not completely close, interpolation methods are used to close
the loop and compute areas in three dimensions. Lower variability
or dispersion in correlation loop areas from cycle to cycle is a
strong indicator of reproducibility in time and space. [0128]
Process 590 reduces these indices into a single parameter, a
coherence reproducibility index, C, comprising the following
assessments: [0129] (a) The maximum correlation reached in each
plane over multiple cycles, represented as loops reaching (x,y). A
higher correlation indicating greater reproducibility and, in one
preferred embodiment, x=0.8, y=0.8. [0130] (b) Slope of the
principal axis of the correlation loop, relative to the line of
identity joining (-1,-1) to (1,1). This is a measurement of spatial
phase and, if coherent, tends towards this line of identity. [0131]
(c) Correlation loop variance between successive cycles for each
spatial plane; a lower variance indicating greater reproducibility.
[0132] (d) Correlation loop area variance between successive cycles
for each spatial plane; a lower variance indicating greater
reproducibility. [0133] C is designed such that a higher value
indicates a greater likelihood of a regular, reproducible
arrhythmia over time. [0134] 6. Panel 3 in this case therefore
reveals spatial coherence in all planes. Temporospatial coherence
indicates that spatial phase is maintained, i.e. that loops lie
parallel to the line of identity (X=Y, Y=Z, X=Z) and have peak
correlations that approach (1,1). From the above analysis,
coherence reproducibility indices are calculated for each plane.
The XY plane (leads V5/aVF) is the most sensitive indicator for
atrial flutter (typical or atypical). In this case, if the XY loop
is not temporospatially coherent then, pending spectral analysis
(described below), another diagnosis is more likely. It should be
stated that data from each plane can be condensed into and derived
from a single three dimensional plot. However, a series of two
dimensional plots is shown for clarity and ease of
understanding.
[0135] Points 1-6 exclude atrial fibrillation and support the
diagnosis of atrial flutter over focal atrial tachycardia. [0136]
7. Panel 3 depicts a major strength of the invention--automatic
segregation of atrial and ventricular activity. Note that a
different correlation loop arises as the atrial template correlates
against each QRS complex (labeled "Vent. take off"). [0137] 8. Note
also that ventricular loops are also consistent and reproducible,
confirming that ventricular morphology does not change during the
recording. [0138] 9. Panel 3 therefore also depicts the ability of
the invention to feature extract a desired waveform, such as the
illustration of atrial and masked atrial activation in FIGS. 6 and
8. Despite the fact that alternate P-waves (or its variant, the
F-wave, in atrial flutter) are clearly masked by QRS complexes (see
FIG. 8A, panel 1), each atrial cycle is clearly seen (see FIG. 8A
panel 3 and 3'). In general, the invention will separate "pure"
atrial or ventricular activity from those influenced by the other
chamber. As shown in FIG. 6, this allows atrial activity to be
consistently detected, and timed precisely with atrial signals from
inside the heart, even for P-waves that are buried within the QRS
complex. [0139] 10. Temporospatial ECG correlation can better
extract the timing of intra-cardiac activation, in certain cases,
when used in conjunction with correlation spectra. When correlation
plots deviate from sinusoidal (that is, they contain a band of
discrete frequencies rather than simply one fundamental), frequency
decomposition of this band will identify times when the activity
under consideration (the F-wave in FIG. 6) occurs. These times
correlate well with intra-cardiac signals in these cases. [0140]
11. Further, panel 3 shows the relative rates of atrial and
ventricular activity. The number and duration of atrial and
ventricular loops remains constant throughout the ECG segment, so
that the ratio of atrial to ventricular events is fixed. [0141] 12.
Panel 3 also shows the exact temporal relationship between atrial
and ventricular activity, in addition to their ratio. Specifically,
each ventricular loop arises from the same point of each atrial
loop. This supports a physiologic atrial to ventricular
relationship, and weighs against arrhythmias where atrial and
ventricular activity are independent but appear associated by
chance because of similar rates (known as "iso-rhythmic
dissociation").
[0142] All of these features point to the most likely diagnosis of
atrial flutter with constant A:V conduction, although a focal
atrial tachycardia cannot yet be excluded. The invention now uses
additional analyses.
[0143] Process 590 of the invention computes Eigen vectors and
leads to define the spatial plane containing the greatest power
content of the ECG. The 2 Eigen vectors of maximum amplitude define
the plane and vector resultant containing the maximum power in all
3 ECG leads. Eigen computation first requires the definition of a
point of zero power or amplitude. This is the rationale behind the
rigorous baseline correction above (processes 420 to 500 in FIG.
5). Eigen vectors are then computed using standard mathematical
techniques for each cycle as well as for the entire sequence. An
Eigen vector whose orientation does not vary between cycles is
another index of a regular and reproducible rhythm; while the
converse is true. Similarly, cases in which one Eigen plane
encompasses most of the ECG power indicates a regular reproducible
rhythm event. Eigen vector analysis can also be focused on ECG
regions, such as atrial or ventricular depolarization or
repolarization. This alternative embodiment can assess variations
in the T-wave, such as T-wave alternans [30], and is computed by
excluding ventricular or atrial activity, respectively, from the
calculation. Similarly, the `isoelectric` interval can be defined
to essentially threshold `in` or `out` the activity of
interest.
[0144] In the example in FIG. 8A, Eigen vector analysis confirms a
temporally and spatially reproducible atrial rhythm. This supports
a diagnosis of typical atrial flutter with reentry around the
tricuspid annulus or focal atrial tachycardia with activation
parallel to this plane. The Eigen vector in this case had minimal
variance, indicating little variation in the three dimensional
plane of maximum energy between cycles.
[0145] Finally, panels 4 and 5 in FIG. 8A show the results of
spectral decomposition across the entire (non-segmented) ECG lead
and its correlation plot. Several methods can be applied to perform
spectral decomposition, including fast and discrete Fourier
transformation, wavelet decomposition and other methods. Results
from this analysis are usually plotted as power or spectral
magnitude (vertically) for several spectral frequencies
(horizontally). Power is calculated in the preferred
embodiment.
