Connectivity analysis for arrhythmia drivers

Patent metadata

Field	Value
Publication number	US-10806359-B2
Application number	US-201715498992-A
Country	US
Kind code	B2
Filing date	Apr 27, 2017
Priority date	Apr 27, 2017
Publication date	Oct 20, 2020
Grant date	Oct 20, 2020

Abstract

One or more non-transitory computer-readable media have instructions executable by a processor and programmed to perform a method. The method includes analyzing the electrical data to locate one or more wave front lines over a given time interval. The electrical data represents electrophysiological signals distributed across a cardiac envelope for one or more time intervals. A respective trajectory is determined for each wave end of each wave front line that is located across the cardiac envelope over the given time interval. A set of connected trajectories are identified based on a duration that the trajectories are connected to each other by a respective wave front line during the given time interval. A connectivity association is characterized for the trajectories in the set of connected trajectories.

First claim

What is claimed is:

1. One or more non-transitory computer-readable media having instructions executable by a processor, the instructions programmed to perform a method comprising:
analyzing electrical data to locate one or more wave front lines over a given time interval, the electrical data representing electrophysiological signals distributed across a spatial cardiac envelope within a patient's body for one or more time intervals;
determining a respective trajectory for each wave end of each wave front line that is located across the cardiac envelope over the given time interval;
identifying a set of connected trajectories based on a duration that the trajectories are connected to each other by a respective wave front line during the given time interval; and
characterizing a connectivity association for the trajectories in the set of connected trajectories.

2. The media of claim 1 , wherein the method further comprises:
determining a distance between the trajectories in the set of connected trajectories; and
discriminating between a plurality of different types of predetermined connectivity associations for the set of connected trajectories based on the determined distance.

3. The media of claim 2 , wherein discriminating between the plurality of different types of predetermined connectivity associations further comprises applying a spatial threshold to ascertain which one of the plurality of different types of predetermined connectivity associations characterizes the connectivity association.

4. The media of claim 3 , wherein applying the spatial threshold further comprises applying multiple spatial thresholds to the determined distances to ascertain which one of the plurality of different types of predetermined connectivity associations characterizes the connectivity association.

5. The media of claim 4 , wherein the plurality of different types of predetermined connectivity associations include a local connectivity association, a far connectivity association and an intermediate connectivity association, and
wherein the method further comprises:
specifying the local connectivity association for the set of connected trajectories in response to determining that the distance is less than a first threshold,
specifying the far connectivity association for the set of connected trajectories in response to determining that the distance exceeds a second threshold, and
specifying the intermediate connectivity association for the set of connected trajectories in response to determining that the distance is outside of the first and second thresholds.

6. The media of claim 1 , wherein identifying connected trajectories further comprises:
determining the duration that the trajectories are connected to each other by the wave front line during the given time interval, and
wherein the trajectories are identified as being connected in response to determining that the duration that the trajectories are connected to each other during the given time interval exceeds a predetermined time period.

7. The media of claim 6 , wherein the predetermined time period is programmable in response to a user input.

8. The media of claim 6 , further comprising:
determining a spatial distance between the trajectories in the set of connected trajectories; and
specifying which type of connectivity association characterizes the connectivity association for the set of connected trajectories based on the determined distance relative to a spatial threshold and the duration that the trajectories are connected to each other during the given time interval relative to a time threshold,
wherein the spatial threshold and/or the time threshold are programmable in response to a user input.

9. One or more non-transitory computer-readable media having instructions executable by a processor, the instructions programmed to perform a method comprising:
analyzing electrical data to locate one or more wave front lines over a given time interval, the electrical data representing electrophysiological signals distributed across a cardiac envelope for one or more time intervals;
determining a respective trajectory for each wave end of each wave front line that is located across the cardiac envelope over the given time interval;
identifying a set of connected trajectories based on a duration that the trajectories are connected to each other by a respective wave front line during the given time interval;
characterizing a connectivity association for the trajectories in the set of connected trajectories and
generating an output visualization to display the connected trajectories spatially on a graphical representation of a heart.

10. The media of claim 1 , wherein the electrophysiological signals correspond to measured or reconstructed signals at a plurality of nodes distributed across the cardiac envelope for a plurality of time intervals,
wherein the method further comprises repeating the analyzing, determining, identifying and characterizing for each of the plurality of time intervals to characterize a respective connectivity association for each set of connected trajectories.

11. The media of claim 10 , wherein the method further comprises generating an output visualization to display a representation of at least some of connected trajectories and/or connectivity associations spatially on a graphical representation of a heart.

12. The media of claim 11 , wherein the method further comprises prioritizing one type of connectivity association relative to another type of connectivity association in the output visualization according to a cause of arrhythmia.

13. The media of claim 12 , wherein the cause of arrhythmia is defined in response to a user input specifying the cause.

14. The media of claim 10 , wherein the method further comprises discriminating between a plurality of different types of predetermined connectivity associations for each set of connected trajectories according to at least one of spatial and/or temporal criteria.

15. The media of claim 1 , wherein the electrophysiological signals distributed across the cardiac envelope correspond to signals at nodes that are derived based on at least one of invasively acquired electrical signals for the patient or non-invasively acquired electrical signals for the patient.

16. A system comprising:
memory to store machine readable instructions and data, the data comprising store electrical data representing electrophysiological signals distributed across a cardiac envelope for one or more time intervals;
at least one processor to access the memory and execute the instructions, the instructions comprising:
a wave front analyzer that analyzes electrical data for a given time interval to identify a wave front line across the cardiac envelope;
a trajectory detector that detects a respective trajectory for wave ends of the wave front line over the given time interval;
a connectivity detector that identifies a set of connected trajectories according to a duration that the trajectories of wave ends are connected to each other by the wave front line over the given time interval;
a connectivity characterization function that applies spatial and/or temporal criteria to characterize a connectivity association for trajectories in the set of connected trajectories; and
an output generator that provides output data to drive a display with a graphical representation of the connectivity association for the trajectories in the set of connected trajectories.

17. The system of claim 16 , wherein the connectivity characterization function determines a distance betwe

Assignees

• Cardioinsight Technologies Inc

Inventors

• Zeng Qingguo
• Lou Qing
• Bokan Ryan M
• Jia Ping
• Edel Connor S
• Ramanathan Charulatha

Classifications

• A61B5/339

  Displays specially adapted therefor · CPC title

• A61B5/349 Primary

  Detecting specific parameters of the electrocardiograph cycle · CPC title

• A61B5/316 Primary

  Modalities, i.e. specific diagnostic methods · CPC title

• A61B5/04012 Primary

  Human Necessities · mapped topic

• A61B5/044

  Human Necessities · mapped topic