Source: https://patents.google.com/patent/CA2739838C/en
Timestamp: 2019-08-18 10:32:46
Document Index: 388857338

Matched Legal Cases: ['art 10', 'art 15', 'art 15', 'art 20', 'art.\n15', 'art.\n16', 'art.\n24', 'art.\n25', 'art.\n27']

CA2739838C - Methods, system and apparatus for the detection, diagnosis and treatment of biological rhythm disorders - Google Patents
Methods, system and apparatus for the detection, diagnosis and treatment of biological rhythm disorders Download PDF
CA2739838C
CA2739838C CA2739838A CA2739838A CA2739838C CA 2739838 C CA2739838 C CA 2739838C CA 2739838 A CA2739838 A CA 2739838A CA 2739838 A CA2739838 A CA 2739838A CA 2739838 C CA2739838 C CA 2739838C
CA2739838A
CA2739838A1 (en
2008-10-09 Priority to US19586608P priority Critical
2008-10-09 Priority to US61/195,866 priority
2009-10-09 Application filed by University of California filed Critical University of California
2009-10-09 Priority to PCT/US2009/060178 priority patent/WO2010042826A1/en
2010-04-15 Publication of CA2739838A1 publication Critical patent/CA2739838A1/en
2016-11-01 Publication of CA2739838C publication Critical patent/CA2739838C/en
Method, system and apparatus to detect, diagnose and treat biological rhythm disorders. In preferred particularly desirable embodiment relating to the real-time detection of heart rhythm disorders, this invention identifies localized sources for complex rhythms including atrial fibrillation to guide the localized application of energy to modify the source and treat the rhythm disorder.
METHODS, SYSTEM AND APPARATUS FOR THE DETECTION, DIAGNOSIS
AND TREATMENT OF BIOLOGICAL RHYTHM DISORDERS
This invention relates generally to thc field of medicine and more specifically to a method, system and machine for diagnosing, finding the source for and treating irregularities and other disorders of biological rhythms. In particular, the present invention can be applied to minimally invasive techniques or surgical techniques to detect, diagnose and treat the disorder. One embodiment directs this invention to disorders of heart rhythm, another to electrical disorders of the brain and nervous system and others to electrical or contractile disorders of the smooth muscle of the gastrointestinal and genitourinary systems.
Heart rhythm disorders are very common in the United States, and are significant causes of morbidity, lost days from work, and death. Heart rhythm disorders exist in many forms, of which the most complex and difficult to treat are atrial fibrillation (AF), ventricular tachycardia (VT) and ventricular fibrillation (VF). Other rhythms are more simple to treat, but may also be clinically significant including atrial tachycardia (AT), supraventricular tachycardia (SVT), atrial flutter (AFL), premature atrial complexes/beats (SVE) and premature ventricular complexes/beats (PVC). Under certain conditions, rapid activation of the normal sinus node can causc the heart rhythm disorder of inappropriatc sinus tachycardia or sinus node reentry.
Treatment of heart rhythm disorders, particularly the complex ones of AF, VF
and VT, can be very difficult. Pharmacologic therapy is particularly suboptimal for AF (Singh, Singh et al. 2005) and VT or VF (Bardy, Lee et al. 2005) and, as a result, there is considerable interest in non-pharmacologic therapy. Ablation is a promising and increasingly used therapy to eliminate heart rhythm disorders by maneuvering a sensor/probe to the heart through the blood vessels, or directly at surgery, then delivering energy to the cause(s) for the heart rhythm disorder to terminate it. Ablation was initially used for 'simple' disorders such as SVT, AFL, PVC, PAC, but is increasingly used for AF (Cappato, Calkins et al. 2005), VT
(Reddy, Reynolds et al. 2007) and, to a lesser extent, VF (Knecht, Sacher et al. 2009).
However, ablation is often difficult because tools to identify and locate the cause of the heart rhythm disorder are poor, hindering attempts to deliver energy to the correct region to terminate and eliminate the disorder. In persistent AF, a highly prevalent form of AF, ablation has a one procedure success rate of only 50-60% (Cheema, Vasamreddy et al. 2006;
Calkins, Brugada et al. 2007) despite lengthy 4-5 hour procedures and a 5-10 %
rate of serious complications (Ellis, Culler et al. 2009) including death (Cappato, Calkins et al.
2009). Even for 'simple' disorders such as atrial tachycardia, tools do not exist to make the diagnosis and suggest a likely successful ablation location.
Even the most sophisticated known systems display data that the practitioner has to interpret, without directly identifying and locating the cause of the disorder to enable the practitioner to detect, diagnose and treat it. This includes currently used methods, described in US patent 5,662,108, patent 5,662,108, patent 6,978,168, patent 7,289,843 and others by Beatty and coworkers, US patent 7,263,397 by Hauck and Schultz, US patent 7,043,292 by Tarjan and coworkers, US patent 6,892,091 and other patents by Ben-Haim and coworkers and US patent 6,920,350 by Xue and coworkers. These methods and instruments detect, analyze and display electrical potentials, often in sophisticated 3-dimensional anatomic representations, but stil fail to identify and locate the cause of heart rhythm disorders, particularly for complex disorders such as AF. This is also true for patents by Rudy and coworkers (US patents 6,975,900 and 7,016,719, among others) that use signals from the body surface to 'project' potentials on the heart.
Certain known methods for identifying and locating causes for heart rhythm disorders may work in simple rhythm disorders, but there are no known methods that have been successful with respect to identifying causes for complex disorders such as AF, VF or polymorphic VT. Activation mapping (tracing activation back to the earliest site) is useful only for simple tachycardias, works poorly for AFL (a continuous rhythm without a clear 'start'), and not at all for AF with variable activation paths. Entrainment mapping uses pacing to identify sites where the stimulating electrode is at the cause of a rhythm, yet pacing cannot be applied in AF and even some 'simple' rhythms such as atrial tachycardias due to
-2-automatic mechanisms. Stereotypical locations are known for the cause(s) of atrioventricular node reentry, typical AFL and patients with early (paroxysmal) AF, but not for the vast majority of patients with persistent AF (Calkins, Brugada et al. 2007), VF and other complex disorders. Thus, no methods yet exist to identify and locate the cause of complex heart rhythm disorders such as AF (Calkins, Brugada et al. 2007).
As an example of systems for 'simple' rhythms with consistent activation from beat to beat is given by U.S. patent 5,172,699 by Svenson and King. This system is based upon finding diastolic intervals, that can be defined in 'simple rhythms' but no complex rhythms such as atrial fibrillation (AF) or ventricular fibrillation (VF) (Calkins, Brugada et al. 2007;
Waldo and Feld 2008). Moreover, this system does not identify or locate a cause, since it is examines diastolic intervals (between activations) rather than activation itself In addition, it is focused on ventricular tachycardia rather than AF or VF, since it analyzes periods of time between QRS complexes on the ECG.
Another example is US patent 6,236,883 by Ciaccio and Wit. This invention uses a concentric array of electrodes to identify and localize reentrant circuits.
Accordingly, this will not find non-reentrant causes such as focal beats. Moreover, this method of using feature and detection localization algorithms will not work for complex rhythms such as AF and VF, where activation within the heart changes from beat to beat. It identifies 'slow conduction within an isthmus of the reentry circuit', that are features of 'simple' arrhythmias such as ventricular tachycardia, but are not defined for AF and VF.
In a subsequent US patent 6,847,839, Ciaccio and coworkers describe an invention to identify and localize a reentry circuit in normal (sinus) rhythm. Again, this will not find causes for an arrhythmia that are not reentrant but focal, from where activation emanates radially. Second, this patent is based on the presence in sinus rhythm of an "isthmus" for reentry, that is accepted for 'simple' rhythms with consistent activation between beats such as VT (see (Reddy, Reynolds et al. 2007)). However, this is not accepted for complex rhythms with varying activation paths such as AF or VF.
US patent 6,522,905 by Desai is an invention that uses the priniciple of finding the earliest site of activation, and determining this to be the cause of an arrhythmia. This approach will not work for simple arrhythmias due to reentry, in which there is no "earliest"
site in reentry because activation is a continuous 'circle'. This approach will also not work for complex arrhythmias in which activation varies from beat to beat, such as AF or VF.
-3-However, even in simple heart rhythm disorders, it is often difficult to apply known methods to identify causes. For instance, ablation success for atrial tachycardias (a 'simple' disorder) may be as low as 70%. When surgeons perform heart rhythm disorder procedures (Cox 2004; Abreu Filho, 2005) it is ideal for them to be assisted by an expert in heart rhythm disorders (cardiac electrophysiologist). Thus, ablating the cause of a heart rhythm disorder can be challenging, and even experienced practitioners may require hours to ablate certain 'simple' rhythm disorders (with consistent beat-to-beat activation patterns) such as atrial tachycardia or atypical (left atrial) AFL. The situation is more difficult still for complex heart rhythm disorders such as AF and VF where activation sequences alter from beat-to-beat.
In the absence of methods to identify and locate causes for human AF, physicians have often turned to the animal literature. In animal models, localized causes for complex and irregular AF (induced by artificial means) have been identified and located in the form of localized 'electrical rotors' or repetitive focal beats (Skanes, Mandapati et al. 1998; Warren, Guha et al. 2003). In animals, rotors are indicated by signals that show a high spectral dominant frequency (DF) (a fast rate) and a narrow DF (indicating regularity) (Kalifa, Tanaka et al. 2006). Such uses of spectral dominant frequencies is described in U.S. patent 7,117,030 issued to Berenfeld and coworkers.
Unfortunately, these animal data have not translated into effective human therapy.
Animal models of AF and VF likely differ from human disease. For instance, animal AF is rarely spontaneous, it rarely initiates from pulmonary vein triggers (that are common in human paroxysmal AF). Both AF and VF are typically studied in young animals without the multiple co-existing pathology (Wijffels, Kirchhof et al. 1995; Gaspo, Bosch et al. 1997;
Allessie, Ausma et al. 2002) seen in older humans who typically experience these conditions.
In AF patients, sites where rate is high (or, sites of high spectral dominant frequency, DF) have not been useful targets for ablation. A recent study by Sanders and coworkers showed that AF rarely terminated with ablation at sites of high DF (Sanders, Berenfeld et al.
