Computer program and system to assist in mapping abnormal heart rhythms

Abstract

This document describes computer programs and systems that assist in identifying cardiac regions that support or initiate abnormal heartbeats. It identifies the electrode activation sequence contributing to the repetitive excitation pattern. On the cardiac chamber surface, it identifies the earliest excitation site, the excitation vector from the identified electrode activation sequence, and the pathway tracing back from the earliest excitation site. It calculates statistical measurements for the repetitive excitation pattern and outputs data identifying the repetitive excitation pattern, including the pathway. This data allows for varying the emphasis on the repetitive excitation pattern based on the statistical measurements.

Description

Technical Field

[0001] [Cross - reference to Related Applications] This application claims the priority of UK Patent Application No. 2308431.2 filed on June 6, 2023, and the entire disclosure of the said application is incorporated herein by reference.

[0002] [Field of the Invention] The present invention relates to a computer - implemented method and system for assisting in mapping abnormalities of the heartbeat rhythm, and more particularly, to a method and system for identifying areas of the heart that are statistically likely to cause abnormal heartbeats.

Background Art

[0003] This application is a related application to the prior and co - pending applications WO 2019 / 206908 and WO 2021 / 084255, and the contents of both applications are incorporated herein by reference. These two applications describe a system and method for mapping a ranked signal's probabilistic trajectory analysis (STAR) as referred to below. Although STAR mapping may be used in the examples, other approaches are also possible as described below.

[0004] Atrial fibrillation (AF) is the most common persistent heart abnormality. Its incidence is increasing, partly due to the aging population, and it is considered a growing epidemic. AF leads to irregular contractions of the heart, causing unpleasant symptoms of palpitations and increasing the risk of stroke, heart failure (HF), and death. Percutaneous catheter ablation (CA) is a safe treatment option for patients with symptoms of AF. The success rate of such treatments is improving over time as our understanding of AF progresses, new techniques and technologies are developed, and physicians gain experience. However, the success rate of such treatments remains at only 50-70%. The main reason for the difficulty in targeting specific sites that cause residual and persistent AF (hereinafter referred to as AF drivers) is the irregular and disordered excitation waveform of atrial fibrillation. Rotational, reentrant, or localized excitations continue to swirl around, and unstable states are repeated, making it very complex to elucidate the sequence of excitations.

[0005] Similar challenges exist in mapping ventricular tachycardia (VT). VT is so frequent that even with automated systems, it is often impossible to perform extensive point-by-point mapping. Furthermore, the period can change, and multiple VT circuits may exist in a single patient, each contributing at different times. Interpreting point-by-point maps, or even maps obtained from high-tachycardia, is difficult, and in many cases, obtaining such maps is impossible unless the patient can maintain adequate blood pressure to enable comprehensive, stepwise mapping of points around the heart.

[0006] More recently, numerous computational and electroanatomical methods have been developed that allow electrical data (i.e., electrophoresis) recorded within the atria to be presented to physicians in a way that enables the recognition of specific "driver" areas. Such drivers may or may not be easy to recognize, depending on the relationship between the frequency of drivers and the frequency of excitation due to the random and disordered activity of non-drivers. Panoramic mapping technology attempts to address this problem. This technology involves inserting a multi-electrode catheter into the target ventricle and simultaneously acquiring signals from within the ventricle. Examples include non-contact mapping methods (Ensite (Abbott Medical or Acutus Medical)) and certain 2D and 3D contact mapping methods (e.g., CARTOFINDER (Biosense-Webster, Johnson & Johnson), Topera (Abbott Medical), Rhythmia (Boston Scientific)).

[0007] There is conflicting evidence as to whether the characteristics of electrograms are useful as surrogate markers for local drivers of persistent atrial fibrillation in humans. These are sometimes referred to as atrial fibrillation drivers (AFD). Since normal non-fibrillatory arrhythmias can sometimes occur from a single AFD, it can be seen that AFD can be understood to indicate atrial fibrillation / arrhythmia drivers. The reliability of the marker of frequency was low because the site that plays a mechanistic role in AF could be better identified by the mechanistic characteristics of the electrogram. Optical mapping studies in animals have shown that AF is maintained by sites showing the shortest cycle length (CL) and the highest dominant frequency (DF). However, in humans, it has been demonstrated that it is insufficient as a predictor of the site that supports AF. The lack of sufficient correlation is also thought to be due to the lack of spatio-temporal stability in the drivers of AF, which may also be the reason why the frequent sites do not appear to be consistent. In addition, optical mapping studies in animals have shown that there is a gradient from high to low frequency in the rotor sites within the atrium. The frequency gradient has also been demonstrated in humans with AF, but this is limited to the gradient between the atria.

