# US 11,896,415 B2 · Systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,896,415 B2 - Document ID: US11896415B2 - Status: Granted - Kind: B2 - Application number: 17/654,883 - Filed: 2022-03-15 - Published: 2022-10-13 - Granted: 2024-02-13 - Earliest claimed: 2020-01-07 - Assignees: Cleerly, Inc. - Applicants: Cleerly, Inc. - Inventors: James K. Min; James P. Earls; Hugo Miguel Rodrigues Marques - Web page: https://patentgrep.com/patent/US11896415B2 ## CPC - A61B 6/504: {for diagnosis of blood vessels, e.g. by angiography} - A61B 5/0066: {Optical coherence imaging} - A61B 5/0075: {by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy (A61B5/0071 takes precedence)} - A61B 5/02007: {Evaluating blood vessel condition, e.g. elasticity, compliance} - A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems} - A61B 5/7267: {involving training the classification device} - A61B 5/742: {using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339)} - A61B 5/7475: {User input or interface means, e.g. keyboard, pointing device, joystick} - A61B 6/032: {Transmission computed tomography [CT]} - A61B 6/037: {Emission tomography} - A61B 6/463: {characterised by displaying multiple images or images and diagnostic data on one display} - A61B 6/467: {characterised by special input means} - A61B 6/481: {involving the use of contrast agents} - A61B 6/5205: {involving processing of raw data to produce diagnostic data} - A61B 6/5217: {extracting a diagnostic or physiological parameter from medical diagnostic data} - A61B 6/583: {using calibration phantoms} - A61B 8/0891: {for diagnosis of blood vessels} - A61B 8/12: in body cavities or body tracts, e.g. by using catheters - A61B 8/14: Echotomography - A61B 8/5223: {for extracting a diagnostic or physiological parameter from medical diagnostic data (for algorithms to analyse biomedical images G06T7/0012)} - A61K 49/04: X-ray contrast preparations - G06F 18/10: Pre-processing; Data cleansing - G06F 18/22: Matching criteria, e.g. proximity measures - G06F 18/2413: based on distances to training or reference patterns - G06T 7/0012: {Biomedical image inspection} - G06V 10/20: Image preprocessing - G06V 10/245: {by locating a pattern; Special marks for positioning} - G06V 10/761: {Proximity, similarity or dissimilarity measures} - G06V 10/764: using classification, e.g. of video objects - G06V 10/82: using neural networks - A61B 5/004: {adapted for image acquisition of a particular organ or body part (A61B5/0082 takes precedence; arrangements for optical scanning A61B5/0062)} - A61B 5/1076: {for measuring dimensions inside body cavities, e.g. using catheters (A61B3/1005 takes precedence)} - A61B 8/587: {Calibration phantoms} - G06T 2207/10081: Computed x-ray tomography [CT] - G06T 2207/10088: Magnetic resonance imaging [MRI] - G06T 2207/10101: Optical tomography; Optical coherence tomography [OCT] - G06T 2207/10104: Positron emission tomography [PET] - G06T 2207/10108: Single photon emission computed tomography [SPECT] - G06T 2207/10116: X-ray image - G06T 2207/10132: Ultrasound image - G06T 2207/20081: Training; Learning - G06T 2207/20084: Artificial neural networks [ANN] - G06T 2207/20101: Interactive definition of point of interest, landmark or seed - G06T 2207/30048: Heart; Cardiac - G06T 2207/30101: Blood vessel; Artery; Vein; Vascular - G06V 10/247: {by affine transforms, e.g. correction due to perspective effects; Quadrilaterals, e.g. trapezoids} - G06V 2201/03: Recognition of patterns in medical or anatomical images - Y02A 90/10: Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - A61K: PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES (devices or methods specially adapted for bringing pharmaceutical products into particular physical or administering forms A61J3/00; chemical aspects of, or use of materials for deodorisation of air, for disinfection or sterilisation, or for bandages, dressings, absorbent pads or surgical articles A61L; soap compositions C11D) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - Y02A: TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE ## 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. ## Claims ### Claim 1 A system for tracking a plaque-based disease based on non-invasive medical image analysis of a medical image of a subject to facilitate determination of a state of plaque progression, regression, or stabilization, 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 a first set of plaque parameters of one or more vessels of a subject, wherein the first set of plaque parameters are derived from a first medical image of the subject comprising the one or more vessels, the first medical image of the subject obtained non-invasively at a first point in time, wherein the first set of plaque parameters comprises total plaque volume, non-calcified plaque volume, and calcified plaque volume identified in the one or more vessels of the subject at the first point in time; access a second medical image