2005a). Other studies show that sites of high DF are common in the atrium, and ablation at these sites does not acutely terminate AF (as would be expected if high DF
sites were causes) (Calkins, Brugada et al. 2007). In part, this may be because the DF method that is effective in animals may be inaccurate in human AF for many reasons, as shown by many workers (Ng, Kadish et al. 2006; Narayan, Krummen et al. 2006d; Ng, Kadish et al.
Nademanee and coworkers have suggested that signals of low amplitude with high-frequency
-4-components (complex fractionated atrial electrograms, CFAE) may indicate AF
causes (Nademanee, McKenzie et al. 2004a). This diagnostic method has been incorporated into commercial systems by Johnson and Johnson/Biosense. However, this method has also been questioned. Oral and coworkers showed that ablation of CFAE does not terminate AF or prevent AF recurrence alone (Oral, Chugh et al. 2007) or when added to existing ablation (Oral, Chugh et al. 2009).
Several inventions in the prior art acknowledge what was felt true until now ¨
that AF
is a "cardiac arrhythmia with no detectable anatomical targets, i.e., no fixed aberrant pathways, " such as US patent 5,718,241 by Ben-Haim and Zachman. This patent, as a result, does not identify and locate the cause for a heart rhythm disorder.
Instead, it focuses treatment on heart geometry by delivering lines of ablation to "interrupt each possible geometric shape." This patent creates maps of various parameters of the heart.
Many inventions use surrogates for the actual cause for a cardiac arrhythmia, without identifying and locating said cause. For instance, US patent 5,868,680 by Steiner and Lesh uses measures of organization within the heart, that are constructed by comparing the activation sequence for one activation event (beat) to the activation sequence for subsequent beats, to determine if "any spatiotemporal order change has occurred".
However, that invention assumes that organization is greatest near a critical site for AF
and is lower at other sites. However, this assumption may not be correct. In animal studies, indexes of organization fall with distance from an AF source, then actually increase again as activation re-organizes at more distant sites (Kalifa, Tanaka et al. 2006). Moreover, US
patent 5,868 requires more than one beat. As a result, methods such as invention 5,868,680 identify many sites, most of which most are not causes of AF. This lack of identifying and locating a cause for AF may explain why methods based on organization have not yet translated into improved treatment to acutely terminate AF.
Similarly, US patent 6,301,496 by Reisfeld is based on the surrogate of mapping physiologic properties created from a local activation time and vector function. This is used to map conduction velocity, or another gradient function of a physiologic property, on a physical image of the heart. However, this patent does not identify or locate a cause of a heart rhythm disorder. For instance, multiple activation paths in AF mean that the conduction path and thus conduction velocity is not known between the points used for triangulation. In addition, in the case of a rotor, activation sequences revolving around, or emanating symmetrically from, a core region may actually produce a net velocity of zero.
6 For these reasons, experts have stated that "no direct evidence of electrical rotors has been obtained in the human atria" in AF (Vaquero, Calvo et al. 2008). Thus, while it would be desirable to identify (and then locate) localized causes for human AF, this is not currently possible.
For human AF, particularly persistent AF, the absence of identified and located causes means that ablation is empiric and often involves damage to approximately 30-40 %
of the atrium that could theoretically be avoided if the cause(s) were identified and located for minimally invasive ablation and/or surgical therapy (Cox 2005).
Human VT or VF are significant causes of death that are poorly treated by medications (Myerburg and Castellanos 2006). Treatment currently involves placing an implantable cardioverter defibrillator (ICD) in patients at risk, yet there is increasing interest in using ablation to prevent repeated ICD shocks from VT/VF (Reddy, Reynolds et al. 2007).
Identifying and locating causes for VT may be difficult and ablation is performed at specialized centers. In VF, animal data suggest that causes of VF lie at fixed regions near His-Purkinje tissue (Tabereaux, Walcott et al. 2007), but again this is very poorly understood in humans. The only prior descriptions of identifying and locating causes for VF required surgical exposure (Nash, Mourad et al. 2006) or were performed in hearts removed from the body after heart transplant (Masse, Downar et al. 2007)). Thus, minimally invasive ablation for VF focuses on identifying its triggers in rare cases (Knecht, Sacher et al. 2009) but cannot yet be performed in a wider population.
Existing sensing tools are also suboptimal for identifying and locating cause(s) for complex disorders such as AF, including single or multi-sensor designs exist (such as U.S.
patent 5,848,972 by Triedman et al.). However, such tools typically have a limited field of view that is inadequate to identify causes for AF, that may lie anywhere in either atria and vary (Waldo and Feld 2008). Alternatively, they may require so many amplifiers for wide-area sampling that they are impractical for human use. Wide area sampling is advantageous and, in animals, is achieved by exposing the heart surgically (Ryu, Shroff et al. 2005) or removing it from the body (Skanes, Mandapati et al. 1998; Warren, Guha et al.
2003). In humans, even surgical studies only examine partial regions at any one time (for instance (Sahadevan, Ryu et al. 2004)), and introduce problems by exposing the heart to air, anesthesia and other agents that may alter the rhythm disorder from the form that occurs clinically.
The present invention discloses methods, systems and devices for identifying, locating and treating heart rhythm disorders. Locating and identifying the causes of the disorders enhances the ability to guide, select and apply curative therapy. In particular, the present, invention provides a method to identify and locate electrical rotors, focal beats and other causes for human AF and other heart rhythm disorders. Once identified, proper treatment may be applied to ameliorate and potentially eliminate the disorder, desirably using minimally invasive techniques as further described herein.
This invention is a significant advance over the prior art. For example, unlike US
patent 5,718,241, our invention identifies and locates causes (targets) for AF
and other rhythm disorders, that may stay at approximately the same location within the heart for hours (see our example in a 47 year old man). Unlike US patent 6,847,839, the present invention is capable of finding sources that transiently appear or may move (they are "functional"), that may explain the variations in AF. Unlike US patent 5,868,680, our invention directly identifies and locates cause(s) for a heart rhythm disorder, using as little as one activation event (beat) as shown in our examples. Unlike US patent 6,301,496, our invention directly identifies and locates electrical rotors, in which activation revolves around a core region, or focal beats with activation radiating radially therefrom.
-7-c.) analyzing said data to identify and locate the existence of one or more causes of said biological rhythm disorder.
a) sensor apparatus for sensing biological activation signals at multiple locations;
and b) a computer processor interfacing with said sensor apparatus for collecting and processing data received therefrom, said collected data including the sensor locations for each signal and the activation time or activation time duration of each signal wherein said processing includes ordering activation onset times at said sensor locations to create an activation trail indicative of a cause for said biological rhythm disorder. Software for performing the ordering, including an algorithm, may also be used.
In yet another aspect of the invention there is included a method for treating a biological rhythm disorder, the method including:
c.) analyzing said data to identify and locate the existence of one or more causes of said biological rhythm disorder; and d.) selecting one or more of said causes as indicating a primary cause of said biological rhythm disorder; and e.) treating said primary cause to ameliorate or eliminate said biological rhythm disorder.
b.) collecting from said one or more sensors data which includes the sensor locations for each signal and the activation time of each signal; and c.) analyzing said data to identify and locate the existence of one or more causes of said heart rhythm disorder.
-8-In another aspect of the invention there is provided a system for detecting and/or treating one or more causes of a heart rhythm disorder, the system including:
a) sensor apparatus for sensing heart activation signals at multiple locations; and b) a computer processor interfacing with said sensor apparatus for collecting and processing data received therefrom, said collected data including the sensor locations for each signal and the activation time or activation time duration of each signal wherein said processing includes ordering activation onset times at said sensor locations to create an activation trail indicative of a cause for said heart rhythm disorder. Software for performing the ordering, including an algorithm, may also be used.
In yet another aspect of the invention there is included a method for treating a heart rhythm disorder, the method including:
c.) analyzing said data to identify and locate the existence of one or more causes of said heart rhythm disorder; and d.) selecting one or more of said causes as indicating a primary cause of said heart rhythm disorder; and e.) treating said primary cause to ameliorate or eliminate said heart rhythm disorder.
a) a tubular shaft body having a first and second end;
b) an expandable sensor configuration attached to one end of said body, said sensor configuration including a plurality of intertwined sensor arms which, upon torsional movement, alters the spacing between the sensor arms, said sensor configuration being capable of contacting the luminal surface of a heart chamber when at least partially expanded; and c) a retraction sheath for retaining and delivering said sensor configuration.
-9-a) a tubular shaft body having a first and second end;
b) a diametrically expandable spirally-shaped sensor configuration, which includes a plurality of sensors, said sensor configuration being capable of contacting the luminal surface of a heart chamber when at least partially expanded; and c) a retraction sheath for retaining and delivering said sensor configuration.
Figure 1 is a depiction of the heart showing the use of sensors, ablation catheter and the electronic processing components of the present invention which processes signals from the heart and orders them in accordance with the invention.
Figure 2 shows a sensor apparatus design of the present invention that detects biosignals for a wide area of the heart chamber at low resolution, then for a narrower area at higher resolution.
Figure 3 shows another sensor apparatus design of the present invention that detects biosignals for a wide area of the heart chamber at low resolution, then for a narrower area at higher resolution.
Figure 4 shows another sensor apparatus design of the present invention that detects biosignals for a wide area of the heart chamber at low resolution, then for a narrower area at higher resolution.
Figure 5 illustrates some signal types from the heart to be analyzed by the invention, and defines some selected terms including activation onset, activation offset and diastolic interval.
Figure 6 is a flowchart showing analysis of signals at multiple locations to identify and locate causes for biological rhythm disorders in accordance with the present invention.
Figure 7 shows an embodiment of the invention depicting computation of rate-behavior (restitution) curves for human signals, with insertion of physiological patterns in some cases.
-10-Figure 8 shows that rate-response (restitution) of human monophasic action potential duration may differ when measured between paced rhythms and AF.
Figure 9 shows direct assignment of phase.
Figure 10 is a flowchart of an embodiment, showing how sensed signals and stored data in a database can be used to create and use a probability map to improve clarity for identifying and localizing causes for a biological rhythm disorder.
Figure 11 is an example of use of the invention in a 47 year old man. Shown is a selection of signals (electrograms) from within the left and right atria and coronary sinus of a patient with atrial fibrillation presenting for therapy.