[0008] <STAR mapping method> The STAR mapping method, as described in detail in the aforementioned patent application, was first demonstrated through in vitro and in vivo mapping of atrial tachycardia (AT) before its use in mapping AF. In essence, the principle of STAR mapping involves utilizing electrogeographic data obtained over a recording period from a series of corresponding detection points on the heart, recorded from multiple electrodes of a multi-electrode cardiac catheter. By comparing the timing of multiple electrogeographic data, each wavefront trajectory associated with AF is established. This is then used to identify regions in the atrium where excitation most frequently precedes adjacent areas. By collecting a large amount of excitation data, a statistical model can be created. This allows for ranking atrial regions according to the time by which excitation precedes adjacent areas. While the timing of unipolar excitation is typically considered as the maximum negative deviation (peak negative dv / dt), excitation timing can also be derived from other methods, such as dipole density, peak bipolar voltage, or total polarity resolution voltage. This mapping method utilizes a predetermined refractory period to avoid assigning excitations from different wavefronts or splitting potentials. Unreasonable electrode timing relationships resulting from suppressed propagation velocity are also excluded by the mapping method.

[0009] One form of STAR map display consists of color-coded electrode positions projected onto a replica of the patient's atrial shape created with a standard 3D mapping system. Each color represents the percentage of time spent with one electrode leading the other in an electrode pair, as highlighted by the color scale shown on the right side of the STAR map.

[0010] In one embodiment of the STAR mapping method, the dominant excitation vector in the area to be calculated is considered. That is, the excitation sequence is recorded for each excitation detected by moving a catheter electrode (e.g., HD Grid® (Abbott), Pentarray®, Octarray® (Biosense-Webster, Johnson & Johnson)). This excitation sequence allows for the calculation of the "optimal" vector of averaged excitations. If many distinct excitations are recorded in one place over a period of time, a large number of excitation vectors are calculated. These excitation vectors can be classified by features such as ratio, excitation sequence, leading electrode, electrographic pattern, excitation sequence recorded by the catheter electrode in a stable position, or excitation sequence recorded by referring to a surface electrocardiogram. If a certain electrode activation (excitation) sequence occurs repeatedly in a similar pattern, it can be called an excitation repeat pattern (RPA), that is, an RPA is an averaged vector of a series of excitations classified as similar due to one or more features. Each RPA is characterized by a vector, and features and statistical measurements may be derived from the order and raw data used to calculate the RPA, such as component vectors, ratios, and morphology.

[0011] <Problems with the current method> Mapping the atria using a basket, employing a mapping system that attempts to identify the proportion of time in which one electrode "leads" an adjacent electrode, can create an overall distribution that ranks potential AF drivers (AFDs). A similar process can be performed for other arrhythmias, such as ventricular tachycardia and atrial tachycardia. However, mapping techniques that use high-density multi-electrode catheters to continuously record data at many different locations near the ventricles provide no information about the relative importance of early sites among such recordings. For example, many sites might appear to all be leading at different acquisition times.

[0012] A further problem in analyzing data acquired with high-density multi-electrode catheters is the complexity of interpreting the previously identified preceding areas located at the edges of the acquisition area.

[0013] Identifying early site excitations, or potential driver sites, using such localized recordings is challenging, especially if those sites are incidentally located in areas not recorded or on the boundaries of multi-electrode catheters. Interpreting these numerous excitation vectors to improve the visualization of areas requiring further mapping or areas that are potential ESAs is difficult. A system that enables visual visualization of areas where cardiac mapping would be particularly effective should simplify and expedite cardiac mapping procedures.

