Atrial fibrillation mapping using atrial fibrillation cycle length (AFCL) gradients

Patent metadata

Field	Value
Publication number	US-11160481-B2
Application number	US-201816108863-A
Country	US
Kind code	B2
Filing date	Aug 22, 2018
Priority date	Aug 22, 2018
Publication date	Nov 2, 2021
Grant date	Nov 2, 2021

Abstract

A method including calculating, at multiple intra-cardiac locations, respective average atrial fibrillation cycle-length (AFCL) values. A determination is made as to whether the calculated average AFCL values are indicative of a regular atrial fibrillation (AF) activity. Gradients between pairs of the average AFCL values are calculated for a plurality of average AFCL values that are determined to be indicative of regular AF activity. The calculated AFCL gradients are presented to a user, overlaid on a map of at least a portion of the heart.

First claim

The invention claimed is:

1. A method for atrial fibrillation mapping using atrial fibrillation cycle length gradients, the method comprising:
calculating, at multiple intra-cardiac locations, respective average atrial fibrillation cycle-length (AFCL) values, wherein the multiple intra-cardiac locations are different locations relative to a source of atrial fibrillation;
determining, utilizing statistical analysis, whether the calculated average AFCL values are indicative of a regular atrial fibrillation (AF) activity for all of the multiple intra-cardiac locations;
for a plurality of average AFCL values that are determined to be indicative of regular AF activity, calculating gradients between pairs of the average AFCL values; and
presenting the calculated AFCL gradients, over time, to a user, overlaid on a map of at least a portion of the heart.

2. The method according to claim 1 , wherein determining whether an average AFCL value is indicative of regular AF activity comprises checking whether the average AFCL value is between a preset lower limit and a preset upper limit.

3. The method according to claim 1 , wherein determining whether an average AFCL value is indicative of regular AF activity comprises checking whether a standard deviation (SD) of the average AFCL value is smaller than a preset SD limit.

4. The method according to claim 1 , wherein calculating the gradients comprises calculating an AFCL gradient for a pair of average AFCL values that were derived from electrocardiograms acquired at different times.

5. The method according to claim 1 , wherein presenting the AFCL gradients comprises color-coding the AFCL gradients according to at least sizes and directions of the AFCL gradients.

6. The method according to claim 1 , wherein presenting the AFCL gradients comprises denoting on the map arrows indicative of locations at which the AF originates, or through which the AF propagates.

7. The method according to claim 1 , wherein presenting the AFCL gradients comprises displaying on the map an animation comprising at least one of initiation and propagation of the regular AF activity.

8. The method according to claim 1 , and comprising presenting the average AFCL values to the user, overlaid on the map.

9. The method according to claim 8 , wherein presenting the average AFCL values comprises color-coding locations on the map according to the average AFCL values at the locations.

10. A system for atrial fibrillation mapping using atrial fibrillation cycle length gradients, the system comprising:
a memory, which is configured to store atrial fibrillation cycle-length (AFCL) values corresponding to respective multiple intra-cardiac locations; and a processor, which is configured to:
calculate from the stored AFCL values, average AFCL values at the respective multiple intra-cardiac locations, wherein the multiple intra-cardiac locations are different locations relative to a source of atrial fibrillation;
determine, using statistical analysis, whether the calculated average AFCL values are indicative of a regular atrial fibrillation (AF) activity for all of the multiple intra-cardiac locations;
for a plurality of average AFCL values that are determined to be indicative of regular AF activity, calculate gradients, over time, between pairs of the average AFCL values; and
present the calculated AFCL gradients to a user, overlaid on a map of at least a portion of the heart.

11. The system according to claim 10 , wherein the processor is configured to determine whether an average AFCL value is indicative of regular AF activity by checking whether the average AFCL value is between a preset lower limit and a preset upper limit.

12. The system according to claim 10 , wherein the processor is configured to determine whether an average AFCL value is indicative of regular AF activity by checking whether a standard deviation (SD) of the average AFCL value is smaller than a preset SD limit.

13. The system according to claim 10 , wherein the processor is configured to calculate an AFCL gradient for a pair of average AFCL values that were derived from electrocardiograms acquired at different times.

14. The system according to claim 10 , wherein the processor is configured to present the AFCL gradients by color-coding the AFCL gradients according to at least sizes and directions of the AFCL gradients.

15. The method according to claim 10 , wherein the processor is configured to present the AFCL gradients by denoting on the map arrows indicative of locations at which the AF originates, or through which the AF propagates.

16. The system according to claim 10 , wherein the processor is configured to present the AFCL gradients by displaying on the map an animation comprising at least one of initiation and propagation of the regular AF activity.

17. The system according to claim 10 , wherein the processor is further configured to present the average AFCL values to the user, overlaid on the map.

18. The system according to claim 10 , wherein the processor is configured to present the average AFCL values by color-coding locations on the map according to the average AFCL values at the locations.

Assignees

• Biosense Webster Israel Ltd
• Pappone Carlo

Inventors

• Zeidan Ziyad
• Turgeman Aharon
• Cohen Benjamin
• Bar-Tal Meir
• Bar-On Tal Haim
• Pappone Carlo

Classifications

• A61B2018/00839

  Bioelectrical parameters, e.g. ECG, EEG · CPC title

• A61B2018/00791

  Temperature · CPC title

• A61B18/00

  Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body (eye surgery A61F9/007; ear surgery A61F11/00) · CPC title

• A61B5/7239 Primary

  using differentiation including higher order derivatives · CPC title

• A61B5/6858

  with a distal basket, e.g. expandable basket · CPC title