Figure 12 shows the results of using the method and system of the invention, which identified an electrical rotor and located it to the right atrium. The activation trail is seen to revolve around a core region. The core region is also shown in the atrial geometry from this patient as a red dot in the lateral wall of the right atrium Figure 13 shows that, during direct ablation at the core region identified in Figure 12 for less than 6 minutes, the AF slowed and terminated to normal rhythm (sinus rhythm), thus demonstrating that the cause of the AF had in fact been located and successfully treated.
Figure 14 shows that, after the AF had been terminated, it was not possible to re-start the AF even by pacing the atria very rapidly (cycle length 230 ms, equivalent to over 260 beats/min). Faster rate pacing was now blocked (did not stimulate the atrium).
Figure 15 shows other patient examples of localized causes of human AF
detected with this invention. Electrical rotors are shown in two patients in the left atrium. To the best of our knowledge, these are the first actual demonstrations of the existence of electrical rotors in human AF.
Figure 16 shows another example of a localized focal beat cause of AF in a 56 year old patient. The figure shows a focal beat cause in the left atrium where the activation trail shows activation emanating radially therefrom. Ablation at this location also acutely terminated AF.
-11-Activation time; For a given heart signal, this is the time of activation onset.
Activation time duration; For the signal of a given heart beat, the time period and the signal waveform between the times of activation onset and offset. Diastolic interval is the time period from activation offset of the prior beat to activation onset of the present beat (figure 3).
Heart rhythm disorder; An abnormal rhythm, often requiring treatment. These include without limitation, rapid rhythms of the top chambers of the heart (atria) such as rapid and abnormal activation of the normal sinus node (inappropriate sinus tachycardia or sinus node reentry), atrial tachycardia (AT), supraventricular tachycardia (SVT), atrial flutter (AFL), premature atrial complexes/beats (PAC) and the complex rhythms of atrial fibrillation (AF) and certain forms of atypical atrial flutter. Rapid rhythms can also occur in the bottom chambers of the heart (ventricles), including such as ventricular tachycardia (VT), ventricular fibrillation (VF), torsades de pointes and premature ventricular complexes/beats (PVC).
Heart rhythm disorders can also be slow, including sinus bradycardia, ectopic atrial bradycardia junctional bradycardia, atrioventricular block and idioventricular rhythm.
Cause of biological or heart rhythm disorder; This term is used interchangeably with 'source' of the biological or heart rhythm disorder in this application. It refers to, without limitation, a rotational pattern of activation sequence around a core region indicative of a rotor, a radially emanating pattern from a core region indicative of a focal beat cause, or a dispersed pattern. In this invention, when a dispersed cause is found, signal sampling is extended to additional multiple locations and the detection and analysis steps of the invention are repeated. These causes are directly responsible for the perpetuation of the heart rhythm disorder.
Sensor; This term is used interchangeably with electrode in this application.
It refers to an apparatus for detecting and transmitting signals from the heart or to the heart.
-12-Prior to the discovery of the present invention, the causes of human biological rhythm disorders, and particularly heart rhythm disorders, had not been identified.
The present invention represents the first known instance where a method of detecting, diagnosing and subsequently effectively treating, in an accurate and minimally invasive manner, the cause(s) __ that sustain, perpetuate, or 'drive' human biological disorders has been described. This method enables the physician to target these sources for modification or elimination to abolish the disorder. Although one preferred embodiment is for minimally invasive procedures for heart rhythm disorders, the invention can also be applied to surgical therapy, and for disorders of electrical impulse generation or propagation in organs such as the brain, __ central nervous system (where it may locate causes of epilepsy or seizure), peripheral nervous system (where it may detect tumors), skeletal muscle and smooth muscle such as the gastrointestinal tract, bladder and uterus.
In accordance with an embodiment of the invention, there is disclosed an apparatus to sample signals, for example a sensor device such as a electrode catheter from multiple __ locations within a human organ, such as the human heart, at varying spatial resolutions and fields of view and with apparatus to alter the number of sensing channels accordingly.
In one embodiment of the invention, data collected from sensors and analyzed is stored as data in a database that is automatically updated. This database is used to assist the __ physician in the diagnosis/detection of localized causes, or to classify a pattern of causes of rhythm disorders. This may take the form of a probability distribution map of causes in patients with specific characteristics.
In accordance with another embodiment of the invention, there is provided an apparatus to display causes for the biological rhythm in a format that can assist the physician __ in treatment. For example, a visual display screen may be connected to a processor to allow for viewing of the activation trail and to allow for visual location of the core of a rotor, focal source or other cause of the disorder. Audio formats may also be used alone or in combination with the visual format. For example, in addition to or instead of the visual
-13-depiction of the source such that the core can be visually identified, the coordinates of the source and its core can be provided to the user by audio indications as to the location and cause of the disorder. Visual depiction is particularly desirable because it provides the practitioner with a clear representation of the cause and provides a reference for identifying the core of the cause, which greatly facilitates the selection of treatments.
For example, a visual representation of the actual rotor or focal beat allows the practitioner to accurately determine where to direct the ablation catheter or other treatment.
In accordance with another embodiment of the invention, once the cause of the disorder is identified, use of a treatment device or method, to modify or destroy the site of an identified and localized source may be employed to treat or eliminate the rhythm disorder.
Non-limiting examples of treatment devices and methods include the use of destructive energy (ablation) such as by ablation catheters, surgical ablation methods, surgical removal or using devices inside the heart such as implanted leads or other physical device, stimulating energy (pacing), direct delivery of pharmacologic agents, cellular therapy or other intervention techniques. In one embodiment, a catheter capable of sensing signals from the body, and particularly from the heart, may also include a means of treatment, such as the ability to delivery ablation energy, stimulation energy, drug therapy, cellular therapy such as stem cells or gene therapy, or other treatment means. Thus, such a catheter may be employed both in the detection and in the treatment of the disorder.
The present invention is particularly suited for the detection, diagnosis and treatment of complex heart rhythm disorders such as, for example, VF, polymorphic VT, torsade de pointes and AF , where once the localized cause is accurately identified and pinpointed, accurate and targeted ablation of the localized cause may be implemented. As discussed above, identification and physical location of the cause was previously not possible, and hence extraordinarily difficult even for experienced practitioners to treat successfully, much less substantially ameliorate or eliminate.
In addition to finding the cause of and subsequently treating complex heart rhythm disorders, the present invention may also be applied to help diagnose and treat 'simple' rhythms that emanate from a single site by accelerating and simplifying analysis for the practitioner. For heart rhythm disorders, such simple disorders include focal atrial tachycardias, multifocal atrial tachycardias (MAT), sinus nodal reentry or inappropriate sinus tachycardia, ventricular tachycardia (VT), premature atrial complexes (PACs) and premature ventricular complexes (PVCs).
-14-Included in the invention are a process and system to collect data, including sensing devices and recording systems The collected data includes at least the location of each sensor which transmitted one or more signals and the onset time at which each activation signal or activation time duration occurred. The processor receives this information and sequentially orders the activation onset times. The result of this computation is the creation of an activation trail which creates a signature pattern for the disorder and indicates both the location and the type of the cause to the disorder, i.e. whether it is a rotor, focal source or a dispersed pattern, i.e. no localized source, hence requiring further data to be collected from a different area of the heart or other body region,. The data once ordered in this manner creates an activation trail which can visually be depicted on a visual display to show, in the case of a rotor source, the actual rotational pattern of the rotor such that the core of the rotor is visually apparent and can easily be identified and hence treated. The same hold true for the depiction of a radially emanating source, such as a focal beat. The sequential ordering of the activation onset times at each sensor permits the location of focal rhythm disorders, such that the focal core can be easily located on the visual display for targeted and accurate treatment.
Desirably, the rhythm sources or causes are displayed over a period of time to allow the practitioner to fully observe the causal point or area and to make a comfortable assessment as to the appropriate treatment at the causal location. In one embodiment the data and/or the visual displays of the processed data (i.e. a "movie" of the activation trail) elucidates the signature pattern of the cause of the rhythm disorder. Such stored information allows for the practitioner to consult previous patterns to aid in improving the identification, localization and treatment of similar causes. In some instances, such stored information allows for extrapolation of measured real-time data to provide predictive models or to clarify certain measured patterns using similar known patterns.
A further embodiment of the invention provides a process and system for the treatment of such causes, often by modification or destruction of tissue where causes reside.
Sixth, a preferred embodiment enables the invention to be used in an 'offline', non-real-time review mode, rather than directly during a procedure to treat a patient.
The process and system of the invention may be employed to localize sources (i.e.
find the physical location of the cause) for abnormal electrical impulse generation or propagation in the brain or central nervous system using the electroencephalogram or other index to guide invasive therapy (surgery) or external beam irradiation to identify and treat seizure or epileptic foci, or focal tumors (malignant or otherwise). The invention may also
-15-be used to identify sources for abnormal impulse propagation in striated muscle (such as injury in skeletal muscle), the gastrointestinal system (such as esophageal spasm), the urogenital and respiratory systems. The invention may also be used to detect tumors (malignant or otherwise) in any body system. The invention also has applications outside of medicine, such as for locating the source of a seismic event or for locating energy sources in tandem with methods such as radar or sonar.
The invention has several aspects to its process and system for carrying out the process. By way of example and not of limitation, in one aspect of the invention, signals are detected from multiple locations in an organ in the rhythm disorder, altering the spacing between sensors to optimize clarity of said sensing. A particularly desirable embodiment also records these signals from a heart, or other body part, during a rhythm disorder and stores them in a data base. The location of each sensor associated with a particular signal, as well as the activation onset times at each sensor are transmitted to a processor for analysis including sequential ordering to form the activation trail identifying the cause of the disorder and its specific location in the body. Creating a database of causes, which may be manually or automatically updated allows for accessing the data base to assist in the identification and localization of disorder causes. This is used when data collection in the current patient is of limited quality, to compare the pattern in a patient to prior recorded rhythms in the patient to determine if the rhythm is the same or different, or to compare the pattern in a patient to that from another patient, such as one with similar clinical characteristics.
Previously stored data from a previous case may be used to help identify, localize and display causes for the rhythm disorder in a present case.
