Detection of Potentially Slowly Conducting Cardiac Tissue Regions in Stable Arrhythmias

Abstract

A method for identifying candidate locations for ablation includes receiving an electrophysiological (EP) map including an anatomical surface of a heart chamber, on which are superimposed (i) activation wave velocity vectors, (ii) data points including locations on the anatomical surface of a heart chamber and respective local activation times (LATs), and (iii) regions designated by early-late junction (EML) LAT ranges. A set of shortest paths on the heart surface is identified between the different EML regions. One or more ranges of LAT values ​​characterized by the lowest prevalence across the data points of the EP map are selected. Composite tags are generated for locations having LAT values ​​within the one or more ranges of LAT values ​​having the lowest prevalence. A subset of the shortest paths is selected based on (i) the density of composite tags along the shortest paths, and (ii) the direction of the activation wave velocity vector for each shortest path. The selected subset of shortest paths is presented as candidate slow conduction regions for ablation.

Description

[Technical field]

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

[0002] Electrophysiological (EP) mapping of cardiac regions to identify cardiac tissue regions of slow conduction has been previously proposed in the patent literature. For example, International Patent Application Publication No. 2020 / 214439 describes an electroanatomical mapping system that can map the electrical activation of tissue, and in particular can create a slow conduction map using multiple electrophysiology data points, each of which includes local activation timing information, by calculating a slow conduction metric for each point using the local activation timing information. The slow conduction metric can be used to classify points as non-conducting points, slow conduction points, and normal conduction points, and the results can be represented graphically, such as as an animated representation of an activation wavefront propagating along a three-dimensional anatomical surface model. [Brief description of the drawings]

[0003] A more complete understanding of the present disclosure will be obtained from the following detailed description of the embodiments of the present disclosure when read in conjunction with the drawings. [Figure 1] 1 is a schematic, diagrammatic, illustrative view of a catheter-based electrophysiological (EP) mapping system, in accordance with an embodiment of the present disclosure; [Figure 2A] 1 is a schematic diagrammatic illustration of algorithm steps for detection of slow conducting cardiac tissue regions in stable arrhythmias, according to an embodiment of the present disclosure; FIG. [Figure 2B] 1 is a schematic diagrammatic illustration of algorithm steps for detection of slow conducting cardiac tissue regions in stable arrhythmias, according to an embodiment of the present disclosure; FIG. [Figure 2C]1 is a schematic diagrammatic illustration of algorithm steps for detection of slow conducting cardiac tissue regions in stable arrhythmias, according to an embodiment of the present disclosure; FIG. [Diagram 3] 1 is a flow chart that generally illustrates a method and algorithm for detection of slow conducting cardiac tissue regions in stable arrhythmias, in accordance with an embodiment of the present disclosure. [Figure 4] 1 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 embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0004] overview Stable arrhythmias, such as atrial flutter (AFL) or stable ventricular tachycardia (VT), are often defined as sustained arrhythmias that are not associated with significant hemodynamic impairment. However, stable arrhythmias can easily deteriorate into life-threatening conditions and therefore, once diagnosed, require prompt treatment, including the option of ablation of the arrhythmogenic tissue locus causing the stable arrhythmia.

[0005] To characterize a patient's stable arrhythmias, a catheter-based electrophysiological (EP) mapping system may be used to generate an EP map of at least a portion of the patient's heart, such as an EP map of a heart chamber. In a typical catheter-based EP mapping procedure, a distal end of a catheter with one or more sensing electrodes is inserted into a heart chamber to sense EP signals, such as unipolar and / or bipolar electrograms (EGMs). As a physician operating the system moves the distal end inside the heart chamber, the EP mapping system acquires EP signals at various locations on the inner surface of the heart chamber, as well as the respective positions of the distal end. Based on these acquired signals, a processor of the mapping system generates the requisite EP map, including local EP tissue properties (e.g., local cycle times between activations) overlaid on an anatomical map of the heart chamber.

