Source: https://patents.justia.com/patent/10434319
Timestamp: 2019-11-22 18:07:27
Document Index: 455102988

Matched Legal Cases: ['Application No. 62', 'Application No. 61', 'art.\n3', 'art.\n4', 'art.\n12', 'art.\n13', 'art.\n21', 'art.\n22']

US Patent for System and method of identifying sources associated with biological rhythm disorders Patent (Patent # 10,434,319 issued October 8, 2019) - Justia Patents Search
Justia Patents HeartUS Patent for System and method of identifying sources associated with biological rhythm disorders Patent (Patent # 10,434,319)
May 2, 2017 - The Regents of the University of California
An example system and method associated with identifying and treating a source of a heart rhythm disorder are disclosed. In accordance therewith, a spatial element associated with a region of the heart is selected. Progressive rotational activations or progressive focal activations are determined in relation to the selected spatial element over a period of time. The selecting and determining are repeated over multiple periods of time. A source parameter of rotation activations or focal activations is determined, wherein the source parameter indicates consistency of successive rotational activations or focal activations in relation to a portion of the region of the heart. The determining of a source parameter is repeated for multiple regions of the heart. Thereafter, representation of the source parameter is displayed for each of the multiple regions of the heart to identify a shape representing the source of the heart rhythm disorder.
This application claims the benefit of the priority of U.S. Provisional Application No. 62/330,734, filed May 2, 2016. This application is a continuation-in-part of U.S. application Ser. No. 14/473,990, filed Aug. 29, 2014, which claims the benefit of the priority of U.S. Provisional Application No. 61/973,626, filed Apr. 1, 2014, and which is a continuation-in-part of U.S. application Ser. No. 13/844,562, filed Mar. 15, 2013, issued as U.S. Pat. No. 9,332,915. Each of the foregoing applications is incorporated herein by reference in its entirety.
This application is related to and incorporates by reference the disclosures of each of U.S. application Ser. No. 12/576,809, filed Oct. 9, 2009, issued as U.S. Pat. No. 8,521,266; U.S. application Ser. No. 13/081,411, filed Apr. 6, 2011, issued as U.S. Pat. No. 8,700,140; U.S. application Ser. No. 13/462,534, filed May 2, 2012, issued as U.S. Pat. No. 8,594,777; U.S. application Ser. No. 13/470,705, filed May 14, 2012, issued as U.S. Pat. No. 9,392,948; and U.S. patent application Ser. No. 13/559,868, filed Jul. 27, 2012, issued as U.S. Pat. No. 9,408,536.
This invention was made with government support under Grants R01 HL83359 and HL103800 awarded by the National Institutes of Health. The government has certain rights in the invention.
Heart rhythm disorders are common and represent significant causes of morbidity and death throughout the world. Malfunction of the electrical system in the heart represents a proximate cause of heart rhythm disorders. Heart rhythm disorders exist in many forms, of which the most complex and difficult to treat are atrial fibrillation (AF), atrial tachycardias that interconvert and hence appear to fluctuate (TAT), multifocal atrial tachycardia (MAT), polymorphic ventricular tachycardia (VT) and ventricular fibrillation (VF). Other rhythm disorders are more simple and often easier 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). While under normal conditions the sinus node keeps the heart in sinus rhythm, under certain conditions rapid activation of the normal sinus node can cause inappropriate sinus tachycardia or sinus node reentry, both of which also represent heart rhythm disorders.
The present application is applicable to identifying sources of various rhythm disorders and directly using this information to treat the rhythm disorders. It is also applicable to normal and disordered heart rhythms, as well as other biological rhythms and rhythm disorders, such as neurological seizures, esophageal spasms, bladder instability, irritable bowel syndrome, and other biological disorders for which biological signals can be recorded to permit determination, diagnosis, and/or treatment of the cause (or source) of the disorders. This application does not rely on activation mapping or examining regions of the biological organ (e.g., heart) that exhibit similar voltages (isopotential mapping) at sensor locations. It is thus particularly useful in complex rhythm disorders that exhibit complex activation patterns and complex varying signals, and is able to identify the source(s) of the complex rhythm disorders even if the sources are influenced and appear to be modified by such complex signals. It is especially useful in identifying the cause(s) of the disorders of the heart rhythm such that they can be treated with expediency.
Locating and identifying the source(s) of rhythm disorders enhances the ability to guide, select, and apply curative therapy, such as ablation. Determining the size and shape of a source(s) of a rhythm disorder enables therapy to be tailored to the particular source(s) to minimize damage to healthy tissue. In particular, the present invention provides a method to identify and locate electrical rotors, focal beats, and other heart rhythm disorders, and further to identify the size and shape of a region of tissue in which they migrate, which has never previously been determined. This property of migration is quite separate and distinct from a point source or a reentrant circuit that does not migrate, and defines a feature of complex rhythm disorders such as fibrillation of the atrium (AF) or the ventricle (VF), or other complex biological rhythm disorders. Once the shape is determined, treatment may be applied to at least a portion of the region and/or proximately to the region in certain cases to ameliorate and potentially eliminate the disorder with minimal collateral damage, desirably using minimally invasive techniques as further described herein.