DESCRIPTION OF USEFUL COMPONENTS ( MODULES) AND DEVICES
Figure 1 shows a schematic of various useful components (modules) which may be used in the process and system of the invention. The modules may be separate form each other and cooperatively interfaced to provide their function, or one or more of them may be
-16-integrated with each other of contained in the processor, such that the system has less separate hardware units. Figure 1 depicts an embodiment which allows a cause of the disorder to be localized during a minimally invasive percutaneous procedure, or other procedures such as using surface ECG, a magnetocardiogram, an echocardiographic and/or Doppler measurements from ultrasound, electromagnetic radiation, sound waves, microwaves, or electrical impedance changes.
In Figure 1, electrical events in the heart 10 are recorded with sensing electrodes.
These electrodes may be catheters 20 placed within the chambers or vasculature of the heart, including custom-designed recording catheters exemplified in Figures 2-4, The electrodes may also be extensions of leads from an implanted pacemaker or cardioverter-defibrillator, catheters used to record monophasic action potentials or other signals, that typically arrive via the vena cavae 20-21 or coronary sinus 22. Thus, although particularly useful in the invention, the process and system of the invention need not, however, employ the specialized catheters of Figures 2-4, as any catheters or sensing devices used inside or outside of the body which capable of accurately transmitting the activation times and location of their occurrence may be employed.
Electrodes 23 may record from the epicardial or pericardial surface of the heart, accessed via electrodes 21 in the coronary sinus, via the electrodes 23 in the pericardial space or other routes. Electrodes may be located in proximity to the nerves supplying the heart 15, which may be located in the left atrium and ventricles. Electrodes may be virtual (computed) electrodes from a computerized mapping system, routine or high-resolution ECG
mapping electrodes 30, electrodes implanted under or on the skin, or derived from methods to non-invasively detect signals without directly contacting the heart or body.
Electrode information may also be derived from stored electrograms in a database 160.
An electrode 25 placed near the heart may be used to modify or destroy regions that are near or at the cause(s) for a rhythm disorder. If the electrode is an ablation catheter, it interfaces to an energy generator 60. Other electrodes may interface with a controller 40, and a pacing module 50, and all desirably communicate with a process controller 70. Ablation or pacing can be directed to nerves supplying the heart 15, which are located at many locations of the heart. Internal ablation electrodes may be replaced with an external ablation system, such as external probes during surgery, or as in external focused irradiation or photon beam as for cancer therapy. In addition, modification of sources, i.e. treatment of the causes of the
-17-disorder, may be achieved by delivering appropriate pharmaceutical compositions, gene therapy, cell therapy, or by excluding tissue (at surgery or by using specialized devices).
The process controller 70 may include various components or modules. On such component or module includes a sampling module 80 which is capable of recording signals during the rhythm disorder, recording at various rates not in the rhythm disorder (by pacing), and/or recording during rates that simulate the heart rhythm disorder (by pacing or other methods). Signal amplifiers (not shown) may be used to enhance the signal clarity and strength, and the process controller may also intelligently assign the fewest number of recording amplifiers to sense from a sufficient number of locations to identify and localize the cause. For instance, the system may use only 50-60 physical amplifier channels to record from 128 sensors (for example, from two commercially available multipolar catheters), by recording those 128 sensors on a `time-share' basis by time-slicing, or by activating individual/multiple sensors close to a rhythm cause while deactivating others.
This 'switching' functionality may be performed by a switching component that connects the sensor device with the electronic control system, and that may be embodied in one or more other components. Switching may be manual or automatic, determined for instance on where causes of the heart rhythm disorder lie. Module 90 interfaces with the pacing module to provide additional heart rates for sensing the biosignal. This is particularly useful for the non-real time mode (mode 6), described herein, because it can study the heart at different heart rates even when not in the particular heart rhythm disorder being diagnosed and treated.
The inventive method and system processes the collected data using analytical methods, which may be performed by analytic modules. For example, in Figure 1, Module 100 is part I of an "Analytic Engine." This portion of the Analytic engine determines the onset and offset for the biologic signal over time, at each sensed location.
This is implemented by creating a series of activation times (onset timing) and recovery times (offset timing) during the rhythm over time (illustrated in Figure 6,). The signal is typically represented as voltage over time (that is, as a voltage-time series).
Activation time can be processed in many ways. The simplest includes manual assignment at each location.
Automated or calculated assignment can be achieved by using zero of the first derivative to define maxima or minima, zero of the second derivative to indicate maximum upstroke or downstroke, or similar methods. Activation onset and offset times can also be assigned when the voltage time-series crosses a threshold. Another possible method to assign activation times is using pattern-matching. For instance, a pattern selected to represent the activation
-18-duration can be correlated to the signal at multiple timepoints over time. The time when said correlation values are high indicate recurrences of said template, and thus are considered activation times. The template used for this analysis can also be obtained from stored data in a database, or computed from a rate estimate for the rhythm at that location.
Simultaneous recordings from multiple sensors can help in analyzing activation, particularly for complex rhythms such as AF or VF when signal quality may be noisy, of poor quality or show multiple components at different times. From simultaneous recordings, a reference signal is selected, preferably at a nearby location to the channel being analysed.
Signals on the reference channel are used to select signal or signal components on the channel being analyzed. This can be done by using components that retain a similar timing over time, using pattern matching or correlation functions, vectorial analysis or other methods. If many methods are required, heuristics, pattern recognition methods and so-called 'fuzzy logic' approaches can be applied, constrained by known pathophysiology of the atrium.
Module 110 is part II of the Analytic Engine that actually computes and localizes, i.e.
determines the existence and location of sources (causes) for the heart rhythm disorder.
Some embodiments of the invention include a "Therapy Engine," which may contain one of more modules designed to cooperatively perform different functions in the system and process. For example, module 120 in Figure 1 may be responsible for determining the location and migration pattern of sources for the rhythm disorder within the heart. This may be a first module of the Therapy Engine, and is used to compute the location and spatial region which is required to be modified in order to treat or eliminate the rhythm disorder.
Treatment may be by delivery of ablation energy or other means as discussed herein, and is not simply one point or region if the source migrates during ablation. Module 130 is representative of another module of the Therapy Engine, and desirably directly interfaces with the energy generator to ablate (destroy), modify (ablate or pace) or stimulate (pace) tissue at sites likely to represent sources. Alternatively, the Module 130 may be used to modify tissue without destructive energy, for example by delivering pharmaceutical agents, or gene or cellular therapies.
Module 170 of the system shown in Fig. 1 is representative of a tool to display the identification or location of causes visually or in auditory fashion, to assist the physician in treating or eliminating the rhythm disorder. For example, this module may include a display screen which permits the textual, graphic and/or auditory visualization on the screen of the rotor, focal or other cause of the disorder to be clearly seen by the practitioner. In some
-19-embodiments, a "movie" clip of the disorder found will be presented on the screen. This clip is a real-time presentation of the actual cause and location of the disorder.
For example, once the analysis of the data has been performed in accordance with the process of the invention, i.e. the location of the signals and their activation onset times have been sequentially ordered, the result of this analysis and computation will be shown on the screen in the form of an activation trail. If the pattern of the activation trail signifies a series of activations revolving around a central core, then a rotor has been found and is in fact a cause of the disorder.
Similarly, if the pattern of the activation trail signifies a series of activations which emanate radially from a central core region, then a focal beat has been found and is in fact a cause of the disorder. Thus, the inventive process permits the direct finding of the cause of the disorder and the convenient visualization of the existence, type and location of the disorder for the practitioner. In the event that no discernable pattern is found, i.e.
the activation trail is not localized, then additional signal sampling by moving the sensor locations and/ or turning-on already placed sensors may be appropriate. The additional signal samples may then be processed in accordance with the invention and shown on the screen. If a cause is found via the additional sampling and processing of the data, then a decision as to the appropriate treatment may be made. In the event that a dispersed activation trail and pattern is found, further additional sampling may be advisable until such time as the practitioner feels is sufficient. In some instances, the result of the process will render a finding of the existence and location of a rotor or a radially emanating focus. In other instances, where a dispersed pattern remains even after repeated sampling and processing, a diagnosis may be made ruling out a rotor or focal beats as the cause. Thus, the finding of a rotor or a focal point (beat) will be essentially a detection and diagnosis concurrently, whereas the lack of such a finding will be a diagnosis which may rule out the presence of either of these causes of the disorder.
MODE 1 SIGNAL SAMPLING (FIGURE 1, REFERENCES 80) Signal sampling can be done in real time, during a procedure to ablate or treat the rhythm disorder, beforehand to plan for a procedure, or afterwards to review the disorder. As stated above, signals are collected at one or more locations from the organ using a variety of sensor types. Contact sensors should maintain as good a contact with the tissue as possible.
In the preferred mode, electrodes should record at multiple sites simultaneously or nearly simultaneously. The fastest heart rhythm disorders such as AF have cycle lengths > 100 ms,
-20-so that signal acquisition for substantially less than this time is considered 'nearly simultaneous'. An alternative mode of operation allows moving a sensor to sequential sites.
The invention may be used with any existing sensor apparatus.
Although a variety of commercially available electrode devices may be used to obtain signal sampling , particularly useful device embodiments for signal sampling are shown in Figures 2-4,. These apparatuses use multiple sensors that may be individually activated or deactivated, or moved relative to one another. This enables adaptive spatial resolution, in that sensor spacing can be increased or decreased as desired. Widely-spaced sensors provide a wide field of view to 'survey' the rhythm for a large portion of the organ (e.g. left atrium of the heart). Once the source location is approximated, the configuration is desirably altered to reduce sensor spacing for higher spatial resolution over a narrow field of view. A tightly spaced sensor configuration is preferred for applying energy to a focused region to treat a source.
Adaptive spatial resolution is an important advantage of various embodiments of the present invention. This can be achieved by physically moving sensors. Figure 2 shows concentric helices (element 200), with multiple sensing elements (electrodes or probes) for sensing signals and in some instances delivering energy or other treatment therapy (element 205). The helices are widely spaced when parts of the catheter remains non-deployed (element 210) inside the shaft (element 215). Rotating and advancing the assembly introduces more probes in the chamber, and reduces their spacing. Figure 3 another embodiment of an inventive sensor catheter in the form of an adjustable fan catheter, with multiple meridians (element 230) each containing multiple sensing elements (electrodes or probes) (elements 240), also for sensing and in some instances for delivering energy or other treatment therapy. By a combination of twisting or tortional motion along the shaft axis (element 245), as depicted in the Figures, the meridians may be more widely spaced (element 230) or more closely spaced (element 235), i.e. spatially adjusted. Figure 4 shows another embodiment of an inventive sensor catheter in the form of an adjustable corkscrew design, with a small number of spiral meridians (element 260) ending on a blunt non-traumatic end (element 270). As with the design structures of Figs. 2 and 3, the meridians of Fig. 4 may include multiple elements (electrodes or probes) (elements 265). The corkscrew can be advanced or retracted into the sheath by manipulating the shaft (element 280), to increase or decrease the corkscrew size and/or probe spacing. These designs can be made larger or smaller to fit a larger or smaller organ (e.g. atria of varying sizes), or substructures including
-21-pulmonary veins or the superior vena cava that may be sources for rhythms such as AF.
