Systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking

Patent metadata

Field	Value
Publication number	US-12558048-B2
Application number	US-202318457197-A
Country	US
Kind code	B2
Filing date	Aug 28, 2023
Priority date	Jan 7, 2020
Publication date	Feb 24, 2026
Grant date	Feb 24, 2026

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

First claim

What is claimed is:

1 . A computer-implemented method of facilitating risk assessment of coronary artery disease (CAD) for a subject by generating a CAD risk stage for the subject based on multivariable information derived from medical image analysis, the computer-implemented method comprising:
accessing, by a computer system, one or more medical images comprising one or more regions of one or more coronary arteries of a subject; identifying, by the computer system, one or more segments of coronary arteries within the one or more medical images; determining, by the computer system, for the identified one or more segments of coronary arteries, one or more plaque parameters and one or more vascular parameters, wherein the one or more plaque parameters are determined automatically based at least in part by applying a machine learning algorithm to the accessed one or more medical images, wherein the one or more plaque parameters comprise one or more of total plaque volume, calcified plaque volume, non-calcified plaque volume, or low density non-calcified plaque volume, wherein the one or more vascular parameters comprise one or more of stenosis severity or likelihood of presence of ischemia; generating, by the computer system, a combined measure of the determined one or more plaque parameters and the one or more vascular parameters to generate the CAD risk stage for the subject; and generating, by the computer system, a graphical representation of the CAD risk stage for the subject, wherein the graphical representation of the CAD risk stage for the subject is configured to facilitate risk assessment of CAD for the subject for determining a CAD treatment for the subject, wherein the computer system comprises a computer processor and an electronic storage medium.

2 . The computer-implemented method of claim 1 , wherein the CAD risk stage is selected from a number of predetermined risk stages determined based at least in part on one or more ranges of total plaque volume.

3 . The computer-implemented method of claim 2 , wherein the number of predetermined risk stages comprises four.

4 . The computer-implemented method of claim 2 , wherein the one or more ranges of total plaque volume comprise 0 mm 3 , 1-250 mm 3 , 251-750 mm 3 , or more than 750 mm3.

5 . The computer-implemented method of claim 1 , wherein stenosis severity is analyzed for one or more of a left main coronary artery or a left anterior descending (LAD) coronary artery.

6 . The computer-implemented method of claim 5 , wherein a stenosis severity above 30 percent stenosis for the left main coronary artery is indicative of an increase in the CAD risk stage.

7 . The computer-implemented method of claim 5 , wherein a stenosis severity above 50 percent stenosis for the LAD coronary artery is indicative of an increase in the CAD risk stage.

8 . The computer-implemented method of claim 1 , wherein ischemia is determined to be likely present based on one or more of the one or more segments of the coronary arteries.

9 . The computer-implemented method of claim 1 , wherein the likelihood of presence of ischemia is determined using a machine learning algorithm.

10 . The computer-implemented method of claim 1 , wherein the CAD risk stage is generated using a machine learning algorithm.

11 . The computer-implemented method of claim 1 , wherein identification of one or more regions of low density non-calcified plaque larger than 2 mm 3 is indicative of an increase in the CAD risk stage.

12 . The computer-implemented method of claim 1 , wherein identification of one or more regions of low density non-calcified plaque larger than 2 mm 3 and with a positive remodeling index of more than 1.1 from analyzing the one or more medical images is indicative of an increase in the CAD risk stage.

13 . The computer-implemented method of claim 1 , wherein low density non-calcified plaque comprises radiodensity values between −189 and 30 Hounsfield units.

14 . The computer-implemented method of claim 1 , wherein the one or more plaque parameters is determined using a machine learning algorithm.

15 . The computer-implemented method of claim 1 , wherein the graphical representation comprises a report displaying the CAD risk stage for the subject.

16 . The computer-implemented method of claim 15 , wherein the report comprises the CAD risk stage, a risk characterization, and the non-calcified plaque volume.

17 . The computer-implemented method of claim 1 , wherein the CAD treatment for the subject is determined based at least in part on the CAD risk stage for the subject, wherein a higher CAD risk stage is reflective of more intensive treatment for the subject.

18 . The computer-implemented method of claim 17 , wherein the CAD treatment comprises one or more of lifestyle changes, medication, or intervention.

19 . The computer-implemented method of claim 17 , wherein the CAD treatment comprises more one or more of aggressive therapy goals or greater number of medications for higher CAD risk stages.

20 . The computer-implemented method of claim 1 , wherein the CAD risk stage is configured to be used as an indication of a risk of major adverse cardiovascular event (MACE).

21 . A system for facilitating risk assessment of coronary artery disease (CAD) for a subject by generating a CAD risk stage for the subject based on multivariable information derived from medical image analysis, the system comprising:
one or more computer readable storage devices configured to store a plurality of computer executable instructions; and one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the system to:
access one or more medical images comprising one or more regions of one or more coronary arteries of a subject;
identify one or more segments of coronary arteries within the one or more medical images;
determine, for the identified one or more segments of coronary arteries, one or more plaque parameters and one or more vascular parameters, wherein the one or more plaque parameters are determined automatically based at least in part by applying a machine learning algorithm to the accessed one or more medical images, wherein the one or more plaque parameters comprise one or more of total plaque volume, calcified plaque volume, non-calcified plaque volume, or low density non-calcified plaque volume, wherein the one or more vascular parameters comprise one or more of stenosis severity or likelihood of presence of ischemia;
generate a combined measure of the determined one or more plaque parameters and the one or more vascular parameters to generate a CAD risk stage for the subject; and
generate a graphical representation of the CAD risk stage for the subject, wherein the graphical representation of the CAD risk stage for the subject is configured to facilitate risk assessment of CAD for the subject for determining a CAD treatment for the subject.

22 . The system of claim 21 , wherein the CAD risk stage is selected from a number of predetermined risk stages determined based at least in part on one or more ranges of total plaque volume.

23 . The system of claim 22 , wherein the one or more ranges of total plaque volume comprise 0 mm 3 , 1-250 mm 3 , 251-750 mm 3 , or more than 750 mm 3 .

24 . The system of claim 22 , wherein stenosis sev

Assignees

• Cleerly Inc

Inventors

• Min James K
• Earls James P
• Rodrigues Marques Hugo Miguel
• Hootnick Ben

Classifications

• A61B5/055

  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging · CPC title

• G06F18/10

  Pre-processing; Data cleansing · CPC title

• G06V40/14

  Vascular patterns · CPC title

• G06V10/245

  by locating a pattern; Special marks for positioning · CPC title

• G06V10/20

  Image preprocessing · CPC title