of the subject, the second medical image of the subject obtained non-invasively at a second point in time, the second point in time being later than the first point in time, wherein the second medical image of the subject comprises the one or more vessels of the subject; analyze the second medical image to generate a second set of plaque parameters of the one or more vessels of the subject, wherein the second set of plaque parameters comprises total plaque volume, non-calcified plaque volume, and calcified plaque volume identified in the one or more vessels of the subject at the second point in time; determine a change between one or more of the first set of plaque parameters and one or more the second set of plaque parameters; and generate a display of the determined change between one or more of the first set of plaque parameters and one or more of the second set of plaque parameters to facilitate determination of the state of plaque progression, regression, or stabilization based at least part on the determined change. ### Claim 2 (depends on 1) The system of claim 1, wherein the first set of plaque parameters and the second set of plaque parameters comprise percent atheroma volume of the one or more vessels. ### Claim 3 (depends on 1) The system of claim 1, wherein the one or more vessels comprises one or more coronary arteries. ### Claim 4 (depends on 1) The system of claim 1, wherein one or more of the calcified plaque volume or the non-calcified plaque volume is determined based at least in part on density. ### Claim 5 (depends on 4) The system of claim 4, wherein the density comprises radiodensity. ### Claim 6 (depends on 1) The system of claim 1, wherein the change between one or more of the first set of plaque parameters and one or more the second set of plaque parameters is determined on one or more of a patient, vessel, segment, or lesion level. ### Claim 7 (depends on 1) The system of claim 1, wherein stabilization of total plaque volume between the first point in time and the second point in time is indicative of plaque stabilization or regression. ### Claim 8 (depends on 1) The system of claim 1, wherein an increase in calcified plaque volume and decrease in non-calcified plaque volume between the first point in time and the second point in time is indicative of plaque stabilization or regression. ### Claim 9 (depends on 1) The system of claim 1, wherein the generated display of the determined change between one or more of the first set of plaque parameters and one or more of the second set of plaque parameters is configured to be used for assessment of a treatment for the subject. ### Claim 10 (depends on 1) The system of claim 1, wherein the system is further caused to: access a first assessment of ischemia of the one or more vessels at the first point in time, wherein the first assessment of ischemia is derived from the first medical image; analyze the second medical image to generate an assessment of ischemia of the one or more vessels at the second point in time; determine a change between the first assessment of ischemia and the second assessment of ischemia; and generate a display of the determined change between the first assessment of ischemia and the second assessment of ischemia. ### Claim 11 (depends on 1) The system of claim 1, wherein the system is further caused to: access a first comparison of the first set of plaque parameters to one or more reference values; generate a second comparison of the second of plaque parameters to the one or more reference values; determine a change between the first comparison and the second comparison; and generate a display of the determined change between the first comparison and the second comparison. ### Claim 12 (depends on 1) The system of claim 1, wherein the medical image comprises a Computed Tomography (CT) image. ### Claim 13 (depends on 12) The system of claim 12, wherein the medical image comprises a non-contrast CT image. ### Claim 14 (depends on 1) The system of claim 1, wherein the medical image is obtained using an imaging technique comprising one or more of CT, x-ray, ultrasound, echocardiography, MR imaging, optical coherence tomography (OCT), nuclear medicine imaging, positron-emission tomography (PET), single photon emission computed tomography (SPECT), or near-field infrared spectroscopy (NIRS). ### Claim 15 A computer-implemented method of tracking a plaque-based disease based on non-invasive medical image analysis of a medical image of a subject to facilitate determination of a state of plaque progression, regression, or stabilization, the method comprising: accessing, by a computer system, a first set of plaque parameters of one or more vessels of a subject, wherein the first set of plaque parameters are derived from a first medical image of the subject comprising the one or more vessels, the first medical image of the subject obtained non-invasively at a first point in time, wherein the first set of