US 12,324,696 B2
Systems, devices, and methods for non-invasive image-based plaque analysis and risk determination
James K. Min, Chapel Hill, NC (US); and Tami Crabtree, Santa Rosa, CA (US)
Assigned to Cleerly, Inc., Denver, CO (US)
Filed by Cleerly, Inc., Denver, CO (US)
Filed on Feb. 16, 2024, as Appl. No. 18/444,339.
Application 18/444,339 is a continuation of application No. 18/508,098, filed on Nov. 13, 2023.
Application 18/508,098 is a continuation in part of application No. 18/179,921, filed on Mar. 7, 2023.
Claims priority of provisional application 63/478,084, filed on Dec. 30, 2022.
Claims priority of provisional application 63/478,076, filed on Dec. 30, 2022.
Claims priority of provisional application 63/477,985, filed on Dec. 30, 2022.
Claims priority of provisional application 63/477,961, filed on Dec. 30, 2022.
Claims priority of provisional application 63/477,656, filed on Dec. 29, 2022.
Claims priority of provisional application 63/477,640, filed on Dec. 29, 2022.
Claims priority of provisional application 63/477,638, filed on Dec. 29, 2022.
Claims priority of provisional application 63/476,255, filed on Dec. 20, 2022.
Claims priority of provisional application 63/476,251, filed on Dec. 20, 2022.
Claims priority of provisional application 63/476,245, filed on Dec. 20, 2022.
Claims priority of provisional application 63/386,376, filed on Dec. 7, 2022.
Claims priority of provisional application 63/386,297, filed on Dec. 6, 2022.
Claims priority of provisional application 63/385,472, filed on Nov. 30, 2022.
Claims priority of provisional application 63/385,179, filed on Nov. 28, 2022.
Claims priority of provisional application 63/383,904, filed on Nov. 15, 2022.
Claims priority of provisional application 63/383,632, filed on Nov. 14, 2022.
Claims priority of provisional application 63/269,136, filed on Mar. 10, 2022.
Claims priority of provisional application 63/362,108, filed on Mar. 29, 2022.
Claims priority of provisional application 63/362,856, filed on Apr. 12, 2022.
Claims priority of provisional application 63/364,078, filed on May 3, 2022.
Claims priority of provisional application 63/364,084, filed on May 3, 2022.
Claims priority of provisional application 63/365,381, filed on May 26, 2022.
Claims priority of provisional application 63/368,293, filed on Jul. 13, 2022.
Claims priority of provisional application 63/381,210, filed on Oct. 27, 2022.
Prior Publication US 2024/0252132 A1, Aug. 1, 2024
Int. Cl. A61B 6/00 (2024.01); A61B 6/03 (2006.01); A61B 6/50 (2024.01); G06T 7/00 (2017.01); G06T 7/62 (2017.01); G06V 10/22 (2022.01); G06V 10/26 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01)
CPC A61B 6/5217 (2013.01) [A61B 6/032 (2013.01); A61B 6/503 (2013.01); A61B 6/504 (2013.01); A61B 6/507 (2013.01); A61B 6/5229 (2013.01); G06T 7/0012 (2013.01); G06T 7/62 (2017.01); G06V 10/22 (2022.01); G06V 10/26 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/30048 (2013.01); G06T 2207/30104 (2013.01); G06V 2201/031 (2022.01)] 18 Claims
OG exemplary drawing
 
1. A computer-implemented method of determining presence of ischemia based at least in part on a plurality of variables derived from non-invasive medical image analysis, the method comprising:
accessing, by a computer system, a medical image of a subject, wherein the medical image of the subject is obtained non-invasively;
analyzing, by the computer system, the medical image of the subject to identify a plurality of vessels, the plurality of vessels comprising a first vessel and a second vessel, wherein the first vessel is a different vessel than the second vessel;
identifying, by the computer system, one or more lesions in the first vessel and one or more lesions in the second vessel;
identifying, by the computer system, one or more regions of plaque within the one or more lesions in the first vessel and the one or more lesions in the second vessel;
analyzing, by the computer system, the one or more lesions in the first vessel, the one or more lesions in the second vessel, the one or more regions of plaque within the one or more lesions in the first vessel, and the one or more regions of plaque within the one or more lesions in the second vessel to determine a plurality of variables for each of the one or more lesions in the first vessel and the one or more lesions in the second vessel, wherein the plurality of variables comprises stenosis, total plaque volume, non-calcified plaque volume, and calcified plaque volume; and
applying, by the computer system, a machine learning algorithm to determine a presence of ischemia in the first vessel based at least in part on the plurality of variables determined for the one or more lesions in the first vessel and the plurality of variables determined for the one or more lesions in the second vessel,
applying, by the computer system, the machine learning algorithm to determine a presence of ischemia in the second vessel based at least in part on the plurality of variables determined for the one or more lesions in the first vessel and the plurality of variables determined for the one or more lesions in the second vessel
wherein the machine learning algorithm is trained on a dataset to accept the plurality of variables as inputs and to output the presence of ischemia,
wherein a presence of the one or more lesions in the second vessel impacts blood flood within the first vessel and the second vessel, and wherein a presence of the one or more lesions in the first vessel impacts blood flow within the first vessel and the second vessel
wherein the first vessel and the second vessel comprise different portions of a network of vessels,
wherein the computer system comprises a computer processor and an electronic storage medium.