[0006] When mapping stable arrhythmias (e.g., AFL), physicians look for specific regions on the surface of cardiac tissue that have abnormal EP properties, such as one or more tissue isthmuses that are EP conduction zones between adjacent scars or between a natural structural barrier and a scar. Such zones can be characterized by EP signals with slow conduction that can promote stable arrhythmias. Thus, physicians can look for slow conduction zones on the EP map and ablate one or more of these target zones to terminate the arrhythmia. This may be used primarily in AFL, but potentially in VT cases as well.

[0007] However, slow conduction areas are characterized by a complex phenomenology, including, among others, lines of scar / blockage areas, synchronous wave direction, instability of local activation time (LAT), and low amplitude bipolar signals, which makes identification of the most relevant slow conduction areas difficult.

[0008] Current systems using current algorithms for identifying and characterizing stable arrhythmias do not provide good pointers to the areas that physicians are most likely to ablate, so physicians must typically perform time-consuming checks of candidate tissue locations before ablation. In particular, current workflows for detecting slow conduction areas in AFL do not provide clear guidance for the most relevant features or workflows that should be used to enhance the detection of those areas. Today, physicians must spend time to activate, configure, and analyze several system features, plus, for example, manually tag a significant number of complex segmented signals, as well as mark potential ablation sites.

[0009] The examples of the present disclosure described herein provide a method and system for providing an integrated automated analysis that allows users to easily detect potential slow conduction areas. The indicated slow conduction areas detected by an algorithm using the slow conduction criteria, which includes the three steps described below, are marked (e.g., superimposed) on an EP map.

[0010] The disclosed algorithm relies on the observation that AFL and some other stable arrhythmias are caused by the occurrence of abnormal activation wave reentry due to EP activation waves moving in a closed orbit within the heart, rather than moving from one end of the heart to the other and terminating. Because EP activation waves propagate continuously with a certain cycle length (e.g., the time between successive peaks in the ECG), wave propagation within the heart chamber can span the entire reentry cycle, with the "late" wave front in a cycle meeting the "early" wave front of the next cycle. As a result, regions may be assigned inaccurate local activation times (LATs), which are either very short or very long (a phenomenon hereafter referred to as "Early Meet Late" or EML).

[0011] Typically, the EML region is bounded by a curve of conduction block, such as the curve described in U.S. Patent No. 9,649,046, assigned to the assignee of the present application. Visualization of the EP map can be used to highlight such potential regions of conduction block, hereinafter referred to as "EML regions", and the enclosing curve of the conduction block, hereinafter referred to as "EML boundaries". An example of such visualization of regions of conduction block (e.g., EML regions) in complex arrhythmias is disclosed in U.S. Patent No. 10,136,828, assigned to the assignee of the present application.

[0012] In some embodiments of the disclosed technology, a processor receives an EP map of a cardiac surface, the EP map including data points with their locations on the surface and their respective local activation times (LATs), as well as regions designated by early-late junction (EML) LAT occurrences. The processor identifies a set of shortest paths between different EML regions where such paths may cross the isthmus zone. The processor does not consider very long paths, i.e., paths between EML regions located far apart, as these paths are unlikely to represent valid paths across the isthmus.

[0013] Using the LAT histogram of the surface, the processor selects one or more ranges (e.g., histogram bins) of LAT values ​​in which the prevalence of such data points is lowest. The processor generates complex subdivision tags for locations on the EP map that have LAT values ​​within these one or more ranges of LAT values ​​with the lowest prevalence. An algorithm for placing complex tags at tissue locations according to the magnitude of the fraction (indicative of stable arrhythmia) is described in U.S. Patent Application No. 17 / 548,558, entitled "Detection of Fractionated Signals in stable arrhythmia," filed December 12, 2021. The processor removes from consideration short paths along regions that have sparse complex tags therein by selecting a subset of the set of shortest paths between EML regions based on the density of complex subdivision tags along the paths.