[0146] Finally, spectral analysis is performed on the ECG as well
as the temporal correlation time series (that is, on panel 1 and
panel 2 data). Panel 4 shows the fast Fourier transform (FFT), with
a prominent peak at or around 4 Hz and regular harmonics for each
lead (plotted in different line styles). Panel 5 shows that the FFT
on correlations shows a more dominant 4 Hz peak with attenuated
harmonic amplitudes. This work is a significant improvement over
the prior art. First, it agrees with work by Stambler et al. [9]
who, from intracardiac signals, showed a 4 Hz peak in AFL. Other
prior art, such as U.S. Pat. No. 6,064,906 issued to Langberg from
the ECG, and No. 6,178,347 issued to Olsson using intracardiac
signals, showed similar frequency spectra in AF (4 Hz dominant
peaks).
[0147] Conclusion. The integration of all of the above analyses
suggest a diagnosis of typical atrial flutter for the case in FIG.
8A. This was confirmed on further study. Atrial activity is
regular, reproducible and spatially in-phase in all three
dimensions, and each ventricular cycle arises at a consistent point
from preceding atrial activity.
Atrial Tachycardia
[0148] FIG. 8B shows another ECG (panel 1) for which temporal
correlations show regular periodicity (panel 2). In panel 3, atrial
temporospatial correlation loops show phase coherence. That is,
they retain spatial phase, since their principal axes lie along the
line of identity, indicating that atrial activity is reproducible
in each plane, and they are similar to template since they approach
the (1,1) coordinate on each cycle. Ventricular correlation loops
are also consistent, at a lower rate. Of note, atrial correlation
loops show correlations which (for the region illustrated by
horizontal lines in FIG. 8B, panel 3) show periods of unchanging
correlation over time ("temporal invariance") such as the XY plot
(panel 3). This is seen by its near-horizontal (Y=-1) and
near-vertical (X=0.6) loops sections, that suggest that the
template is being correlated to an isoelectric or unchanging ECG
region. Inspecting panel 1 (FIG. 8B) reveals this horizontal ECG
section (particularly in the Y lead).
[0149] This finding strongly supports a diagnosis of focal atrial
tachycardia with such an isoelectric or unchanging ECG region,
since atrial activation on the ECG in atrial flutter is continuous,
without diastole. Further, correlation plots show a fixed
atrio-ventricular ratio and timing relationships, weighing against
atrial fibrillation.
[0150] Eigenvector analysis showed a reproducible vector of maximum
energy, also weighing against AF and supporting the diagnosis of
focal atrial tachycardia. Finally, spectral analysis in panels 4
and 5 show regular atrial activity, without a prominent 4 Hz peak
but with regular harmonics. Correlation spectra (panel 5) emphasize
a narrower range of frequencies at 2.5 and 10 Hz.
[0151] Conclusion. These findings suggest the diagnosis of focal
atrial tachycardia, at a rate of 150 beats per minute. This was
confirmed on further study. The differential diagnosis includes
sinus tachycardia, sinus node reentrant tachycardia or focal atrial
tachycardia. The mechanism of tachycardia, whether from reentry or
abnormal automaticity, and the location of the tachycardia, can be
confirmed from mode C: Intracardiac Diagnosis and Arrhythmia
Localization, described later.
Non-Isthmus Dependent Atrial Flutter
[0152] FIG. 8C shows another ECG (panel 1), its temporal
correlations (panel 2) and temporospatial correlation loops (panel
3). However, several differences are seen compared to the example
in FIG. 8A. First, temporal correlations are irregular, despite the
somewhat regular ECG appearance, and rarely reach 1. This indicates
a lack of similarity to the template (which can be any atrial
region) over time. Second, atrial correlation loops (panel 3) are
not reproducible in the XY, YZ or XZ planes. This weighs against
typical AFL. Furthermore, these loops do not pass the previously
described threshold correlation coordinate of (0.8, 0.8), which is
consistent with this dissimilarity. Third, ventricular loops have
variable take-offs from atrial loops. Fourth, the absence of
temporal invariance (described above in the section in atrial
tachycardia) weighs against the diagnosis of focal atrial
tachycardia.
[0153] The diagnosis at this point suggests either atypical atrial
flutter or atrial fibrillation. Eigenvector analysis revealed
significant variability in the maximum-energy plane between cycles.
This is consistent with either an atypical atrial flutter, an
organized form of atrial fibrillation or atrial tachycardia from
multiple distinct foci. Finally, frequency analysis provides a clue
to clinch the final diagnosis. In panel 4, FFT on the ECG showed a
broad bandwidth of frequencies. However, by eliminating magnitude
differences between atrial and ventricular complexes, and
frequencies contributing to their different waveforms, correlation
analysis more cleanly assessed true atrial rate. Correlation
spectra showed a predominant peak at 4 Hz peak, similar to FIG. 8A.
This differs from the broad bandwidth of AF from U.S. Pat. No.
6,064,906 issued to Langberg and U.S. Pat. No. 6,178,347 issued to
Olsson.
[0154] Conclusions This example shows that this ECG, although
consistent with typical AFL, is clearly not typical AFL using the
present invention. This was confirmed on further study. Despite the
lack of a clear spatial phase relationship, spectral analysis of
temporal correlations confirmed one predominant activation rate,
consistent with atypical AFL. Atypical AFL sometimes shows
spatially coherent loops in the XY plane, while the YZ and XZ
planes may be clearly non-coherent. Correlation plots, and spectral
analysis on correlation series, are critical to the diagnosis of
these arrhythmias.