Physical movement can be achieved manually by the physician or automatically by using machines. Given the observed properties of sources for heart rhythm disorders observed by the inventors, it is desirable that the sensors sense from at least about 25 %
of the surface area of each one or more chambers of the heart. These designs are illustrative only, and are not intended to limit the actual physical design or application of this invention.
Optimal contact for each sensor can be monitored by the process controller 70 for adequacy in various ways. For example, the process controller 70 can verify contact via stability in the amplitude of sensed signals. Alternatively, the process controller 70 can condition the pacing module 50 to emit signals through electrodes 20-30, and use the amplitude of evoked responses to verify contact. As a third alternative, the processing module 70 can determine contact by confirming stable tissue impedance (in AF, for instance, where pacing is not possible). As other alternatives, catheters designed to examine mild injury patterns, or designed to directly measure contact force, can be used.
In addition, catheter manipulation can be controlled robotically in semi-automated or automated fashion, as well as manually.
Adaptive spatial resolution can also be achieved electronically. Sensors in this adjustable sensor device are connected to an electronic control system that may activate or deactivate individual sensors. This may be performed manually, such as if the physician wishes only to focus on one region of the organ, or automatically by the process controller in Figure 1 to focus on a region determined to be where the heart rhythm source lies. An electronic switching apparatus controls independent switching of connections between the sensors and electronic control system, in order to maximize use of a practical number of amplifier channels. These electronic components may be embodied by various combinations of traditional (wired) electrodes, fiber optics, etched-wafer circuit designs, biologic sensors, chemical sensors, pharmaceutical sensors, piezoelectric sensors, infrared sensors, patient-compliant optical imaging, optrodes, remote sensors and other designs.
Electronic switching may also be achieved by time-slicing. A large number of locations may need to be sensed, but the number of sensing channels may be limited. Signal time-slicing can record a larger number of sensing channels from a smaller number of channels. For instance, signals are often sampled every 1 ms (at 1 kHz) although data acquired every 10 milliseconds (ms) or so is often sufficient for AF or VF
Thus, the system can sense at location 1 for 3 ms, locations 2 and 3 for 3 ms each, then return
-22-to sensor 1 to repeat the cycle at the 10 ms timepoint. In this way, 90 locations can be sensed using 30 channels. Any appropriate configuration can be used, depending on the switching time in hardware or software, and allowing for noise factors when switching between channels. Many other methods can be used to increase the effective number of channels, including sending multiplexed signals along a fiber optic or other device, or storing signals in random access memory, then using off-line analysis to amplify and analyze each in turn.
In certain preferred embodiments, sensing can be performed using one or more sensors (probes) moved sequentially within the organ during the heart rhythm disorder.
When a single probe is used, signals from each location are aligned relative to a timing signal fiducial. This method is easy to apply when a rhythm is relatively regular within the heart, such as the 'simple' disorders of focal atrial tachycardia or atrial flutter.
However, this method can also be used as an approximate guide if the rhythm is irregular within the heart, such as the complex rhythms of AF or VF. This has the advantage of requiring fewer sensors, and will work if sources show some stability in space. For instance, while AF is irregular, activation may be regular at localized sources, for example at certain locations such as near the pulmonary veins.
One particularly useful embodiment for using sequential sensing at multiple locations is now illustrated for a moving probe with two sensors (such as the two bipoles of a clinical quadripolar catheter), although more sensors may be applied if available. At each location, one sensor is considered the reference and the onset times for successive cycles (beats) are fiducials. The difference in activation time at the second sensor is used to indicate relative timing. The probe is now moved so that one sensor overlies the previously sensed location.
The second sensor now senses a fresh location and can record relative timing onsets for multiple beats here. The process is repeated for the entire region of interest. Because this process introduces stability in relative timing between locations, variability can be reintroduced stochastically using observed beat-to-beat timing variations at each location.
-23-An alternative approach is to use gradients in rate and/or organization within the chamber, compared to stored data from a database for that rhythm (including AF
or VF).
After sensing sequential locations, the activation rate in both chambers is compared to stored patterns that describe this relationship at various sources (rotors or focal beats) and surrounding sites. An error-minimization approach (such as least-square-errors) may be used to estimate the source location. Estimates may be refined adaptively, based on similarity to subsets of stored patterns and using algorithmic, heuristic, fuzzy logic or other pattern recognition scheme. This process is repeated iteratively. For a spatially consistent source, second and subsequent iterations will add precision to the original estimate, and may be focused at locations closest to the estimated source.
Delivery of treatment may be another feature of the sensor device, that will be described in detail later herein.
The first step in analysis is to determine the signal type, using a lookup table as illustrated in Figure 5, reference numerals 400-460. This step determines if the signal arises from the heart (cardiac), brain, respiratory system, gastrointestinal tract, urogenital system, and so on. If cardiac, the signal may be a surface ECG, intracardiac, echocardiographic or other signal. If intracardiac, the signal is further classified as an action potential (monophasic action potential), bipolar electrogram, unipolar electrogram or other. Some of these signals provide high quality information (e.g. monophasic action potential recordings in the heart), while others do not. Lower quality signals are more likely to require pre-processing, filtering, averaging, comparison against stored signals in a database, in that patient at different times and other computational steps to allow source localization.
In Figure 6, the signal is parsed between steps 800-840 to identify its type in the lookup table (from Figure 5). This includes assigning activation onset and offset, and the interval between beats (diastolic interval) that depends upon the signal type illustrated in the lookup table in Figure 5. The lookup table can be a comprehensive biosignal inventory, with data on the distinct physiological role of each component for computational purposes.
Components may vary with rate and may fluctuate from beat to beat. Each signal component may reflect a distinct aspect of normal or abnormal physiology and thus indicate likelihood that the rhythm disorder may arise. Examples are not intended to limit the scope of the
-24-lookup table, which may include signals from other muscles (e.g. skeletal muscle, bladder and gastrointestinal tract), the brain and the nervous system.
The next step in analysis is to define, for each sensed location, the physiological signal to be analyzed. The goal is that the resulting signal best represents actual physiological activation and recovery occurring in the heart rhythm disorder at each location.
When the recorded signal is 'clean' (has a high signal-to-noise ratio), this will be the physiological signal. If signals are noisy, then filtering, noise reduction and other schemes may be needed to reveal the physiological signal. Said noise schemes may require recording while the patient holds his/her breath for several seconds. For analysis of atrial rhythm disorders, the physiological signal is best recorded between ventricular activations (in the R-R interval), that may be facilitated if the heart beat is reduced (R-R
interval is prolonged) using agents to slow ventricular rate or by reducing pacemaker rate in patients with such devices.
Figure 7 panels 600-670 illustrate a particularly useful embodiment for constructing physiological signals using computational methods to compensate for limitations due to noisy or low quality data. First, the response to rate of each signal type (monophasic action potentials, MAP, illustrated in panels 600, 620, 640) is determined. This is performed by sensing signals at varying rates when in the rhythm disorder, or when not in the rhythm disorder (such as by pacing, see mode 6). The response of the signal duration (illustrated for MAP) to rate is shown in panels 610, 630, 650, and shows that MAP shortens at increasing rate (that is, when diastolic interval shortens). It is to be noted that the response to the same set of rates may vary when the patient is and is not in the heart rhythm disorder. Figure 8, panels 700 to 740 show this. Pacing with delivery of a single extrabeat in panel 700 results in the restitution plot shown in Figure 6, 710 as soon as AF begins. However, after several minutes, the restitution curve changes as shown in panels 720-740.
One approach embodied in the present invention is to create a 'hybrid' signal by inserting a physiological pattern at the time of each activation time onset (panels 660-670).
The physiological pattern may be obtained by averaging recorded signals over time (algebraically, from the median beat average or other method), averaging signals at neighboring locations (spatial averaging), from monophasic action potentials at various locations (panels 660-670), by filtering existing unipolar or bipolar signals in the frequency or time-frequency domain, or by using stored patterns from a database (Figure 1, 160). When stored signals are used, properties including duration of these physiological patterns may be
26 adjusted for rate using rate-response (restitution) behavior. Stored signals may be obtained from this patient, another patient with similar characteristics or another stored relationship.
These processes may be applied to individual activations, or to the entire signal.
This method results in a physiological representation of activity at each location over time that may otherwise be difficult to obtain in the beating heart of patients during minimally invasive procedures. It has applications outside of heart rhythm disorders. For instance, said physiological pattern may be a model of cellular ion function.
This enables the function of these ion currents at each sensor to be modeled cells timed to each observed activation, for the study of dynamics of calcium fluxes, potassium currents or other processes within the beating heart of this patient. By way of a further example, this physiological pattern may be a model of a pharmacological ligand, allowing study on the behavior of the beating heart to specific pharmacologic agents. In the gastrointestinal tract, cellular hormone release models could be studied for each peristaltic 'beat'. In the brain, known kinetics of neurotransmitter or endorphin release for discrete brain waves (non-invasive, via the scalp electroencephalogram or invasive, as surgery) may help to understand and treat various conditions. Treatment of conditions of epilepsy, using the present invention, is one embodiment of the invention. This invention also includes a method for determining the effect of a pharmalogical or bioeffecting agent on the body by correlating the behavior of the beating heart or rhythm of another body part with the release, binding capacity or rate, or other action of the agent in the body.
Pertaining to phase-space methods, a well-known technique assigns a phase (I) to the signal at every electrode and at every time point. The phase at the exact location of the tip of the rotor is undefined and summing up the phase of neighboring electrodes results in a "phase jump" of 27c. Thus, a rotor location corresponds to a phase singularity.
