Determining ablation location using probabilistic decision-making

• US 10,639,100 B2
• Filed: 02/09/2018
• Issued: 05/05/2020
• Est. Priority Date: 02/10/2017
• Status: Active Grant

• Current Assignee: St. Jude Medical Cardiology Division Incorporated (Abbott Laboratories Incorporated)
• Original Assignee: St. Jude Medical Cardiology Division Incorporated (Abbott Laboratories Incorporated)
• Inventors: Mahapatra, Srijoy
• Primary Examiner(s): Voorhees, Catherine M
• Application Number:
  US15/892,994
• Publication Number:
  US 20180228536A1
• Time in Patent Office: 816 Days
• CPC Class Codes: A61B 18/02 by cooling, e.g. cryogenic techniques devices for cooling specific reflex points of the body within cell-life limits A61H39/06
• CPC Class Codes: A61B 18/12 by passing a current through the tissue to be heated, e.g. high-frequency current
• CPC Class Codes: A61B 18/1492 having a flexible, catheter-like structure, e.g. for heart ablation A61B18/1477 takes precedence
• CPC Class Codes: A61B 2018/00351 Heart
• CPC Class Codes: A61B 2018/00357 Endocardium
• CPC Class Codes: A61B 2018/00369 Heart valves
• CPC Class Codes: A61B 2018/00375 Ostium, e.g. ostium of pulmonary vein or artery
• CPC Class Codes: A61B 2018/00404 Blood vessels other than those in or around the heart
• CPC Class Codes: A61B 2018/00577 Ablation
• CPC Class Codes: A61B 2018/00648 using more than one sensed parameter
• CPC Class Codes: A61B 2018/00791 Temperature
• CPC Class Codes: A61B 2018/00839 Bioelectrical parameters, e.g. ECG, EEG
• CPC Class Codes: A61B 2018/0262 using a circulating cryogenic fluid
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/107 Visualisation of planned trajectories or target regions
• CPC Class Codes: A61B 2034/256 having a database of accessory information, e.g. including context sensitive help or scientific articles
• CPC Class Codes: A61B 2034/258 providing specific settings for specific users
• CPC Class Codes: A61B 2090/364 Correlation of different images or relation of image positions in respect to the body
• CPC Class Codes: A61B 2090/365 augmented reality, i.e. correlating a live optical image with another image
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 34/30 : Surgical robots
• CPC Class Codes: A61B 5/05 : Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves impedance plethysmography A61B5/0295; measuring movement of the entire body or parts thereof A61B5/11; detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof A61B5/24
• CPC Class Codes: A61B 5/287 : Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS]
• CPC Class Codes: A61B 5/4836 : Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/742 : using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 90/37 : Surgical systems with images on a monitor during operation
• CPC Class Codes: A61M 25/0147 : with movable mechanical means, e.g. pull wires
• CPC Class Codes: A61N 2007/003 : Destruction of nerve tissue
• CPC Class Codes: A61N 7/02 : Localised ultrasound hyperthermia hyperthermia in general A61F7/00
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders
• CPC Class Codes: G16H 70/20 : relating to practices or guidelines

Abstract

A method of determining a candidate ablation location using historical ablation data includes generating a database including a plurality of ablation records, and generating a set of probability parameters describing each ablation record. The method also includes developing an algorithm based upon the probability parameters for the ablation records. For a candidate ablation procedure, the method includes receiving patient parameters associated with a patient receiving the candidate ablation procedure, and determining at least one candidate condition associated with the patient and a respective probability associated with each candidate condition. The method further includes applying the algorithm to determine at least one candidate ablation location based upon the respective probabilities associated with the at least one candidate condition, and displaying the at least one candidate ablation location on a visual interface of a cardiac mapping system.

Claims

1. A method of determining a candidate ablation location using historical ablation data, the method comprising:

generating a database including a plurality of ablation records, each ablation record of the plurality of ablation records associated with a corresponding ablation procedure;

generating a set of probability parameters associated with different types of conditions and different types of patients, and describing each ablation record of the plurality of ablation records;

developing, using a regression analysis, an algorithm based upon the sets of probability parameters for the plurality of ablation records; and

for a candidate ablation procedure;

receiving a plurality of patient parameters associated with a patient receiving the candidate ablation procedure;

determining at least one candidate condition associated with the patient and a respective probability associated with each candidate condition;

applying the algorithm to determine at least one candidate ablation location and a probability that ablating in the at least one candidate ablation location will be successful based upon the respective probabilities associated with the at least one candidate condition; and

displaying the at least one candidate ablation location on a visual interface of a cardiac mapping system.

2. The method of claim 1 further comprising:

performing the candidate ablation procedure at least at one candidate ablation location; and

adding a data record associated with the candidate ablation procedure to the database.

3. The method of claim 2 further comprising:

monitoring an outcome of the candidate ablation procedure; and

adding a data element associated with the outcome of the candidate ablation procedure to the data record associated with the candidate ablation procedure.

