Detection of potential slow conduction cardiac tissue regions in stable arrhythmias

Abstract

A method for identifying candidate locations for ablation includes receiving an electrophysiology (EP) map including an anatomical surface of a heart cavity superimposing (i) an activation wave velocity vector, (ii) data points including locations on the surface and corresponding local activation times (LATs), and (iii) regions specified by an early-to-late (EML) LAT range. A set of shortest paths on the heart surface is identified between different EML regions. One or more ranges of LAT values are selected, the one or more ranges characterized by a lowest prevalence rate on data points of the EP map. A composite tag is generated for a location having the LAT value within one or more ranges of LAT values having the lowest morbidity. A subset of the shortest paths is selected based on (i) a density of the composite labels along the shortest paths and (ii) a direction of the activation wave velocity vector relative to each of the shortest paths. A subset of the selected shortest paths is presented as candidate slow conduction regions for ablation.

Description

Technical Field

[0001] The present disclosure relates generally to analysis of electrophysiological (EP) signals, and in particular to methods for detecting slow conduction in stable cardiac arrhythmias such as atrial flutter. Background Art

[0002] Electrophysiological (EP) mapping of cardiac regions has been previously proposed in the patent literature to identify slow-conducting cardiac tissue regions. For example, International Patent Application Publication WO 2020 / 214439 describes an electroanatomical mapping system that can map the electrical activation of tissue, and specifically, using a plurality of electrophysiological data points, each of which includes local activation timing information, to create a slow conduction map by calculating a slow conduction metric for each point using the local activation timing information. The slow conduction metric can be used to classify each point into a non-conduction point, a slow conduction point, and a normal conduction point, and the results can be expressed graphically, including as an animated representation of an activation wavefront propagating along a three-dimensional anatomical surface model. BRIEF DESCRIPTION OF THE DRAWINGS

[0003] The present disclosure will be more fully understood through the following detailed description of examples of the present disclosure in conjunction with the accompanying drawings, in which:

[0004] Figure 1 is a schematic illustration of a catheter-based electrophysiological (EP) mapping system according to an example of the present disclosure;

[0005] FIG. 2A to FIG. 2C is a schematic illustration of algorithm steps for detecting slow-conducting cardiac tissue regions in stable arrhythmias according to an example of the present disclosure;

[0006] Figure 3 is a flow chart schematically illustrating a method and algorithm for detecting slow conduction cardiac tissue regions in stable arrhythmias according to an example of the present disclosure; and

[0007] Figure 4 is a volume rendering of an EP map of the left atrium showing potential slow-conducting tissue locations that may cause stable arrhythmias according to an example of the present disclosure. DETAILED DESCRIPTION

[0008] Overview

[0009] Stable arrhythmias, such as atrial flutter (AFL) or stable ventricular tachycardia (VT), are generally defined as sustained arrhythmias that are not associated with significant hemodynamic compromise. However, stable arrhythmias can easily deteriorate into life-threatening conditions, so once diagnosed, they require prompt treatment, which includes selective ablation of the arrhythmogenic tissue site causing the stable arrhythmia.

[0010] In order to characterize a patient's stable arrhythmia, a catheter-based electrophysiological (EP) mapping system can be used to generate an EP map of at least a portion of the patient's heart, such as an EP map of a cardiac chamber. In a typical catheter-based EP mapping procedure, the distal end of a catheter including one or more sensing electrodes is inserted into a cardiac chamber to sense EP signals, such as a bipolar electrogram (EGM). As a physician operating the system moves the distal end within the cardiac chamber, the EP mapping system acquires EP signals at various locations on the inner surface of the cardiac chamber and at corresponding locations of the distal end. Based on these acquired signals, a processor of the mapping system generates the desired EP map, which includes local EP tissue characteristics (e.g., local cycle times between activations) overlaid on an anatomical map of the cardiac chamber.

[0011] When mapping stable arrhythmias (e.g., AFL), the physician looks for specific areas on the surface of the cardiac tissue with abnormal EP characteristics, for example, one or more tissue isthmuses, which are areas of EP conduction between adjacent scars or between a natural structural barrier and a scar. Such areas may be characterized by having slowly conducted EP signals that may promote stable arrhythmias. Thus, the physician may view the slow conduction areas on the EP map and ablate one or more of these target areas to terminate the arrhythmia. This may be primarily used in AFL, but may also potentially be used in VT cases.

