Method to determine wavefront vector flow-field and vorticity from spatially-distributed recordings

Patent metadata

Field	Value
Publication number	US-2019104958-A1
Application number	US-201716087560-A
Country	US
Kind code	A1
Filing date	Mar 24, 2017
Priority date	Mar 24, 2016
Publication date	Apr 11, 2019
Grant date	—

Abstract

Methods and systems are provided for determination and mapping of vector fields which characterize wavefront motion through space and time. The inventive methods and systems utilize data from spatially-distributed locations and maps wavefront vector flow fields in an entirely automated manner. These maps can be used to characterize the activation as planar, centrifugal, or rotational. Further, the strength of rotation or divergence is determined from these fields and can be used to select spatial points of significantly increased rotational or focal activity. As applied to electrophysiological data recorded during heart rhythm disorders in patients, the inventive method provides a means of visual interpretation of complex activation maps. The information related to the strength and location of rotation and centrifugal activity during episodes of arrhythmia can guide therapies designed to treat such disorders.

First claim

1 . A method for analyzing complex cardiac activation patterns, comprising:
collecting, via a computer processor, a plurality of cardiac signals at a plurality of locations corresponding to spatial locations of a patient's heart; determining activation times within the cardiac signals; binning the activation times according to a selected bin size; coarse-graining the binned activation times to generate coarse-grained data; determining at least one wavefront flow field (WFF) for a plurality of time windows using the coarse-grained data; computing a local wavefront vorticity using the at least one WFF to determine rotational activity surrounding each spatial location; and generating a vorticity map indicating likely rotational sources of complex cardiac activations.

2 . The method of claim 1 , wherein determining the activation times further comprises interpolating the activation times.

3 . The method of claim 2 , further comprising smoothing the interpolated activation times by determining a time-averaged phase of a chosen time window.

4 . The method of claim 1 , wherein determining the wavefront flow field further comprises:
determining a direction of movement of each point on a wavefront between a first time point and a second time point to define a wavefront flow vector (WFV i ) for all times and all spatial points across a given window of time; and summing the WFV i for all spatial points over all times in a given time window to generate the WFF for all spatial points for the given time window.

5 . The method of claim 4 , wherein the WFV i is defined in forward time and reverse time.

6 . The method of claim 1 , further comprising:
computing a local wavefront divergence using the at least one WFF to determine focal activity surrounding each spatial location; and generating a divergence map indicating likely focal sources of complex cardiac activations.

7 . The method of claim 6 , wherein the step of generating a vorticity map or divergence map comprises convolving the vorticity map with a smoothing filter.

8 . The method of claim 6 , wherein likely rotational or focal sources of complex cardiac activations comprise points in the vorticity or divergence map exceeding a predetermined threshold.

9 . A system for analyzing complex cardiac activation patterns, the system comprising:
a computer processor programmed to execute the steps of:
collecting, via a computer processor, a plurality of cardiac signals at a plurality of locations corresponding to spatial locations of a patient's heart;
determining activation times within the cardiac signals;
binning the activation times according to a selected bin size;
coarse-graining the binned activation times to generate coarse-grained data;
determining at least one wavefront flow field (WFF) for a plurality of time windows using the coarse-grained data;
computing a local wavefront vorticity using the at least one WFF to determine rotational activity surrounding each spatial location; and
generating a vorticity map indicating likely rotational sources of complex cardiac activations.

10 . The system of claim 9 , wherein determining the activation times further comprises interpolating the activation times.

11 . The system of claim 10 , further comprising smoothing the interpolated activation times by determining a time-averaged phase of a chosen time window.

12 . The system of claim 10 , wherein determining the wavefront flow field further comprises:
determining a direction of movement of each point on a wavefront between a first time point and a second time point to define a wavefront flow vector (WFV i ) for all times and all spatial points across a given window of time; and summing WFV i for all spatial points over all times in a given time window to generate the at least one WFF for all spatial points for the given time window.

13 . The system of claim 12 , wherein the WFV i is defined in forward time and reverse time.

14 . The system of claim 9 , further comprising:
computing a local wavefront divergence using the at least one WFF to determine focal activity surrounding each spatial location; and generating a divergence map indicating likely focal sources of complex cardiac activations.

15 . The system of claim 14 , wherein the step of generating a vorticity map or divergence map comprises convolving the vorticity map with a smoothing filter.

16 . The system of claim 9 , wherein likely rotational or focal sources of complex cardiac activations comprise points in the vorticity map exceeding a predetermined threshold.

17 . A method for analyzing complex cardiac activation patterns, comprising:
collecting, via a computer processor, a plurality of cardiac signals at a plurality of locations corresponding to spatial locations of a patient's heart; determining activation times within the cardiac signals; binning the activation times according to a selected bin size; coarse-graining the binned activation times to generate coarse-grained data; determining at least one wavefront flow field (WFF) for a plurality of time windows using the coarse-grained data; computing a local wavefront divergence using the at least one WFF to determine focal activity surrounding each spatial location; and generating a divergence map indicating at least one likely focal source of complex cardiac activations.

18 . The method of claim 17 , wherein determining the wavefront flow field further comprises:
determining a direction of movement of each point on a wavefront between a first time point and a second time point to define a wavefront flow vector (WFV i ) for all times and all spatial points across a given window of time; and summing the WFV i for all spatial points over all times in a given time window to generate the WFF for all spatial points for the given time window.

19 . The method of claim 17 , further comprising:
computing a local wavefront vorticity using the at least one WFF to determine rotational activity surrounding each spatial location; and generating a vorticity map indicating at least one likely rotational source of the complex cardiac activations.

Assignees

• Univ California

Inventors

• Rappel Wouter-Jan
• Vidmar David

Classifications

• A61B5/0452

  Human Necessities · mapped topic

• A61B5/0422

  Human Necessities · mapped topic

• A61B5/0006

  ECG or EEG signals · CPC title

• A61B5/04011 Primary

  Human Necessities · mapped topic

• A61B5/4836

  Diagnosis combined with treatment in closed-loop systems or methods (A61B5/0036 takes precedence) · CPC title