[0014] There are particular advantages to using statistical methods for many excitations to identify the main excitation vectors from which the retrograde trajectory region can be calculated. Firstly, even in "normal" tachycardia, subtle differences in excitation vectors are often observed. These differences are more pronounced when ectopic beats occur outside the tachycardia circuit but do not interrupt the tachycardia. In this case, using these ectopic beats as the basis for the vector will exaggerate inappropriate retrograde trajectories because it is based on only one beat of the tachycardia. Such errors are further exacerbated by the relatively narrow reach of many multi-electrode mapping catheters, which can give physicians inaccurate information about the RPA direction. Secondly, in arrhythmias with changing periods, classifying vectors by period makes mapping extremely complex. Thirdly, in disordered arrhythmias such as atrial fibrillation, a summary of numerous vectors is required to provide useful information about the important vectors contributing to the excitation. [Overview of the project] [Means for solving the problem]

[0015] <Statement of Invention> According to one feature of the present invention, a computer program comprising computer program code means for, when the computer program is executed on a computer, to perform a method performed by the computer to identify one or more regions of the heart that are factors supporting or initiating an abnormal heartbeat, wherein the method performed by the computer utilizes electrographic data obtained over a recording period from a series of corresponding detection locations on the heart, recorded from multiple electrodes of a multi-electrode cardiac catheter, and the method To obtain data on the shape of the heart, which has recorded the aforementioned electromagnet data, From the electromagnet data, identify the sequence of electrode activations that contributes to the repetitive excitation pattern over the recording period, For each repetition pattern of excitation, i) Identify the earliest excitation site and excitation vector from the identified electrode activation sequence, ii) Identifying a pathway on the surface of the cardiac chambers, tracing back from the earliest excitation site, wherein the surface is identified from the data obtained regarding the shape of the heart, and the pathway is identified by a vector projected as a ray onto the surface of the cardiac chambers and guided by a vector opposite in direction to the excitation vector. iii) Calculating statistical measurements over the recording period for the aforementioned repetition pattern of excitation, iv) Outputting data that identifies the repetitive pattern of excitation including the pathway, wherein the data changes the degree of attention given to the repetitive pattern of excitation based on the statistical measurement value. A computer program including this is provided.

[0016] The computer program may further include a step of changing the degree of attention given to the aforementioned repetition pattern of excitation relative to other repetition patterns of excitation.

[0017] The computer program may include generating a visual representation of the surface of the cardiac chambers and a visual representation of repetitive excitation patterns that traverse the pathways and are displayed based on their level of attention.

[0018] The statistical measurement values may include the frequency of repetition over the period and / or the uniformity of excitation in the direction of excitation over the period, or other statistical measurement values.

[0019] The visual representation of the excitation repetition pattern may vary depending on one or more of the width of the path, the color of the path, the dimensions and / or type of the marker indicating the direction of excitation.

[0020] The computer program a) for at least a selected repetition pattern of excitation, for the points on the surface, the distance on the surface from the point to the earliest excitation point in the excitation repetition pattern, and the distance from the point to the nearest point on the path, and the angle between the earliest excitation point, the point, and the nearest point on the path and measure them; b) based on the two distances and the angle, determine a score for the point; c) vary the degree of attention of the point in the data output based on the score and may further include.

[0021] The degree of attention of the point may be varied with respect to a fixed scoring criterion.

[0022] The degree of attention of the point may be varied with respect to the scores of other points.

[0023] The computer program may further include performing the above a) - c) for all points on the surface.

[0024] When there are multiple excitation repetition patterns, the computer program may further include calculating a comprehensive score for each point. The comprehensive score is calculated based on the scores for each point for each excitation repetition pattern, and c) may be performed based on the comprehensive score.

[0025] The computer program may further include calculating an overall score, which may include calculating a normalized score.

[0026] Calculating the overall score may involve applying a penalty factor, thereby increasing the score depending on how many repetition patterns of excitation the point was involved in.

[0027] The above a) may further include modifying one or more of the angle and distance measurements according to a statistical measurement of the repeating pattern of excitation.

[0028] The above a) may further include accessing external data about the heart and modifying one or more of the angle and distance measurements or scores according to that external data.

[0029] External data may include voltage maps obtained early in the procedure, known ablation sites, anatomical data, or data on biological structure or physiological function obtained from mapping databases.

[0030] The computer program may further include highlighting points where the pathways of repeating excitation patterns intersect.

[0031] The data output may include data that identifies the earliest excitation site.

[0032] Embodiments of the present invention aim to apply an approach to locate the earliest site of excitation (ESA) or potential source along the surface of one or more cavities of a patient's heart by enabling retrospective trajectory tracking from one or more stable contact recordings.

