Factor analysis in medical imaging

• US 8,175,355 B2
• Filed: 03/30/2009
• Issued: 05/08/2012
• Est. Priority Date: 10/15/2004
• Status: Active Grant

• Current Assignee: Beth Israel Deaconess Medical Center, Inc. (Beth Israel Lahey Health, Inc.)
• Original Assignee: Beth Israel Deaconess Medical Center, Inc. (Beth Israel Lahey Health, Inc.), Brigham and Women's Hospital Incorporated
• Inventors: El Fakhri, Georges, Sitek, Arkadiusz
• Primary Examiner(s): Alavi, Amir
• Application Number:
  US12/414,153
• Publication Number:
  US 20090226064A1
• Time in Patent Office: 1,135 Days
• Field of Search: 382/103, 382128-132, 382/154, 382/173, 382/190, 382224-225, 382/228, 382/272, 382/285, 600/407, 600/420, 600/431, 600/437, 600/509, 345/424, 210/489, 706/46, 434/262, 434/272, 434/323, 250/363.04, 250/394, 250/476, 378/4, 378/8, 378/9, 378/41, 378/901
• US Class Current: 382/128
• CPC Class Codes: A61B 6/037 Emission tomography
• CPC Class Codes: A61B 6/503 for diagnosis of the heart
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: G06T 2207/30024 Cell structures in vitro; Tissue sections in vitro
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A method for estimating kinetic parameters from image data includes using a processor to execute instructions for providing a model of kinetic contributions from first and second physiological regions; grouping voxels of the image data into first and second groups; determining an average value of the factors associated with the first group, the factors corresponding to blood-flow time activity curves; incorporating the average value of the factors associated with the first group into the model of kinetic contributions from the first and second physiological regions; and estimating the kinetic parameters based on the model of kinetic contributions.

Claims

1. A method for estimating kinetic parameters from image data, the method comprising using a processor to execute instructions for:

providing a model of kinetic contributions from first and second physiological regions;

grouping voxels of the image data into first and second groups;

determining an average value of the factors associated with the first group, the factors corresponding to blood-flow time activity curves;

incorporating the average value of the factors associated with the first group into the model of kinetic contributions from the first and second physiological regions; and

estimating the kinetic parameters based on the model of kinetic contributions.

2. The method of claim 1, further comprising providing input functions to the model, the input functions comprising factors determined for the first and second physiological regions.

3. The method of claim 1, further comprising reducing a vector space spanned by the voxels to a subspace within the vector space, the subspace being defined by principal vectors of the voxels.

4. The method of claim 1, wherein:

providing the model comprises selecting the model to be a two-compartment model of myocardial factors and of kinetic contributions from a left ventricle and a right ventricle; and

wherein estimating the kinetic parameters comprises determining extraction and egress rates of transport between myocardial tissue and freely diffusible space.

5. A non-transitory computer-readable medium having encoded thereon software for estimating kinetic parameters from image data, said software comprising instructions for:

providing a model of kinetic contributions from first and second physiological regions;

grouping voxels of the image data into first and second groups;

determining an average value of the factors associated with the first group, the factors corresponding to blood-flow time activity curves;

incorporating the average value into the model; and

estimating the kinetic parameters based on the model.

6. The non-transitory computer-readable medium of claim 5, wherein the software further comprises instructions for providing input functions to the model, the input functions comprising factors determined for the first and second physiological regions.

7. The non-transitory computer-readable medium of claim 5, wherein the software further comprises instructions for reducing a vector space spanned by the voxels to a subspace within the vector space, the subspace being defined by principal vectors of the voxels.

8. The non-transitory computer-readable medium of claim 5, wherein the software further comprises instructions for determining a first seed voxel for which a sum of distances between the first seed voxel and other voxels of the image data is greatest.

9. The non-transitory computer-readable medium of claim 8, wherein the software further comprises instructions for:

determining ungrouped voxels located within a minimum distance from the first seed voxel; and

wherein the instructions for grouping voxels of the image data into the first group comprise instructions for grouping the ungrouped voxels and the first seed voxel.

10. The non-transitory computer-readable medium of claim 5, wherein the software further comprises instructions for:

selecting, from ungrouped voxels, a first predefined number of ungrouped voxels that are located nearest to the first seed voxel; and

wherein the instructions for grouping voxels of the image data into the first group comprise instructions for defining a first group that includes the selected ungrouped voxels and the first seed voxel.

