Quantification of noncalcific and calcific valve tissue from coronary CT angiography

Patent metadata

Field	Value
Publication number	US-12376814-B2
Application number	US-202217993819-A
Country	US
Kind code	B2
Filing date	Nov 23, 2022
Priority date	Nov 24, 2021
Publication date	Aug 5, 2025
Grant date	Aug 5, 2025

Abstract

Calcific and noncalcific aortic tissue components can be quantified. Pre-intervention planning computed tomography angiography imaging data is received. A region of interest is defined between the lower coronary ostium and the virtual basal ring. Cross-sectional images of the region of interest are rendered and calcific and noncalcific tissue components are identified based on Hounsfield unit thresholds. The volumes of the identified calcific and noncalcific tissue components are calculated and used to determine a total tissue volume (e.g., fibrocalcific volume) for the valve, as well as component percentages of the total tissue volume for the calcific and noncalcific components. These volumes and/or component percentages can be leveraged to predict severe AS, identify prognosis of post-TAVI outcomes, or otherwise facilitate planning of medical intervention.

First claim

What is claimed is:

1. A system, comprising:
one or more data processors; and
a non-transitory computer-readable storage medium containing instructions which, when executed on the one or more data processors, cause the one or more data processors to perform operations including:
receiving imaging data of a portion of a heart containing a valve;
determining a region of interest, wherein the region of interest contains the valve;
generating cross-sectional images of the region of interest based at least in part on the determined region of interest and the received imaging data;
identifying both calcific tissue components and noncalcific tissue components within the region of interest based at least in part on the generated cross-sectional images;
calculating a calcific tissue volume based at least in part on the calcific tissue components;
calculating a noncalcific tissue volume based at least in part on the noncalcific tissue components; and
calculating a fibrocalcific volume associated with the valve based at least in part on the calcific tissue volume and the noncalcific tissue volume.

2. The system of claim 1 , wherein determining the region of interest includes:
generating multiplanar reconstructions based at least in part on the imaging data;
automatically detecting a lower coronary ostium associated with the valve using the multiplanar reconstructions;
automatically detecting a virtual basal ring of the valve using the multiplanar reconstructions; and
automatically defining the region of interest as bounded by the detected lower coronary ostium and the detected virtual basal ring.

3. The system of claim 1 , wherein identifying both calcific tissue components and noncalcific tissue components within the region of interest includes:
determining Hounsfield unit (HU)_values for voxels within the region of interest;
applying Gaussian mixture modeling to the HU values to determine a set of HU distributions, the set of HU distributions including a blood pool HU distribution, a calcific tissue HU distribution, and a noncalcific tissue HU distribution;
determining a calcific tissue lower threshold and a noncalcific tissue upper threshold based at least in part on at least one HU distribution of the set of HU distributions;
determining the calcific tissue components based at least in part on the calcific tissue lower threshold; and
determining the noncalcific tissue components based at least in part on the noncalcific tissue upper threshold.

4. The system of claim 3 , wherein determining the noncalcific tissue components is further based at least in part on a preset noncalcific tissue lower threshold.

5. The system of claim 1 , wherein generating the cross-sectional images of the region of interest include rendering, based at least in part on the imaging data, serial multiplanar images orthogonal to a longitudinal axis of an ascending aorta associated with the heart.

6. The system of claim 1 , wherein identifying both the calcific tissue components and the noncalcific tissue components includes, for each tissue component within the region of interest:
determining a Hounsfield unit value associated with the tissue component;
identifying the tissue component as a calcific tissue component when the Hounsfield unit value exceeds a calcific tissue threshold value; and
identifying the tissue component as a noncalcific tissue component when the Hounsfield unit value is below a non-calcific tissue threshold value.

7. The system of claim 6 , wherein the calcific tissue threshold value is between 600 HU and 700 HU, and wherein the non-calcific tissue threshold value is between 300 HU and 400 HU.

8. The system of claim 1 , further comprising a display device, wherein the operations further include:
presenting the imaging data on the display device; and
presenting, on the display device and in association with the imaging data, i) the calcific tissue volume; ii) a calcific tissue percentage of the fibrocalcific volume; iii) the noncalcific tissue volume; iv) a noncalcific tissue percentage of the fibrocalcific volume; v) the fibrocalcific volume; vi) a fibrocalcific ratio of calcific tissue volume to noncalcific tissue volume; or vii) any combination of i-vi.

9. The system of claim 1 , wherein the operations further include generating a severe aortic stenosis score based at least in part on the noncalcific tissue volume, wherein the severe aortic stenosis score is indicative of a severity of aortic stenosis associated with the valve.

10. A computer-implemented method, comprising:
receiving imaging data of a portion of a heart containing a valve;
determining a region of interest, wherein the region of interest contains the valve;
generating cross-sectional images of the region of interest based at least in part on the determined region of interest and the received imaging data;
identifying both calcific tissue components and noncalcific tissue components within the region of interest based at least in part on the generated cross-sectional images;
calculating a calcific tissue volume based at least in part on the calcific tissue components;
calculating a noncalcific tissue volume based at least in part on the noncalcific tissue components; and
calculating a fibrocalcific volume associated with the valve based at least in part on the calcific tissue volume and the noncalcific tissue volume.

11. The method of claim 10 , wherein determining the region of interest includes:
generating multiplanar reconstructions based at least in part on the imaging data;
automatically detecting a lower coronary ostium associated with the valve using the multiplanar reconstructions;
automatically detecting a virtual basal ring of the valve using the multiplanar reconstructions; and
automatically defining the region of interest as bounded by the detected lower coronary ostium and the detected virtual basal ring.

12. The method of claim 10 , wherein identifying both calcific tissue components and noncalcific tissue components within the region of interest includes:
determining Hounsfield unit (HU)_values for voxels within the region of interest;
applying Gaussian mixture modeling to the HU values to determine a set of HU distributions, the set of HU distributions including a blood pool HU distribution, a calcific tissue HU distribution, and a noncalcific tissue HU distribution;
determining a calcific tissue lower threshold and a noncalcific tissue upper threshold based at least in part on at least one HU distribution of the set of HU distributions;
determining the calcific tissue components based at least in part on the calcific tissue lower threshold; and

determining the noncalcific tissue components based at least in part on the noncalcific tissue upper threshold.

13. The method of claim 12 , wherein determining the noncalcific tissue components is further based at least in part on a preset noncalcific tissue lower threshold.

14. The method of claim 10 , wherein generating the cross-sectional images of the region of interest include rendering, based at least in part on the imaging data, serial multiplanar images orthogonal to a longitudinal axis of an ascending aorta associated with the heart.

15. The method of claim 10 , wherein identifying both the calcific tissue components and the noncalcific tissue components includes, for each tissue component within the region of interest:
determining a Hounsfield unit value associated with the tissue component;
identifying the tissue component as a calcific tissue component when the Hounsfield unit value exceeds a calcific tissue threshold value; and

Assignees

• Cedars Sinai Medical Center

Inventors

• Dey Damini
• Cadet Sebastien
• Slomka Piotr
• Makkar Rajendra

Classifications

• A61B6/5217

  extracting a diagnostic or physiological parameter from medical diagnostic data · CPC title

• A61B6/504 Primary

  for diagnosis of blood vessels, e.g. by angiography · CPC title