[0033] The system imports a 3D geometric representation of the surface of one or more cardiac chambers of the patient and identifies the dominant excitation vectors on the cardiac chamber surface for repeated excitation patterns (RPAs) from the received electrophysiological data. An RPA can be defined as a vector originating from a preceding electrode position, following the aggregated excitation sequence of each atrial depolarization. Alternatively, other methods for calculating excitation vectors exist. The importance of each RPA is determined by its stability, ratio, or other characteristics; typically, higher frequency or more uniform RPAs are considered more important for maintaining AF. The level of importance can be represented by various visual characteristics of the RPA. For example, thickness and color correlate with the frequency of RPA repetitions. Thicker lines and darker colors indicate more frequent RPA repetitions. Arrow shape can also be used to indicate the direction of uniformity in the vector direction of each atrial depolarization. For example, smaller arrow sizes indicate lower vector direction uniformity.

[0034] In the WaveTrail method, a retrospective trajectory region is calculated for each RPA. This retrospective trajectory region includes areas of the cardiac chamber surface that likely resulted from the excitation pattern exhibited by the RPA, and therefore highlight areas that may require further investigation before considering treatment.

[0035] When determining whether a point is suitable to be included in the retrograde orbital region, the system of a preferred embodiment considers two factors. These are: i) The distance from the RPA recording location to that point, and ii) The direction in which the excitement must proceed to reach the RPA recording location. Therefore, for a point on the cardiac chamber surface, two distances are preferably calculated: the distance from the RPA recording location, and the distance from the geodetic curve extending backward in the negative propagation direction from the RPA recording location.

[0036] Typically, a cutoff distance from the RPA recording site is used, which is similar in size to the implantation area of ​​a mobile multi-electrode mapping catheter such as Abbott's HD Grid™. Beyond this point, the distance calculation stops, and points further away are not included in the calculation. Preferably, the measured directional deviation is determined from the ratio of the distance to the geodesic to the distance to the source (for a flat surface, this ratio is sine with respect to the RPA direction).

[0037] The retrograde pathway from the earliest excitation site (retrograde trajectory pathway) and the area surrounding this pathway may also be processed to highlight further detections that should be investigated / recorded. These further detections may be signs of other drivers of the early excitation site or abnormal heartbeat. This feedback (using the identified RPA and retrograde trajectory to select other areas that should be mapped but have not yet been measured) results in a semi-autonomous process that is resource- and time-efficient, focused on mapping relevant areas of the heart, rather than random measurement or mapping entire areas. This process can be used to guide clinicians to focus on the areas most likely to be important, limiting diagnostic actions and / or highlighted areas to ablation or other treatments.

[0038] [Brief description of the drawing] Embodiments of the present invention will be described solely by reference to the following accompanying drawings. [Brief explanation of the drawing]

[0039] [Figure 1] This is a flowchart of a computer-based method according to one embodiment. [Figure 2a] This is a schematic diagram illustrating the operational characteristics of the method shown in Figure 1. [Figure 2b] This is a schematic diagram illustrating further characteristics of the operation of the method shown in Figure 1. [Figure 2c] This is a schematic diagram that combines the features of Figure 2a and Figure 2b. [Figure 3]This image shows exemplary data illustrating the identification of repetitive patterns of cardiac excitation according to one embodiment. [Figure 4] This is a schematic diagram showing data that identifies two earliest excitation sites and their interaction. [Figure 5] This is a schematic diagram illustrating the characteristics of the process performed in one embodiment. [Figure 6] This image shows illustrative data illustrating the identification of numerous repetitive patterns of cardiac excitation according to one embodiment. [Figure 7] This is a schematic diagram illustrating an embodiment in which other data is incorporated into data that identifies repetitive excitation patterns. [Modes for carrying out the invention]

[0040] [Detailed explanation] Figure 1 is a flowchart showing a computer-based method according to one embodiment. Figure 2a is a schematic diagram illustrating the operational characteristics of the method shown in Figure 1. Figure 2b is a schematic diagram illustrating further operational characteristics of the method shown in Figure 1. Figure 2c is a schematic diagram showing a combination of the characteristics of Figures 2a and 2b.