[0012] However, slow conduction areas are characterized by complex phenomenology, such as scars / lines of occluded areas, synchronization wave directions, instabilities in local activation time (LAT), and low-amplitude bipolar signals, which makes it difficult to identify the most relevant slow conduction areas.

[0013] Current systems using current algorithms for identifying and characterizing stable arrhythmias do not provide good pointers to physicians on areas most likely to be ablated, so physicians must typically perform time-consuming inspections of candidate tissue locations prior to ablation. Specifically, current workflows for detecting slow conduction areas in AFL do not provide clear guidance on the most relevant features or workflows that should be used to enhance detection of those areas. Today, physicians need to spend time activating, configuring, and analyzing multiple system features, and in addition, manually mark a large number of, for example, complex graded signals, as well as mark potential ablation sites.

[0014] Examples of the present disclosure described herein provide a method and system for providing an integrated automated analysis that enables a user to easily detect potential slow conduction areas. Indicated slow conduction areas detected by an algorithm using a slow conduction criterion comprising the three steps described below are marked (e.g., superimposed) on an EP map.

[0015] The disclosed algorithm relies on the observation that AFL and some other stable arrhythmias are caused by the occurrence of abnormal activation wave reentry, which is caused by the EP activation wave traveling in a closed trajectory within the heart, rather than moving from one end of the heart to the other and then terminating. When the EP activation wave propagates continuously with a certain cycle length (e.g., the time between consecutive peaks in the ECG), the wave propagation in the heart chamber may span the entire reentrant cycle, where the "late" wavefront in the cycle meets the "early" wavefront of the next cycle. Therefore, a region may be assigned an incorrect local activation time (LAT), which is very short or very long (a phenomenon hereinafter referred to as "early meets late" or EML).

[0016] Typically, the EML region is bounded by a curve that blocks conduction, such as the curve described in U.S. Pat. No. 9,649,046, which is assigned to the assignee of the present application. EP map visualization can be used to highlight such potential regions of blocked conduction, potential regions of conduction blockage hereinafter referred to as "EML regions," and surrounding curves of blocked conduction referred to as "EML boundaries." Examples of such visualizations of regions of blocked conduction (e.g., EML regions) in complex arrhythmias are disclosed in U.S. Pat. No. 10,136,828, which is assigned to the assignee of the present application.

[0017] In some examples of the disclosed technology, a processor receives an EP map of a heart surface, the EP map comprising data points including locations on the surface and corresponding local activation times (LATs), and regions specified by early-meet-late (EML) LAT occurrences. The processor identifies a set of shortest paths between different EML regions, where such paths may cross an isthmus. The processor does not consider ultra-long paths, i.e., paths between remotely located EML regions, because they are unlikely to represent valid paths across the isthmus.

[0018] Using a LAT histogram of the surface, the processor selects one or more ranges of LAT values ​​(e.g., bars of the histogram) with the lowest prevalence of such data points. The processor generates composite graded labels for locations on the EP map having LAT values ​​within these one or more ranges of LAT values ​​with the lowest prevalence. An algorithm for placing composite labels at tissue locations based on the magnitude of the grade (indicating stable arrhythmias) is described in U.S. patent application No. 17 / 548,558, entitled "Detection of Fractionated Signals in stable arrhythmias," filed on December 12, 2021. The processor removes short paths along regions with sparse composite labels from consideration by selecting a subset of the set of shortest paths between EML regions based on the density of composite graded labels along the paths.

[0019] The EP map also includes activation wave velocity. The processor further filters a subset of the shortest paths between EML regions by selecting paths whose velocity vectors propagate in the isthmus region in the general direction along the isthmus without propagating between EML regions. Propagation along the isthmus may be a source of reentrant arrhythmias, whereas propagation across the isthmus may be the result of EP wavefront collisions therein, which is clinically irrelevant.

[0020] Finally, the processor presents the selected subset of pathways as candidate slow EP conduction gaps for ablation aimed at eliminating arrhythmias such as AFL.