[0014] The EP map further includes activation wave velocity. The processor further filters a subset of shortest paths between EML regions by selecting paths where the velocity vectors within the isthmus region propagate in a general direction along the isthmus and do not propagate between EML regions. Propagation along the isthmus is likely to be the cause of reentrant arrhythmias, while propagation across the isthmus is likely the result of impingement of EP wavefronts therein, which is clinically irrelevant.

[0015] Finally, the processor presents a subset of the selected pathways as candidate slow EP conduction gaps for ablation aimed at eliminating arrhythmias (such as AFL).

[0016] System Description FIGURE 1 is a schematic diagrammatic illustration of a catheter-based electrophysiological (EP) mapping system 21, according to an embodiment of the present disclosure. FIGURE 1 illustrates a physician 27 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 embodiments, the distal end of the catheter includes a magnetic sensor (not shown) that allows for magnetically tracking the position of the electrodes 22 or for calibrating the aforementioned electrical tracking signal to improve the accuracy of the electrical position tracking method.

[0017] During a mapping procedure, the positions of the electrodes 22 are tracked while they are within the patient's heart 23. For that purpose, electrical signals are passed between the electrodes 22 and 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, only one external electrode is shown in FIG. 1.

[0018] Based on the signals, and taking into account the known locations of the electrodes 24 on the patient's body, the processor 28 calculates an estimated location of each electrode 22 within the patient's heart. Respective electrophysiological data, such as bipolar electrogram traces, are additionally acquired from the heart 23 tissue by using the electrodes 22. Thus, the processor may associate any given signal received from the electrodes 22, such as a bipolar EP signal, with the location at which the signal was acquired. The processor 28 receives the acquired 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 (also stored in the memory 33 for uploading by the processor 28) and an EGM or ECG trace 40, which are presented on the display 26. One tracking system and method by which the map 31 can be generated is the Advanced Current Location (ACL) system implemented in various medical applications, for example, the CARTO™ system manufactured by Biosense-Webster Inc., which is described in detail in U.S. Pat. No. 8,456,182, the disclosure of which is incorporated herein by reference.

[0019] Magnetic tracking systems (not shown) and methods that can generate map 31 or improve the accuracy of the ACL method are described in U.S. Pat. Nos. 5,391,199, 6,690,963, 6,484,118, 6,239,724, 6,618,612, and 6,332,089, PCT Patent Publication No. 96 / 05768, and U.S. Patent Application Publication Nos. 2002 / 0065455(A1), 2003 / 0120150(A1), and 2004 / 0068178(A1).

[0020] Processor 28 typically comprises a general-purpose computer with software programmed to perform the functions described herein. The software may be downloaded to the computer in electronic form, for example over a network, or alternatively or additionally may be provided and / or stored on a non-transitory tangible medium, such as magnetic, optical, or electronic memory. In particular, processor 28 executes the dedicated algorithms disclosed herein, including FIG. 3, which enable processor 28 to perform the disclosed steps, as described further below.

[0021] The exemplary illustration shown in FIG. 1 is chosen solely for conceptual clarity. Other types of electrophysiological sensing catheter geometries may be employed, such as the Lasso® catheter (manufactured by Biosense Webster Inc., Irvine, California). Additionally, a contact sensor may be mounted at the distal end of the mapping catheter 29 to transmit data indicative of the physical quality of electrode contact with tissue. In an embodiment, measurements of one or more electrodes 22 may be discarded if their physical contact quality is indicated as poor, while measurements of other electrodes may be considered valid if their contact quality is indicated as sufficient.

[0022] Detection of Potentially Slowly Conducting Cardiac Tissue Regions in Stable Arrhythmias 2A-2C are schematic, diagrammatic illustrations of algorithm steps for detection of slow conducting cardiac tissue regions in stable arrhythmias, according to one embodiment of the present disclosure.

[0023] 2A-2C are a high-level visual illustration of the algorithmic steps briefly described above and detailed in FIG.