Precession of the source can obscure detection of a rotational circuit on fixed electrodes, since, for instance, the rotational activation around the core to the left (for instance at 06:00 clock face position during clockwise rotation) will be obscured if the core moves to the right, and similarly for other movements of the rotor core relative to fixed electrode over time (e.g., FIG. 15). The present invention detects such rotational activation. It also enables detection of rotational activation along a perimeter that is not clearly circular and may be ellipsoid or have another shape depending on the refractoriness and conduction properties of surrounding tissue. Such non-circular perimeters will also confuse traditional recording approaches, but can be detected by the present invention. Finally, this invention is able to detect rotational activation even if the sequence is interrupted along sectors (portions) of its perimeter (circumference′) by disorganized waves as described herein.
An important problem with diagnosis and treatment of complex heart rhythm disorders is that even when sources are identified, often multiple sources are present and difficult to identify concurrently. This can give the erroneous impression that fewer sources are present, or that sources “migrate” even though they are stable within a limited region (“precession locus”). Stable sources can be difficult to identify in this situation for many reasons. When multiple sources are present, a first source can be difficult to identify due to colliding and conflicting electrical waves from one or more additional sources. This may be because waves from a second or additional source may encroach upon the ‘organized domain’ of the first source, reducing its apparent size of ‘control’ (FIG. 3, upper right of panel). In this case, even though the first source continues to be present, it may be small or even below the detection resolution of the recording apparatus. Another issue with multiple sources is that electrical signals from the second or further sources may algebraically add to or cancel those from the first source. Nevertheless, multiple sources within a locus or spatial region over time can still be identified, either concurrently or in staggered periods of time alternating with the identification of other sources (FIG. 33). Additionally, if trying to observe one or multiple sources in real-time with continuous information, the data presented is so large that it becomes impossible for a human to visually track and interpret such information to identify all sources noted over time.
Additionally, disorganized activation can have numerous effects on the source. First, disorganized activation can arise if activation from the source undergoes disorganization away from its center or core (e.g., FIG. 16, left display). In this case, disorganized activation can surround the source but not perturb it, in which case, the central functionality of the source is largely unperturbed. If the source is associated with a complex rhythm disorder, such disorganization is often termed “fibrillatory conduction” from the rotor or focal source. The present invention provides the ability to quantify fibrillatory conduction and to define its functional effect, neither of which was previously characterized. Disorganization (or fibrillatory conduction) can be due to functional properties such as abnormalities in repolarization, abnormalities in conduction, abnormalities in tissue capacitance, or abnormalities in impulse generation. This disorganization can also be due to the electrical impact of structural factors, such as heterogeneous cellular types (including fibrosis, scar, gene therapy or stem cell therapy), geometrical curvature of the organ (e.g., heart), or mechanical motion including stretch, piezoelectric effects and other manifestations of mechano-electrical feedback. This disorganization can also be due to abnormalities in nervous system function or innervation, such as the autonomic nervous system, resulting in abnormal spatially varying electrical properties in the tissue of the organ (e.g., heart).
Treatment of all sources should eliminate the arrhythmia in the long-term, although the arrhythmia may continue transiently via disorganized activity (“fibrillatory conduction”). This transient fibrillatory conduction may be disorganized when measured by several metrics, and last from seconds to days. In the latter case, treatment may appear to result in “no apparent change” during the treatment procedure yet yield long-term treatment success (freedom from the arrhythmia). Cases have been observed when the arrhythmia (e.g., atrial fibrillation) terminates days or even weeks after treatment directed to sources by this approach and is then absent on follow-up for years.
This invention describes a system and method of determining whether rotational activation or focal activation is present during a heart rhythm disorder (e.g., complex heart rhythm disorder) within the context of electrical disturbances or noise mentioned above, and using this information to treat the human heart rhythm disorder in patients. In one embodiment, an index of progressive angular deviation (PAD) is determined, which indicates whether activation is rotational on one or more beats even if interruptions disrupt portions of the activation within any beat. Angles are assigned to progressively activating sites. If these sites demonstrate PAD, even if interrupted for a portion of the circumference due to physiology such as “fibrillatory conduction,” rotational activity is assigned. The same approach can be used to identify a focal source as zero sum rotation in all directions (i.e. centrifugal activation) from a region of tissue. These regions (or sites) can be targeted for treatment (such as ablation) as described below.
In yet another embodiment, this invention uses vectorial approaches to demonstrate rotational or centrifugal (focal) activation in simple or complex rhythm disorders. A vector is constructed that indicates the direction of activation between electrode sites in a pair and the speed of conduction between them, based upon differences in activation time and the relative distance. This is repeated for successive electrode pairs, then during and between successive heart beats (e.g., over time). Vectors that trace a circle are ‘simple’ reentry. If conduction slows for a portion, that arc of the circumference is shortened, making the vector loop more elliptical. This site of arc shortening (due to slow conduction) may be a prime target for therapy, such as ablation, drug therapy, pacing and so on.
