SYSTEM AND METHOD FOR TEMPORAL SPARSE PROMOTING IMAGING OF CARDIAC ACTIVATION

• US 20160287116A1
• Filed: 11/17/2014
• Published: 10/06/2016
• Est. Priority Date: 11/18/2013
• Status: Active Grant

• Current Assignee: Regents of The University of Minnesota (University of Minnesota)
• Original Assignee: Regents of The University of Minnesota (University of Minnesota)
• Inventors: He, Bin, Yu, Long
• Granted Patent: US 10,098,557 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2576/023 for the heart
• CPC Class Codes: A61B 5/0044 for the heart
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/282 Holders for multiple electrodes for introduction into the body A61B5/287
• CPC Class Codes: A61B 5/283 Invasive
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/6852 Catheters
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/503 for diagnosis of the heart
• CPC Class Codes: A61B 6/5205 involving processing of raw data to produce diagnostic data
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A system and method for cardiac activation imaging includes non-invasively or minimally invasively acquiring data about an electrical activation of a heart of a subject using at least one sensor. An activation image of the heart of the subject is reconstructed using a weighted sparse constrained reconstruction.

Claims

1. A system for cardiac activation imaging, the system comprising:

at least one data acquisition device configured to acquire data about an electrical activation of a heart of a subject; and

a processor configured to receive the data acquired by the at least one data acquisition device and generate a cardiac electrical activation image by reconstructing an activation image of the heart of the subject using a weighted sparse constrained reconstruction.

2. The system of claim 1 wherein the weighted sparse constrained reconstruction includes a dipole-wise temporal weighted sparse reconstruction applied as:

3. The system of claim 1 wherein the processor is further configured to apply an image reconstruction framework that incorporates a cardiac electrophysiological property into a physical-model based cardiac electrical imaging approach as temporal constraints.

4. The system of claim 3 wherein the physical-model based cardiac electrical imaging approach is a three-dimensional (3D) physical-model based cardiac electrical imaging approach.

5. The system of claim 1 further comprising a display configured to provide the activation image in a color coding along a continuum from early activation to late activation.

6. The system of claim 1 wherein the processor is configured to receive body surface ECG time courses measured by body surface electrodes as an input and use the body surface ECG time courses as a temporal sparse constraints in the weighted sparse constrained reconstruction to identify cardiac activation sequence.

7. The system of claim 1 wherein the processor is configured to receive body surface MCG time courses measured by MCG sensors out of the body as an input and use the MCG time courses as a temporal sparse constraints in the weighted sparse constrained reconstruction to identify cardiac activation sequence.

8. The system of claim 1 wherein the processor is configured to balance fit with the data acquired and loss of detailed information.

9. The system of claim 8 wherein the weighted sparse constrained reconstruction includes an electrophysiologically based sparse property that protects against loss of detailed information from the data acquired.

10. The system of claim 9 wherein the electrophysiologically based sparse property is a temporal sparse property of cardiac electrical dynamics derived directly from electrophysiological knowledge of myocardial cellular depolarization.

11. The system of claim 1 wherein the at least one data acquisition device includes one of an electrocardiography (ECG) device or an interventional cardiac monitoring device such as a cardiac catheter.

12. A method for cardiac activation imaging, the method comprising:

acquiring data about an electrical activation of a heart of a subject using at least one sensor;

reconstructing an activation image of the heart of the subject using the acquired data and a weighted sparse constrained reconstruction; and

displaying the activation image of the heart.

13. The method of claim 12 wherein the weighted sparse constrained reconstruction includes a dipole-wise temporal weighted sparse reconstruction.

14. The method of claim 13 wherein the dipole-wise temporal weighted sparse reconstruction is applied as:

15. The method of claim 12 wherein the weighted sparse constrained reconstruction applies an image reconstruction framework that incorporates a cardiac electrophysiological property into a physical-model based cardiac electrical imaging approach as temporal constraints

16. The method of claim 15 wherein the cardiac electrophysiological property is a temporal sparse property of cardiac electrical dynamics derived directly from electrophysiological knowledge of myocardial cellular depolarization.

17. The method of claim 15 wherein the physical-model based cardiac electrical imaging approach is a three-dimensional (3D) physical-model based cardiac electrical imaging approach.

18. The method of claim 12 further comprising receiving body surface ECG time course data measured by body surface electrodes and using the body surface ECG time course data as a temporal sparse constraints in the weighted sparse constrained reconstruction to identify cardiac activation time.

19. The method of claim 12 further comprising receiving MCG time course data measured by MCG sensors and using the MCG time course data as a temporal sparse constraints in the weighted sparse constrained reconstruction to identify cardiac activation time.

20. The method of claim 12 wherein the weighted sparse constrained reconstruction includes an electrophysiologically based sparse property that protects against loss of detailed information from the acquired data.

21. The method of claim 20 wherein the electrophysiologically based sparse property is a temporal sparse property of cardiac electrical dynamics derived directly from electrophysiological knowledge of myocardial cellular depolarization.

22. The method of claim 12 wherein the acquired data includes at least one an electrocardiography (ECG) acquired using surface electrodes or an interventional electrode such as a cardiac catheter.

23. The method of claim 12 wherein reconstructing includes defining a constrained convex problem that has a unique solution.