[0024] 2A shows a set of shortest paths (212, 213, 214) identified on the EP map 202 by the processor using the disclosed algorithm. The paths are plotted on candidate slow conduction gaps between EML regions 205. The input for this step includes EML regions 205, each defined by a curvature around an area of ​​blocked conduction, referred to herein as an EML boundary 215, and by a predefined limit 209 on the maximum path length (also referred to below as "MAX_GAP_LENGTH") to be considered in order to eliminate irrelevant (e.g., too long) paths, i.e., paths between remotely located EML regions, as described above and detailed in FIG. 3.

[0025] 2B shows that paths 214 are removed from consideration using the LAT histogram 210, of which only the lowest prevalence bin 204 is considered (LAT bin 204 includes data ponites in the EP map 202 that are within the LAT range [minLAT 206, maxLAT 208]). As seen on the EP map 202, only composite tags 218 associated with LAT bin 204 are considered (i.e., filtered), which leaves for consideration only paths based on the density of associated composite tags 218 along each path in the group of paths (212, 213).

[0026] Finally, FIG. 2C shows the selected pathway 212, which is left on the EP map 202 and shown to the user (222) as a pathway across a possible slow conduction gap 220. Pathway 212 is left after filtering out pathways, such as filtering out pathway 213 (219), except that the activation wave velocity 207 indicates propagation across the gap more than perpendicular or at an angle to pathway 212, since only the latter indicates possible reentrant activation through a gap (e.g., isthmus) 220 between adjacent EML regions 205. In other words, FIG. 2C shows pathway selection based on filtering out pathways whose velocity vectors are parallel to a tangent at the pathway up to a given angular tolerance over the parallelism. On the other hand, a velocity vector that is nearly perpendicular to the pathway at the EML boundary 215 where the pathway meets the EML region (i.e., parallel to a tangent to the EML boundary) indicates reentrant propagation that may cause arrhythmia.

[0027] 3 is a flow chart that generally illustrates a method and algorithm for detection of slow conducting cardiac tissue regions 220 in stable arrhythmias, according to one embodiment of the present disclosure. The algorithm executes a process that, according to the presented example, begins with EP map receiving step 302, where a processor, such as processor 28, receives an EP map, such as map 202, that includes (i) surface locations and respective LAT values ​​at those 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, as shown by the EP map of FIG. 4, such EP maps are typically color coded on a continuous LAT scale that interpolates between the measured discrete LAT values.

[0028] The process then performs steps 304 and 306 in parallel with step 308 to generate both inputs required for step 310.

[0029] In a LAT bin selection step 304, the processor selects one or more LAT bins of a LAT histogram of the LAT values ​​of step 302. The processor may select the lowest prevalence LAT bin, such as bin 204 of Figure 2B, or may select, for example, both the lowest prevalence LAT bin and the second lowest prevalence LAT bin. Step 304 may include calculating a LAT histogram if one is not already available.

[0030] Next, in a composite tag generation step 306, processor 28 applies the composite tag algorithm described above in U.S. patent application Ser. No. 17 / 548,558, with [minLAT,maxLAT] bins 204 as "time frames within the WOI" to identify the location of a subset of such tags on the map surface.

[0031] In parallel, in a path identification step 308, the processor 28 finds the hypothetical shortest paths (212, 213, 214) between all EML regions 205. As a preliminary step, the processor 28 utilizes an existing algorithm to find all EML regions 205 if they are not already provided on the EP map 202. Step 308 further filters out paths that have a length that exceeds a predefined maximum path length "MAX_GAP_LENGTH" to remove irrelevant (e.g., too long) paths and thus paths that are not paths that cross the isthmus.

[0032] In a path subset selection step 310, the processor further filters out irrelevant paths based on low density of tags along the path (eg, within the region that contains the path).

[0033] In a final path selection step 312, processor 28 retains only those paths that satisfy the last step in the slow conduction criterion by retaining paths whose velocity vectors along the EML boundary are consistent in direction and parallel to the EML boundary tangent direction to within a predetermined parallelism tolerance.

[0034] Finally, in a pathway presentation step 314, processor 28 presents a subset of the selected pathways as candidate slow conduction gaps for ablation aimed at eliminating the cardiac arrhythmia.

