Estimation and visualization of electric anatomical (EA) analysis quality of EA map

Abstract

To visualize analysis quality in an electric anatomical (EA) map.SOLUTION: A method includes reception of an electric anatomical (EA) map of at least a part of a cardiac ventricle. Quality of EA analysis of the EA map is scored. On the basis of scoring, one or more regions are identified in a mapped part which is mapped as the part where defined quality reference is not satisfied. One or more regions are displayed on the EA map displayed for a user.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates generally to the analysis of electroanatomical (EA) maps, and more particularly to systems and methods for visualization of analysis quality in EA maps. [Background technology]

[0002] EA map visualization methods have been previously discussed in the patent literature. For example, U.S. Patent No. 11,478,182, filed January 7, 2021, describes a method that includes receiving (i) a modeled surface of at least a portion of a heart, and (ii) a plurality of EA values ​​measured at a plurality of respective locations within the heart. A plurality of regions are defined on the modeled surface, and for each region, a confidence level for the EP value in which the location of the EA value falls within the region is estimated. The modeled surface is presented to a user, including (i) the EA values ​​overlaid on the modeled surface, and (ii) a graphically visualized confidence level within each region of the modeled surface.

[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. [Brief description of the drawings]

[0004] [Figure 1] FIG. 1 is a schematic, pictorial illustration of a catheter-based electroanatomical (EA) mapping and ablation system, according to one embodiment of the present disclosure. [Figure 2A] 1 is an EA map of the left atrium according to an example of the present disclosure. [Figure 2B] 2B is a shading mask showing areas of the EA map of FIG. 2A having poor EA analysis quality, according to an example of the present disclosure. [Figure 2C] 2C is a combined EA map resulting from overlaying the mask of FIG. 2B on the EA map of FIG. 2A according to an example of the present disclosure. [Diagram 3]1 is a flow chart that generally illustrates a method for estimating and visualizing EA analysis quality of an EA map, according to an example of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0005] overview Electroanatomical (EA) mapping of the ventricles of patients suffering from arrhythmia requires the acquisition of a sufficient number of data points to adequately capture each cardiac chamber wall location and its respective electrical information. A physician performing cardiac EA mapping aims to achieve an optimal diagnostic quality EA map of at least a portion of the ventricle. The quality of the EA map depends, for example, on the stability of the arrhythmia and the ability to cover a sufficient portion of the ventricle. The EA quality is reflected in the output of a dedicated algorithm that analyzes the EA characteristics based on the set of acquired data points.

[0006] Examples of analyses performed by such EA algorithms include calculation of local conduction vectors (LCV) based on the strongest detected trend in local activation times (LAT), coherent mapping analysis, and contact proximity index (TPI). These calculations provide outputs after spatial interpolation. Other examples include CARTO® points / "visitags" distance from the surface, and data point density, which can cause geographic anatomical inaccuracies if not accurate / sufficient.

[0007] As found by the inventors, the EP quality of the above EA analysis algorithms may be insufficient or absent in some areas of the EA map unless the user is fully aware of this fact. For example, in the LCV algorithm, if the algorithm cannot detect a trend in the LAT values, it will not present a vector on the map. The lack of trend may be caused due to insufficient data points in a specified area or intramural signal that may present similar LAT values. Another example is coherent mapping, where excessive interpolation may be applied due to a lack of EA data points. Furthermore, there is no general method to estimate the overall EA quality of a map. In particular, there is no indication for each map region that can easily reflect the EA quality of the output of the EA algorithm used in analyzing and visualizing the EA map therein.

[0008] The examples of the present disclosure described herein provide a technique that includes an automated algorithm that provides an overlap map that scores the EA quality of the output of one or more EA algorithms used to construct the EA map at each location on the EA map. The disclosed technique can guide the physician to avoid misinterpretation of the EA map. Based on the instructions from the disclosed method, rather than accepting the EA map as is, the physician may attempt to improve a poor EA analysis by remapping a particular ventricular area or by correcting the analysis.

