IDENTIFYING INDIVIDUAL SUB-REGIONS OF THE CARDIOVASCULAR SYSTEM FOR CALCIUM SCORING

• US 20130230225A1
• Filed: 11/09/2011
• Published: 09/05/2013
• Est. Priority Date: 11/12/2010
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Waechter-Stehle, Irina, Kneser, Reinhard, Weese, Juergen
• Granted Patent: US 9,317,919 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/463 characterised by displaying multiple images or images and diagnostic data on one display
• CPC Class Codes: A61B 6/466 adapted to display 3D data
• CPC Class Codes: A61B 6/503 for diagnosis of the heart
• CPC Class Codes: A61B 6/504 for diagnosis of blood vessels, e.g. by angiography
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/30048 Heart; Cardiac
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/0014 using an image reference approach
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A method includes identifying a plurality of different anatomical sub-regions of the cardiovascular system of a subject in image data of the subject based on a subject specific cardiovascular anatomical model, wherein the plurality of different regions corresponds to regions where calcifications occur, searching for and identifying calcifications in the sub-regions based on voxel grey value intensity values of the image data, and generating a signal indicative of one or more regions of voxels of the image data respectively corresponding to sub-regions including identified calcifications. A computing system (118) includes a processor that automatically determines a plurality of different groups of voxels of image data of a subject, wherein each group of voxels corresponds to a different sub-region of the cardiovascular system of the subject and each group of voxels corresponds to a region that includes a calcification identified in the image data.

Claims

1. A method, comprising:

identifying a plurality of different anatomical sub-regions of the cardiovascular system of a subject in image data of the subject based on a subject specific cardiovascular anatomical model, wherein the plurality of different regions corresponds to regions where calcifications occur;

searching for and identifying calcifications in the sub-regions based on voxel grey value intensity values of the image data; and

generating a signal indicative of one or more regions of voxels of the image data respectively corresponding to sub-regions including identified calcifications.

2. The method of claim 1, further comprising:

obtaining a generic anatomical model of the cardiovascular system; and

generating the subject specific cardiovascular anatomical model based on the image data and the generic anatomical model of the cardiovascular system.

3. The method of claim 1, further comprising:

employing a pre-determined threshold to identify a calcification in a sub-region,

4. The method of claim 3, wherein the threshold is based on intensity values of a blood pool near the region.

5. The method of claim 4, wherein the threshold is based on an average value of the intensity values plus a margin.

6. The method of claim 3, wherein the threshold is based on a mean intensity and standard deviation in structures neighboring the sub-region in the subject specific cardiovascular model.

7. The method of claim 3, wherein a first threshold is used for a first sub-region, a second threshold is used for a second sub-region of the regions, and the first and second thresholds are different.

8. The method of claim 1, further comprising.

determining calcium scores for at least one of the sub-regions.

9. The method of claim 8, further comprising.

growing at least one of the regions of voxels outside of a corresponding search sub-region into an expanded region;

and

determining a calcium score based on the expanded region.

10. The method of claim 8, further comprising.

visually presenting the calcium scores along with indicia indicating respective sub-regions of the anatomical sub-regions.

11. The method of claim 10, further comprising:

associating a different color with each of the sub-regions;

visually presenting the calcium scores along and with the indicia, using the respective colors for the sub-regions; and

visually presenting the subject specific cardiovascular anatomical model, using the respective colors of the sub-regions to identify the sub-regions in the subject specific cardiovascular anatomical model.

12. The method of claim 8, further comprising:

generating a mapping between the calcium scores and the subject specific cardiovascular anatomical model;

visually presenting the subject specific cardiovascular anatomical model; and

visually presenting a calcium score for a sub-region in response to receiving a signal indicative of a user input selecting the sub-region.

13. The method of claim 8, further comprising:

determining relative severities for the calcium scores;

assigning a different color to the different severities;

generating a mapping between the relative severities and a surface of the subject specific cardiovascular anatomical model; and

visually presenting the subject specific cardiovascular anatomical model, using the different colors assigned to the severities to identify the relative severities in corresponding sub-regions.

14. The method of claim 13, further comprising:

assigning a transparency value to the surface; and

visually presenting the subject specific cardiovascular anatomical model, using the different colors to identify the relative severities in corresponding sub-regions behind the surface.

15. A computing system, comprising:

a processor that automatically determines a plurality of different groups of voxels of image data of a subject, wherein each group of voxels corresponds to a different sub-region of the cardiovascular system of the subject and each group of voxels corresponds to a region that includes a calcification identified in the image data.

16. The system of claim 15, wherein the processor determines the plurality of different sub-regions based on a subject specific cardiovascular anatomical model.

17. The system of claim 16, wherein the processor determines the subject specific cardiovascular as model based on the image data and a generic anatomical model of the cardiovascular system, using a model-based segmentation.

18. The system of claim 15, wherein the processor identifies calcifications based on a pre-determined voxel intensity value threshold.

19. The system of claim 18, wherein the threshold is based on at least one of a blood pool near the sub-region or tissue surrounding the sub-region.

20. The system of claim 15, wherein the processor identifies the sub-regions by growing a region around a landmark starting from a surface of the subject specific cardiovascular model.

21. The system of claim 15, wherein the processor determines calcium score values for the one or more sub-regions.

22. The system of claim 15, wherein the processor visually presents the calcium scores along with indicia indicating respective sub-regions of the anatomical sub-regions.

23. The system of claim 22, wherein the processor associates a different color with each of the sub-regions, visually presents the calcium scores along and with the indicia, using the respective colors of the sub-regions, and visually presents the subject specific cardiovascular anatomical model, using the respective colors of the sub-regions to identify the sub-regions in the subject specific cardiovascular anatomical model.

24. The system of claim 22, wherein the processor generates a mapping between the calcium scores and the subject specific cardiovascular anatomical model, visually presents the subject specific cardiovascular anatomical model, and visually presents a calcium score for a sub-region in response to receiving a signal indicative of a user selected sub-region.

25. The system of claim 22, wherein the processor determines relative severities for the calcium scores, assigns a different color to the different severities, generates a mapping between the relative severities and a surface of the subject specific cardiovascular anatomical model, and visually presents the subject specific cardiovascular anatomical model, using the different colors to identify the relative severities in corresponding sub-regions.

26. The system of claim 21, wherein the processor recommends a course of action based on a calcium score for a given sub-region.

27. The system of claim 21, wherein the processor recommends a course of action based on a compilation of calcium scores for multiple sub-regions.

28. The system of claim 26, wherein the recommends includes at least one of an access point for an implant or a size of the implant.

29. A method, comprising:

automatically determining and visualizing calcium score for different individual sub-regions of the cardiovascular system of a subject.