[0035] The flowchart shown in Figure 3 has been selected solely for the purposes of conceptual clarity, and other possible steps have been intentionally omitted from the disclosure herein in order to provide a more simplified flowchart.

[0036] 4 is a volume rendering 400 of a left atrium EP map showing potential slow conduction tissue locations that may cause stable arrhythmias, according to one embodiment of the present disclosure. As shown, the processor shows (402) regions of the isthmus between EML regions 405 that are identified as being crossed by pathways that meet the three elements of the slow conduction criteria described above. 1. High density composite tags in the path region418 2. Path length <MAX_GAP_LENGTH 3. Velocity vectors along a path that are aligned in direction and not parallel to the tangent direction of the path

[0037] As shown, other potential arrhythmia-causing isthmuses, such as the isthmus in region 411, are automatically excluded by the disclosed technique.

[0038] 4 further illustrates a LAT histogram 404, which, as described above, is used in filtering designed to retain only relevant composite tags 418. Also shown is a continuous LAT scale 406 and histogram 404 of the EP map 400 that a physician can use to verify the location of slow activation times indicative of arrhythmias, such as those found within the regions (402) enhanced by the disclosed techniques, to consider ablation therein. EXAMPLES

[0039] Example 1 A method for identifying candidate locations for ablation includes receiving an electrophysiological (EP) map (202) including an anatomical surface of a heart chamber, onto which are superimposed (i) activation wave velocity vectors (207), (ii) data points including locations on the anatomical surface of the heart chamber and respective local activation times (LATs), and (iii) regions (205) specified by early-late junction (EML) LAT ranges. A set of shortest paths (212, 213, 214) on the heart surface are identified (205) between the different EML regions. One or more ranges (204) of LAT values ​​characterized by a lowest prevalence across the data points of the EP map are selected. Composite tags (218) are generated for locations having LAT values ​​within the one or more ranges (204) of LAT values ​​having the lowest prevalence. A subset of the shortest paths 212 is selected based on (i) the density of composite tags 218 along the shortest paths and (ii) the direction of the activation wave velocity vector 207 for each of the shortest paths. The selected subset of the shortest paths 212 is presented as candidate slow conduction regions for ablation.

[0040] Example 2 2. The method of example 1, wherein selecting one or more ranges of LAT values ​​comprises selecting one or more LAT bins (204) of a LAT histogram (210).

[0041] Example 3 2. The method of claim 1, wherein selecting the subset of shortest paths (212, 213) comprises filtering paths (214) that are longer than a predetermined path length.

[0042] Example 4 The method of any one of Examples 1 to 3, wherein receiving an EP map (202) having a region (205) specified by an early-late junction (EML) LAT range comprises receiving a region (205) bounded by a conduction block curve (215).

[0043] Example 5 The method according to any one of claims 1 to 4, wherein selecting the shortest path based on the direction of the activation wave velocity vector (207) comprises filtering paths (213) whose activation wave velocity vector is parallel to a tangent to the path (213) up to a given angular tolerance.

[0044] Example 6 2. The method of claim 1, wherein generating the composite tag (218) comprises annotating electrograms with segmented regions and extracting LAT values ​​using the annotated electrograms.

[0045] Example 7 2. The method of claim 1, wherein the heart chamber is the atrium and the arrhythmia is atrial flutter.

[0046] Example 8 2. The method of claim 1, wherein the heart chamber is a ventricle and the arrhythmia is ventricular tachycardia.

[0047] Example 9 A system for identifying candidate locations for ablation, the system comprising: an interface (35) and a processor (28), the interface (35) configured to receive (i) activation wave velocity vectors (207), (ii) data points including locations on an anatomical surface of a heart chamber and respective local activation times (LATs), and (iii) an electrophysiological (EP) map including an anatomical surface of a heart chamber onto which a region (205) specified by an early-late junction (EML) LAT range is superimposed. The processor (28) is configured to (a) identify a set of shortest paths (212, 213, 214) on the cardiac surface between different EML regions (205); (b) select one or more ranges (204) of LAT values ​​characterized by a lowest prevalence across the data points of the EP map; (c) generate composite tags (218) for locations having LAT values ​​within the one or more ranges (204) of LAT values ​​having the lowest prevalence; (d) select a subset of the shortest paths (212) based on (i) a density of the composite tags (218) along the shortest paths and (ii) a direction of the activation wave velocity vector (207) for each of the shortest paths; and (e) present the selected subset of the shortest paths (212) as candidate slow conduction regions for ablation.

