US 7,117,030 B2Granted

Method and algorithm for spatially identifying sources of cardiac fibrillation

AssigneeThe Research Foundation of State University of New York

InventorsOmer Berenfeld, Jose Jalife, Ravi Vaidyanathan

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Abstract

A method and computer program product comprising an algorithm adapted to execute a method of identifying the spatial coordinates of a sustaining source of fibrillatory activity in a heart by computing a set of point-dependent dominant frequencies and a set of point-dependent regularity indices for a set of products of point-dependent unipolar discrete power spectra and point-dependent bipolar discrete power spectra, derived by spectral analyses of corresponding unipolar and bipolar cardiac depolarization signals simultaneously acquired from a set of points of the heart. A maximum dominant frequency is selected whose associated coordinates identify the point of the sustaining source of fibrillatory activity. The magnitude of the regularity index is interpreted to verify the identification of the spatial coordinates of the sustaining source of fibrillatory activity. When indicated, surgical intervention is directed to the spatial coordinates of the sustaining source of fibrillatory activity.

Claims34

Dependent claims

A method for identifying the spatial coordinates of at least one sustaining source of fibrillatory activity (“SSFA”) in a heart, said method comprising the steps of:

a. simultaneously acquiring a unipolar time-dependent depolarization signal SUP(t) and a corresponding bipolar time-dependent depolarization signal SBP(t) from each acquisition point Pi(xi, yi, zi) of an acquisition set of points {Pi(xi, yi, zi)} on or within said heart, each said acquisition point Pi(xi, yi, zi) having unique spatial coordinates (xi, yi, zi) identified from a set of cardiac points {cPi(xi, yi, zi)};
b. forming a set of unipolar time-and-point-dependent depolarization signals {SUPi(t, xi, yi, zi)} by assigning to each said unipolar time-dependent depolarization signal SUP(t) the spatial coordinates (xi, yi, zi) of the acquisition point Pi(xi, yi, zi) from which it was acquired;
and, forming a set of corresponding bipolar time-and-point-dependent depolarization signals {SBPi(t, xi, yi, zi)} by assigning to each said corresponding bipolar time-dependent depolarization signal SBP(t) the spatial coordinates (xi, yi, zi) of the acquisition point Pi(xi, yi, zi) from which it was simultaneously acquired;
c. forming a set of unipolar point-dependent discrete power spectra {DPSUPi(f, xi, yi, zi)} by computing a unipolar point-dependent discrete power spectrum DPSUPi(f, xi, yi, zi) for each said unipolar time-and-point-dependent depolarization signal SUPi (t, xi, yi, zi);
and, forming a set of corresponding bipolar point-dependent discrete power spectra {DPSBPi(f, xi, yi, zi)} by computing a corresponding bipolar point-dependent discrete power spectrum DPSBPi(f, xi, yi, zi) for each said corresponding bipolar time-and-point-dependent depolarization signal SBPi(t, xi, yi, zi);
d. forming a set of point-dependent discrete power spectrum products {DPSPRODi(f, xi, yi, zi)} by multiplying each said unipolar point-dependent discrete power spectrum DPSUPi(f, xi, yi, zi) of said set of unipolar point-dependent discrete power spectra {DPSUPi(f, xi, yi, zi)} by each said corresponding bipolar point-dependent discrete power spectrum DPSBPi(f, xi, yi, zi) of said set of corresponding bipolar point-dependent discrete power spectra {DPSBPi(f, xi, yi, zi)};
e. computing a point-dependent product dominant frequency DFPRODi(xi, yi, zi) for each point-dependent discrete power spectrum product DPSPRODi(f, xi, yi, zi), thereby forming a set of point-dependent product dominant frequencies {DFPRODi (xi, yi, zi)};
f. selecting a maximum point-dependent product dominant frequency DFMAXPRODi(xi, yi, zi) from said set of point-dependent product dominant frequencies {DFPRODi (xi, yi, zi)};
g. assigning the coordinates of said maximum point-dependent product dominant frequency DFMAXPRODi (xi, yi, zi) to said at least one SSFA.

6 more elements

A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, wherein the computer readable program code comprises an algorithm adapted to execute a method of identifying the spatial coordinates of at least one sustaining source of fibrillatory activity (“SSFA”) in a heart, said method comprising the steps of:

a. simultaneously acquiring a unipolar time-dependent depolarization signal SUP(t) and a corresponding bipolar time-dependent depolarization signal SBP(t) from each acquisition point Pi(xi, yi, zi) of an acquisition set of points {Pi(xi, yi, zi)} on or within said heart, each said acquisition point Pi(xi, yi, zi) having unique spatial coordinates (xi, yi, zi) identified from a pre-stored set of cardiac points {cPi (xi, yi, zi)};
b. forming a set of unipolar time-and-point-dependent depolarization signals {SUPi (t, xi, yi, zi)} by assigning to each said unipolar time-dependent depolarization signal SUP(t) the spatial coordinates (xi, yi, zi) of the acquisition point Pi(xi, yi, zi) from which it was acquired;
and, forming a set of corresponding bipolar time-and-point-dependent depolarization signals {SBPi (t, xi, yi, zi)} by assigning to each said corresponding bipolar time-dependent depolarization signal SBP(t) the spatial coordinates (xi, yi, zi) of the acquisition point Pi(xi, yi, zi) from which it was simultaneously acquired;
c. forming a set of unipolar point-dependent discrete power spectra {DPSUPi(f, xi, yi, zi)} by computing a unipolar point-dependent discrete power spectrum DPSUPi(f, xi, yi, zi) for each said unipolar time-and-point-dependent depolarization signal {SUPi (t, xi, yi, zi)};
and, forming a set of bipolar point-dependent discrete power spectra {DPSBPi (f, xi, yi, zi)} by computing a bipolar point-dependent discrete power spectrum DPSBPi(f, xi, yi, zi) for each said corresponding bipolar time-and-point-dependent depolarization signal {SBPi (t, xi, yi, zi)};
d. forming a set of point-dependent discrete power spectrum products {DPSPRODi (f, xi, yi, zi)} by multiplying each said unipolar point-dependent discrete power spectrum DPSUPi (f, xi, yi, zi) of said set of unipolar point-dependent discrete power spectra {DPSUPi(f, xi, yi, zi)} by each said corresponding bipolar point-dependent discrete power spectrum DPSBPi(f, xi, yi, zi) of said set of corresponding bipolar point-dependent discrete power spectra {DPSBPi(f, xi, yi, zi)};
e. computing a point-dependent product dominant frequency DFPRODi(xi, yi, zi) for each point-dependent discrete product power spectrum DPSPRODi (f, xi, yi, zi) of said set of point-dependent discrete power spectrum products {DPSPRODi (f, xi, yi, zi)}, thereby forming a set of point-dependent product dominant frequencies {DFPRODi (xi, yi, zi)};
f. selecting a maximum point-dependent product dominant frequency DFMAXPRODi(xi, yi, zi) from said set of point-dependent product dominant frequencies {DFPRODi (xi, yi, zi)};
g. assigning the coordinates of said maximum point-dependent product dominant frequency DFMAXPRODi (xi, yi, zi) to said at least one SSFA.

6 more elements

Dependencies are inferred from the claim text.