In the various embodiments, analyses of rotational or centrifugal (focal) activation are performed within a defined spatial region that encompasses an area of precession (limited meander or ‘wobble’) of a rotor or focal source of a rhythm disorder. In simple rhythm disorders, this precession area is very small (effectively zero, but actually non-zero due to slight stochastic changes in functional property of tissue over time). In complex rhythm disorders such as atrial fibrillation, the precession area of a source is on average 2-3 cm2(<10 cm2) of tissue surface.
In accordance with an embodiment, an aggregate, summated, or average representation is provided to combine the identified regions where each source has been identified over time. This preferred embodiment of the representation is dynamically updated as more data is processed to identify regions where a source is present. Such a representation may include an image, a series of images, or a composite movie of the images in continuous or ‘time-lapse’ form. Each image conveys the three-dimensional structure of the mapped biological (heart) chamber together with source identification. Source identification may take the form of relative numerical percentages, ratios, color coding, three dimensional ‘bar charts’ or ‘topological’ maps, or other relative information to provide a user with qualitative and/or quantitative information regarding how frequently a source is identified in a particular region of the representation of the heart.
These aggregate, summated or average quantities may be simple summations, or may be weighted based on criteria such as the number of rotations of the source, the size of the chamber influenced (‘controlled’) by the source, wavefront propagation from/to the source, stability of wavefronts associated with the source, centrifugal patterns such as those that may be associated with focal sources, or other factors. Information may also be provided to convey how likely a region is to harbor a source. In this way, less ‘strong’ or less ‘convincing’ sources, such as those that are continuously interrupted in their course by interaction with additional sources, may be represented differently from definitive source regions. Other embodiments of the aggregate, summated, or average representation may include video images with source regions and/or characteristics associated with sources, numerical displays, icons, or other representative symbols to identify the spatial region displayed either on an isolated display, a three dimensional abstract representation, a three dimensional representation of the cardiac tissue, polar representations, or other geometric or cartographic representations that correlate to the cardiac tissue. These images are thus n-dimensional, providing three (3) structural dimensions, and at least one (1) dimension for the index at each structural location.
In accordance with another embodiment, a method associated with identifying and treating a source of a heart rhythm disorder is disclosed. In accordance with the method, a spatial element associated with a region of the heart is selected. Progressive rotational activations or progressive focal activations are determined in relation to the selected spatial element over a period of time. The selecting and determining are repeated over multiple periods of time. An index of rotational activations or focal activations is determined, wherein the index indicates consistency of successive rotational activations or focal activations in relation to a portion of the region of the heart. The determining of an index is repeated for multiple regions of the heart. A representation of the index is displayed for each of the multiple regions of the heart to identify a shape representing the source of the heart rhythm disorder.
In accordance with a further embodiment, a system associated with identifying and treating a source of a heart rhythm disorder is disclosed. The system includes a processor and a memory storing instructions that, when executed by the processor, cause the processor to perform the following operations. The operations include selecting a spatial element associated with a region of the heart, and determining progressive rotational activations or progressive focal activations in relation to the selected spatial element over a period of time. The operations also include repeating the selecting and determining over multiple periods of time, and determining an index of rotational activations or focal activations, wherein the index indicates consistency of successive rotational activations or focal activations in relation to a portion of the region of the heart. The operations further include repeating the determining of an index for multiple regions of the heart. Furthermore, the operations include displaying a representation of the index for each of the multiple regions of the heart to identify a shape representing the source of the heart rhythm disorder.
In accordance with yet another embodiment, there is disclosed a storage medium storing instructions that, when executed by the processor, cause the processor to perform operations associated with identifying and treating a source of a heart rhythm disorder. The operations include selecting a spatial element associated with a region of the heart, and determining progressive rotational activations or progressive focal activations in relation to the selected spatial element over a period of time. The operations also include repeating the selecting and determining over multiple periods of time, and determining an index of rotation activations or focal activations, wherein the index indicates consistency of successive rotational activations or focal activations in relation to a portion of the region of the heart. The operations further include repeating the determining of an index for multiple regions of the heart. Furthermore, the operations include displaying a representation of the index for each of the multiple regions of the heart to identify a shape representing the source of the heart rhythm disorder.
In some embodiments or aspects, the index can be associated with a frequency of successive rotational activations in the region of the heart. The index can be associated with a frequency of progressive angular displacement in the region of the heart. Moreover, the index can be a regularity with which the rotational activations or focal activations are present. In this regard, the regularity may be one of periodicity, repetitiveness, and/or frequency of occurrence of rotational or focal activations.
In some embodiments or aspects, the representation can use an arithmetic mean of the index of the region over time. The representation can also use a geometric or other mean of the index of the region over time. Moreover, the representation can use a weighted average of the index of the region over time.
In accordance with still another embodiment, a method of identifying and treating a source of a heart rhythm disorder is disclosed. In accordance with the method, a spatial element associated with a region of the heart is selected. Progressive rotational activations or progressive focal activations are determined in relation to the selected spatial element over a period of time. The selecting and determining are repeated over multiple periods of time. An index of rotational activations or focal activations is determined, wherein the index indicates consistency of successive rotational activations or focal activations in relation to a portion of the region of the heart. The determining of an index is repeated for multiple regions of the heart. A representation of the index is displayed for each of the multiple regions of the heart to identify a shape representing the source of the heart rhythm disorder. Thereafter, a region of the heart associated with the shape is selectively modified in order to terminate or alter the heart rhythm disorder.