Atrial Fibrillation
[0155] In FIG. 8D, panel 1 shows irregular atrial activity and
panel 2 shows that temporal correlations are not reproducible over
time in any lead. Panel 3 shows temporospatial correlation loops
that are disorganized and space-filling in all planes. Rather than
being reproducible, correlation loops intersect in highly variable
directions, reflecting variable spatial activation patterns between
cycles in all axes. Furthermore, atrial and ventricular loops have
no consistent relationships, and ventricular loops have variable
take-offs from atrial loops. These findings suggest an irregular
atrial rhythm, such as AF, atypical AFL or focal atrial tachycardia
from multiple foci (compare against FIG. 8A-C).
[0156] Eigen vectors in this case showed approximately equal
magnitude between axes, without evidence that one plane contained
most of the power. This suggests spatial variability in atrial
activity and supports the diagnosis of AF. In panel 4, spectral
decomposition showed absence of a peak at 4 Hz or consistent
harmonics, but rather a broad bandwidth spectrum in all 3 leads.
This remains true in panel 5 in correlation spectra, although the
bandwidth is narrowed somewhat. From U.S. Pat. No. 6,064,906 issued
to Langberg and U.S. Pat. No. 6,178,347 issued to Olsson, although
based on intra-cardiac data, this supports the diagnosis of AF.
[0157] Conclusions. The combination of irregular and spatially
non-uniform atrial activation, with variable atrio-ventricular
relationships, confirms the diagnosis of AF. This was confirmed on
later study. This pattern is clearly distinct from atypical AFL
(FIG. 8C) although traditional prior art methods sometimes cannot
distinguish these rhythms.
Monomorphic Ventricular Tachycardia with Atrioventricular
Dissociation
[0158] FIG. 8E, panel 1 shows an ECG of regular wide complex
tachycardia. Ventricular activity was used as a template in this
case. In panel 2, correlations to this template are regular and
periodic, and approach 1.0 for each cycle. In panel 3, activation
is reproducible for all cycles. Notably, there is spatial coherence
over significant portions of the cycle, shown by those parts of the
correlation loop that lie predominantly parallel to the line of
identity (1,1) to (-1, -1).
[0159] Notably, slight variations in the ventricular correlation
loops were seen. These corresponded to the presence of dissociated
atrial activity seen from intracardiac recordings. Therefore, this
analysis was able to discern atrial activity that was not evident
on visual inspection of the ECG.
[0160] These findings strongly support monomorphic VT. The presence
of dissociated atrial activity discounts the possibility of a
regular supraventricular tachycardia with wide QRS complexes due to
bundle branch block ("SVT with aberrant ventricular conduction").
Eigen vector analysis showed minimal variation in the plane of
maximum power, while spectral decomposition, shown in panels 4 and
5, showed regular spectra, each with a clean dominant peak at 2.5
Hz and the absence of non-harmonic frequencies.
[0161] Conclusion. These features suggest the diagnosis of
monomorphic ventricular tachycardia, which was confirmed. The
ability of the method to detect slight correlation irregularities
corresponding to atrial activity that is not clearly evident with
the naked eye greatly simplifies the diagnosis of VT, which is
clinically difficult in many cases [6].
Ventricular Tachycardia with Variable Intracardiac Activation
[0162] In FIG. 8F, panel 1 shows an ECG of a very irregular and
rapid wide complex tachycardia. In panel 2, analysis of
correlations shows that, although they show some reproducibility,
they appear to have different phase relative to each lead. This is
confirmed by the temporospatial loops in panel 3, which are spatial
filling and reach all four vertices of the plot. Correlation lines
cross each other in clearly variable directions, as also observed
in AF (FIG. 8D). As also seen in AF, Eigen vectors showed that the
plane of maximum energy did not contain most of the power.
Interestingly, despite tachycardia irregularity on visual
inspection, spectra (panels 4 and 5) show a dominant peak at around
5 Hz, with some frequency smearing. There was very little
difference between ECG and correlation spectra, supporting that
most of the ECG activity arises from either the atria or
ventricles.
[0163] Conclusion. These results suggest a diagnosis of ventricular
fibrillation or polymorphic VT. This was confirmed later, with a
rate consistent with the spectral peak. This example also
demonstrates that temporospatial correlation (showing lack of
temporospatial coherence) clearly adds to the information from
spectral analysis (showing one predominant frequency).
5. ECG Comparison Mode
[0164] This mode is provided to enable the physician to use the
routine 12-lead ECG to determine whether a current rhythm is a
recurrence of a previous event, such as atrial flutter after
ablation, or a new arrhythmia, such as atypical atrial flutter.
This determination is otherwise very difficult using prior art
methods. Alternatively, the current arrhythmia can be compared to a
previously-stored typical or classic rhythm, such as atrial flutter
or right ventricular outflow tract ventricular tachycardia that
have stereotypical ECG patterns.
[0165] A particular strength of this temporospatial correlation
method, that makes this mode possible, is that the template need
not be sampled from the ECG being analyzed. The template can
actually be any signal shape, or a generic beat, or a template
previously sampled from any one of a plurality of potential cardiac
events. This is possible since the invention tolerates differences
in amplitude scaling, noise and other factors. Previously stored
electrograms are uploaded from the database 197 or external
interface 198 to the process controller 190, and used as templates
for which to compare the current ECG of interest. Electrograms
imported in this way have their sample rates matched to that of the
ECG of interest using interpolation methods.
[0166] Temporospatial correlations will differ somewhat from the
above detailed description in this mode when non-ECG sampled
templates are used. First, maximal correlations may no longer
approach 1.0 if the new template does not match the ECG at any
point along its duration. Second, therefore, principal loop axes
may no longer lie parallel to the line of identity even in regular
rhythms (typical AFL, monomorphic VT). However, such analysis will
still produce reproducible loops, and atrial and ventricular
components will be readily segregated. Many of the above analyses
can still therefore be made.