[0041] In step 10, recorded data is received. This recorded data is preferably electrographic data recorded from a series of detection points on the heart 200 corresponding to multiple electrodes of a multi-electrode cardiac catheter, over the recording period. Figure 2a shows one detection point 100, from which data is recorded from each part 110 of the heart 200 corresponding to the position of each electrode. Data recording may be performed before the method is carried out, in which case it can be applied to offline data.

[0042] The explanatory diagrams in Figures 2a-2c, 4, and 7 have been simplified for ease of understanding and do not represent all the data that may be output in the embodiment. Similarly, the illustration of the heart has been simplified for ease of understanding and display. The illustrated heart 200 also includes an illustration of the mitral valve 210, which is included to indicate that in a selected embodiment, the illustrated data may consider non-tissue areas (areas where there is no data, or where only spurious data that the embodiment would supplement through suppression, etc.). The box and arrow around region 110 in Figure 2a are for illustrative purposes only and indicate that this data corresponds to the data shown on the right side of the figure. This box and arrow do not constitute part of the data displayed in the embodiment.

[0043] In step 20, repeated excitation pattern sites (RPAs) are identified from the recorded data. Preferably, this is done using the STAR mapping algorithm described above. Here, a large number of excitations are recorded, and the excitation vector is calculated for each excitation at the recorded site. A dominant excitation vector may be determined using statistical methods, and this may be subdivided by other characteristics of the excitation (e.g., the order of excitations recorded by other electrophysiological catheters in the heart). Each classified measurement of the obtained dominant repeated excitation vector has an associated dataset that includes characteristics such as differences in vector direction, frequency and conduction velocity, and the site of the fastest excitation. Such sites are called "repeated excitation pattern" sites (RPAs). RPAs may also be calculated using methods other than STAR, such as the classification of excitation vector gradients between electrode groups of the mapping catheter.

[0044] For each of the identified excitation repetition patterns, i) In step 30, the earliest excitation site 120 and excitation vector 130 are identified from the identified electrode activation (excitation) sequence (Figure 2a). ii) In step 40, the pathway 140 is identified on the surface of the cardiac chambers, tracing back from the earliest excitation site 120. This surface is identified from data obtained about the shape of the heart, and the pathway is projected as a ray onto the surface of the cardiac chambers and guided by a vector opposite in direction to the excitation vector (Figure 2a). iii) In step 50, statistical measurements are calculated for the repeating pattern of excitation over the period. iv) Step 60 outputs data that identifies the earliest excitation site and the excitation repetition pattern including the pathway. Based on statistical measurements, this data is used to change the emphasis on the excitation repetition pattern and / or the pathway and / or the region near the pathway (Figure 2b).

[0045] The output data may be coded / digitized so that it can be easily transmitted or saved for later consumption. However, preferably the data is a visual representation, or converted into a visual representation where area density, color gradients, and shading indicate the values ​​of statistical measurements. An example is shown in Figure 3.

[0046] In one embodiment, each RPA is represented by a vector 130 pointing from the earliest excitation site 120 (leading electrode) across the recording site of the RPA in the dominant propagation direction. A trace trajectory region 150 is shown along the drawn path, radiating from the end of the arrow 130 of the represented vector, with regions of higher importance arising from this line. The importance of points within this region may be determined by both the distance from the RPA and the lateral distance from the path, as well as other statistical characteristics, tissue or electrographic characteristics. The final importance can also be shown on a map. As shown in the figure, importance can be indicated by the intensity of shading, coloring, or other methods of the trace trajectory region. In the example in Figure 2a, importance is indicated by the intensity of shading, with the darkest shading indicating the highest importance and the lightest shading indicating the lowest importance. A simple example showing only one RPA is shown in Figure 2c. This is a 2D rendering, but 3D renderings, such as those shown in Figure 3, can also be used. In Figure 3, the retrospective trajectory line 140 is shown along the surface representation of the cardiac chambers, making it appear as if it is drawing an irregular curve on the surface (which is actually the surface of the simulated heart). In Figure 3, the importance of various regions is represented by color, with yellow shading in the peripheral areas indicating the lowest importance, changing to green as the relevance of the area increases, and finally to blue shading. This is just an example, and of course, other color schemes can be chosen.

[0047] Numerous RPAs may be output to add interactions in the retro-orbit region. This is shown in Figure 4 as overlapping regions 150 and 150', where the dark areas indicate overlapping retro-orbit regions. This can be calculated by cumulative or additive calculations and normalization of the statistical importance evaluation criteria. An example of numerous potential RPAs and retro-orbit interactions that can be output is shown in Figure 4.