11. The non-transitory computer-readable medium of claim 10, wherein the software further comprises instructions for:

determining a second seed voxel for which a sum of distances between the second seed voxel and other voxels of the image data is greatest, the other voxels being remaining ungrouped voxels;

selecting, from the remaining ungrouped voxels, a second predefined number of ungrouped voxels that are located nearest to the second seed voxel; and

wherein the instructions for grouping voxels of the image data into the second group comprise instructions for defining a second group that includes the selected remaining ungrouped voxels and the second seed voxel.

12. The non-transitory computer-readable medium of claim 11, wherein the software further comprises instructions for selecting the first predefined number to be equal to the second predefined number.

13. The non-transitory computer-readable medium of claim 5, wherein:

the instructions for providing the model comprise instructions for selecting the model to be a two-compartment model of myocardial factors and of kinetic contributions from a left ventricle and a right ventricle; and

wherein the instructions for estimating the kinetic parameters comprise instructions for determining extraction and egress rates of transport between myocardial tissue and freely diffusible space.

14. A non-transitory computer-readable medium having encoded thereon software for estimating kinetic parameters from image data, said software comprising instructions for:

providing a model of kinetic contributions from first and second physiological regions;

determining a first seed voxel for which a sum of distances between the first seed voxel and other voxels of the image data is greatest;

selecting, from ungrouped voxels, a first predefined number of ungrouped voxels that are located nearest to the first seed voxel;

grouping voxels of the image data into first and second groups, wherein the first group includes the selected ungrouped voxels and the first seed voxel;

determining an average value of the factors associated with the first group;

incorporating the average value into the model; and

estimating the kinetic parameters based on the model.

15. The non-transitory computer-readable medium of claim 14, wherein the software further comprises instructions for:

determining a second seed voxel for which a sum of distances between the second seed voxel and other voxels of the image data is greatest, the other voxels being remaining ungrouped voxels;

selecting, from the remaining ungrouped voxels, a second predefined number of ungrouped voxels that are located nearest to the second seed voxel; and

wherein the instructions for grouping voxels of the image data into the second group comprise instructions for defining a second group that includes the selected remaining ungrouped voxels and the second seed voxel.

16. The non-transitory computer-readable medium of claim 15, wherein the software further comprises instructions for selecting the first predefined number to be equal to the second predefined number.

17. A non-transitory computer-readable medium having encoded thereon software for estimating kinetic parameters from image data, said software comprising instructions for:

providing a model of kinetic contributions from first and second physiological regions;

determining a first seed voxel for which a sum of distances between the first seed voxel and other voxels of the image data is greatest;

determining ungrouped voxels located within a minimum distance from the first seed voxel;

grouping voxels of the image data into first and second groups, wherein the first group includes the selected ungrouped voxels and the first seed voxel;

determining an average value of the factors associated with the first group;

incorporating the average value into the model; and

estimating the kinetic parameters based on the model.

18. A non-transitory computer-readable medium having encoded thereon software for estimating kinetic parameters from image data, said software comprising instructions for:

providing a model of kinetic contributions from first and second physiological regions, wherein providing the model includes selecting the model to be a two-compartment model of myocardial factors and of kinetic contributions from a left ventricle and a right ventricle;

grouping voxels of the image data into first and second groups;

determining an average value of the factors associated with the first group;

incorporating the average value into the model; and

estimating the kinetic parameters based on the model, wherein estimating the kinetic parameters includes determining extraction and egress rates of transport between myocardial tissue and freely diffusible space.

19. Data processing hardware programmed to execute instructions stored on a machine-readable medium for estimating kinetic parameters from image data, said hardware comprising

a machine-readable medium having encoded thereon instructions for:

providing a model of kinetic contributions from first and second physiological regions,

grouping voxels of the image data into first and second groups,

determining an average value of the factors associated with the first group, the factors corresponding to blood-flow time activity curves,

incorporating the average value into the model, and

estimating the kinetic parameters based on the model;

a processor for executing instructions stored on said machine-readable medium;

a data communication link for providing electronic data communication between said machine-readable medium and said processor; and

a monitor for displaying, to a user, data representative of said kinetic parameters, said monitor being in data communication with said processor.