6. Methods for Computation of Baseline
[0167] Baseline correction can be used in the invention,
particularly for the calculation of Eigen Vectors. Baseline
correction is traditionally performed in the PR or TP segments
(where cardiac activity is minimal). However, several rhythms do
not show this clear isoelectric segment, such as the continuous
atrial activity of atrial flutter. The invention includes a novel
method for calculating baseline in these circumstances, using
temporospatial correlation as described above.
[0168] FIG. 5 process 405 offers the user a choice of considering
real-time, previously stored or archived data, or a combination
thereof. Process 410 can identify from the ECG components
representing ventricular depolarization (QRS complex), ventricular
repolarization (T wave) and atrial activity. This may be based on
actual ECGs (real-time or stored) or on a derived ECG such as a
vector resultant lead. QRS complexes can be identified using
methods discussed by Watanabe et al. [25], U.S. Pat. No. 4,552,154
issued to Hartlaub, and U.S. Pat. No. 6,035,231 issued to Sommo.
QRS complexes can then aligned using one of several columnar
techniques, including alignment about the point of largest positive
or negative slope, peak values, minimum mean square differences, or
metrics based on derived signals. T-waves are then similarly
identified and aligned, and atrial activity lies in the intervening
intervals.
[0169] First, atrial and ventricular activity are defined in
processes 480, 490 and 500, from the points where correlation to an
atrial template approaches 1. Process 480 identifies points of
maximum or minimum atrial correlation, zero crossings or other
fiducial points. Process 490 computes a linear or non-linear
baseline signal through these fiducials using the methods of cubic
spline, linear interpolation or other methods. This baseline is
then subtracted from each ECG lead to produce a wander-corrected
ECG. Process 500 then computes an average signal offset, by
aligning atrial cycles. This alignment can be accomplished by time
and frequency domain methods or the fiducial points of reproducible
correlation values (maxima, minima, zero or other values). The
signal offset is the average between the maximum and minimum
amplitude points of the atrial signal. This offset is subtracted
from each wander-corrected ECG lead to yield the final
baseline-corrected ECG. This process may be repeated iteratively to
remove baseline artifact.
[0170] This method is a significant improvement over prior art
methods of baseline correction, such as U.S. Pat. No. 6,035,231
issued to Sornmo. These methods assume that a segment, generally
the TP or PR interval, is isoelectric, and subtract it from the
ECG. This also helps in reducing T-wave artifacts. Unfortunately,
this introduces significant errors in arrhythmias such as AFL,
where the isoelectric interval is absent, and when atrial and QRS
activity have variable timing. The current invention enables
baseline correction even during AFL and other atrial arrhythmias.
However, various other methods for baseline correction known to
those skilled in the art of ECG signal processing, such as
isoelectric subtraction with or without P wave alignment and
averaging, can also be incorporated, in addition to or as an
alternative to the above-described temporospatial correlation based
methods.
C. Intracardiac Diagnosis and Arrhythmia Localization
[0171] An overview of this mode of operation of the invention is
provided in FIG. 4 commencing at process 620. As can be seen, this
mode of operation follows and complements mode B: Surface ECG
Diagnosis and Localization in the preferred embodiment. It is then
followed, in turn, by mode C: Intracardiac Diagnosis and Arrhythmia
Localization.
1. Background for Arrhythmia Localization
[0172] By way of overall explanation for a re-entrant arrhythmia,
such as VT or AFL, the site most appropriate for ablation typically
constitutes a slow conduction zone, labeled SCZ in FIG. 9.
Depolarization wave fronts A (designated DWF in FIG. 9) entering
the slow conduction zone SCZ (site A in FIG. 9) break into errant,
circular propagation patterns (designated B and C in FIG. 9),
called "circus motion." Circus motion disrupts the normal pattern
of depolarization, and therefore disrupts the normal contraction of
heart tissue to cause the cardiac event.
[0173] The event-specific ECG and intracardiac electrode samples
labeled S.sub.i (i=1 to 3, although of course greater or fewer can
be recorded) in FIG. 1B record these depolarization patterns. If a
pacing signal is applied at the site of SCZ, the pacing signal gets
caught in the same circus motion (i.e., paths B and C in FIG. 9)
that triggers the targeted cardiac event. Therefore, many of the
pacing morphologies P.sub.i at the sensing electrodes (where i=1 to
3 in FIG. 1B, although of course greater or fewer can be recorded)
will be similar to event-specific samples S1. This will result in a
high temporospatial correlation (that is, coherence) when using a
paced template against the event-specific ECG, or vice versa, using
the methods outlined above.
[0174] However, if a pacing signal is applied outside an SCZ, the
pacing signal is not caught in the same circus motion. It
propagates free of circus motion and creates a significantly
different propagation pattern than that recorded during the
event-specific samples S.sub.i. The pacing morphologies P.sub.i at
the sensing electrodes will therefore have quite different
temporospatial correlations than the event-specific samples
S.sub.i. This leads to smaller overall correlation, the absence of
coherence and different (but potentially reproducible) patterns in
each lead-pair plane.
[0175] Therefore, the coherence reproducibility metrics have been
designed to increase in value when the pacing electrode ROVE is
closer to the SCZ, which is a potential site for ablation.
Differences in surface propagation when pacing inside as opposed to
outside a SCZ are most pronounced during concealed entrainment
pacing. For this reason, the invention has been designed to employ
concealed entrainment pacing. Of note, any electrode can be used
for pacing and recording S.sub.i and P.sub.i, but in the preferred
embodiment the ROVE catheter is used for this purpose (as shown in
FIG. 1B).
2. Acquisition Module
[0176] This module is activated first, as shown in FIG. 4 process
630. The process controller 190 records intracardiac and ECG
signals during a cardiac event. This is analogous to mode A. Signal
Samplingfor ECG signals, above. In this module, electrodes on the
body surface 130 must not be repositioned, while those elsewhere
134', 136, 138 must remain in a fixed location relative to the
heart 110 and its vasculature 114. In the illustrated and preferred
embodiment, the cardiac event comprises an arrhythmia that the
physician seeks to treat, for example, ventricular tachycardia
(VT), atrial tachycardia (AT), atrial flutter (AFL) or atrial
fibrillation (AF).