[0009] When using the LCV algorithm, a map region may receive a low score due to areas where the conduction vectors are intentionally omitted by the algorithm due to the fact that there is no reciprocal trend in the LAT, for example. A physician unaware of that intentional omission may miss clinically significant demarcated areas that do not show a strong LAT trend, but rather circular multi-directional propagation, due to the nature of conduction through diseased tissue. By shading areas with low EA algorithm output quality in the map, the disclosed technology alerts the physician not to make such errors.

[0010] Another example of a map region with a low quality score is an area in a coherent EA map where over-interpolation has occurred. A physician who is unaware of the over-interpolation will trust the EA map without suspecting that the actual data in that area is sparse. Again, by shading areas in the map with low EA quality, the disclosed technique warns the physician not to make such an error.

[0011] In one example, a method is provided that includes receiving an EA mapped portion of a ventricle. The portion includes analyzed EA characteristics of the ventricle using one or more EA analysis algorithms. A processor executes an algorithm to score a quality of the EA analysis output over the EA mapped portion. In one example, the EA quality score may be normalized to a range between 0 and 1, and based on this score, the processor estimates whether the EA quality is insufficient (e.g., the EA quality does not meet a defined quality criterion) in one or more regions of the EA mapped portion. The processor marks any EAs found to be insufficient in one or more regions on the EA map. The display map is displayed to a user.

[0012] The processor may indicate such poor EA analysis map areas by constructing a grayscale map of only those locations that are above a high threshold or below a low threshold. The processor may blend (e.g., combine) the grayscale information with the current EA map coloring. Blending may be reflected in some visualizations, such as applying shading (e.g., a lower level of transparency) to areas that have a quality score below a given threshold. In another blending example, the processor overlays the EA map with a layer of graphical symbols whose format varies according to the quality score.

[0013] The input to the scoring algorithm depends on the clinical problem. Different clinical scenarios (e.g., atrial arrhythmias vs. ventricular arrhythmias) use different EA algorithms. The disclosed technique estimates the algorithm output quality to score the associated EA map. In some examples, the EA algorithm is preselected and the map is received and estimated as is. In other examples, the user can select or deselect all or some of the above EA analysis algorithms (or others) via a graphical user interface (GUI). The selection may be available, for example, as a checkbox in the GUI.

[0014] In the example detailed below, the quality score is a weighted sum of the quality scores of the outputs from two or more EA analysis algorithms (eg, bipolar amplitude and TPI values).

[0015] In another example, to indicate insufficiency of EA analysis in one or more regions on the EA map, the disclosed techniques may apply steps of filtering outlier data points (based on scores), projecting the data points onto the anatomical map surface, and then applying Laplacian interpolation to the quality scores.

[0016] System Description FIG. 1 is a schematic, pictorial illustration of a catheter-based electroanatomical (EA) mapping and ablation system 10, according to one embodiment of the present disclosure.

[0017] The system 10 includes multiple catheters that are percutaneously inserted by the physician 24 through the patient's vascular system into the cavities or vasculature of the heart 12 (see inset 45). Typically, a delivery sheath catheter is inserted into a ventricle, such as into the left or right atrium, near the desired location of the heart 12. The multiple catheters can then be inserted into the delivery sheath catheter to reach the desired location. The multiple catheters can include catheters dedicated to pacing, catheters for sensing intracardiac electrogram signals, catheters dedicated to ablation, and / or catheters dedicated to both EA mapping and ablation. The exemplary catheter 14 shown herein is configured to sense bipolar electrograms. The physician 24 brings a distal tip 28 of the catheter 14 (hereinafter referred to as the "distal end assembly 28") into contact with the heart wall to sense the target site of the heart 12. For ablation, the physician 24 similarly brings the distal end of an ablation catheter to the target site.

[0018] As seen in inset 65, catheter 14 is an exemplary catheter including a basket-like distal tip 28 including one or preferably multiple electrodes 26, optionally distributed across multiple splines 22 at distal tip 28, and configured to sense IEGM signals. Catheter 14 may further include a position sensor 29 embedded in or near distal tip 28 on shaft 46 of catheter 14 to track the position and orientation of distal tip 28. Optionally and preferably, position sensor 29 is a magnetic-based position sensor including three magnetic coils for sensing three-dimensional (3D) position and orientation. As seen, distal tip 28 further includes an expander / collapse rod 42 of expandable assembly 28, which is mechanically connected to basket assembly 28 at distal edge 41 of assembly 28.