4. The method of claim 2 further comprising:

determining an ablation practitioner that performed the ablation procedure; and

determining whether the ablation practitioner meets at least one expert criterion,

wherein adding a data record associated with the candidate ablation procedure to the database comprises only adding the data record to the database when the ablation practitioner meets the at least one expert criterion.

5. The method of claim 2 further comprising updating the algorithm based upon the data record associated with the candidate ablation procedure.

6. The method of claim 1, wherein generating a database including a plurality of ablation records comprises generating a subset of the plurality of ablation records based upon published data of the corresponding ablation procedures.

7. The method of claim 1, wherein generating a database including a plurality of ablation records comprises generating a subset of the plurality of ablation records based upon historical ablation procedures performed by one or more ablation practitioners who meet at least one expert criterion.

8. The method of claim 1, wherein displaying the at least one candidate ablation location on a visual interface comprises adding at least one visual indicator of a corresponding ablation location onto a map of the cardiac mapping system.

9. The method of claim 8, wherein adding at least one visual indicator comprises adding at least one color to the map to form a probability map identifying the at least one candidate ablation location.

10. The method of claim 8, wherein adding at least one visual indicator comprises adding at least one probability indicator to a respective location on the map corresponding to the at least one candidate ablation location.

11. The method of claim 1, wherein receiving a plurality of patient parameters associated with a patient receiving the candidate ablation procedure comprises receiving at least one of a patient age, a patient gender, a patient weight, one or more known patient conditions, and one or more known patient symptoms.

12. The method of claim 1, wherein generating a database including a plurality of ablation records comprises generating the database including the plurality of ablation records, wherein each ablation record identifies a condition and an ablation location associated with the corresponding ablation procedure.

13. The method of claim 1, wherein displaying the at least one candidate ablation location on a visual interface comprises:

associating each at least one candidate ablation location with a corresponding point on an ablation map of the ablation system; and

adding at least one visual indicator onto each point on the ablation map associated with each at least one candidate ablation location.

14. A cardiac mapping system comprising:

a database;

a display device; and

a processing apparatus in communication with the database and the display device, the processing apparatus configured to;

populate the database with a plurality of ablation records, each ablation record of the plurality of ablation records associated with a corresponding ablation procedure;

generate a set of probability parameters associated with different types of conditions and different types of patients, and describing each ablation record of the plurality of ablation records;

develop, using a regression analysis, an algorithm based upon the sets of probability parameters for the plurality of ablation records; and

for a candidate ablation procedure;

receive a plurality of patient parameters associated with a patient receiving the candidate ablation procedure;

determine at least one candidate condition associated with the patient and a respective probability associated with each candidate condition;

apply the algorithm to determine at least one candidate ablation location and a probability that ablating in the at least one candidate ablation location will be successful based upon the respective probabilities associated with the at least one candidate condition; and

display the at least one candidate ablation location on the display device.

15. The cardiac mapping system of claim 14, wherein the processing apparatus is further configured to add a data record associated with the candidate ablation procedure to the database after the candidate ablation procedure is performed.

16. The cardiac mapping system of claim 15, wherein the processing apparatus is further configured to:

receive an indication of an outcome of the candidate ablation procedure;

add a data element associated with the outcome of the candidate ablation procedure to the data record associated with the candidate ablation procedure; and

update the algorithm based upon the data record associated with the candidate ablation procedure.

17. The cardiac mapping system of claim 14, wherein the processing apparatus is further configured to add at least one of a visual indicator of a corresponding ablation location and a probability indicator onto a map displayed on the display device.

18. At least one non-transitory computer-readable storage medium having computer-executable instructions embodied thereon, wherein when executed by at least one processor in communication with a database and a display device, the computer-executable instructions cause the at least one processor to:

populate the database with a plurality of ablation records, each ablation record of the plurality of ablation records associated with a corresponding ablation procedure;

generate a set of probability parameters associated with different types of conditions and different types of patients, and describing each ablation record of the plurality of ablation records;

develop, using a regression analysis, an algorithm based upon the sets of probability parameters for the plurality of ablation records; and

for a candidate ablation procedure;

receive a plurality of patient parameters associated with a patient receiving the candidate ablation procedure;

determine at least one candidate condition associated with the patient and a respective probability associated with each candidate condition;

apply the algorithm to determine at least one candidate ablation location and a probability that ablating in the at least one candidate ablation location will be successful based upon the respective probabilities associated with the at least one candidate condition; and

display the at least one candidate ablation location on the display device.

19. The non-transitory computer-readable storage medium of claim 18, wherein the computer-executable instructions further cause the at least one processor to add at least one visual indicator of a corresponding ablation location onto a map displayed on the display device.

20. The non-transitory computer-readable storage medium of claim 19, wherein the computer-executable instructions further cause the at least one processor to add at least one probability indicator to a respective location on the map corresponding to the at least one candidate ablation location.