[0177] The process controller 190 in this module processes a
selected number of electrogram samples obtained from each electrode
during the known cardiac event. These event-specific electrogram
samples (designated for the purpose of illustration in FIG. 1B as
S.sub.1 to S.sub.3) may be recorded unipolar (between electrode
134', 136 or 138 on the heart 110 or its vasculature 114, and a
reference electrode, not shown) or bipolar (between electrodes on
each multielectrode catheter 134', 136 or 138 on the heart 110 or
its vasculature 114). Bipolar signals may be recorded from
specialized catheters such as those recording monophasic action
potentials (EP Technologies, Sunnyvale, Calif.), which resemble
extracellular action potentials. The samples S.sub.1 to S.sub.3 can
also comprise one heart beat or a specified number of beats.
Multiple beats may be averaged to reduce noise, if desired.
[0178] The host processor 195 stores the set of event-specific
electrogram samples S.sub.1 to S.sub.3 in memory. The process
controller 190 can, for an individual patient, retain sets of
event-specific samples for different cardiac events. For example, a
patient may undergo different episodes of VT, each with a different
morphology. The host processor 195 can automatically detect
different VT morphologies and store samples of each episode for
analysis. The process controller 190 can also download the samples
to the database 197 for off-line analysis at a subsequent time.
3. Pacing Module
[0179] In the preferred embodiment, the Pacing Module (FIG. 4, box
635) follows the acquisition module, and must be performed without
moving electrodes 130, 134', 136, 138, which must occupy the same
positions as they did during the Acquisition Module. The process
controller 190 conditions the pacing module 160 to pace the heart
110 in a user-programmable fashion while conditioning the signal
processing modules 150 and 158 to record a number of the resulting
electrograms. Pacing (or stimulating) the heart results in a paced
cardiac signal, which may represented by several ECG leads.
[0180] The pacing signal induces depolarization, emanating at the
pacing ROVE electrode.
[0181] Of course, pacing can be applied to any electrode, but in
the preferred embodiment this is the ROVE catheter. The process
controller 190 processes the resulting paced electrogram samples
sensed at each electrode (any combination of 130, 134', 136, 138
deployed in FIG. 1B) during pacing. The paced electrogram samples
are designated P.sub.1 to P.sub.3 in FIG. 1B.
[0182] Different conventional pacing techniques, including burst
pacing and multiple extrastimuli, can be used to obtain the paced
samples P.sub.1 to P.sub.3. Regardless of the particular pacing
technique used, the pacing stimulus may be monophasic, biphasic, or
triphasic. The paced morphology P.sub.1 to P.sub.3 at each
electrode can be from one heart beat or a specified number of heart
beats. The length of the morphologies P.sub.1 to P.sub.3 can have
any relationship to the length of the event-specific samples
S.sub.1 to S.sub.3 for the same electrodes obtained during the
acquisition module. Typically, they are of equal duration.
[0183] The pacing module can be performed in two preferred modes of
operation: [0184] (a) to pace the heart without inducing the
cardiac event of interest (the Pace-Map module); or, [0185] (b) to
pace the heart during the cardiac event of interest without
altering this event (the Concealed Entrainment module). 4. Pace-Map
Module
[0186] The pace-map module is used at a time when the patient is
not experiencing the cardiac event of interest. The goal is to
compare ECG (and/or electrogram signals) resulting from pacing to
those from the cardiac event of interest (recorded previously in
the Acquisition Module, uploaded from the database 197 or imported
from the interface 198). These signals will become more similar as
the ROVE catheter moves closer to the arrhythmia circuit (see
Background above and FIG. 9).
[0187] Pacing stimuli are applied from the ROVE catheter placed
within the heart 110 or its vasculature 114. In a preferred
embodiment, this is the ablation catheter 138, but pacing can also
be applied at electrodes 130, 134', 136. Pacing is applied at a
rate close to that of the cardiac event of interest, but it can be
important that the arrhythmia not be induced. The electrodes 130,
134', 136 and 138 must not change their position relative to the
heart 110 throughout this module.
[0188] In FIG. 4 process 640, temporospatial correlation analysis
is repeated using a current template during pacing on a previously
stored example of the cardiac event of interest. This is analogous
to ECG comparisons in mode B: Surface ECG Diagnosis and
Localization mode. First, the process controller 190 selects a
template from the ECO and electrogram samples P.sub.1 to P.sub.3
during pacing. In an alternative embodiment, P.sub.1 to P.sub.3 and
simultaneous paced ECGs can be stored in memory for later
retrieval, or uploaded from a database 197 or interface 198.
Alternatively, the input module 200 controls an off-line function
whereby event-specific samples and paced morphologies can be
analyzed without the presence of the patient. In all cases,
electrograms must be aligned in time, using one of several
approaches, to enable temporal correlations and spatial coherence
to be assessed.
[0189] Second, the paced template is used to probe the sensed
sequence, by using temporospatial correlation analysis to compare
paced to sensed signals for corresponding ECG leads or electrogram
channels. For example, paced ECG lead X (points P.sub.i) is
compared to lead X during the cardiac event (points S.sub.i). This
is then repeated for leads Y and Z. All of the analyses in mode B,
including temporospatial correlation, spectral and eigenvector
analyses are performed. If the ROVE catheter is placed close to the
location of the arrhythmia circuit, the loops of P.sub.i versus
S.sub.j, as well as each being reproducible and narrow, will be
similar to each other with principal axes that lie parallel to the
line of identity. The invention provides precise time alignment, to
allow loop axes to lie along this line of identity. Also, the
invention will ensure that an equal number of cycles is examined
even if one rhythm is faster than the other. This is done by
choosing template durations that reflect the ratio of the longer
cycle length (slower rhythm) to the shorter cycle length (faster
rhythm). For example, if the cardiac event (say, monomorphic
ventricular tachycardia) is 1.25 times faster than the paced rhythm
(from the ROVE catheter), the duration of the cardiac event
template will be made equal to 0.8 times (=1/1.25) the duration of
the paced rhythm template (for example, 160 ms versus 200 ms,
respectively). The number of correlation points will be identical
between paced and cardiac event sequences by the uniform omission
of points from the slower rate ECG or by linear interpolation of
points into the faster rate ECG. Correlations of paced versus
cardiac event ECGs will therefore examine comparable spatial phase
despite cycles of different lengths.