[0019] The magnetic-based position sensor 29 may operate in conjunction with a location pad 25 that includes a plurality of magnetic coils 32 configured to generate a magnetic field within a predetermined working volume. The real-time position of the distal tip 28 of the catheter 14 may be tracked based on the magnetic field generated by the location pad 25 and sensed by the magnetic-based position sensor 29. Details of magnetic-based position sensing technology are described in U.S. Patent Nos. 5,5391,199; 5,443,489; 5,558,091; 6,172,499; 6,239,724; 6,332,089; 6,484,118; 6,618,612; 6,690,963; 6,788,967; and 6,892,091.

[0020] The system 10 includes one or more electrode patches 38 positioned for skin contact on the patient 23 to establish a positional reference for the location pads 25 and impedance-based tracking of the electrodes 26. For impedance-based tracking, a current is directed to the electrodes 26 and sensed at the electrode skin patch 38, so that the location of each electrode can be triangulated via the electrode patch 38. Details of impedance-based position tracking technology are described in U.S. Patent Nos. 7,536,218, 7,756,576, 7,848,787, 7,869,865, and 8,456,182.

[0021] Recorder 11 displays cardiac signals 21 (e.g., electrograms acquired at each tracked cardiac tissue location) acquired using body surface ECG electrodes 18, and intracardiac electrograms acquired using electrodes 26 of catheter 14. Recorder 11 may include pacing capability for pacing the cardiac rhythm and / or may be electrically connected to a stand-alone pacer.

[0022] The system 10 may include an ablation energy generator 50 adapted to deliver ablation energy to one or more electrodes at the distal tip of a catheter configured for ablation. The energy generated by the ablation energy generator 50 may include, but is not limited to, radio frequency (RF) energy or pulsed field ablation (PFA) energy, including unipolar or bipolar high voltage direct current pulses such as may be used to effect irreversible electroporation (IRE), or combinations thereof.

[0023] The patient interface unit (PIU) 30 is an interface configured to establish electrical communication between the catheters, the electrophysiology equipment, the power source, and the workstation 55 to control the operation of the system 10 and to receive EA signals from the catheters. The electrophysiology equipment of the system 10 may include, for example, a number of catheters, location pads 25, body surface ECG electrodes 18, electrode patches 38, an ablation energy generator 50, and a recorder 11. Optionally and preferably, the PIU 30 additionally includes processing capabilities to perform real-time calculations of catheter position and perform ECG calculations. The interface 30 may also be configured to receive files (e.g., files of EA maps), for example, using a communication line or a memory stick.

[0024] The workstation 55 includes a processor 56 unit having a memory 57, a memory or storage device loaded with suitable operating software, and a user interface function. The workstation 55 may optionally provide multiple functions, including (i) modeling the endocardial anatomical structures in three-dimension (3D) and rendering the model or anatomical map 20 for display on the display device 27, (ii) displaying activation sequences (or other data) compiled from the recorded cardiac signals 21 in a representative visual display or image superimposed on the rendered anatomical map 20 on the display device 27, (iii) displaying real-time positions and orientations of multiple catheters within the cardiac chambers, and (iv) displaying sites of interest, such as locations where ablation energy is applied, on the display device 27. One commercially available product embodying elements of the system 10 is available as the CARTO™ 3 system, available from Biosense Webster, Inc., 31A Technology Drive, Irvine, Calif., 92618.

[0025] In the disclosed example, processor 56 executes an algorithm that provides an overlap map (e.g., including a shading layer superimposed on anatomical map 20) that represents a score of the EA quality of the EA map at each location on the EA map. The EA analysis algorithms may be preselected or physician 24 may select / deselect, e.g., via GUI 111, at least a portion of the above-listed EA analysis algorithms to be used in the EA map analysis.

[0026] In some embodiments, processor 56 typically comprises a general-purpose computer that is programmed with software to perform the functions described herein. The software may be downloaded into the computer in electronic form, for example over a network, or alternatively or additionally may be provided and / or stored on non-transitory tangible media, such as magnetic, optical, or electronic memory.