FIGS. 2-5 illustrate an example embodiment for the formation of progressive angular deviations (PADs) in relation to a spatial element;
FIGS. 6-7 illustrate a first correlation of PADs in an analysis time interval;
FIGS. 8-10 illustrate a correlation of PADs using a first time window in an analysis time interval;
FIGS. 11-12 illustrate a second correlation of PADs using a second time window in an analysis time interval;
FIG. 13 illustrates a method of determining and correlating progressive angular deviations (PADs) in connection to spatial elements;
FIG. 25 indicates correlated progressive angular deviations that show rotational activation although the rotor periphery (spiral arms) are interrupted and the rotor core precesses Similar results could be obtained using another metric of progressive rotation;
FIG. 26 indicates two concurrent rotors for which correlations of the progressive angular deviations show both rotors (of opposite chirality) despite each interfering with the other. Similar results could be obtained using another metric of progressive rotation;
FIG. 31 indicates polar analyses just outside the core of the rotor in FIG. 29, which shows polar metrics indicating partial rotational activity;
FIG. 32 indicates polar analyses of rotation (PAR) outside the core of the rotor in FIG. 29, which shows polar metrics indicating passive non-rotational activation; and
FIGS. 33A-33D show averaging/aggregating of concurrent sources, illustrated by isochronal representations of rotational activation sources at two different regions (“site 1” and “site 2”), surrounded by disorganized activation, over four different time segments in the same patient.
A system and method for identifying one or more sources of a biological rhythm disorder (e.g., heart rhythm disorders) are disclosed herein. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of example embodiments. It will be evident, however, to one skilled in the art, that an example embodiment may be practiced without all of the disclosed specific details.
The analysis database 118 is configured to support or aid in the analysis of the signals by the computing device 116. In some embodiments, the analysis database 118 can store the APM video 150, as will be described in greater detail herein. The analysis database 118 can also provide storage of intermediate data (e.g. PAD pairs of spatial elements) associated with the determining one or more areas associated with a heart rhythm disorder.
FIG. 2 illustrates an example frame representation 200 of the APM video 150 (e.g., a monophasic action potential (MAP) as described in U.S. Pat. No. 8,165,666) received, accessed, or generated by the computing device 116. The APM video 150 identifies activation information for a selected analysis time interval or period of time (e.g., 4000 msec) associated with a heart rhythm disorder. For illustrative purposes, the frame representation 200 illustrates activation information occurring at a first time point (e.g., 10 msec) of the analysis time interval.
A spatial element 202 associated with a sensor (e.g., indicated in red) is selected for processing in the APM video 150. It should be noted that one or more of a plurality of spatial elements (e.g., spatial elements 120 from FIG. 1) can be processed sequentially or in parallel in accordance with the methodology described herein in connection with spatial element 202.
A circle 204 (e.g., indicated in green) having a radius (e.g., two (2) sensor distance) extending from the selected spatial element 202 is determined. The radius is given as an example, and a larger or a smaller radius can be selected. Thereafter, a set including a plurality of sensors 104 on or within the circle 204 is then determined for processing in connection with spatial element 202. It should be noted that a differently dimensioned and/or sized shape can be used (e.g., square, diamond, etc.) to determine the set.
The first time point (10 msec) indicates a first activation onset time of any sensor in the determined set of sensors during the analysis time interval (e.g., 4000 msec). For example, the activation onset time at 10 msec is associated with a sensor 206. The black line 201 indicates 0 . . . 2 pi about the circle 204 in a counterclockwise direction. An angle 208 is determined from the selected spatial element 202 to the associated sensor 206. Thereafter, a pair which includes the angle and the activation time is generated (e.g., Pair 1=(pi/2, 10) for the first activation onset time. It should be noted that one or more additional pairs can be generated for any another sensors in the set that have associated activation onset time at 10 msec.
The second time point (36 msec) indicates a second activation onset time of any sensor in the determined set of sensors during the analysis time interval (e.g., 4000 msec). For example, the activation onset time at 36 msec is associated with a sensor 212. An angle 214 is determined from the selected spatial element 202 to the associated sensor 212. Thereafter, a pair which includes the angle and the activation time is generated (e.g., Pair 2=(pi/2, 36) for the second activation onset time. It should be noted that one or more additional pairs can be generated for any another sensors in the set that have associated activation onset times at 36 msec.
The third time point (62 msec) indicates a third activation onset time of any sensor in the determined set of sensors during the analysis time interval (e.g., 4000 msec). For example, the activation onset time at 62 msec is associated with a sensor 218. An angle 220 is determined from the selected spatial element 202 to the associated sensor 218. Thereafter, a pair which includes the angle and the activation time is generated (e.g., Pair 3=(pi, 62) for the third activation onset time. It should be noted that one or more additional pairs can be generated for any another sensors in the set that have associated activation onset time at 62 msec.
