Automatic creation of multiple electroanatomic maps

• US 10,376,221 B2
• Filed: 07/06/2016
• Issued: 08/13/2019
• Est. Priority Date: 07/06/2016
• Status: Active Grant

• Current Assignee: Biosense Webster Israel Ltd. (Johnson & Johnson)
• Original Assignee: Biosense Webster Israel Ltd. (Johnson & Johnson)
• Inventors: Iyun, Ofra, Salomon, Noga, Givaty, Galia, Guzi, Eliran, Rubinstein, Vladimir, Bar-Tal, Meir, Ziv-Ari, Morris
• Primary Examiner(s): Schaetzle, Kennedy
• Application Number:
  US15/202,990
• Publication Number:
  US 20180008203A1
• Time in Patent Office: 1,133 Days
• Field of Search: None
• CPC Class Codes: A61B 5/287 Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS]
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/339 Displays specially adapted therefor
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/35 by template matching
• CPC Class Codes: A61B 5/6858 with a distal basket, e.g. expandable basket
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G09B 23/288 for artificial respiration or heart massage
• CPC Class Codes: G09B 23/30 Anatomical models G09B23/281 - G09B23/288 take precedence
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Cardiac electrograms are recorded in a plurality of channels. Beats are classified automatically into respective classifications according to a resemblance of the morphologic characteristics of the beats to members of a set of templates. Respective electroanatomic maps of the heart are generated from the classified beats.

Claims

1. A method, comprising the steps of:

recording electrograms of a heart of a living subject in a plurality of channels, the electrograms comprising a plurality of beats having morphologic characteristics;

automatically placing the beats into respective classifications according to a resemblance of the morphologic characteristics of the beats to members of a set of templates by calculating respective overall correlations between instances of a selected beat in all the channels and the members of the set of templates and associating the selected beat with a member of the set of templates having a highest ranked one of the overall correlations when the highest ranked one of the overall correlations exceeds a predefined correlation threshold; and

concurrently generating multiple electroanatomic maps of the heart from the beats in the respective classifications.

2. The method according to claim 1, wherein recording is performed with a plurality of electrodes to produce multiple respective electrograms.

3. The method according to claim 1, wherein the set of templates comprises predefined templates.

4. The method according to claim 1, further comprising the steps of:

when none of the overall correlations exceeds the predefined correlation threshold creating a new member of the set of templates with the selected beat.

5. The method according to claim 1, wherein placing the beats into respective classifications comprises the steps of:

creating a new member of the set of templates with a selected beat;

calculating an overall correlation between instances of the selected beat in all the channels and the new member; and

when the overall correlation exceeds a predefined correlation threshold associating the selected beat with the new member.

6. The method according to claim 5, wherein calculating an overall correlation comprises:

calculating respective correlations between the instances of the selected beat in the channels and the new member; and

weighting the respective correlations according to maximum signal amplitudes of the instances of the selected beat in the electrograms.

7. The method according to claim 5, further comprising:

when the overall correlation fails to exceed the predefined correlation threshold;

shifting a phase of the electrograms; and

thereafter iterating the steps of calculating and associating.

8. An apparatus comprising:

a probe having a plurality of electrodes on a distal portion thereof;

electrical circuitry for recording respective time-varying electrograms from the electrodes when the probe is at a location in a heart of a living subject;

a memory for storing the electrograms;

a display; and

a processor connected to the memory and operative for performing the steps of;

recording the electrograms in a plurality of channels, the electrograms comprising a plurality of beats having morphologic characteristics;

automatically placing the beats into respective classifications according to a resemblance of the morphologic characteristics of the beats to members of a set of templates by calculating respective overall correlations between instances of a selected beat in all the channels and the members of the set of templates and associating the selected beat with a member of the set of templates having a highest ranked one of the overall correlations when the highest ranked one of the overall correlations exceeds a predefined correlation threshold; and

concurrently generating multiple electroanatomic maps of the heart from the beats in the respective classifications; and

presenting the maps on the display.

9. The apparatus according to claim 8, wherein the set of templates comprises predefined templates.

10. The apparatus according to claim 8, wherein the processor is operative for performing the step of:

when none of the overall correlations exceeds the predefined correlation threshold creating a new member of the set of templates with the selected beat.

11. The apparatus according to claim 8, wherein placing the beats into respective classifications comprises the steps of:

creating a new member of the set of templates with a selected beat;

calculating an overall correlation between instances of the selected beat in all the channels and the new member; and

when the overall correlation exceeds a predefined correlation threshold associating the selected beat with the new member.

12. The apparatus according to claim 11, wherein calculating an overall correlation comprises:

calculating respective correlations between the instances of the selected beat in the channels and the new member; and

weighting the respective correlations according to maximum signal amplitudes of the instances of the selected beat in the electrograms.

13. The apparatus according to claim 11, wherein the processor is operative for performing the steps of:

when the overall correlation fails to exceed the predefined correlation threshold;

shifting a phase of the electrograms; and

thereafter iterating the steps of calculating and associating.

14. A computer software product, including a non-transitory computer-readable storage medium in which computer program instructions are stored, which instructions, when executed by a computer, cause the computer to perform the steps of:

accepting electrograms of a heart of a living subject in a plurality of channels, the electrograms comprising a plurality of beats having morphologic characteristics;

automatically placing the beats into respective classifications according to a resemblance of the morphologic characteristics of the beats to members of a set of templates by calculating respective overall correlations between instances of a selected beat in all the channels and the members of the set of templates and associating the selected beat with a member of the set of templates having a highest ranked one of the overall correlations when the highest ranked one of the overall correlations exceeds a predefined correlation threshold; and

concurrently generating multiple electroanatomic maps of the heart from the beats in the respective classifications.

15. The computer software product according to claim 14, wherein the computer is further instructed to perform the steps of:

when none of the overall correlations exceeds the predefined correlation threshold creating a new member of the set of templates with the selected beat.

16. The computer software product according to claim 14, wherein placing the beats into respective classifications comprises the steps of:

creating a new member of the set of templates with a selected beat;

calculating an overall correlation between instances of the selected beat in all the channels and the new member; and

when the overall correlation exceeds a predefined correlation threshold associating the selected beat with the new member.

17. The computer software product according to claim 16, wherein calculating an overall correlation comprises:

calculating respective correlations between the instances of the selected beat in the channels and the new member; and

weighting the respective correlations according to maximum signal amplitudes of the instances of the selected beat in the electrograms.

18. The computer software product according to claim 16, further comprising:

when the overall correlation fails to exceed the predefined correlation threshold;

shifting a phase of the electrograms; and

thereafter iterating the steps of calculating and associating.