Mathematically, these phase singularities can be found by evaluating a line integral over a closed curve as 0 = di = 2 7z- where the line integral is taken over a path / surrounding the phase singularity.
Since the signal from the electrode is a single observable, the determination of the phase requires special attention. We will employ several different methods depending on the quality of the electrode signal.
Since the shape of the action potential may be stable between beats, the method next defines a mapping from the membrane potential V to the phase 4). This map assigns a unique value of 4) to each value of V such that the maximum and minimum of the phase variable differs by 27c. The detailed form of this map is arbitrary and the phase is computed using 0 = 2R-(v- 0.5) . The corresponding time trace of the phase variable results in construction of the signal and its phase instantaneously as in Figure 8 (panels 710-730).
Once the phase map is constructed the method will calculate, for each time, the sum of the phase for all four points of the fine regular grid separated by a grid spacing that form a square (topological charge method). A result not equal to zero indicates the existence of a phase singularity and a rotor. The analysis will be further aided by the tracking of wave fronts. The location of these fronts will be computed using the regular fine grid by determining where and when V crosses a threshold value with a positive derivative dV/dt.
Performing this calculation along the x and y direction of the fine regular grid and using linear interpolation between the grid points, will result in a set of points that lie on the wave front.
The wave front is then constructed by connecting these points. A similar analysis will be performed for phase, where isophase lines are tracked. A two-dimensional visual representation is then constructed that plots for each time point the value of the membrane potential using a grayscale or color scale, lines representing the wave fronts, lines representing similar phase (isophase lines), and symbols locating the phase singularities. This visual aid will greatly benefit the practitioner in interpreting the results of the inventice process and system. Note that the crossings of the lines representing the wave fronts and the
-27-iso phase lines represent the phase singularity. Phase singularities indicate core regions, and thus can be used to localize the rotors.
The phase transform is able to demonstrate focal beats in AF ¨ typically as centrifugal sources emanating from a localized area. A focal beat is characterized by a location that fulfills three criteria: 1) its activation time is earlier that at surrounding locations; 2) this region was previously inactive (in diastole) for a specified period of time;
3) the subsequent spread of activation emanates radially from the core region. Recognizing these 3 criteria, the invention finds these sources automatically. This algorithm will first determine locations that exhibit activation times ahead of their four nearest and four next-nearest neighbors and mark these as potential focal sources. Next, it determines the activation times at locations surrounding a potential focal source. If the activation times of these locations are earlier than their surrounding electrodes, the potential focal source is confirmed and is marked accordingly. These sites are plotted using our plotting technique as described above, greatly aiding the practitioner in localizing and interpreting these sources.
Once such method is the Hilbert transform. The Hilbert transform shifts the phase of the negative frequencies of a signal by 7c/2 and the phase of the positive frequencies by -7c/2.
In this approach, determination of the phase 4) of the signal is achieved by plotting voltage against the Hilbert transform of the voltage. The particularly useful embodiment applies a detrending algorithm to set the voltages at the activation times (maximum dV/dt) to zero.
The Hilbert transform is used to construct the phase plane of detrended signals. The Hilbert transform at all locations is interpolated across the fine regular grid created across the biological surface. Phase is then calculated from the state-space plot of voltage versus its Hilbert transform. Again, the spatial distributions of phase will be analyzed with the topological charge technique described above to locate phase singularities associated with phase singularities (the ends of wavefronts) such as at the tip of a reentrant wave. Activation wavefronts are constructed using the same technique as described above while isolines of zero phase will also be tracked. An example of our methods in the human atria is shown in Figure 12 elements 1030 and 1040 which show rotors in the left atrium computed using frequency-domain methods.
-28-Another useful method employs a time delay embedding technique to determine the phase of the signal. This technique consists of plotting V(t+ r)- V* vs. V(t)-V* for a fixed time delay T and offset V*, resulting in a value of the phase 4) for each time point and each location. In practice, the time delay and offset will be determined by the practitioner after examining these plots for several locations using different values for T and V*. Optimal values lead to trajectories that do not cross (that would lead to a non-unique value for the phase) and that encircle the origin (ensuring that the minimum and maximum phase differs by 27c). Both the signal and the phase are interpolated across a fine regular grid created across the biological surface. The resulting phase map will then be examined for phase singularities and wave fronts will be tracked as described above.
Yet another useful method used to determine the phase of the signal is a wavelet transform. The exact form of this wavelet is variable, and an example includes the Haar wavelet. The wavelet transform will be computed for each location. The wavelet allows us to view the signal in multiple frequency resolutions. This will enable us to filter unwanted noise at specific frequencies (or frequency bands). In this approach, the phase transformation is achieved by plotting voltage against the phase shifted wavelet transform of the voltage. Once the phase (I) has been calculated, we will precede as before, including refining the grid through bi-linear interpolation, finding phase singularity and tracking wave fronts.
Several types of activation trails may result, producing corresponding discernible signature patterns for various types of causes for a rhythm disorder. An activation trail in which sequences of activation revolve around a central 'core' region is termed a rotor. An activation trail that emanates radially from a core region is termed a focal beat (or a site of repetitive focal activations or beats). Another activation trail type is a dispersed pattern, in which a localized source is not clearly identified. In particularly useful embodiment, in such cases, signal sensing is repeated at additional locations or for additional periods of time.
Localization of a cause for a heart rhythm disorder is based on the location of the core region and additional activation from this region. Some embodiments identify the core region
-29-directly. For instance, the Hilbert Transform and direct phase assignment methods identify the core region as the site where real and imaginary parts of the analysis intersect. In contrast, the direct sequential ordering method of the present invention indicates a core region either visually or analytically.
Figure 10, referenced by panels 1400-1495 describe the process of optimally identifying, locating and selecting cause(s) that are most likely to indicate primary causes of the rhythm disorder. In one particularly desirable embodiment, a probability map 1480 for sources of the disorder is constructed. This indicates a likelihood that each sensed location harbors a cause of the rhythm disorder, relative to other sensed locations. A
higher relative likelihood is assigned for sites where core regions sustain for longer periods of time (or, for more rotations or beats), where the rate of activation is faster, where the rate of activation is more organized, that activate surrounding tissue in a 1:1 fashion (thus, there is electrogram linking) and activate larger regions of tissue in phase (and thus have a large space constant), when fewer concurrent sources are identified, for sources that lie near known regions of high likelihood for rhythm disorders such as the pulmonary veins in human AF, for sources with less migration over time, and for rotor versus focal beat types of source. In one particularly useful embodiment, probabilities are assigned after comparison with stored examples in a database; the comparison may take the form of a stepwise multivariate comparison. In the limit case, a spatially fixed source, that is a solitary electrical rotor and that directly activates the entire organ is by definition a primary cause of that heart rhythm disorder.
Surrogates for the activation trail also exist. These are data that approximate the identification and localization provided by the invention using data from fewer locations, less lengthy or detailed recordings, or using information from other resources such as the ECG
rather than from within the heart. Thus, surrogates enable approximation of the activation trail using a reduced number of sensor locations compared to an analysis that directly measures the activation trail. These surrogates, used independently or in combinations, include sites of rapid rate during the rhythm disorder, the presence of very regular sites surrounded by less regular sites, the presence of stable beat-to-beat configuration (shape) for successive signals as opposed to varying signal configurations, signals where amplitude is particularly low, signals that are very prolonged for each activation is very prolonged, proximity to anatomic features known to be associated with particular rhythm disorders (such as pulmonary veins in AF, His-Purkinje system in VF), or a combination thereof may also assist in identifying and locating sources.
-30-Surrogates may be detected from the ECG, and thus be used to plan a procedure or guide therapy in a patient. Vectorial analyses of the ECG for regions of regularity and high rate, particularly if surrounded by regions of lower regularity and rate, indicate locations within the heart where sources lie.
Figure 10, panels 1400-1495, summarize the approach to identify and locate sources.
Panels 1400-1450 determine if sufficient sensor resolution is present to identify a cause.
Criteria for sufficiency include the absence of discontinuities in the wave front calculation, and absence of jumps in the location of core regions, and an absolute sensor spacing that should not exceed approximately 1 cm. This is based upon computations that the minimum circumference of a reentry wave is > 2 cm in the human atrium and larger in the human ventricle. Panels 1460-1490 then use a combination of optimized sensed data and stored data to compute sources, that are then treated, panel 1495. The present invention includes the wide use of filtered or unfiltered clinical data, data from a database including this and other patients, or computational estimates to represent the signal to be analyzed as well as the results of analysis. In addition, the hybrid use of existing patient-acquired data, signal processing methods, numerical methods and stored signals from a database are major advantages of the inventive process and system, particularly because high-resolution physiological data from human atria or ventricles may be extremely difficult, if not impossible, to obtain at clinical electrophysiologic study without open heart surgery.
All of the above approaches may be applied to any complex rhythm, including VF.
Of course, these approaches may also be applied to "simple rhythms" such as reentry around an anatomical obstacle or rotors anchored at scar tissue (such as atrial flutter).
Data on sources for rhythm disorders desirably may be stored in a database 160. This may be useful to classify sources in different patients, to help identify sources in a single patient, or to determine if a patient has returned with the same or a different source. Data in the database will thus include the characteristics described above, including the number of concurrent sources, rate, variability in rate over time, duration, size of biological organ whose
-31-activation is directly caused by the source (the space constant), location, whether this location migrates over time, rate within multiple regions of the heart at the time that the source was detected (such as left and right atrial rate during AF), and the response of each source to ablation.
The invention and database interface may include an expert system that compares current data with stored data. Based on the closest match or matches, logic within the invention determines if additional heart rhythm sources or additional characteristic should be studied, and whether they may lie based on stored information. This uses a 'goodness of fit' against various stored parameters. This functionality is included because in practice, the number of sensed locations is limited by time constraints, in practice, many sensor locations may provide suboptimal data, thus limiting the actual sensed resolution, and because the inventor has observed that many patients show similar source locations and characteristics.
-32-The invention includes methods and apparatus to communicate the identification, location and above characteristics of sources for biological rhythm disorders to the practitioner. This includes a visual display means, typically in the form of a graphical display on a computer monitor, or a printout showing the source in relation to cardiac anatomy, or a basic textual line summary of the location and/or sensor site where the source lies.