The fourth time point (77 msec) indicates a third activation onset time of any sensor in the determined set of sensors during the analysis time interval (e.g., 4000 msec). For example, the activation onset time at 77 msec is associated with a sensor 224. An angle 224 is determined from the selected spatial element 202 to the associated sensor 224. Thereafter, a pair which includes the angle and the activation time is generated (e.g., Pair 4=(5 pi/4, 77) for the fourth activation onset time. It should be noted that one or more additional pairs can be generated for any another sensors in the set that have associated activation onset time at 77 msec.
For illustrative purposes, FIGS. 2-5 detail four (4) example frame representations of activation onset times associated with sensors in the determined set of sensors occurring during the analysis time interval (e.g., 4000 msec). However, it should be noted that there could be significantly more activation onset times associated with sensors in the determined set during the analysis time interval (e.g., 4000 msec).
FIG. 6 illustrates a graphical representation 600 of the generated pairs 605. The graphical representation 600 illustrates the generated pairs 605 plotted on a time-angle graph, i.e., angle 602, time 604. As an example, pair 1 (pi/2, 10) of frame representation 200 is plotted as pair 606 and pair 4 (5 pi/4, 77) of frame representation 222 is plotted as pair 612. It should be noted that the graphical representation 600 illustrates a plurality of generated pairs 605, such as pairs 606-620, which are shown for illustrative purposes.
At operation 1316, an angle is calculated from the selected spatial element to the sensor associated with the activation onset time. Thereafter, at operation 1318, a pair of values referred to as “pair”) is generated. The generated pair includes the angle and the activation onset time. At operation 1320, a determination is made as to whether there any more sensors associated with the selected activation onset time. If so, the method 1300 iterates over operations 1314-1320 to generate additional pairs (e.g., pair=[angle, activation onset time]) for those sensors. If not, the method 1300 continues at operation 1322.
At operation 1328, an index is defined and set to the first pair (e.g., index pair) in the analysis time interval (e.g., 4000 msec). At operation 1330, a first window of the first window size is determined as starting from the activation onset time of the index pair. Thereafter, a subset of all pairs that is within the first window is determined at operation 1332. At operation 1334, a best-fit line is calculated in reference to the subset of pairs in the first window. The slope of the best-fit line, location of the best-fit line, and fit of the pairs to the best-fit line are determined.
If there is progressive angular deviation in connection with a potential site, then at operation 2310, a determination is made as to whether other criteria are met, such as consistency in the progressive angular deviations and whether a plausible cycle length is possible in connection with consistent progressive angular deviations. If so, at operation 2212 a potential rotor can be indicated by such consistency and plausible cycle length. At operation 2214, the progressive angular deviations can be characterized by line slope, non-linearity (slow conduction), regionality, rate and periodicity.
If there is progressive angular deviation in connection with a potential site, then at operation 2310, a determination is made as to whether other criteria are met, such as consistency in the progressive angular deviations and whether a plausible cycle length is possible in connection with consistent progressive angular deviations. If so, at operation 2312 a potential focal source can be indicated by such consistency and plausible cycle length. At operation 2314, the progressive angular deviations can be characterized by line slope, non-linearity (slow conduction), regionality, rate and periodicity.
FIG. 25 is a pictorial representation of successive rotations of a rotor within a complex rhythm (e.g., atrial fibrillation) in a patient. The rotor is stable but interrupted by activation from outside the rotor, which may indicate fibrillatory conduction or another source. The rotor also precesses (wobbles′) showing slight spatial movement but within a stable spatial area. The progressive angular deviation plots show straight lines of theta against time, but with some biological noise reflecting these interruptions.
FIG. 26 is a pictorial representation of successive rotations of 2 concurrent rotors in a patient with atrial fibrillation. As illustrated, both rotors are stable with some interruptions by the fibrillatory milieu. Rotor 1 is interrupted more than rotor 2. Both rotors also show slight precession (wobble′). Accordingly, progressive angular deviation plots show straight lines of theta against time, but with some biological noise reflecting these interruptions.
FIG. 27 is a flowchart for analyzing a polar analysis of rotations (PAR) for a rotational activation trail using polar analyses. Each operation provides a polar index of rotation, which are combined (or weighted) to determine a rotor. Operation 1 determines activation delay for all adjacent sites for an entire tracing (at least a majority of one complete cycle). In general, conduction time within human atria is 40-200 cm/second, such that activation time delay between electrodes spaced 0.6 cm apart is 3-15 milliseconds (typically 5-10 msec), scaled appropriately for different spacing between electrodes. Conversely, if a rotor is present then activation at adjacent electrodes could be separated by an entire cycle length if they lie at the head versus tail, i.e., activation has to complete a rotation to reach the tail (up to ˜200 msec). Operation 2 determines the angular displacement for successively activated sites within the atria. If successively activated sites mostly show the angular deviation expected from a rotation, i.e., 2 pi/8 (for 8 surrounding electrodes), then the central electrode is consistent with the core of rotor. Operation 3 examines and determines systematically for all sites in the chamber, if successive surrounding electrodes (in a clock face type of orientation) trace successive angular deviations over time. If so, this is consistent with rotational activation. Operation 4 determines the number of activations at each surrounding electrode per cycle. If this is less than one (1), then dropout (or block into that site) may exist. If this is more than one (1), then double counting or disorganization (fibrillatory conduction) may exist.