[0190] Third, the above process is repeated by correlating sensed
samples to the paced electrograms, and by correlating paced ECG
templates against sensed ECGs of different orientations (such as
paced lead X versus sensed lead Y), and by determining whether the
XY, YZ and XZ loops are essentially superimposible for native
versus paced sequences. Regions of slow conduction, indicated by
deviations of temporospatial coherence from a uniform timing, are
also used to help position the catheter. In process 645, the
process controller 190 uses these analyses to determine the
numerical difference between paced and event-specific samples. The
difference is displayed in module 230 (FIG. 1B) and termed a good,
indifferent or bad pace map. If good, then the text-label SITE is
displayed.
4. Concealed Entrainment Module
[0191] The concealed entrainment module (FIG. 4, process 650) is
only activated while the patient is experiencing the cardiac event
of interest. It uses the principle of entrainment with concealed
fusion to determine if the current pacing catheter, typically ROVE,
is located close to the arrhythmia circuit.
[0192] Paced samples P.sub.1 to P.sub.3 are obtained in a slightly
different manner than in the Pace Map module. Here, pacing occurs
during the cardiac event, but at a slightly higher rate and shorter
period (typically by 20-40 milliseconds). The process controller
190 operates the pacing module 160 to emit pacing signals from the
ROVE catheter which, in the preferred embodiment, is an ablation
electrode 138 (see FIG. 1B). The process controller 190 records and
stores, in host processor 195, database 197 or via interface 198,
surface ECG signals acquired from electrodes 130 and intracardiac
signals from the ROVE catheter and intracardiac electrodes 134',
136 and 138. These electrodes must remain in the same position
throughout analysis.
[0193] The invention now uses temporospatial correlations to
determine the difference and similarity in ECG and intracardiac
signals between pacing and the cardiac event. The invention
compares paced electrogram samples P.sub.1 to P.sub.3 and the
surface ECG to the analogous event-specific samples S.sub.1 to
S.sub.3 and the ECG using the same electrodes. If correlation maps
are dissimilar, the activation exit points between pacing and the
cardiac event cannot be the same. The ROVE catheter is then moved
closer to the arrhythmia circuit per the Catheter Guidance mode
(mode D), described fully below.
[0194] As in the Pace-Map module, the invention will ensure precise
time alignment and that template durations are proportional to rate
differences between entrained and native rhythms. Since entrained
(paced) rhythms are slightly faster than native rhythms (by
design), entrained templates will be proportionally shorter. For
example, if the entrained rhythm (from the ROVE catheter) is 1.1
times faster than the native rhythm (say, typical atrial flutter),
then the duration of the entrained template will be made equal to
0.91 times (=1/1.1) the duration of the native rhythm template (for
example, 227 ms versus 250 ms, respectively). The number of
correlation points will be identical between paced and cardiac
event sequences by the uniform omission of points from the slower
rate ECG or by linear interpolation of points into the faster rate
ECG. ECG correlations will therefore potentially span the same
number of cycles to examine spatial phase for cycles of different
cycle lengths.
[0195] Temporospatial correlation is used to perform the following
component analyses of entrainment with concealed fusion (as per
work by Waldo et al. [27] and Almendral et al. [31]): [0196] 1.
Similarity of ECG morphologies between pacing and event-specific
recordings; [0197] 2. Similarity of intracardiac electrogram
morphologies between pacing and event-specific recordings.
Monophasic action potential or unipolar intracardiac recordings
facilitates this analysis. [0198] 3. Examination of the similarity
between the post-pacing interval and the event-specific cycle
length; [0199] 4. Similarity between stimulus to QRS and
electrogram to QRS intervals; [0200] 5. Demonstration that the QRS
and intracardiac electrogram complexes show progressive fusion with
incrementally faster pacing. Specifically, the following analyses
are performed (FIG. 4, processes 650 to 660): [0201] 1. During the
cardiac event, the duration of time between the electrogram on the
ROVE catheter and the ECG complex corresponding to activation of
that chamber. The time of activation is provided by the correlation
loop take off, reducing errors commonly introduced when determining
exact QRS onset from a noisy time-domain signal, for example.
[0202] 2. During concealed entrainment pacing, the duration of time
between the ROVE catheter electrogram and the start of surface ECG
activation will also be determined as above in #1. [0203] 3.
Demonstration that #1 and #2 are equivalent. This uses
temporospatial correlation to establish an equivalent timing
(`phase`) between the electrogram to QRS (#1) and stimulus to QRS
(#2) intervals during entrainment [27]. [0204] 4. Compare the
timing of the return of the ROVE catheter electrogram after the
termination of pacing, with the timing of each cycle during the
cardiac event of interest. This will be done using temporospatial
correlation analysis. Demonstration that the post-pacing interval
equals the tachycardia cycle length is a major criterion for
entrainment [27]. [0205] 5. With faster pacing, the invention will
demonstrate that ECG temporospatial correlation loops lie on a
progressive spectrum from event-specific to pacing-specific. This
uses temporospatial correlation to demonstrate progressive fusion,
as per Waldo et al. [27]. [0206] 6. With faster pacing, demonstrate
that temporospatial correlation loops from intracardiac
electrograms at the ROVE catheter lie on a progressive spectrum
between event-specific and paced. This demonstrates progressive
electrogram fusion, as per Waldo et al. [27].
