SYSTEM AND METHOD FOR LESION-SPECIFIC CORONARY ARTERY CALCIUM QUANTIFICATION

• US 20100156898A1
• Filed: 12/21/2009
• Published: 06/24/2010
• Est. Priority Date: 12/19/2008
• Status: Active Grant

• Current Assignee: Piedmont Healthcare
• Original Assignee: Piedmont Healthcare
• Inventors: Qian, Zhen, Voros, Szilard
• Granted Patent: US 8,970,578 B2
• Time in Patent Office: Days
• US Class Current: 345/419
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/504 for diagnosis of blood vessels, e.g. by angiography
• CPC Class Codes: A61B 6/5288 involving retrospective matching to a physiological signal
• CPC Class Codes: G06T 15/08 Volume rendering
• CPC Class Codes: G06T 2200/24 involving graphical user interfaces [GUIs]
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/30048 Heart; Cardiac
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Methods and systems utilizing the data provided by a non-contrast-enhanced CAC scan that is left unused by the “whole-heart” Agatston or volume scores. Agatston and volume scores summarize overall coronary calcium burden, but do not show the number of vessels involved, the geographic distribution of the lesions, the size and shape of the individual lesions and the distance of the lesions from the coronary ostium. The methods and systems described herein extract and use the enhanced information provided by 3-D CAC scan data and significantly increases its clinical predictive value by providing vessel and lesion specific CAC scores which are superior to the whole-heart Agatston and volume scores in predicting obstructive Coronary artery disease (CAD).

Claims

1. A method for predicting the risk of a coronary event for a human comprising:

generating a non-contrast-enhanced volumetric image of the cardiac region of the human utilizing a computed tomography coronary artery calcium scan generated by a computed tomography scanner;

storing said volumetric image in a storage device as stored volumetric data, where said storage device is operably connected to a processor adapted to load and process said stored volumetric data;

transforming said stored volumetric data to a binary calcium volume data by applying an intensity threshold to said stored volumetric data using said processor;

identifying a calcific lesion within said binary calcium volume;

measuring geometric and morphologic characteristics of said calcific lesion;

measuring a distance between said calcific lesion and the origin of the coronary artery said calcific lesion is occluding; and

,

estimating a risk profile based on said geometric and morphologic characteristics and said distance.

2. The method of claim 1, further comprising:

assessing whole heart risk based at least in part upon a 3d Agatston score; and

assessing likelihood of a particular coronary event in a specific region of the heart.

3. The method of claim 1, further comprising presenting to a user an overlaid image comprising a color-coded calcium volume image over a gray-scale image of said stored volumetric data.

4. The method of claim 1, wherein said intensity threshold is selected to maximize the contrast of calcific regions.

5. The method of claim 1, further comprising identifying the origin of an artery and estimating a probability of a coronary event based at least in part on the distance between said calcific lesion and said origin.

6. The method of claim 5, further comprising adjusting said probability based at least in part on width of said calcific lesion.

7. The method of claim 1 further comprising volumetrically identifying a 3d volume of said calcific lesion by performing a volumetric fill of the region sounding a point within said stored binary calcium data.

8. The method of claim 7, further comprising determining the first and third eigenvectors of said 3d volume wherein said first eigenvector is substantially aligned with said artery and said third eigenvector is substantially perpendicular to said artery.

9. The method of claim 8, further comprising:

i estimating the maximum length of said 3d volume projected along the first eigenvector; and

ii estimating the maximum width of said 3d volume projected along said third eigenvector.

10. The method of claim 7 further comprising de-noising said 3d volume by eliminating any continuous regions within the stored binary calcium data with a total volume of less than about 1 mm̂

3.

11. The method of claim 7, further comprising determining a lesion density by averaging said calcific density in said 3d volume.

12. The method of claim 11, further comprising calculating a 3D Agatston score corresponding to said calcific lesion using at least said lesion density.

13. The method of claim 11, further comprising estimating a cardiac risk factor attributable to an arterial branch of said cardiac region by summing said 3D Agatston scores for each of said calcific lesions associated with said arterial branch.

14. The method of claim 13, further comprising

i calculating a whole heart 3D Agatston score by summing said 3D Agatston scores for each of said calcific lesions;

ii determining a maximum 3D Agatston score;

iii estimating a lesion distance between each of said calcific lesions and an origin of the respective arterial branch where said calcific lesion is located; and

,

iv estimating likelihood of cardiac event based the factors selected from the consisting of said whole heart 3D Agatston score;

said maximum 3D Agatston score and said lesion distance.

15. A method for predicting the risk of a coronary event for a human comprising:

performing a computed tomography coronary artery calcium scan on the human;

generating a non-contrast-enhanced volumetric image of the cardiac region of the human;

storing said volumetric image in a storage device as stored volumetric data, where said storage devices is operably connected to a processor adapted to load and process said stored volumetric data;

identifying at least one calcific lesion within said stored volumetric data for analysis;

selecting an intensity threshold of said stored volumetric data lesion via said processor;

transforming said stored volumetric data to a stored binary calcium volume data by applying said intensity threshold to said stored volumetric data using said processor;

identifying said calcific lesion within said binary calcium volume;

measuring geometric and morphologic characteristics of said calcific lesion;

measuring a distance between said calcific lesion and the origin of the coronary artery said lesion is occluding; and

,

estimating a risk profile based on said geometric and morphologic characteristics and said distance.

16. The method of claim 15, further comprising:

assessing whole heart risk based at least in part upon a 3d Agatston score; and

assessing likelihood of a particular coronary event in a specific region of the heart.