[0027] This particular configuration of system 10 is provided as an example to illustrate the particular problems addressed by the embodiments of the present disclosure and to demonstrate the application of these embodiments in improving the performance of such systems. However, the embodiments of the present disclosure are in no way limited to this particular type of exemplary system, and the principles described herein may be applied to other types of medical systems as well. For example, other multi-electrode catheter types may be used, such as OCTARAY™ catheters or flat catheters.

[0028] Visualization of EA analysis quality for ventricular EA maps 2A-2C are as follows: FIG. 2A is an EA map of the left atrium; FIG. 2B is a shading mask to indicate areas of the EA map with poor EA analysis quality; and FIG. 2C is a combined EA map resulting from overlaying the mask of FIG. 2B on the EA map of FIG. 2A, according to an example of the present disclosure.

[0029] The EA map 200 (seen in FIG. 2A) includes an anatomical surface and respective electrical values ​​(e.g., activation amplitude and / or time) at each mapped location on the surface. To provide a continuous format EA map, interpolation on the EA values ​​is used in the EA map. However, in some regions of the EA map 200, the interpolation may be of poor EA analysis quality, such as in region 204.

[0030] The disclosed algorithm scores the EA analysis quality and provides a score in the form of a shading mask 201 (seen in FIG. 2B ). The shading mask 201 includes quality scores for at least some of the regions of the EA map 200, where the scores are normalized in the range [0,1].

[0031] As can be seen in Figure 2B, the shading mask 201 contains dark regions 205 with low scores. The dark areas indicate to the user that the EA analysis quality in these regions is poor and therefore unreliable.

[0032] The combined EA map 202 (seen in FIG. 2C) shows this poor quality EA analysis as a gray area 206. Based on this indication, the user may, for example, EA remap the area 206.

[0033] More generally, mixing information from the quality mask with the EA map 200 coloring can be reflected by several visualizations.

[0034] 1. As a transparent layer, the transparency and gray level color are also affected by the score.

[0035] 2. Bump mapping, where the bump is influenced by the score (e.g. a high score indicates a smaller bump, a low score indicates a larger bump).

[0036] In an exemplary implementation, a processor receives a region of interest (ROI) on an anatomical map.

[0037] The quality is calculated from the EA analysis algorithm based on the following criteria: LCV incoherence (possible indication of fractionated signals) Data point tag distance from surface (geometric anatomical inaccuracies) Contact level TPI · Data point density Excessive interpolation of coherent areas

[0038] All or some of the above algorithms (or others) may be pre-selected or selected / deselected by the user via GUI 111 of FIG.

[0039] Finally, while the score visualization seen in the example of FIG. 2B is of EA analysis quality of atrial fibrillation (AFib) maps, in general the scores are problem dependent: different clinical scenarios (e.g., atrial arrhythmias vs. ventricular arrhythmias) will use different EA analysis algorithms due to the disclosed techniques using their outputs to score the relevant EA maps.

[0040] Scoring EA analysis quality of ventricular EA maps An example of the disclosed method for calculating the EA quality score is provided herein. i Assume the following selected characteristics of each EA analysis algorithm (eg, bipolar amplitude and TPI): ·Each F i is m i <F i <M i has a range of At each location p on the map, each feature F i There exists a value for (p) Then, the EA quality score can be given by the weighted sum

[0041]

number

[0042] A method for estimating and visualizing EA analysis quality of ventricular EA maps 3 is a flow chart that illustrates a schematic of a method for estimating and visualizing the quality of an EA map 200 according to an example of the present disclosure. According to the example presented, the algorithm executes a process that starts with an EA map reception step 302, where the processor 56 receives an EA map that has been EA analyzed using an EA analysis algorithm (such as the LCV described above). It is noted that the physician 24 may adjust the EA analysis parameters or algorithms used via the GUI 111.

[0043] Next, the processor executes the disclosed algorithm to assign an EA quality score to the EA analysis in the EA map in a scoring step 304 .

[0044] Based on the score, the processor, in a region estimation step 306, estimates one or more regions of the EA map (eg, of EA map 200) as having too low (eg, insufficient) EA analysis quality.

[0045] In an area indication step 308, the processor indicates (e.g., marks) one or more areas (e.g., regions) of the EA map as having insufficient EA analysis quality (e.g., EA quality, not meeting a defined quality criterion).