[0021] System Description

[0022] Figure 1 is a schematic illustration of a catheter-based electrophysiological (EP) mapping system 21 according to an example of the present disclosure. Figure 1 A physician 27 is depicted using an electroanatomical mapping catheter 29 to perform electroanatomical mapping of a heart 23 of a patient 25. The mapping catheter 29 includes one or more arms 20 at its distal end, each of which is coupled to a bipolar electrode 22 including adjacent electrodes 22a and 22b. In some examples, the distal end of the catheter includes a magnetic sensor (not shown) that allows the position of the electrode 22 to be magnetically tracked or to calibrate the aforementioned electrical tracking signal to improve the accuracy of the electrical position tracking method.

[0023] During the mapping procedure, the position of the electrode 22 is tracked while it is located inside the patient's heart 23. To this end, electrical signals are transmitted between the electrode 22 and the external electrodes 24. For example, three external electrodes 24 may be coupled to the patient's chest and another three external electrodes may be coupled to the patient's back. For ease of illustration, Figure 1 Only one outer electrode is shown.

[0024] Based on the signals and in view of the known positions of the electrodes 24 on the patient's body, the processor 28 calculates an estimated position of each electrode 22 within the patient's heart. Using the electrodes 22, corresponding electrophysiological data, such as a bipolar electrogram trace, is additionally acquired from the tissue of the heart 23. Thus, the processor can associate any given signal received from the electrode 22 (such as a bipolar EP signal) with the location where the signal was acquired. The processor 28 receives the resulting signals via the electrical interface 35, and uses the information contained in these signals and stored in the memory 33 to construct an electrophysiological map 31 (which will also be stored in the memory 33 for uploading by the processor 28) and an EGM or ECG trace 40, and presents these signals on the display 26. One tracking system and method capable of generating the map 31 is used in various medical applications (for example, in the CARTO ELECTRONIC® system produced by Biosense-Webster Corporation). TM The Advanced Current Location (ACL) system implemented in the system is described in detail in U.S. Patent No. 8,456,182, the disclosure of which is incorporated herein by reference.

[0025] Magnetic tracking systems (not shown) and methods capable of producing a map 31 or improving the accuracy of the ACL method are described in U.S. Patents 5,391,199, 6,690,963, 6,484,118, 6,239,724, 6,618,612, 6,332,089, PCT Patent Publication WO 96 / 05768, and U.S. Patent Application Publications 2002 / 0065455A1, 2003 / 0120150A1, and 2004 / 0068178A1.

[0026] The processor 28 typically comprises a general purpose computer having software programmed to perform the functions described herein. The software may be downloaded to the computer in electronic form over a network, for example, or it may alternatively or additionally be provided and / or stored on a non-transitory tangible medium such as magnetic, optical, or electronic memory. Specifically, the processor 28 operates as disclosed herein and includes Figure 3 , which enables the processor 28 to perform the disclosed steps, as further described below.

[0027] Figure 1 The example illustrations shown are chosen solely for conceptual clarity. Other types of electrophysiological sensing catheter geometries may be employed, such as Catheter (produced by Biosense-Webster, Inc., Irvine, California). In addition, a contact sensor can be mounted at the distal end of the mapping catheter 29 to transmit data indicating the physical quality of the electrode-tissue contact. In an example, if the physical contact quality of one or more electrodes 22 is indicated as poor, their measurements can be discarded, and if the contact quality of other electrodes is indicated as adequate, their measurements can be considered valid.

[0028] Detecting potential areas of slow-conducting cardiac tissue in stable arrhythmias

[0029] FIG. 2A to FIG. 2C is a schematic illustration of algorithm steps for detecting slow-conducting cardiac tissue regions in stable arrhythmias according to an example of the present disclosure.

[0030] FIG. 2A to FIG. 2C is briefly described above and in Figure 3 A high-level visual description of the algorithm steps described in detail in .

[0031] Figure 2A A set of shortest paths (212, 213, 214) identified by the processor on the EP map 202 using the disclosed algorithm is shown. Paths are drawn on candidate slow conduction gaps between EML regions 205. The input to this step includes the EML regions 205, each of which is defined by a curve surrounding a region of blocked conduction (referred to herein as an EML boundary 215) and by a predefined limit 209 of the maximum path length considered (hereinafter also referred to as "max_gap_length") to remove irrelevant (e.g., too long) paths, i.e., paths between remotely located EML regions, as described above and in Figure 3 Described in detail in .