[0048] Next, as shown in Figure 5, the following steps are repeated for each RPA.

[0049] 2. Geodesic raycasting from the start The initial retrograde trajectory tracing is performed by establishing the earliest excitation site for each RPA, and then establishing a path along a geodesic path that traces backward from this site in the opposite direction to the dominant excitation vector. This is called geodesic ray casting. This geodesic path follows the curvature of the atrium, and "opposite direction" is defined as the vector direction in the tangent plane to the origin of the RPA vector, forming a 180-degree angle. Preferably, the process stops when the ray reaches a predetermined length, and since the uncertainty of whether the site is related to the RPA site increases with distance from the RPA, a "cutoff" of 1.5 cm from the RPA is set beyond which the process stops.

[0050] 3. Calculation of distance to the origin and calculation of distance to the ray. For each point on the cardiac chamber surface, two distances are calculated: the distance to the earliest excitation site of the RPA and the distance to the light ray. Therefore, for each point on the cardiac chamber surface, the distance to the RPA start point and the distance to the light ray are calculated. The ratio of these two distances is the angle (sine angle).

[0051] 4. Score calculation for each RPA Each point on the cardiac chamber surface is assigned a score for each RPA, taking into account both distance and angle measurements. For example, an exponential penalty is applied to the product of the deviation from 0 distance to the origin and the deviation from 0 angle. Other penalties may also relate to the characteristics of the RPA that derive the score, such as changes in the vector angle constituting the RPA, changes in period, or the absolute period contributing to each RPA. Further additional modifiers for each score can also be provided from previously acquired data, such as voltage maps obtained early in the procedure, known ablation sites, anatomical data, and biostructural or physiological function data obtained from mapping databases.

[0052] 5. Calculation of the overall score For each point in the geometric shape used to calculate the score, the multiplied RPA scores are combined to form a single score. For example, the sum of each score may be expressed as an absolute value, or normalized to the maximum and minimum scores of all scores in the entire map. Alternatively, all RPAs contributing to overlapping areas can be considered as a local set of RPAs and normalized to the local maximum or minimum value. Furthermore, penalty or adjustment factors can be introduced to adjust the score, thereby increasing the score based on how many RPAs contribute to each local set of RPAs, and awarding points when more RPAs contribute to the score calculation, indicating higher attention and certainty than when only one RPA contributes. Such scores can also be visualized as a color scheme that highlights the area with the highest score as a potential source.

[0053] The specificity and sensitivity of identifying potential arrhythmia sources can be adjusted according to the data related to RPA statistics, including the measurement of angle and distance. For example, a penalty may be imposed on sources if there are large changes in direction, ratio, or excitation order, or relative to the ratio of RPAs. Such penalties may be imposed in an absolute manner or normalized to the data from all identified RPAs. For example, the calculation of traceback sources from RPAs with higher excitation frequencies may be given higher priority than those with lower excitation rates.

[0054] Perform this procedure for each RPA, recording the number of regions it encompasses for each point in the geometric shape. Points that fall within the trace trajectory regions of multiple RPAs can be highlighted as interesting regions to investigate further.

[0055] Figure 6 is a further exemplary image generated by one embodiment.

[0056] Other physiological data, electromorphological data, or external data can also be integrated into the retrograde trajectory map, and data obtained through external imaging or during electroanatomical mapping, such as from a "scar map," can be combined with the retrograde trajectory map to further influence the area of ​​focus, as shown in Figure 7. In this example, the other data 300 pertains to areas of scars 310, 320 that are separately identified for the same heart 200. When calculating the retrograde trajectory region 150, in a preferred embodiment, the calculated retrograde trajectory region and / or the area of ​​focus is modified by considering other available data. In this example, the scar region 310 increases the visibility of the retrograde trajectory region 151. This may be incorporated into the score calculation (for example, applied to modify the score of pixels or points identified as scar locations or near them in steps 4 and / or 5 above), or, if other data overlaps, it may be incorporated at the image level with adjusted pixel values ​​and / or coloring. The user interface can also enable a hierarchical approach, allowing users to selectively switch one or more "other" data sources on or off and see a map showing the effects with and without them.