FIG. 28 is a flowchart of an example method of analyzing a polar analysis of rotations (PAR) for a focal (centrifugal) activation trail. Each operation provides a focal index of rotation, combined (or weighted) equally or non-uniformly to determine a focal source. Operation 1 determines activation delay for all adjacent sites for an entire tracing (at least one complete cycle). In general, conduction time within human atria is 40-200 cm/second, such that activation time delay between electrodes spaced 0.6 cm apart is 3-15 msec (typically 5-10 msec), scaled appropriately for different spacing between electrodes. For a focal source, there will be simultaneous activation of electrodes on concentric circles, unless/until the source disorganizes (fibrillatory conduction). Operation 2 determines angular displacement for successively activated sites within the atria. If successively activated sites mostly show patterns expected from a focal source, then the central electrode is consistent with a focal origin. Operation 3 examines and determines systematically for all sites in the chamber, if successively activated electrodes (in a clock face type of orientation) trace zero angular deviations along each radius from the origin, i.e., centrifugal. Operation 4 determines the number of activations at each surrounding electrode per cycle. If this is less than one (1), then dropout may exist (or block into that site). If this is more than one (1), then double counting or disorganization (fibrillatory conduction) may exist.
FIG. 30 illustrates detection of the rotor core by polar analysis of rotations (PAR). The inset (right) shows a clear polar spiral line indicating an uninterrupted rotor at the central point (labeled H5 in the spatial plot in FIG. 29). The top graph indicates cumulative angular deviation in number of rotational spins around this central site (vertical axis, 20) for 160 activations at 8 surrounding electrodes (i.e., 20 spins). The top left angular displacement histogram indicates that each angular position around the central core (i.e., all surrounding 8 electrodes) are activated 20 times each (vertical scale), i.e., equally per each location. The electrode with 19 activations indicates possible signal drop out. The middle left time delay histogram shows that many adjacent sites in the entire field activate with delays of 25 msec, 35 msec or 45 msec, far longer than supported by passive conduction. The bottom left angular position histogram shows that all sites (i.e., 160 activations, for 20 activations at 8 sites activated successively in time) are separated by an angular deviation of 2 pi/8, i.e., pi/4 radians—the angular deviation between two (2) adjacent electrodes.
FIG. 31 illustrates polar analyses of rotation (PAR) for a site just outside the rotor (GH56). Is should be noted that the raw polar plot shows additional lines that deviate from a spiral, indicating subsidiary (fibrillatory) activation. The top central graph shows complete rotations (vertical scale) over 240 activations at 12 surrounding electrodes (i.e., 20 spins). The top left angular displacement histogram shows that most electrodes (vertical scale) are activated per cycle. The middle left time delay histogram shows the beginning of a bimodal distribution—in that a dominant number of electrodes activate rapidly (i.e., within 5-10 msec), indicating possible passive activation, with some still activating late as expected of rotational activity. The bottom left angular position histogram shows that many sites (vertical scale) activated successively in time are often separated by pi/4, but often by pi/2 radians (i.e., further away—not rotational).
FIG. 32 illustrates polar analysis of rotation (PAR) for a site distant from the rotor (EF23). That raw polar plot shows nearly chaotic activity that does not trace a spiral, which indicates non-rotational activation. The top central graph shows that the cumulative rotational counter does not rise progressively, and actually reverses periodically (falls below zero, i.e., anti-phase). The top left angular displacement histogram shows that many electrodes (vertical scale) are not activated at all, likely indicating signal dropout or regions of block. This metric thus enables one to identify sites—where the organized rotor domain ends and fibrillatory conduction starts. The middle left time delay histogram shows that nearly all electrodes activate rapidly (i.e., within 5-15 msec) indicating passive conduction and inconsistent head-meets-tail rotation. The bottom left angular position histogram shows that sites activated successively in time (vertical scale) are often widely separated in space (i.e., pi/4, pi/2 and even pi radians—i.e., up to 180 degrees separated). This indicates very little or no sequential organization—not rotational.
FIGS. 33A-33D illustrate examples of averaging/aggregating of concurrent sources using isochronal representations of rotational activation sources at two different regions (“site 1” (3300)” and “site 2” (3302)), surrounded by disorganized activation over four different time segments in the same patient. Precession of a first counterclockwise rotational activation source is noted at site 1 (3300) (with “wobble”) in FIGS. 33A, 33B, and 33D. Similarly, precession of a second counterclockwise rotational source is noted at site 2 (3302) (with “wobble”) in FIGS. 33B and 33C. As these maps have slightly different the appearances during different time segments, it would be warranted to develop a visual representation that can combine the information from each of these time segments, potentially using an index, in order to determine the shape of the region of precession of each source. This will aid in the diagnosis and potential treatment of the source of the heart rhythm disorder.