plaque parameters comprises total plaque volume, non-calcified plaque volume, and calcified plaque volume identified in the one or more vessels of the subject at the first point in time; accessing, by the computer system, a second medical image of the subject, the second medical image of the subject obtained non-invasively at a second point in time, the second point in time being later than the first point in time, wherein the second medical image of the subject comprises the one or more vessels of the subject; analyzing, by the computer system, the second medical image to generate a second set of plaque parameters of the one or more vessels of the subject, wherein the second set of plaque parameters comprises total plaque volume, non-calcified plaque volume, and calcified plaque volume identified in the one or more vessels of the subject at the second point in time; determining, by the computer system, a change between one or more of the first set of plaque parameters and one or more the second set of plaque parameters; and generating, by the computer system, a display of the determined change between one or more of the first set of plaque parameters and one or more of the second set of plaque parameters to facilitate determination of the state of plaque progression, regression, or stabilization based at least part on the determined change, wherein the computer system comprises a computer processor and an electronic storage medium. ### Claim 16 (depends on 15) The computer-implemented method of claim 15, wherein the first set of plaque parameters and the second set of plaque parameters comprise percent atheroma volume of the one or more vessels. ### Claim 17 (depends on 15) The computer-implemented method of claim 15, wherein the one or more vessels comprises one or more coronary arteries. ### Claim 18 (depends on 15) The computer-implemented method of claim 15, wherein one or more of the calcified plaque volume or the non-calcified plaque volume is determined based at least in part on density. ### Claim 19 (depends on 18) The computer-implemented method of claim 18, wherein the density comprises radiodensity. ### Claim 20 (depends on 15) The computer-implemented method of claim 15, wherein the change between one or more of the first set of plaque parameters and one or more the second set of plaque parameters is determined on one or more of a patient, vessel, segment, or lesion level. ### Claim 21 (depends on 15) The computer-implemented method of claim 15, wherein stabilization of total plaque volume between the first point in time and the second point in time is indicative of plaque stabilization or regression. ### Claim 22 (depends on 15) The computer-implemented method of claim 15, wherein an increase in calcified plaque volume and decrease in non-calcified plaque volume between the first point in time and the second point in time is indicative of plaque stabilization or regression. ### Claim 23 (depends on 15) The computer-implemented method of claim 15, wherein the generated display of the determined change between one or more of the first set of plaque parameters and one or more of the second set of plaque parameters is configured to be used for assessment of a treatment for the subject. ### Claim 24 (depends on 15) The computer-implemented method of claim 15, further comprising: accessing, by the computer system, a first assessment of ischemia of the one or more vessels at the first point in time, wherein the first assessment of ischemia is derived from the first medical image; analyzing, by the computer system, the second medical image to generate an assessment of ischemia of the one or more vessels at the second point in time; determining, by the computer system, a change between the first assessment of ischemia and the second assessment of ischemia; and generating, by the computer system, a display of the determined change between the first assessment of ischemia and the second assessment of ischemia. ### Claim 25 (depends on 15) The computer-implemented method of claim 15, further comprising: accessing, by the computer system, a first comparison of the first set of plaque parameters to one or more reference values; generating, by the computer system, a second comparison of the second of plaque parameters to the one or more reference values; determining, by the computer system, a change between the first comparison and the second comparison; and generating, by the computer system, a display of the determined change between the first comparison and the second comparison. ### Claim 26 (depends on 15) The computer-implemented method of claim 15, wherein the medical image is obtained using an imaging technique comprising one or more of CT, x-ray, ultrasound, echocardiography, MR imaging, optical coherence tomography (OCT), nuclear medicine imaging, positron-emission tomography (PET), single photon emission computed tomography (SPECT), or near-field infrared spectroscopy (NIRS).