[0032] Figure 2B Paths 214 are shown being removed from consideration using the LAT histogram 210, where only the lowest prevalence bin 204 is considered (LAT bin 204 includes data points in the EP map 202 that are within the LAT range [min LAT 206, max LAT 208].) As seen on the EP map 202, only the composite labels 218 associated with the LAT bin 204 are considered (i.e., filtered), which leaves the paths for consideration based solely on the density of the associated composite labels 218 along each path in the path group (212, 213).

[0033] at last, Figure 2CA selected path 212 is shown, which remains on the EP map 202 and is indicated (222) to the user as a path over a possible slow conduction gap 220. Path 212 remains after filtering out paths (such as filtering out (219) path 213), except that the activation wave velocity 207 shows propagation mostly across the gap, rather than more perpendicular or at an angle relative to path 212, as only the latter indicates possible re-entrant activation via a gap (e.g., isthmus) 220 between closed EML regions 205. In other words, Figure 2C Path selection is shown based on filtering out paths where the velocity vector is parallel to the tangent of the path until a given angular tolerance on the degree of parallelism is achieved. On the other hand, a velocity vector that is mostly orthogonal to the path (i.e., parallel to the tangent of the EML boundary) at the EML boundary 215 where the path meets the EML region indicates reentrant propagation that may cause arrhythmia.

[0034] Figure 3 is a flow chart schematically illustrating a method and algorithm for detecting slow conduction cardiac tissue regions 220 in stable arrhythmias according to an example of the present disclosure. According to the example presented, the algorithm performs a process beginning with an EP map receiving step 302, wherein a processor (such as processor 28) receives an EP map (such as map 202) that includes (i) surface locations and corresponding LAT values ​​at the locations, (ii) activation wave velocity vectors (e.g., vector 207) and EML regions (e.g., region 205). The surface locations and LAT values ​​are not explicitly shown in the map, but rather are indicated as indicated by Figure 4 Such EP maps are typically color-coded using a continuous LAT scale interpolated between the measured discrete LAT values, as shown in EP maps of FIG.

[0035] Next, the process runs steps 304 and 306 in parallel with step 308 to generate the two necessary inputs for step 310 .

[0036] At a LAT bin selection step 304, the processor selects one or more LAT bins of the LAT histogram of the LAT values ​​of step 302. The processor may select the lowest prevalence LAT bin, such as Figure 2B 204, or for example, select both the lowest prevalence LAT column and the second lowest prevalence LAT column. Step 304 may involve calculating a LAT histogram if such a histogram is not already available.

[0037] Next, at a composite label generation step 306, processor 28 applies the aforementioned composite label algorithm of US patent application Ser. No. 17 / 548,558, with [min LAT, max LAT] column 204 as the "time frame within the WOI" to identify the location of such a subset of labels on the map surface.

[0038] In parallel, at a path identification step 308, the processor 28 finds virtual shortest paths (212, 213, 214) between all EML regions 205. As a preparatory step, the processor 28 uses existing algorithms to find all EML regions 205 if these regions are not already given on the EP map 202. Step 308 also excludes paths whose length exceeds a predefined maximum path length "max_gap_length" to remove irrelevant (e.g., too long) paths, so these paths are not paths that cross the isthmus.

[0039] At the path subset selection step 310 , the processor further filters out irrelevant paths based on a low density of labels along the paths (eg, within a region including the paths).

[0040] At the final path selection step 312, processor 28 maintains only the path that meets the last step in the slow conduction criterion by maintaining the path with velocity vectors along the EML boundary being directionally consistent and parallel to the EML boundary tangential direction until a predefined parallelism tolerance is reached.

[0041] Finally, at a pathway presentation step 314, processor 28 presents the selected subset of pathways as candidate slow conduction gaps for ablation aimed at eliminating the arrhythmia.

[0042] Figure 3 The flowchart shown is selected purely for conceptual clarity. In order to provide a more simplified flowchart, other possible steps are intentionally omitted from the disclosure of this article.