[0048] Although the embodiments described herein primarily address cardiac diagnostic applications, the methods and systems described herein may also be used in other medical applications.

[0049] It will be understood that the embodiments described above are given by way of example, and that the present disclosure is not limited to what is particularly shown and described herein above. Rather, the scope of the present disclosure includes both combinations and subcombinations of the various features described herein above, as well as variations and modifications thereof not disclosed in the prior art that would occur to one skilled in the art upon reading the foregoing description.

[0050] [Embodiment] (1) A method for identifying candidate locations for ablation, the method comprising: receiving an electrophysiological (EP) map including an anatomical surface of a heart chamber overlaid with (i) activation wave velocity vectors, (ii) data points including locations on the anatomical surface of the heart chamber and respective local activation times (LATs), and (iii) an area specified by an early meet late (EML) LAT range; identifying a set of shortest paths on the cardiac surface between different EML regions; selecting one or more ranges of LAT values ​​characterized by a lowest prevalence across the data points of the EP map; generating a composite tag for said locations having LAT values ​​within said one or more ranges of said LAT values ​​having said 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 the activation wave speed vector for each of the shortest paths; presenting the selected subset of the shortest paths as candidate slow conduction regions for ablation; A method comprising: (2) The method of embodiment 1, wherein selecting the one or more ranges of LAT values ​​comprises selecting one or more LAT bins of a LAT histogram. (3) The method of embodiment 1, wherein selecting the subset of the shortest paths includes filtering paths that are longer than a predetermined path length. (4) The method of embodiment 1, wherein receiving the EP map having the region specified by an early-late junction (EML) LAT range includes receiving a region bounded by a conduction block curve. (5) The method of claim 1, wherein selecting the shortest path based on the direction of the activation wave velocity vector includes filtering paths where the activation wave velocity vector is parallel to a tangent to the path up to a given angular tolerance.

[0051] (6) The method of embodiment 1, wherein generating the composite tag includes annotating electrograms with segmented regions and extracting LAT values ​​using the annotated electrograms. (7) The method of embodiment 1, wherein the heart chamber is the atrium and the arrhythmia is atrial flutter. (8) The method of embodiment 1, wherein the heart 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 (i) activation wave velocity vectors, (ii) data points including locations on an anatomical surface of a heart chamber and respective local activation times (LATs), and (iii) an electrophysiological (EP) map including an anatomical surface of the heart chamber overlaid with regions specified by early-late junction (EML) LAT ranges; A processor; wherein the processor: Identifying a set of shortest paths on the cardiac surface between different EML regions; selecting one or more ranges of LAT values ​​characterized by a lowest prevalence across the data points of the EP map; generating composite tags for said locations having LAT values ​​within said one or more ranges of said LAT values ​​having said 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 the activation wave speed vector for each of the shortest paths; The system is configured to present the selected subset of the shortest paths as candidate slow conduction regions for ablation. (10) The system of embodiment 9, wherein the processor is configured to select the one or more ranges of LAT values ​​by selecting one or more LAT bins of a LAT histogram.

[0052] (11) The system of embodiment 9, wherein the processor is configured to select the subset of shortest paths by filtering paths longer than a predetermined path length. (12) The system of embodiment 9, wherein the interface is configured to receive the EP map having the region specified by an early late junction (EML) LAT range by receiving a region bounded by a conduction block curve. (13) The system of claim 9, wherein the processor is configured to select the shortest path based on the direction of the activation wave velocity vector by filtering paths where the activation wave velocity vector is orthogonal to a tangent to the path up to a given angular tolerance. (14) The system of embodiment 9, wherein the processor is configured to generate the composite tag by annotating an electrogram with segmented regions and extracting a LAT value using the annotated electrogram. (15) The system of embodiment 9, wherein the heart chamber is the atrium and the arrhythmia is atrial flutter.