[0207] For a given ROVE catheter position, the invention uses these
analyses to generate the indices described in Mode B that determine
whether ROVE is close to the arrhythmia circuit. As summarized in
FIG. 4, processes 650 and 660, the invention displays this
information on the display component 230 in FIG. 1B.
D. Catheter Guidance System
[0208] Mode D (FIG. 4, process 665), Catheter Guidance System,
operates as an adjunct to the Intracardiac Diagnosis and Arrhythmia
Localization mode (mode C). In general, this mode determines the
spatial plane of poorest correlation between paced and
event-specific samples from the ROVE catheter. Analyses are then
used to indicate to the user the direction in which to move ROVE
catheter to improve this correlation and, therefore, improve
contact with the arrhythmia circuit (see FIG. 9). This is used in
two preferred operating modes (I) placement of an ablation catheter
(electrode 138 in FIG. 1B) to deliver ablation energy; and (2)
placement of an implanted catheter such as a pacemaker or
implantable defibrillator lead, to deliver defibrillation energy or
pacing impulses.
1. Placement of an Ablation Catheter
[0209] First, the invention determines the plane in which ECG
correlations are poor when pacing from the ROVE catheter (at the
rate of the cardiac event) and comparing the resulting electrograms
to those during sensed signals from the cardiac event (FIG. 4,
process 665), stored in the memory of the host processor 195 or
uploaded 197, 198. The correlation and reproducibility indices
described above are determined in the XY, YZ and XZ planes. Eigen
vectors are used to determine whether the planes of maximal energy
coincide between pacing and the cardiac event of interest.
[0210] By way of example, consider a ROVE catheter position from
whence pacing produces ECGs whose correlation to the cardiac event
match poorly in the YZ plane, but lies along the line of identity
in the XY plane. The ROVE catheter is then moved parallel to the
Z-axis (ECG lead V1). The direction in which to move the ROVE
catheter is determined by signal polarity (FIG. 4, process 670).
Since a wavefront moving towards an electrode generates a positive
potential, if the paced ECG is more positive than the event for the
V1 lead, ROVE must be moved away from V1 (i.e. away from the front
of the chest) to get closer to the arrhythmia circuit. The opposite
is also true. The invention calculates these comparisons for all
leads simultaneously and displays them on module 230 as graphics
and text MOVE V, where V is this vector of movement (FIG. 4,
process 675). This lifts the burden of making multiple comparisons
from the physician, and is also more accurate.
[0211] Second, once paced and sensed ECGs match, the catheter is
moved even more precisely to the arrhythmia circuit by matching
intracardiac signals. This is done using temporospatial
correlation, and cross-correlation of electrogram shapes
(morphologies), between paced samples, P.sub.i, and event-specific
samples, S.sub.i, at all intracardiac electrodes 134', 136, ROVE.
When the ROVE catheter lies at the exit point of the cardiac event
of interest (SCZ in FIG. 9), pacing will cause exactly timed and
very similarly shaped electrograms to those during the cardiac
event at all intracardiac locations. In an alternative embodiment,
pacing is performed from electrodes 134', 136 or 138. That
electrode producing the closest electrogram correlations to the
cardiac event is closest to a potential ablation site. The ROVE
catheter is moved next to this electrode and then pacing is
repeated from ROVE. This process continues until all intracardiac
signals are correlation-matched between pacing from the ROVE
catheter and the event. A minimum number of intracardiac electrodes
must therefore be placed to optimize spatial resolution. In the
preferred embodiment this includes electrodes in the coronary
sinus, right atrium and His bundle position for atrial diagnosis
and also at the right ventricular apex, and possibly cardiac veins,
for ventricular diagnosis.
[0212] In the preferred embodiment, intracardiac signals are
recorded in unipolar or monophasic action potential configurations.
This enables electrogram shapes to be used to further confirm
electrogram matches. An ideal shape match is characterized by
maximal morphology cross-correlations between paced and sensed
signals. Many cross-correlation coefficients can be used, such as
the Pearson and Fischer methods. For this stage, the ROVE catheter
is moved as before, electrogram shapes are compared by
cross-correlation after each pacing intervention, as well as
temporospatial correlation analysis.
[0213] When temporospatial correlation and morphology correlation
indicates a precise match between ROVE and the arrhythmia circuit,
within acceptable biologic tolerances, the text label SITE is
displayed 230 (FIG. 4, process 690). The physician will typically
perform ablation at this site. However, this process may also be
used to locate the arrhythmia tissue to deliver electrical
defibrillation (an electrical shock) or other modulation (such as
delivering pharmaceuticals, cells or genes).
[0214] The described here improves upon the cross-correlation
method in U.S. Pat. No. 5,792,064 issued to Panescu. Panescu et al.
analyze one single beat, especially the beat that initiates AF,
while this invention analyzes a continuous arrhythmia tracing using
temporospatial morphology correlation (on electrograms as well as
ECGs) to extract atrial versus ventricular features. In addition,
Panescu et al. analyzed only the signal shape, while this invention
fully and rigorously analyzes the activation sequence and timing of
all signals. Their method is therefore less well-suited to analyze
sustained tachycardia, for confirming a diagnosis, or for
confirming the success of ablation (which will be discussed
later).
2. Placement of Pacemaker or Implantable Defibrillator Lead
[0215] This module is very similar to the above module. Since the
cardiac event of interest will typically have arisen before device
implantation, its ECG and intracardiac signals are typically
uploaded from memory, the database 197 or an external interface
198.
[0216] Since the maneuverability of an implantable lead is lower
than of an ablation electrode, even using guiding stylets, the
operator may elect to rely upon ECG localization in this mode.