[0046] Finally, in an EA quality indication map presenting step 310, the processor 56 presents an EA quality indication EA map (eg, EA map 202) to the user.

[0047] The flowchart shown in Figure 3 has been chosen solely for purposes of conceptual clarity: other examples of the technique may include different algorithms and / or visualization steps, such as using blinking to highlight areas scored by the disclosed technique as having poor EA analysis quality. EXAMPLES

[0048] Example 1 The method includes receiving an electroanatomical (EA) map (200) of at least a portion of a cardiac chamber. The EA map is scored for quality of an EA analysis. Based on the scoring, one or more regions (204) are identified in the mapped portion as not meeting defined quality criteria. The one or more regions are indicated (206) on the EA map (202) that is displayed to a user.

[0049] Example 2 The method described in Example 1, wherein the EA analysis is performed by at least one algorithm selected from the list of algorithms consisting of: (i) local conduction vector (LCV), (ii) coherent EA (CEA) propagation, (iii) contact indication index (TPI), (iv) late activation time (LAT), and (v) fractional score.

[0050] Example 3 3. The method of any of Examples 1 and 2, wherein scoring the quality comprises calculating a weighted sum of quality scores of the output from two or more algorithms from the list.

[0051] Example 4 4. The method of any of Examples 1 to 3, wherein indicating (206) one or more regions on the EA map comprises overlaying the EA map with a layer of transparency according to the scoring.

[0052] Example 5 5. The method of any of the preceding claims, wherein indicating (206) one or more regions on the EA map includes overlaying the EA map with a layer of graphical symbols whose format varies according to the scoring.

[0053] Example 6 The method of any of Examples 1 to 5, wherein indicating (206) one or more regions (204) on the EA map includes (i) filtering outlier points based on the scoring, (ii) projecting the scoring onto the surface of the map, and (iii) applying Laplacian interpolation to the scoring.

[0054] Example 7 7. The method of any of the preceding claims, comprising displaying to a user an EA map (202) including the identified one or more regions (204).

[0055] Example 8 The system (10) includes an interface (30) and a processor (56). The interface is configured to receive an electroanatomical (EA) map (200) of at least a portion of a cardiac chamber. The processor (56) is configured to (i) score a quality of an EA analysis of the EA map, (ii) identify one or more regions (204) within the mapped portion as not meeting defined quality criteria based on the scoring, and (iii) indicate (206) the one or more regions on the EA map (202) that are displayed to a user.

[0056] Although the embodiments described herein primarily address cardiac diagnostic applications, the methods and systems described herein may also be used in other medical applications.

[0057] 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.

[0058] [Embodiment] (1) A method comprising: receiving an electroanatomical (EA) map of at least a portion of a cardiac chamber; Scoring a quality of the EA analysis of the EA map; and identifying one or more regions within the mapped portion as not meeting a defined quality criterion based on the scoring; indicating the one or more regions on an EA map to be displayed to a user. (2) The method of embodiment 1, wherein the EA analysis is performed by at least one algorithm selected from the list of algorithms consisting of: (i) local conduction vector (LCV), (ii) coherent EA (CEA) propagation, (iii) contact indication index (TPI), (iv) late activation time (LAT), and (v) fractional score. (3) The method of embodiment 2, wherein scoring the quality comprises calculating a weighted sum of quality scores of the output from two or more algorithms from the list. (4) The method of embodiment 1, wherein showing the one or more regions on the EA map includes overlaying the EA map with a layer of transparency according to the scoring. (5) The method of embodiment 1, wherein showing the one or more regions on the EA map includes overlaying the EA map with a layer of graphical symbols whose format varies according to the scoring.