[0053] (16) The system of embodiment 9, wherein the heart chamber is a ventricle and the arrhythmia is ventricular tachycardia.

Claims

1. 1. A system for identifying candidate locations for ablation, the system comprising: an interface configured to receive (i) activation wave velocity vectors, (ii) data points including locations on an anatomical surface of a heart chamber and respective local activation times (LATs), and (iii) an electrophysiological (EP) map including an anatomical surface of the heart chamber overlaid with regions specified by early-late junction (EML) LAT ranges; A processor; wherein the processor: Identifying a set of shortest paths on the cardiac surface between different EML regions; selecting one or more ranges of LAT values ​​characterized by a lowest prevalence across the data points of the EP map; generating composite tags for said locations having LAT values ​​within said one or more ranges of said LAT values ​​having said 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 the activation wave speed vector for each of the shortest paths; The system is configured to present the selected subset of the shortest paths as candidate slow conduction regions for ablation.

2. The system of claim 1 , wherein the processor is configured to select the one or more ranges of LAT values ​​by selecting one or more LAT bins of a LAT histogram.

3. The system of claim 1 , wherein the processor is configured to select the subset of shortest paths by filtering paths that are longer than a predetermined path length.

4. 2. The system of claim 1, wherein the interface is configured to receive the EP map having the region specified by an early late junction (EML) LAT range by receiving a region bounded by a conduction block curve.

5. 2. The system of claim 1, wherein the processor is configured to select the shortest path based on the direction of the activation wave velocity vector by filtering paths where the activation wave velocity vector is orthogonal to a tangent to the path up to a given angular tolerance.

6. 2. The system of claim 1, wherein the processor is configured to generate the composite tag by annotating electrograms with segmented regions and extracting LAT values ​​using the annotated electrograms.

7. The system of claim 1 , wherein the heart chamber is the atrium and the arrhythmia is atrial flutter.

8. The system of claim 1 , wherein the heart chamber is a ventricle and the arrhythmia is a ventricular tachycardia.

9. 1. A method for identifying candidate locations for ablation, the method comprising: receiving an electrophysiological (EP) map including an anatomical surface of a heart chamber, overlaid with (i) activation wave velocity vectors, (ii) data points including locations on the anatomical surface of the heart chamber and respective local activation times (LATs), and (iii) an area specified by an early late junction (EML) LAT range; identifying a set of shortest paths on the cardiac surface between different EML regions; selecting one or more ranges of LAT values ​​characterized by a lowest prevalence across the data points of the EP map; generating a composite tag for the locations having LAT values ​​within the one or more ranges of the LAT value 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 the activation wave speed vector for each of the shortest paths; presenting the selected subset of the shortest paths as candidate slow conduction regions for ablation; A method comprising:

10. The method of claim 9 , wherein selecting the one or more ranges of LAT values ​​comprises selecting one or more LAT bins of a LAT histogram.

11. The method of claim 9 , wherein selecting the subset of the shortest paths comprises filtering paths that are longer than a predetermined path length.

12. 10. The method of claim 9, wherein receiving the EP map having the region specified by an early-late junction (EML) LAT range comprises receiving a region bounded by a conduction block curve.

13. 10. The method of claim 9, wherein selecting the shortest path based on the direction of the activation wave velocity vector comprises filtering paths where the activation wave velocity vector is parallel to a tangent to the path up to a given angular tolerance.

14. 10. The method of claim 9, wherein generating the composite tag comprises annotating electrograms with segmented regions and extracting LAT values ​​using the annotated electrograms.

15. 10. The method of claim 9, wherein the heart chamber is the atrium and the arrhythmia is atrial flutter.

16. 10. The method of claim 9, wherein the heart chamber is a ventricle and the arrhythmia is ventricular tachycardia.

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