METHOD AND SYSTEM FOR HUMAN JOINT TREATMENT PLAN AND PERSONALIZED SURGERY PLANNING USING 3-D KINEMATICS, FUSION IMAGING AND SIMULATION

• US 20130185310A1
• Filed: 01/16/2013
• Published: 07/18/2013
• Est. Priority Date: 01/16/2012
• Status: Active Grant

• Current Assignee: Emovi Inc.
• Original Assignee: Emovi Inc.
• Inventors: De Guise, Jacques, Mezghani, Neila, Fuentes, Alexandre, Grimard, Guy, Aissaoui, Rachid, Szmutny, ric, Ranger, Pierre, Hagemeister, Nicole, Cresson, Thierry, Clment, Julien
• Granted Patent: US 9,286,355 B2
• Time in Patent Office: Days
• US Class Current: 707/748
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

The present document describes a method for producing a knee joint treatment plan and/or surgery plan for a patient, the method comprising: obtaining 3D kinematic data of the knee joint in movement; determining, from the 3D kinematic data, scores characterising the joint function of the patient, the one or more scores being relative to one or more criteria; and comparing the scores to data in a database which characterize a plurality of treatment plans and/or surgery plans to generate the list of one or more treatment plans and/or surgery plans which match the scores.

Claims

1. A method for generating a list of one or more joint treatment plans and/or surgery plans for a joint of a patient, the method comprising:

obtaining, from motion sensors, 3D kinematic data of the joint in movement;

determining, from the 3D kinematic data, scores characterising a joint function of the patient, the scores being relative to one or more and

comparing the scores to data in a database which characterize a plurality of treatment plans and/or surgery plans to generate the list of one or more joint treatment plans and/or surgery plans which match the scores.

2. The method of claim 1, further comprising simulating the one or more joint treatment plans and/or surgery plans using the 3D kinematic data to produce a plurality of modified 3D kinematic data.

3. The method of claim 2, further comprising comparing the plurality of modified 3D kinematic data to kinematic data for a healthy joint model to determine which one from the list of one or more treatment plans and/or surgery plans will produce optimal results for the patient.

4. The method of claim 3, wherein the comparing comprises applying a pattern recognition technique on the modified 3D kinematic data, the pattern recognition technique comprising one of:

a parametric or non-parametric technique, a neural network, a nearest neighbour classification technique, a projection technique, a decision tree technique, a stochastic method, a genetic algorithms and an unsupervised learning and clustering technique.

5. The method of claim 4, wherein the comparing further comprises classifying the modified 3D kinematic data of the joint of the patient, to which were applied the pattern recognition technique, in one of several classes of known knee joint treatment plan and/or surgery plan.

6. The method of claim 1, wherein the obtaining 3D kinematic data from a 3D kinematic sensor comprises obtaining 3D kinematic data from at least one of:

a camera, an accelerometer, an electromagnetic sensor, a gyroscope, an optical sensor.

7. The method of claim 1, further comprising:

obtaining, from a 3D static imagery sensor, 3D static imagery data of the joint in a static position;

merging the 3D kinematic data and the 3D static imagery data of the joint, to produce merged 3D joint data for the joint of the patient; and

using the 3D joint data to produce and display a 3D animation of the joint.

8. The method of claim 7, further comprising simulating the one or more joint treatment plans and/or surgery plans using the 3D joint data to produce a plurality of modified 3D joint data.

9. The method of claim 8, further comprising comparing the plurality of modified 3D joint data to joint data for a healthy joint model to determine which one from the list of one or more joint treatment plans and/or surgery plans will produce optimal results for the patient.

10. The method of claim 9, further comprising recalibrating the 3D joint data for a healthy joint model to adapt to measurements of the patient and thereby produce recalibrated 3D joint data for use as the 3D joint data for comparison to the plurality of modified 3D joint data.

11. The method of claim 1, wherein the joint comprises one of a knee, a shoulder, a wrist, an ankle, an elbow and a hip.

12. The method of claim 1, further comprising storing the 3D kinematic data in memory.

13. A method for producing a 3D animation of a joint of patient, the 3D animation used in the determination of a list of one or more joint treatment plans and/or surgery plans for the joint of the patient, the method comprising:

obtaining, from motion sensors, 3D kinematic data of the joint in movement;

obtaining, from a 3D static imagery sensor, 3D static imagery data of the joint in a static position;

merging the 3D kinematic data and the 3D static imagery data of the joint, to produce merged 3D joint data for the joint of the patient; and

using the 3D joint data to produce and display a 3D animation of the joint.

14. The method of claim 13, further comprising simulating the one or more joint treatment plans and/or surgery plans using the 3D joint data to produce a plurality of modified 3D joint data.

15. The method of claim 14, further comprising comparing the plurality of modified 3D joint data to joint data for a healthy joint model to determine which one from the list of one or more joint treatment plans and/or surgery plans will produce optimal results for the patient.

16. The method of claim 15, further comprising recalibrating the 3D joint data for a healthy joint model to adapt to measurements of the patient and thereby produce recalibrated 3D joint data for use as the 3D joint data for comparison to the plurality of modified 3D joint data.

17. The method of claim 16, wherein the recalibrating comprises performing one of a dot by dot technique and a regionalization technique.

18. The method of claim 13, wherein the obtaining 3D static imagery data from a static imagery sensor comprises obtaining 3D static imagery data from a radiological examination device comprising one of an X-ray machine, a Magnetic Resonance Imaging machine and a CT scanning machine.

19. The method of claim 13, further comprising storing the 3D joint data for a healthy joint model in a database.

20. An apparatus for generating a list of one or more joint treatment plan and/or surgery plan for a joint of a patient, the apparatus comprising:

an input for receiving 3D kinematic data of the joint in movement;

a processing device in communication with the input;

a memory for storing instructions which cause the processing device to;

determine, from the 3D kinematic data, scores characterising a joint function of the patient, the one or more scores being relative to one or more criteria; and

compare the scores to data in a database which characterize a plurality of treatment plans and/or surgery plans to generate the list of one or more joint treatment plans and/or surgery plans which match the scores; and

an output for outputting the list of one or more joint treatment plans and/or surgery plans which match the scores.