However, the full benefits of intracardiac analysis are also
available, if desired. As above, temporospatial correlations are
performed to detect differences in activation pattern and shape
between the current ROVE (typically the implanted lead) and cardiac
event electrograms. When correlations match, the display module 230
indicates the text label SITE (FIG. 4, process 690), and the pacing
or defibrillation lead is fixed in this position, preferably by an
active fixation method such as screwing the lead into the
myocardium in standard fashion. In an alternative implementation, a
more maneuverable ablation catheter (ROVE) is first directed to
locate the arrhythmia site, and the implantable lead is then moved
adjacent to that catheter.
[0217] In an alternative embodiment, the invention can be used in
conjunction with an intracardiac anatomic mapping system, such as
that made by Biosense-Webster, Inc. (Diamond Bar, Calif.),
described in the prior art by U.S. Pat. No. 5,568,809 issued to
Ben-Haim, or Endocardial Solutions, Inc. (St. Paul, Minn.). In this
embodiment, the ROVE catheter position is known at all times to the
mapping system. ECG analyses are then performed to improve upon
spatial localization using entrainment and pace-mapping functional
data.
E. Determination of Ablation Success
[0218] This mode is shown in FIG. 4, processes 695-705. The process
controller 190 determines that successful ablation has been
achieved if pacing from the ROVE catheter at the ablation site can
no longer reproduce prior correlation maps or electrogram
morphologies. The rationale for this approach is that tissue
ablated in or close to the slow conduction zone, SCZ in FIG. 9,
prevents subsequent depolarization. The destroyed tissue is thereby
"closed" as a possible path of propagation. Since depolarization
events bypass the ablated region and no longer become caught in
circus motion, ablation restores normal heart function. Similarly,
electrograms following pacing at this site will now cause different
temporospatial correlation.
[0219] Following ablation, the process controller 190 conditions
the pacing module 160 to pace the heart using the ROVE electrode at
the cycle length of the cardiac event. Intracardiac electrograms
134', 136, 138 and ECG signals 130 are recorded using the recording
components 150 and 158. The process controller 190 and host
processor 195 perform temporospatial correlation and the other
analyses above, and compare the results between pre- and
post-ablation at this position.
[0220] In one implementation, the host processor 195 sets a numeric
threshold B for these analyses. A higher index, indicating
similarity of activation before versus after ablation, indicates a
high probability that the arrhythmia circuit is still present.
Since the Catheter Guidance Mode (mode D) is automatically engaged
during pacing, if correlations remain high then proximity criteria
are again met, and the host processor 195 will display 230 the
text-label SITE. A repeat attempt at ablation may be performed at
this site.
[0221] Successful ablation is indicated if the correlation between
pre- and post-ablation pacing is low for the same electrode
position. If this occurs, the system recommends that the physician
move the ROVE catheter slightly and repeat the analysis. This is
repeated for slight ROVE movements along each vector. If
correlations remain poor, then the procedure is completed by
attempting to re-induce the cardiac event. This is routinely
performed in the prior art. If the event can also no longer be
re-induced, the invention determines that there is a very high
likelihood that the event arrhythmia has been successfully
ablated.
F. Arrhythmia Prediction
[0222] This mode (FIG. 4, processes 710 to 750) detects the
substrates for atrial or ventricular arrhythmias by detecting
variability in temporospatial correlations during progressively
faster pacing. The rationale for this approach is as follows.
During heart rate acceleration in the presence of substrates,
atrial or ventricular recovery will eventually be unable to keep up
with activation, and subsequent activation will split into two or
more distinct populations. From the prior art, incremental pacing
at the right ventricle encroaches upon its recovery, causing T-wave
alternans. This was previously detected using spectral
decomposition in U.S. Pat. No. 4,802,491 issued to Cohen and U.S.
Pat. No. 5,148,812 issued to Verrier. The present invention
provides a new means of showing T-wave alternans, as a bifurcation
into two distinct T-wave temporospatial correlation loops. However,
this invention can also similarly demonstrate alternans of atrial
intracardiac signals, which have recently been shown to predict AF
from work by Narayan et al. [20].
[0223] The process controller 190 conditions the pacing module 160
to emit pacing signals to the trans-esophageal electrode 136 or an
intracardiac electrode 134' or 138. The recording components 150
and 158 record the surface ECG from electrodes 130, as well as
intracardiac signals from the above electrodes, at user-specified
and stored paper (sweep) speed and electrogram gain. Pacing is
performed for 10 or more seconds at each rate. The process
controller 190 performs correlation analysis at each pacing rate at
this site. Since there is no prior cardiac arrhythmia event, the
process controller 190 stores pacing correlation maps for each
progressive rate at the same pacing site in the heart 110 on the
host processor 195, or database 197, then compares them against
each other as above.
[0224] In one implementation, a high likelihood for the presence of
an arrhythmia circuit, is indicated by poor reproducibility of
temporospatial correlations, an (alternating) fluctuation in the
Eigen vector of the specific waveform of interest (such as atrial
activity, or ventricular T-wave repolarization), or variability in
the principal axis slopes of successive correlation loops. This is
shown in processes 730 to 750. It must be stressed that this
analysis cannot be performed at excessive heart rates, since
bifurcation may occur in normal individuals at rates above 110
beats per minute (cycle length 545 milliseconds) for ventricular
pacing, and 250 beats per minute (cycle length 240 milliseconds)
for the atrium. By contrast, highly reproducible correlations
indicate a low risk (processes 740 to 750). Intermediate risk is
assigned to the presence of some of the above metrics.
[0225] The implementation of the system described herein is based
largely upon digital signal processing techniques. However, it
should be appreciated that a person of ordinary skill in this
technology area can easily adapt the digital techniques for analog
signal processing.
[0226] While the invention has been described in connection with
preferred embodiments, they are not intended to limit the scope of
the invention to the particular form set forth, but on the
contrary, they are intended to cover such alternatives,
modifications, and equivalents as may be included within the spirit
and scope of the invention as defined by the appended claims.
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