Image-based computational mechanical analysis and indexing for cardiovascular diseases

• US 20060149522A1
• Filed: 12/08/2005
• Published: 07/06/2006
• Est. Priority Date: 12/10/2004
• Status: Active Grant

• Current Assignee: Worcester Polytechnic Institute
• Original Assignee: Worcester Polytechnic Institute
• Inventors: Tang, Dalin
• Granted Patent: US 7,751,984 B2
• Time in Patent Office: Days
• US Class Current: 703/11
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

A method and a computer system, for providing an assessment for disease status of a disease, such as a cardiovascular disease, employ construction of image-based 3D computational model of an organ representative of the disease status; computationally obtaining a certain mechanical distribution using the 3D-organ model; and computational, quantitative analysis of the mechanical distribution to provide an assessment for disease status of a disease. The image-based 3D computational model includes a fluid-structure interaction and multiple components within the organ.

Claims

1. A method for providing an assessment for disease status of a disease, comprising the steps of:

a) constructing a computational, three-dimensional model of an organ representative of said disease status of a disease based on data for the organ, wherein the organ data includes image data of the organ, and the three-dimensional model includes a fluid-structure interaction and multiple components of the organ;

b) computationally obtaining a certain mechanical distribution using the three-dimensional organ model; and

c) computationally applying quantitative analysis of the mechanical distribution to provide an assessment for disease status of a disease.

2. The method of claim 1, wherein the organ data includes any combination of patient-specific data, morphology data, deformation data and fluid flow information data, of the organ.

3. The method of claim 1, wherein the disease is a cardiovascular disease.

4. The method of claim 1, wherein said multiple components include solid and liquid components within the organ.

5. The method of claim 1, wherein said fluid-structure interaction includes a blood-vessel interaction.

6. The method of claim 1, wherein said mechanical distribution includes a stress and strain distribution.

7. The method of claim 6, wherein said stress and strain distribution is modeled under an unsteady condition.

8. The method of claim 1, wherein said assessment for disease status is a quantitative assessment.

9. The method of claim 1, wherein the organ data includes any of:

magnetic resonance imaging data of the organ and ultrasound technology data of the organ.

10. The method of claim 1, wherein said assessment for disease status is assessment for plaque vulnerability to rupture.

11. The method of claim 10, wherein said assessment for plaque vulnerability to rupture is in a digital format.

12. The method of claim 11, wherein said quantitative analysis further includes the steps of:

identifying one or more critical sites where plaques are vulnerable to rupture;

analyzing a certain mechanical distribution on the critical sites using the three-dimensional model;

analyzing pathological data of plaques, and classifying vulnerability of the plaques used for pathological analysis in a numeric format, thereby providing a standard value for plaques vulnerability to rupture;

scaling the plaques at the critical sites in a numeric format by comparing the plaques at the critical sites and the mechanical distribution on the critical sites with the standard value; and

regressively correlating the numerical values of the plaques at the critical sites with the standard value, such that said numerical assessment for plaque rupture is provided.

13. The method of claim 12, wherein the analyzing a certain mechanical distribution includes quantifying at least one of:

effect of pulsating pressure condition, effect of plaque cap thickness and effect of material property of a component of plaque, on the mechanical distribution.

14. The method of claim 12, wherein the mechanical distribution is a stress and strain distribution of the plaque.

15. The method of claim 12, further including the step of validating said numerical assessment for plaque rupture with clinical data.

16. A computer system, comprising:

a) a data source containing data of an organ representative of disease status of a disease, the organ data including image data of the organ;

b) a modeler coupled to receive data from the data source, the modeler generating a three-dimensional model of the organ based on the organ data, said model including a fluid-structure interaction and multiple components of the organ; and

c) a routine for computationally obtaining a certain mechanical distribution using the three-dimensional organ model and for applying computational, quantitative analysis of the mechanical distribution, wherein the quantitative analysis of the mechanical distribution provides an assessment for said disease status of a disease.

17. The computer system of claim 16, wherein the organ data includes at least one of patient-specific data, morphology data, fluid flow and deformation data, of the organ.

18. The computer system of claim 16, wherein the organ image data includes any of:

magnetic resonance imaging data of the organ and ultrasound technology data of the organ.

19. The computer system of claim 16, wherein said multiple components include solid and liquid components within the organ.

20. The computer system of claim 16, wherein the routine solves the three-dimensional model by employing a nonlinear incremental iterative procedure to handle a fluid-structure interaction.

21. The computer system of claim 16, wherein said quantitative analysis of the mechanical distribution includes identifying correlation between said mechanical distribution and disease status of a disease, and quantifying the correlation.

22. The computer system of claim 21, wherein the assessment for disease status is in a digital format showing the quantified correlation between the mechanical distribution and disease status.

23. The computer system of claim 16, wherein the disease is a cardiovascular disease.

24. The computer system of claim 16, wherein said organ model is a three-dimensional model of an artery having a plaque.

25. The computer system of claim 16, wherein said model is a model of heart muscles.

26. The computer system of claim 25, wherein said modeler includes a field force introducing a force to govern heart muscle contraction and relaxation.