[0043] Figure 4 400 is a volume rendering of an EP map of the left atrium according to an example of the present disclosure, which shows the location of tissue with potential slow conduction that may cause stable arrhythmias. As shown, the processor indicates (402) the isthmus region between EML regions 405, which is identified as being traversed by a path that meets the above three elements of the slow conduction criteria:

[0044] 1. High density of complex tags 418 in the path area

[0045] 2. Path length < maximum gap length

[0046] 3. The velocity vector along the path is consistent in direction and not parallel to the tangent direction of the path

[0047] As shown, the disclosed technique automatically excludes other possible isthmuses that may cause arrhythmias, such as the isthmus at region 411 .

[0048] Figure 4Also shown is a LAT histogram 404 for use with filtering designed to maintain only relevant complex labels 418, as described above. Also shown is the EP map 400 and a continuous LAT scale 406 of the histogram 404 that a physician can use to verify locations of late activation times indicative of arrhythmias, such as those found within the regions highlighted (402) by the disclosed techniques for consideration of ablation therein.

[0049] Example

[0050] Example 1

[0051] A method for identifying candidate locations for ablation, the method comprising receiving an electrophysiological (EP) map (202), the EP map comprising an anatomical surface of a heart chamber superimposed with: (i) activation wave velocity vectors (207), (ii) data points comprising locations on the surface and corresponding local activation times (LATs), and (iii) regions (205) specified by early encounter late (EML) LAT ranges. A set of shortest paths (212, 213, 214) on the heart surface are identified between different EML regions (205). One or more ranges (204) of LAT values ​​are selected, the one or more ranges being characterized by a minimum prevalence at the data points of the EP map. A composite label (218) is generated for a location having a LAT value within the one or more ranges (204) of LAT values ​​having the minimum prevalence. A subset (212) of the shortest paths is selected based on (i) the density of the composite tags (218) along the shortest paths and (ii) the direction of the activation wave velocity vector (207) relative to each of the shortest paths. The selected subset (212) of the shortest paths is presented as a candidate slow conduction area for ablation.

[0052] Example 2

[0053] The method of embodiment 1, wherein selecting the one or more ranges of LAT values ​​comprises selecting one or more LAT bars (204) of a LAT bar graph (210).

[0054] Example 3

[0055] The method of embodiment 1, wherein selecting the subset of shortest paths (212, 213) includes filtering out paths longer than a predefined path length (214).

[0056] Example 4

[0057] The method of any one of Examples 1 to 3, wherein receiving an EP map (202) having a region (205) specified by an early encounter late (EML) LAT range comprises receiving a region (205) bounded by a curve (215) of blocked conduction.

[0058] Example 5

[0059] The method according to any one of embodiments 1 to 4, wherein selecting the shortest path based on the direction of the activation wave velocity vector (207) includes filtering out paths (213) where the activation wave velocity vector is parallel to a tangent of the path (213) until a given angle tolerance is reached.

[0060] Example 6

[0061] The method of claim 1, wherein generating the composite label (218) includes annotating the electrogram at the graded regions and extracting the LAT value using the annotated electrogram.

[0062] Example 7

[0063] The method of claim 1, wherein the cardiac chamber is an atrium and the arrhythmia is atrial flutter.

[0064] Example 8

[0065] The method of claim 1, wherein the cardiac chamber is a ventricle and the arrhythmia is ventricular tachycardia.

[0066] Example 9

[0067] A system for identifying candidate locations for ablation, the system comprising an interface (35) and a processor (28). The interface (35) is configured to receive an electrophysiological (EP) map, the EP map comprising an anatomical surface of a cardiac chamber superimposed with: (i) activation wave velocity vectors (207), (ii) data points comprising locations on the surface and corresponding local activation times (LATs), and (iii) regions (205) specified by early encounter late (EML) LAT ranges. The processor (28) is configured to (a) identify a set (212, 213, 214) of shortest paths between different EML regions (205) on the surface of the heart, (b) select one or more ranges (204) of LAT values ​​characterized by a minimum prevalence at data points on an EP map, (c) generate a composite label (218) for a location having the LAT value within the one or more ranges (204) of LAT values ​​having the minimum prevalence, (d) select a subset (212) of the shortest paths based on (i) a density of the composite labels (218) along the shortest paths and (ii) a direction of an activation wave velocity vector (207) relative to each of the shortest paths, and (e) present the selected subset (212) of the shortest paths as candidate slow conduction regions for ablation.