[0057] Naturally, the generated data can be stored in various data storage locations, including centralized or distributed file storage locations, and databases (such as SQL and other relational or non-relational database types). This can be done using storage devices such as hard disks, random access memory, solid-state disks, or other forms of storage media. Naturally, the processors described herein refer to a single processor or aggregated processors operating synchronously, semi-synchronously, or asynchronously.

[0058] Naturally, one embodiment of the present invention described below may be incorporated as code (e.g., a software algorithm or program) present on a computer-usable medium that has a control theory enabling execution on a computer system having firmware and / or a computer processor. Such a computer system typically includes a memory device that constitutes a processor by execution, configured to execute and output the code. The code may be deployed as firmware or software, or it may be constructed as a set of modules such as individual code modules, function calls, procedure calls, or objects in an object-oriented programming environment. When implemented using modules, the code may consist of a single module or multiple modules that work together.

[0059] Any embodiment of the present invention is understood to include, individually or collectively, any combination of two or more parts, elements, or features mentioned or suggested herein, and where this invention refers to a particular integer known in the art to be equivalent, such known equivalents shall be incorporated herein as separately described.

[0060] While illustrated embodiments of the present invention have been described, those skilled in the art should understand that various changes, substitutions, and modifications can be made without departing from the present invention as defined by the following claims and their equivalents.

Claims

1. A computer program comprising, when the computer program is executed on a computer, computer program code means for performing a method performed by the computer to identify one or more regions of the heart that are factors supporting or initiating an abnormal heartbeat, wherein the method performed by the computer utilizes electrographic data obtained over a recording period from a series of corresponding detection locations on the heart, recorded from multiple electrodes of a multi-electrode cardiac catheter, and the method To obtain data on the shape of the heart, which has recorded the aforementioned electromagnet data, From the electromagnet data, identify the sequence of electrode activations that contributes to the repetitive excitation pattern over the recording period, For each repetition pattern of excitation, i) Identifying the earliest excitation site and excitation vector from the identified electrode activation sequence, ii) Identifying a pathway on the surface of the cardiac chambers, tracing back from the earliest excitation site, wherein the surface is identified from the data obtained regarding the shape of the heart, and the pathway is identified by a vector projected as a ray onto the surface of the cardiac chambers and guided by a vector whose direction is opposite to that of the excitation vector. iii) Calculating statistical measurements over the recording period for the aforementioned repeating pattern of excitation, iv) Outputting data that identifies the repetitive pattern of excitation including the pathway, wherein the data changes the degree of attention given to the repetitive pattern of excitation based on the statistical measurement value. A computer program that includes [this].

2. The computer program according to claim 1, further comprising the step of changing the degree of attention given to the aforementioned repetition pattern of excitation relative to other repetition patterns of excitation.

3. The computer program according to claim 1 or 2, wherein step iv) comprises generating a visual representation of the surface of at least a region of the heart on which electrographic data has been recorded, the visual representation comprising a visual representation of the repetitive pattern of excitations traversing the pathway along the surface.

4. The computer program according to claim 3, wherein the statistical measurement includes the frequency of repetitions over the period.

5. The computer program according to claim 3 or 4, wherein the statistical measurement includes the uniformity of excitation in the direction of excitation over the period.

6. The computer program according to claim 3, 4, or 5, wherein the visual representation of the repeating pattern of excitation varies by one or more of the width of the path, the color of the path, the dimensions and / or type of a marker indicating the direction of excitation.

7. a) With respect to at least selected repetition patterns of excitation, with respect to the points on the surface, The distance on the surface from the point to the earliest point of excitation in the aforementioned repeating pattern of excitation, The distance from the aforementioned point to the nearest point on the aforementioned path, The angle between the earliest excitation point, the point, and the nearest point on the path Measuring and b) Determining a score for the point based on the two distances and the angle, c) Changing the emphasis on the points in the data output based on the score, A computer program according to any of the prior claims, further comprising:

8. The computer program according to claim 7, which changes the degree of attention given to the aforementioned points relative to a fixed scoring standard.

9. The computer program according to claim 7, which changes the level of attention of the aforementioned point relative to the scores of other points.

10. A computer program according to any one of claims 7 to 9, further comprising performing a) to c) for all points on the surface.

11. A computer program according to any one of claims 7 to 10, further comprising, if there are many repeating patterns of excitation, calculating a total score for each point, wherein the total score is calculated based on the score for each point for each of the repeating patterns of excitation, and performing c) based on the total score.