In operation as described in FIGS. 1-33, the identification of source(s) of heart rhythm disorders as described herein can be used to identify patients in whom therapy can be effective and to assist in guiding such therapy, which can include delivery of one or more of ablation, electrical energy, mechanical energy, drugs, cells, genes and biological agents to at least a portion of the identified source(s) of the heart.
As illustrated in FIG. 14, the computer system 1400 may include a processor 1402, e.g., a central processing unit (CPU), a graphics-processing unit (GPU), or both. Moreover, the computer system 1400 may include a main memory 1404 and a static memory 1406 that can communicate with each other via a bus 1426. As shown, the computer system 1400 may further include a video display unit 1410, such as a liquid crystal display (LCD), an organic light emitting diode (OLED), a flat panel display, a solid-state display, or a cathode ray tube (CRT). Additionally, the computer system 1400 may include an input device 1412, such as a keyboard, and a cursor control device 1414, such as a mouse. The computer system 1400 can also include a disk drive unit 1416, a signal generation device 1422, such as a speaker or remote control, and a network interface device 1408.
In a particular non-limiting, example embodiment, the computer-readable medium can include a solid-state memory, such as a memory card or other package, which houses one or more non-volatile read-only memories. Further, the computer-readable medium can be a random-access memory or other volatile re-writable memory. Additionally, the computer-readable medium can include a magneto-optical or optical medium, such as a disk or tapes or other storage device to capture carrier wave signals, such as a signal communicated over a transmission medium. A digital file attachment to an e-mail or other self-contained information archive or set of archives may be considered a distribution medium that is equivalent to a tangible storage medium. Accordingly, any one or more of a computer-readable medium or a distribution medium and other equivalents and successor media, in which data or instructions may be stored, are included herein.
It should also be noted that software that implements the disclosed methods may optionally be stored on a tangible storage medium, such as: a magnetic medium, such as a disk or tape; a magneto-optical or optical medium, such as a disk; or a solid-state medium, such as a memory card or other package that houses one or more read-only (non-volatile) memories, random access memories, or other re-writable (volatile) memories. The software may also utilize a signal containing computer instructions. A digital file attachment to e-mail or other self-contained information archive or set of archives is considered a distribution medium equivalent to a tangible storage medium. Accordingly, a tangible storage medium or distribution medium as listed herein, and other equivalents and successor media, in which the software implementations herein may be stored, are included herein.
In the foregoing description of the embodiments, various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting that the claimed embodiments have more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Description of the Embodiments, with each claim standing on its own as a separate example embodiment.
1. A method associated with identifying a source of a heart rhythm disorder, the method comprising a computing device:
selecting a spatial element associated with a region of the heart;
determining progressive rotational activations or progressive focal activations in relation to the selected spatial element over a period of time;
repeating the selecting and determining over multiple periods of time;
determining an index of rotational activations or focal activations, wherein the index indicates consistency of successive rotational activations or focal activations in relation to a portion of the region of the heart;
repeating the determining of an index for multiple regions of the heart; and
displaying a representation of the index for each of the multiple regions of the heart to identify a shape representing the source of the heart rhythm disorder.
2. The method of claim 1, wherein the index is associated with a frequency of successive rotational activations in the region of the heart.
3. The method of claim 1, wherein the index is associated with a frequency of progressive angular displacement in the region of the heart.
4. The method of claim 1, wherein the index is a regularity with which the rotational activations or focal activations are present.
5. The method of claim 4, wherein the regularity is one of periodicity, repetitiveness, and/or frequency of occurrence of rotational or focal activations.
6. The method of claim 1, wherein displaying the representation of the index comprises displaying a representation of an arithmetic mean of the index of the region over time.
7. The method of claim 1, wherein displaying the representation of the index comprises displaying a representation of a geometric mean of the index of the region over time.
8. The method of claim 1, wherein displaying the representation of the index comprises displaying a representation of a weighted average of the index of the region over time.
9. The method of claim 1, further comprising displaying the representation of the index on at least one of an isolated display, a three-dimensional abstract representation, a three-dimensional representation of the cardiac tissue or a polar representation.
10. A system associated with identifying a source of a heart rhythm disorder, the system comprising:
a memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising: selecting a spatial element associated with a region of the heart; determining progressive rotational activations or progressive focal activations in relation to the selected spatial element over a period of time; repeating the selecting and determining over multiple periods of time; determining an index of rotational activations or focal activations, wherein the index indicates consistency of successive rotational activations or focal activations in relation to a portion of the region of the heart; repeating the determining of an index for multiple regions of the heart; and displaying a representation of the index for each of the multiple regions of the heart to identify a shape representing the source of the heart rhythm disorder.
11. The system of claim 10, wherein the index is associated with a frequency of successive rotational activations in the region of the heart.
12. The system of claim 10, wherein the index is associated with a frequency of progressive angular displacement in the region of the heart.
13. The system of claim 10, wherein the index is a regularity with which the rotational activations or focal activations are present.
14. The system of claim 13, wherein the regularity is one of periodicity, repetitiveness, and/or frequency of occurrence of rotational or focal activations.