[0068] Although the examples described herein are primarily directed to cardiac diagnostic applications, the methods and systems described herein can also be used in other medical applications.

[0069] It should be understood that the above examples are cited by way of example, and the present disclosure is not limited to what is specifically shown and described above. On the contrary, the scope of the present disclosure includes combinations and sub-combinations of the various features described above, as well as variations and modifications thereof, which should occur to those skilled in the art when reading the above description and which are not disclosed in the prior art.

Claims

1. A method for identifying candidate locations for ablation, the method comprising: receiving an electrophysiological (EP) map comprising an anatomical surface of a cardiac chamber superimposed with: (i) an activation wave velocity vector, (ii) data points comprising locations on the surface and corresponding local activation times (LATs), and (iii) a region specified by an early-late (EML) LAT range; Identifying the set of shortest paths between different EML regions on the heart surface; selecting one or more ranges of LAT values, the one or more ranges characterized by a lowest prevalence at the data point of the EP map; generating a composite label for locations having the LAT value within the one or more ranges of LAT values ​​having the lowest prevalence; selecting a subset of the shortest paths based on (i) a density of the composite tags along the shortest paths and (ii) a direction of an activation wave velocity vector relative to each of the shortest paths; as well as The selected subset of the shortest paths is presented as candidate slow conduction areas for ablation.

2. The method according to claim 1, wherein: Selecting the one or more ranges of LAT values ​​includes selecting one or more LAT bins of a LAT histogram.

3. The method according to claim 1, wherein: Selecting the subset of the shortest paths includes filtering out paths that are longer than a predefined path length.

4. The method according to claim 1, wherein: Receiving the EP map having the region specified by an early-meeting-late (EML) LAT range includes receiving a region bounded by a curve that blocks conduction.

5. The method according to claim 1, wherein: Selecting the shortest path based on the direction of the activation wave velocity vector includes filtering out paths where the activation wave velocity vector is parallel to a tangent of the path until a given angle tolerance is reached.

6. The method according to claim 1, wherein: Generating the composite label includes annotating electrograms at graded regions, and extracting LAT values ​​using the annotated electrograms.

7. The method according to claim 1, wherein: The heart chamber is the atrium and the arrhythmia is atrial flutter.

8. The method according to claim 1, wherein: The cardiac chamber is a ventricle and the arrhythmia is ventricular tachycardia.

9. A system for identifying candidate locations for ablation, the system comprising: an interface configured to receive an electrophysiological (EP) map comprising an anatomical surface of a cardiac chamber superimposed with: (i) an activation wave velocity vector, (ii) data points comprising locations on the surface and corresponding local activation times (LATs), and (iii) a region specified by an early-late (EML) LAT range; and A processor, the processor being configured to: Identifying the set of shortest paths between different EML regions on the heart surface; selecting one or more ranges of LAT values, the one or more ranges characterized by a lowest prevalence at the data point of the EP map; generating a composite label for locations having the LAT value within the one or more ranges of LAT values ​​having the lowest prevalence; selecting a subset of the shortest paths based on (i) a density of the composite tags along the shortest paths and (ii) a direction of an activation wave velocity vector relative to each of the shortest paths; as well as The selected subset of the shortest paths is presented as candidate slow conduction areas for ablation.

10. The system according to claim 9, wherein: The processor is configured to select the one or more ranges of LAT values ​​by selecting one or more LAT bars of a LAT histogram.

11. The system according to claim 9, wherein: The processor is configured to select the subset of the shortest paths by filtering out paths that are longer than a predefined path length.

12. The system according to claim 9, wherein: The interface is configured to receive the EP map having the region specified by an early-meeting-late (EML) LAT range by receiving a region defined by a curve of blocked conduction.

13. The system according to claim 9, wherein: The processor is configured to select the shortest path based on the direction of the activation wave velocity vector by filtering out paths where the activation wave velocity vector is orthogonal to a tangent of the path until a given angle tolerance is achieved.

14. The system according to claim 9, wherein: The processor is configured to generate the composite label by annotating the electrogram at the graded regions and extracting the LAT value using the annotated electrogram.

15. The system according to claim 9, wherein: The heart chamber is the atrium and the arrhythmia is atrial flutter.

16. The system of claim 9, wherein: The cardiac chamber is a ventricle and the arrhythmia is ventricular tachycardia.

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