In addition to the processes and systems of the invention used to detect and diagnose the cause of the rhythm disorder, the invention also includes devices and methods to treat the source for the biological rhythm disorder, in order to modify, ameliorate or eliminate said rhythm disorder.
-33-Alternatively, therapy may be targeted at locations neighboring the core region for a source, with the intention of disconnecting the source from surrounding tissue.
Treatment may take the form of ablation, delivered via a catheter in the heart (element in figure 1), on the epicardial surface, or an electrode present on one of the multi-electrode catheter designs included herein, for example see Figures 2-4.
In preferred particularly desirable embodiment, the multi sensor catheter (Figures 2-4) includes an assembly that can deliver therapy in the form of ablation. In this embodiment, sensors at locations where the source lies are activated to deliver ablation energy to modify or eliminate the source.
The system may deliver therapy in a spatial locus, as well as at fixed locations. In this system, the location of the source core region is analyzed constantly throughout therapy.
Therapy, such as ablation energy, is directed at varying locations and potentially multiple locations to constrain movement of the source. An analogy is to construct a 'fence' of ablated tissue around a moving source in order to keep it in one location.
This may require therapy delivery (such as ablation) at multiple sensors of said poles of said assembly
-34-concurrently. This process is continued until the rhythm terminates or a remote source becomes dominant.
-35-Signals are first uploaded from stored electrograms in a database 160 to the processor controller 70. This database can be the master database that stores data on multiple patients, or a patient-specific database. Data storage and retrieval can be implemented for any signal type. Stored signals can be derived from another source, a catalogued source, or computed or virtual signals such as from Ensite 3000 or NavX by St Jude Medical, or Carto by Biosense-Webster. Signals may also be derived from a different individual, querying the database for a patient with similar demographics and heart rhythm disorder.
In the preferred embodiment, to measure restitution it is necessary to sense signals for a wide range of rates at each location, as indicated in figure 1 element 90.
This may be achieved using pacing. In this case, the process controller (figure 1, element 70) conditions the Pacing module 50, to stimulate the heart using electrodes in the heart 20-25, on the body surface 30, in the esophagus 150 or elsewhere. The wider the range of rates, particularly fast rates, the more comprehensive the data range for that signal for analysis of restitution. When pacing is not an option, the invention will prompt the user to increase heart rate using other options or to use stored information from a database.
In this embodiment, the rate-response ("restitution") curve is created at each rate for each component of signals shown in figure 5. For example, this step may compute how monophasic action potential duration (time from phase 0 to phase 3) varies with rate (APD
rate restitution). Examples of atrial APD restitution are shown in figures 5, 6 (items 600-720). Using pacing to increase the range of sampled heart rates provides a comprehensive assessment of rate response of each biosignal.
Figure 7, references 600, 620, 640 show a useful embodiment, whereby recordings of human action potentials made by the inventor in the left atrium 420, each of which provides high quality information including depolarization (phase 0), repolarization (phases 1-3),
-36-phase 2 amplitude and action potential duration (time interval from phase 0 to phase 3).
Phase 4 indicates the interval between one beat and the next. The invention may determine rate response (restitution) of multiple components, focusing on rate-response of AP duration (time from phase 0-3), and AP phase II amplitude.
Reference 400 (Figure 5) is an ECG. This includes intra-atrial components (the P
wave and PR interval), and ventricular components including depolarization (the QRS
complex) and repolarization (the T wave). For atrium, the invention records how P-wave duration varies with rate, using analyses shown later in Figure 7, 600-650.
For the ventricle, the invention records how QT interval varies with rate as a measure of ventricular APD rate-behavior (restitution). Individual QRS complexes are aligned using one of several columnar techniques, including methods that align electrograms about the point of largest positive or negative slope, their peak values or minimize their mean square differences, or metrics based on derived signals. T-waves are identified and aligned similarly. Atrial activity is considered to lie in the intervening intervals.
If the signal is a unipolar electrogram, it is also analyzed in analogous fashion. Each is analyzed for waveform shape as well as duration. Figure 5, Items 430-440 indicate unipolar electrograms from the human left atrium 430 and left ventricle 440 respectively, with depolarization and repolarization measured collectively as the activation-recovery interval, a surrogate for the monophasic action potential duration. The invention determines adjustment of various components for rate.
In AF, MAP restitution may differ from MAP when not in AF. Figure 8 element shows the initiation of AF after pacing. Element 710 shows MAP restitution during pacing in black. Immediately after AF onset (red points), APDs track previously derived MAP
restitution. However, this may not be not true for longer-lasting AF. Elements 720, 730 and 740 show patients with long-lasting AF, in whom APD restitution differs from that obtained in pacing prior to AF.
-37-Thus, it may be advantageous to use APD restitution obtained from the patient in AF, at this time or a previous time, or from stored APDs in this or other patients, or filtered or computed data, for signal processing and analysis.
Figure 11 panels 900-910 illustrate a representative patient, a 47 year old man with persistent atrial fibrillation (AF) for over five years. The patient continued to have symptomatic racing of the heart, which required him to visit hospital emergency rooms for treatment, despite various therapy with amiodarone and other appropriate therapy, and despite prior ablation procedures for AF. Given the severity of his symptoms, the patient
-38-therefore elected to return to the electrophysiology laboratory for further evaluation and ablation.
Figure 11 panels 900-910 shows signals from the right and left atria during AF
at the commencement of electrophysiologic study. It can be seen that the AF cycle length (time between successive activation onset times) is quite short, shown as 172 ms and 165 ms for the first two cycles in the right atrium (panel 910), and varies, as is typical for AF. Notably, signals were more fractionated and disorganized in shape in the left atrium (post LA') and coronary sinus (CSP' proximal coronary sinus; `CSD' distal coronary sinus) than in the right atrium (I-IRA' high right atrium; Tat RA' lateral right atrium; 'post RA' posterior right atrium), as is common.
These findings would normally guide ablation towards the left atrium. A
typical procedure in this case would commence by ablating near the pulmonary veins and confirming isolation, followed by additional ablation selecting at sites including: (a) left atrial sites of fractionated electrograms, linear ablation at the roof, linear ablation at the mitral annulus, other linear ablation, then (b) right atrial ablation including sites of fractionation and the cavotricuspid isthmus. This proposed procedure would take approximately 2-3 hours with a < 50 % chance of terminating AF, meaning that electrical cardioversion would be required to restore normal rhythm at the conclusion of the procedure (Calkins, Brugada et al. 2007).
Rather than use this known approach, an embodiment of the method and treatment of the present invention was applied. A catheter assembly containing 64 sensors (electrodes) was inserted via the femoral veins into the right atrium, and across a trans-septal puncture into the left atrium of the patient. These were connected via wire cables to a recording system for collecting signals at each sensor during AF. These signals were converted to digital form, and input into a computer program. Activation onset times were recorded for 2 seconds of AF at each sensor. While two seconds was used with this patient, greater or lesser periods of time may be useful. Desirably, one second or less may be used. Alternatively, milliseconds may be used. Activation onset times at each sensor location were sequentially ordered in time. Stored action potential tracings were used to create an electrograph (voltage-time series), by inserting said tracings at the activation time onsets for each sensor. Finally, a direct phase assignment technique was used to identify a core region. An activation trail is directly indicated by the relationship of these activation sequences to a core region ¨ if they revolve around a core, then an electrical rotor is detected and considered to be a cause, but if
-39-they emanate radially from a core region, then a focal beat is detected and considered a cause.
Results were displayed as an animation on a computer monitor for physician review.
The activation trail (panel 1035 in figure 12) revealed an electrical rotor as the cause for this man's AF. In figure 12 panel 1000, activation onset times can been seen to revolve around a core region in the right atrium at times color-coded from 10 ms (blue) to 200 ms (red) (panel 1010). No localized cause was found in the left atrium (panel 1020). Panel 1040 displays this same rotor in a different form, as three snapshots in time of tissue that is depolarized (activated; red) and repolarized (not activated, blue). Viewed chronologically (from left to right), these snapshots also trace activation sequences revolving around a core region (a rotor). This core region had a high likelihood of being a cause, since it was a solitary source that controlled electrical activation for almost all of the surrounding atrium (large space constant).
Ablation commenced directly at the rotor core in the right atrium (panel 1050), at a site indicated by the red dot in Figure 12 panel 1060. Notably, AF slowed within 30 seconds of energy delivery to a cycle length of 227 ms. Subsequent ablation at immediately adjacent sites, indicated by white dots in figure 10 panel 1050, further slowed AF
until it terminated to sinus rhythm within 6 minutes' ablation as shown in Figure 13. In Figure 13, panels 1100 to 1120, AF can be seen to stop (panel 1110), followed by the restoration of normal sinus rhythm (labeled 1120). At this point, AF could not be restarted using the typical technique of rapid pacing as shown in Figure 14, where panel 1210 shows rapid pacing with capture of the atrium, panel 1220 shows no induction of AF and panel 1230 shows sinus rhythm after the end of pacing.
This result is paradigm-shifting compared to the current state-of-the-art, where slowing of AF typically occurs after lengthy ablation that is widely and empirically applied (to 30-40% of the atrium), yet termination of persistent AF is still uncommon.
Conversely, we acutely slowed and acutely terminated AF with ablation of less than approximately 2-3 %
of the atrium. Ablating only at one site identified a priori in persistent AF, and seeing immediate slowing and termination of AF is not known to have been performed previously.
-40-OTHER EXAMPLES OF IDENTIFICATION AND LOCALIZATION OF CAUSES
A 77 year old man presented for ablation of atrial fibrillation (AF). His history was notable for paroxysmal AF despite multiple antiarrhythmic medications, a slightly enlarged left atrium (diameter 45 mm) and normal left ventricular ejection fraction (58%). At invasive electrophysiology study, catheters were inserted into the atria as described.
The invention was applied to multiple sensors. In Figure 15 panel 900 shows a localized source in the form of an electrical rotor near the left inferior pulmonary vein. Inspection of panels from left to right (forwards in time) shows that the depolarized (activated) tissue in warmer colors (red) revolves clockwise around a core region on the medial lip of the left inferior pulmonary vein (see outline as black hourglass). Ablation at this site terminated AF acutely.