15. The system of claim 10, wherein displaying the representation of the index comprises displaying a representation of an arithmetic mean of the index of the region over time.
16. The system of claim 10, wherein displaying the representation of the index comprises displaying a representation of a geometric mean of the index of the region over time.
17. The system of claim 10, wherein displaying the representation of the index comprises displaying a representation of a weighted average of the index of the region over time.
18. The system of claim 10, wherein the representation of the index is displayed on at least one of an isolated display, a three-dimensional abstract representation, a three-dimensional representation of the cardiac tissue or a polar representation.
19. A non-transitory storage medium storing instructions that, when executed by a processor, cause the processor to perform operations associated with identifying a source of a heart rhythm disorder, the operations comprising:
20. The storage medium of claim 19, wherein the index is associated with a frequency of successive rotational activations in the region of the heart.
21. The storage medium of claim 19, wherein the index is associated with a frequency of progressive angular displacement in the region of the heart.
22. The storage medium of claim 19, wherein the index is a regularity with which the rotational activations or focal activations are present.
23. The storage medium of claim 22, wherein the regularity is one of periodicity, repetitiveness, and/or frequency of occurrence of rotational or focal activations.
24. The storage medium of claim 19, wherein displaying the representation of the index comprises displaying a representation of an arithmetic mean of the index of the region over time.
25. The storage medium of claim 19, wherein displaying the representation of the index comprises displaying a representation of a geometric mean of the index of the region over time.
26. The storage medium of claim 19, wherein displaying the representation of the index comprises displaying a representation of a weighted average of the index of the region over time.
27. The storage medium of claim 19, wherein the representation of the index is displayed on at least one of an isolated display, a three-dimensional abstract representation, a three-dimensional representation of the cardiac tissue or a polar representation.
28. A method of identifying and treating a source of a heart rhythm disorder, the method comprising a computing device:
repeating the determining of an index for multiple regions of the heart;
displaying a representation of the index for each of the multiple regions of the heart to identify a shape representing the source of the heart rhythm disorder; and
selectively modifying a region of the heart associated with the shape in order to terminate or alter the heart rhythm disorder.
5836889 November 17, 1998 Wyborny et al.
6553251 April 22, 2003 Ländesmäki
7457664 November 25, 2008 Zhang et al.
8165666 April 24, 2012 Briggs et al.
8594777 November 26, 2013 Briggs et al.
9055876 June 16, 2015 Narayan et al.
9107600 August 18, 2015 Narayan et al.
9398860 July 26, 2016 Macneil et al.
9398883 July 26, 2016 Narayan et al.
20130006131 January 3, 2013 Narayan
20160360983 December 15, 2016 Narayan et al.
20170007176 January 12, 2017 Narayan et al.
1768342 May 2006 CN
0284685 October 1988 EP
2269691 January 2011 EP
1808124 April 2011 EP
1996025096 August 1996 WO
1996032885 October 1996 WO
1996032897 October 1996 WO
1996039929 December 1996 WO
1997024983 July 1997 WO
2000045700 August 2000 WO
2003011112 February 2003 WO
2006052838 May 2006 WO
2006066324 June 2006 WO
2007078421 July 2007 WO
2007106829 September 2007 WO
2007137077 November 2007 WO
2007146864 December 2007 WO
Eckman, et al. “Recurrence plots of dynamical systems,” Europhys. Left., 4 (3), Nov. 1, 1987 pp. 973-977.
EP09819953 Supplementary European Search Report & European Search Opinion dated Feb. 7, 2012, 12 pages.
EP12711553 Supplementary European Search Report & European Search Opinion , dated Sep. 11, 2013, 7 pages.
EP12779506.0 Supplementary European Search Report & European Search Opinion dated Nov. 18, 2014, 8 pages.
PCT/US2012/068639 International Preliminary Report on Patentability and Written Opinion, dated Jun. 10, 2013; 6 pages
Saksena, S., et al., “Regional Endocardial Mapping of Spontaneous and Induced Atrial Fibrillation in Patients With Heart Disease and Refractory Atrial Fibrillation”, Am J Cardiol, 1999; 84:880-889.
Sun, Yan, et al., “Characteristic wave detection in ECG signal using morphological transform”, BMC Cardiovascular Disorders, vol. 5, No. 28, 2005, 7 pages.
Yenn-Jiang L, et al. “Electrophysiological Mechanisms and Catheter Ablation of Complex Atrial Arrhythmias from Crista Terminalis: Insight from Three-Dimentional Noncontact Mapping,” Pacing and Clinical Electrophysiology, vol. 27, No. 9, Sep. 1, 2004, pp. 1231-1239.
Patent Publication Number: 20170232263
Inventors: Sanjiv M. Narayan (Palo Alto, CA), Carey Robert Briggs (La Jolla, CA), Ruchir Sehra (Scottsdale, AZ)
Application Number: 15/585,091
International Classification: A61B 5/024 (20060101); A61B 5/00 (20060101); A61B 5/042 (20060101); A61N 1/37 (20060101); A61N 1/362 (20060101); A61N 1/365 (20060101); A61N 1/378 (20060101); A61B 18/00 (20060101);