[0059] (6) The method of claim 1, wherein indicating the one or more regions on the EA map includes: (i) filtering outlier points based on the scoring; (ii) projecting the scoring onto a surface of the map; and (iii) applying Laplacian interpolation to the scoring. (7) The method of embodiment 1, further comprising displaying the EA map including the identified one or more regions to a user. (8) A system comprising: an interface configured to receive an electroanatomical (EA) map of at least a portion of a cardiac chamber; and a processor, the processor comprising: Score the quality of the EA analysis of the EA map; identifying one or more regions within the mapped portion as not meeting a defined quality criterion based on the scoring; The system is configured to indicate the one or more regions on an EA map to be displayed to a user. (9) The system of embodiment 8, wherein the EA analysis is performed by at least one algorithm selected from the list of algorithms consisting of: (i) local conduction vector (LCV), (ii) coherent EA (CEA) propagation, (iii) contact indication index (TPI), (iv) late activation time (LAT), and (v) fractional score. (10) The system of embodiment 9, wherein the processor is configured to score the quality by calculating a weighted sum of quality scores of output from two or more algorithms from the list.

[0060] (11) The system of embodiment 8, wherein the processor is configured to indicate the one or more regions on the EA map by overlaying the EA map with a layer of transparency according to the scoring. (12) The system of embodiment 8, wherein the processor is configured to indicate the one or more regions on the EA map by overlaying the EA map with a layer of graphical symbols whose format varies according to the scoring. (13) The system of embodiment 8, wherein the processor is configured to indicate the one or more regions on the EA map by (i) filtering outlier points based on the scoring, (ii) projecting the scoring onto a surface of the map, and (iii) applying Laplacian interpolation to the scoring. (14) The system of embodiment 8, wherein the processor is further configured to display the EA map including the identified one or more regions to a user.

Claims

1. 1. A system comprising: an interface configured to receive an electroanatomical (EA) map of at least a portion of a cardiac chamber; and a processor, the processor comprising: Score the quality of the EA analysis of the EA map; Identifying one or more regions within the mapped portion as not meeting a defined quality criterion based on the scoring; The system is configured to indicate the one or more regions on an EA map to be displayed to a user.

2. 2. The system of claim 1, wherein the EA analysis is performed by at least one algorithm selected from the list of algorithms consisting of: (i) local conduction vector (LCV), (ii) coherent EA (CEA) propagation, (iii) contact indication index (TPI), (iv) late activation time (LAT), and (v) fractional score.

3. The system of claim 2 , wherein the processor is configured to score the quality by calculating a weighted sum of quality scores of outputs from two or more algorithms from the list.

4. The system of claim 1 , wherein the processor is configured to indicate the one or more regions on the EA map by overlaying the EA map with a layer of transparency according to the scoring.

5. 2. The system of claim 1, wherein the processor is configured to indicate the one or more regions on the EA map by overlaying the EA map with a layer of graphical symbols that change format according to the scoring.

6. 2. The system of claim 1, wherein the processor is configured to: (i) filter outlier points based on the scoring; (ii) project the scoring onto a surface of the map; and (iii) indicate the one or more regions on the EA map by applying a Laplacian interpolation to the scoring.

7. The system of claim 1 , wherein the processor is further configured to display the EA map including the identified one or more regions to a user.

8. 1. A method comprising: receiving an electroanatomical (EA) map of at least a portion of a cardiac chamber; Scoring the quality of the EA analysis of the EA map; and identifying one or more regions within the mapped portion as not meeting a defined quality criterion based on the scoring; indicating the one or more regions on an EA map to be displayed to a user.

9. 9. The method of claim 8, wherein the EA analysis is performed by at least one algorithm selected from the list of algorithms consisting of: (i) local conduction vector (LCV), (ii) coherent EA (CEA) propagation, (iii) contact indication index (TPI), (iv) late activation time (LAT), and (v) fractional score.

10. The method of claim 9 , wherein the scoring of the quality comprises calculating a weighted sum of quality scores of the output from two or more algorithms from the list.

11. The method of claim 8 , wherein indicating the one or more regions on the EA map comprises overlaying the EA map with a layer of transparency according to the scoring.

12. The method of claim 8 , wherein indicating the one or more regions on the EA map includes overlaying the EA map with a layer of graphical symbols that change format according to the scoring.

13. 9. The method of claim 8, wherein indicating the one or more regions on the EA map comprises: (i) filtering outlier points based on the scoring; (ii) projecting the scoring onto a surface of the map; and (iii) applying a Laplacian interpolation to the scoring.

14. The method of claim 8 , further comprising displaying the EA map including the identified one or more regions to a user.

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