A 40 year old patient with persistent AF presented for ablation. The AF was resistant to flecainide and other anti-arrhythmic medications, his left atrial diameter was 52 mm and left ventricular ejection fraction was 69 %. At invasive electrophysiology study, catheters were inserted into the atria as described above. The invention was applied to multiple sensors. Figure 15 panel 910 shows a localized source in the form of an electrical rotor in the posterior wall of the left atrium. Again, viewing panels from left to right shows that activated (depolarized) tissue revolves counter-clockwise around a core region on the posterior wall of the left atrium between the pulmonary veins. After ablation at this site, the patient remains free of AF.
A 56 year old patient with paroxysmal AF and significant symptoms presented for ablation. The AF continued despite several anti-arrhythmic medications. His left atrium was moderately enlarged. At invasive electrophysiology study, catheters were inserted into the atria as described above. The invention was applied to multiple sensors.
Figure 16 panel 1610 shows the output of a localized source in the left atrium, between the pulmonary veins although not lying at these veins. The source was repetitive (panel 1620). In panel 1630, the activation trail (1630) shows activation emanating radially from this site. In panel 1640, left atrial activation is seen to be fibrillatory (disorganized). Ablation was applied to this focal beat cause, and AF terminated acutely. This is a paradigm shifting because normal ablation lesions in this patient, that circle the pulmonary veins, would have missed this source. Thus, this patient would likely have been one who would have recurred after ablation, if the prior art known techniques of treating AF were used.
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1. A method of detecting signals associated with one or more causes of a heart rhythm disorder, the method comprising:
sensing heart activation signals at multiple locations using a plurality of sensors;
collecting from said plurality of sensors, data comprising a sensor location of each sensor and an activation onset time of each heart activation signal at each sensor location such that a plurality of activation onset times at a plurality of sensor locations is collected;
arranging a sequence of the plurality of activation onset times at the plurality of sensor locations to create an activation trail; and determining at least one approximate core region in relationship to the activation trail indicative of the one or more causes of said heart rhythm disorder.
2. The method of claim 1, further comprising selecting a cause from said one or more causes indicative of a primary cause of said heart rhythm disorder.
3. The method of claim 1 or 2, wherein the activation trail comprises a rotational pattern or a radially emanating pattern.
4. The method of any one of claims 1 to 3, wherein the activation onset times in the sequence are arranged based on their relative activation onset time.
5. The method of any one of claims 1 to 4, further comprising visually depicting sequences of activation onset times at each sensor location to display the activation trail indicative of a cause of said heart rhythm disorder.
6. The method of claim 3, wherein the rotational pattern revolves about the at least one approximate core region or the radially emanating pattern emanates from the at least one approximate core region.
7. The method of claim 3, wherein said rotational pattern or said radially emanating pattern is visually displayed.
8. The method of claim 6, wherein said approximate core region is a rotor.
9 The method of claim 3, wherein said rotational pattern or said radially emanating pattern is repeating.
10. The method of any one of claims 1 to 9, wherein said activation trail is visually displayed.
11. The method of any one of claims 1 to 10, wherein said at least one approximate core region is a focal activation.
12. The method of any one of claims 1 to 11, wherein arranging comprises determining a dispersed pattern of activation onset times.
13. The method of any one of claims 1 to 12, further comprising performing sensing, collecting, arranging and determining for additional multiple locations.
14. The method of any one of claims 1 to 13, wherein at least 15 sensors are used for each one or more chambers of the heart.
15. The method of any one of claims 1 to 14, wherein said plurality of sensors are used to sense from at least about 25% of a surface area of each of one or more chambers of the heart.
16. The method of any one of claims 1 to 15, further comprising visually displaying the activation trail.
17. The method of claim 16, wherein said visually displaying is enhanced to increase the contrast and image clarity of said one or more causes of said heart rhythm disorders.
18. The method of any one of claims 1 to 17, further comprising filtering signal noise.
19. The method of any one of claims 1 to 18, further comprising creating the activation trail based on at least one of a direct phase, Hilbert transform, and time-domain analysis associated with the signals.
20. The method of any one of claims 1 to 19, wherein activation time associated with the activation onset time of a heart activation signal at a sensor location includes the activation onset time and a corresponding offset time.
21. The method of claim 20, wherein said activation time includes a diastolic interval.
22. The method of claim 2, wherein said selecting said cause is based on criteria selected from the group consisting of a number of activation trail repetitions, a rate of activation trail repetitions, a number of localized causes, a volume of tissue associated with the activation trail, whether a cause is localized or dispersed, a location of the cause within the heart and combinations thereof.
23. The method of any one of claims 1 to 22, wherein the multiple locations are within the heart.
24. The method of any one of claims 1 to 23, wherein the multiple locations are outside the heart.
25. The method of any one of claims 1 to 24, wherein the multiple locations are within the body.
26. The method of any one of claims 1 to 25, wherein the multiple locations are proximal to the heart.
27. The method of any one of claims 1 to 26, wherein said sensing of said heart activation signals at multiple locations is performed concurrently.
28. The method of any one of claims 1 to 27, wherein said sensing of said heart activation signals at multiple locations is performed stepwise.
29. The method of any one of claims 1 to 28, wherein said heart rhythm disorders are selected from a group consisting of supraventricular tachycardia, supraventricular bradycardia, ventricular bradycardia, atrial fibrillation, atrial flutter, atrial tachycardia, ventricular tachycardia, ventricular fibrillation or a combination thereof.
30. The method of claim 3, further comprising storing data associated with said activation trail in a database.
31. The method of claim 3, further comprising augmenting or modifying the activation trail based upon comparisons with similar activation trails associated with data stored in a database.
32. The method of any one of claims 1 to 31, further comprising constructing an electrograph having a voltage-time tracing of heart function at each of the multiple locations, wherein said constructing is achieved by inserting a physiological pattern in said electrograph at the activation onset time of each heart activation signal at each sensor location.
33. The method of claim 32, wherein said physiological pattern comprises a pattern selected from the group consisting of a prior recording from a same patient, a prior recording from a different patient, or a simulated pattern.
34. The method of claim 32, wherein said physiological pattern is a pattern selected from a group consisting of unipolar electrogram, bipolar electrogram, action potential representations, or a combination thereof.
35. The method of claim 32, wherein said physiological pattern is adjusted for rate.
36. The method of claim 32, wherein said physiological pattern is a model of cellular ion function.
37. The method of claim 32, wherein said physiological pattern is a model of a pharmacological ligand.
38. The method of claim 5, further comprising analyzing the heart activation signals at one or more of the multiple locations to approximate the activation trail indicative of a cause of said heart rhythm disorder.
39. The method of claim 38, wherein analyzing the signals comprises analyzing one of rate, regularity, amplitude, duration, and location.
40. The method of claim 38, wherein a number of locations is reduced as compared to an analysis that directly measures the activation trail.
41. A system to detect signals associated with one or more causes of a heart rhythm disorder, the system comprising:
a plurality of sensors at multiple locations to sense heart activation signals;
a processor interfacing with the plurality of sensors, wherein the processor is configured to:
collect from the plurality of sensors, data comprising a sensor location of each sensor and an activation onset time of each heart activation signal at each sensor location such that a plurality of activation onset times at a plurality of sensor locations is collected;
arrange a sequence of the plurality of activation onset times at the plurality of sensor locations to create an activation trail; and determine at least one approximate core region in relationship to the activation trail indicative of the one or more causes of said heart rhythm disorder.
42. The system of claim 41, further comprising software for processing said data.
43. The system of claim 41, further comprising determining whether a cause is a primary cause of said heart rhythm disorder.
44. The system of claim 43, wherein criteria used for determining whether a cause is a primary cause are selected from the group consisting of the number of activation trail repetitions, the rate of activation trail repetitions, the number of localized causes, the volume of tissue contained within the activation trail, whether the cause is localized or dispersed, the location of the cause within the heart and combinations thereof
45. The system of any one of claims 41 to 44, further comprising a display for visualization of said data.
46. The system of claim 45, wherein said visualization of said data comprises displaying the activation trail of said heart rhythm disorder.
47. The system of any one of claims 41 to 46, further comprising an electronic control system for connecting to one or more of said plurality of sensors.
48. The system of claim 47, further comprising an electronic connection switching component for independently switching connections between said plurality of sensors and said electronic control system.
49. The system of claim 47, further comprising a signal processing component for altering the signal strength and clarity.
50. The system of any one of claims 41 to 49, further comprising a sensor device for sensing heart rhythm disorders.
51. The method of claim 1, further comprising selecting one or more of said causes as indicating a primary cause of said heart rhythm disorder for enabling the treatment of said primary cause of said heart rhythm disorder.
52. The method of claim 51, wherein the activation trail comprises a rotational pattern or a radially emanating pattern.
53. The method of claim 51 or 52, further comprising a module for enabling treatment of said one or more causes of said heart rhythm disorder.
54. A method of detecting signals associated with one or more causes of a biological rhythm disorder, the method comprising:
sensing biological activation signals at multiple locations using a plurality of sensors;
collecting from said plurality of sensors, data comprising a sensor location of each sensor and an activation onset time of each biological activation signal at each sensor location such that a plurality of activation onset times at a plurality of sensor locations is collected;
arranging a sequence of the plurality of activation onset times at the plurality of sensor locations to create an activation trail; and determining at least one approximate core region in relationship to the activation trail indicative of the one or more causes of said biological rhythm disorder.
55. A system of detecting signals associated with one or more causes of a biological rhythm disorder, the system comprising:
a plurality of sensors at multiple locations to sense biological activation signals;
collect from the plurality of sensors, data comprising a sensor location of each sensor and an activation onset time of each biological activation signal at each sensor location such that a plurality of activation onset times at a plurality of sensor locations is collected;
arrange a sequence of the plurality of activation onset times at the plurality of sensor locations to create an activation trail; and determine at least one approximate core region in relationship to the activation trail indicative of the one or more causes of said biological rhythm disorder.
56. The method of claim 54, further comprising selecting one or more of said causes as indicating a primary cause of said biological rhythm disorder for enabling treatment of said primary cause of said biological rhythm disorder.
CA2739838A 2008-10-09 2009-10-09 Methods, system and apparatus for the detection, diagnosis and treatment of biological rhythm disorders Active CA2739838C (en)
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CA2942986A CA2942986A1 (en) 2008-10-09 2009-10-09 Methods, system and apparatus for the detection, diagnosis and treatment of biological rhythm disorders
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JP2005506097A (en) 2005-03-03 System for processing electrocardiogram signal with a superimposed composite
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