12. The computer program according to claim 11, wherein calculating the overall score includes calculating a normalized score.

13. The computer program according to claim 11 or 12, wherein calculating the overall score includes applying a penalty factor, the score increasing in proportion to how many repetition patterns of excitation the point was involved in.

14. The computer program according to any one of claims 7 to 13, wherein the above a) further includes modifying one or more of the angle and distance measurements according to a statistical measurement of the repeating pattern of excitation.

15. The computer program according to any one of claims 7 to 13, wherein the above a) further includes accessing external data about the heart and changing one or more of the angle and distance measurements or scores according to the external data.

16. The computer program according to claim 15, wherein the external data includes a voltage map obtained early in the procedure, ablation sites known to have been performed, anatomical data, or data relating to biological structure or physiological function obtained from a mapping database.

17. This further includes highlighting the points where the pathways of repeated excitation patterns intersect. A computer program according to any one of claims 7 to 16.

18. The computer program according to any of the preceding claims, wherein the iv) outputs data identifying the earliest site of excitation.

19. A computer system for identifying one or more regions of the heart that are contributing to or initiating an abnormal heartbeat, using electrographic data obtained over a recording period from a series of corresponding detection sites on the heart, recorded from multiple electrodes of a multi-electrode cardiac catheter, wherein the system Processor and A first memory for recording the received electromagnetism data, The second memory that stores the program code and Includes, When the processor executes the aforementioned program code, it will then... To obtain data on the shape of the heart, which has recorded the aforementioned electromagnet data, From the aforementioned electromagnetism data, the sequence of electrode activations that contributes to the repetitive excitation pattern over the recording period is identified, For each repetition pattern of excitation, i) Identifying the earliest excitation site and excitation vector from the identified electrode activation sequence, ii) Identifying a pathway on the surface of the cardiac chambers, tracing back from the earliest excitation site, wherein the surface is identified from the data obtained regarding the shape of the heart, and the pathway is identified by a vector projected as a ray onto the surface of the cardiac chambers and guided by a vector whose direction is opposite to that of the excitation vector. iii) Calculating statistical measurements over the recording period for the aforementioned repeating pattern of excitation, iv) Outputting data that identifies the repetitive pattern of excitation including the pathway via an output device, wherein the data changes the degree of attention given to the repetitive pattern of excitation based on the statistical measurement value. To have them do it, Computer system.

20. A computer program comprising, when the computer program is executed on a computer, computer program code means for performing a method performed by the computer to identify one or more regions of the heart that are factors supporting or initiating an abnormal heartbeat, wherein the method performed by the computer utilizes electrographic data obtained over a recording period from a series of corresponding detection locations on the heart, recorded from multiple electrodes of a multi-electrode cardiac catheter, and the method To obtain data on the shape of the heart, which has recorded the aforementioned electromagnet data, From the aforementioned electromagnetism data, the sequence of electrode activations that contributes to the repetitive excitation pattern over the recording period is identified, For each repetition pattern of excitation, i) Identifying the earliest excitation site and excitation vector from the identified electrode activation sequence, ii) Identifying a pathway on the surface of the cardiac chambers, tracing back from the earliest excitation site, wherein the surface is identified from the data obtained regarding the shape of the heart, and the pathway is identified by a vector projected as a ray onto the surface of the cardiac chambers and guided by a vector whose direction is opposite to that of the excitation vector. iii) At least a portion of the points on the surface The distance on the surface from the point to the earliest point of excitation in the aforementioned repeating pattern of excitation, The distance from the aforementioned point to the nearest point on the aforementioned path, The angle between the earliest point of excitation, the aforementioned point, and the nearest point on the path A score for the point based on the two aforementioned distances and angles. Measuring and iv) Calculating statistical measurements over the recording period for the aforementioned repeating patterns of excitation, v) Outputting data that identifies the repetitive pattern of excitation including the pathway, comprising generating a visual representation of the surface of at least an area of ​​the heart on which electrographic data has been recorded, wherein the visual representation includes a visual representation of the repetitive pattern of excitation traversing the pathway along the surface, and the visual representation changes the visual attention to the repetitive pattern of excitation based on the statistical measurements and the visual representation of at least some of the points scored in iii), wherein the visual representation of each point is based on its score, and outputting data. A computer program that includes [this].

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