# US 11,308,617 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 11,308,617 B2 - Document ID: US11308617B2 - Status: Granted - Kind: B2 - Application number: 17/394,154 - Filed: 2021-08-04 - Published: 2021-11-25 - Granted: 2022-04-19 - 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/US11308617B2 ## 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 characterizing a change in calcium level based on image analysis of one or more medical images of a subject, 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 calcium level of the subject and a first weighted measure of a first set of plaque parameters for the subject, the first calcium level and the first set of plaque parameters obtained at a first point in time, wherein the first set of plaque parameters comprises one or more of a ratio or function of volume or surface area, heterogeneity index, geometry, radiodensity, or location of one or more regions of plaque of the subject at the first point in time; access a second calcium level of the subject and one or more medical images of the subject, the second calcium level and the one or more medical images obtained at a second point in time, wherein the one or more medical images of the subject comprises the one or more regions of plaque; determine a change in calcium level of the subject between the first point in time and the second point in time; generate a second weighted measure of a second set of plaque parameters for the subject, the second set of plaque parameters derived from analyzing the one or more medical images, wherein the second set of plaque parameters comprises one or more of a ratio or function of volume or surface area, heterogeneity index, geometry, radiodensity, or location of the one or more regions of plaque at the second point in time; analyze a change between the first weighted measure of the first set of plaque parameters and the second weighted measure of the second set of plaque parameters; and characterize the change in calcium level of the subject between the first point in time and the second point in time based at least in part on the analyzed change between the first weighted measure of the first set of plaque parameters and the second weighted measure of the second set of plaque parameters. ### Claim 2 (depends on 1) The system of claim 1, wherein the system is further caused to generate a proposed treatment for the subject based at least in part on the characterized change in calcium level of the subject between the first point in time and the second point in time. ### Claim 3 (depends on 1) The system of claim 1, wherein a decrease in a ratio of volume to surface area of the one or more regions of plaque between the first point in time and the second point in time is indicative of a positive characterization of the change in calcium level of the subject between the first point in time and the second point in time. ### Claim 4 (depends on 1) The system of claim 1, wherein a decrease in the heterogeneity index of the one or more regions of plaque between the first point in time and the second point in time is indicative of a positive characterization of the change in calcium level of the subject between the first point in time and the second point in time. ### Claim 5 (depends on 1) The system of claim 1, wherein the heterogeneity index of the one or more regions of plaque is determined by generating a spatial mapping of radiodensity values within the one or more regions of plaque. ### Claim 6 (depends on 1) The system of claim 1, wherein the heterogeneity index of the one or more regions of plaque is determined by generating a three-dimensional histogram of radiodensity values within a geometric shape of the one or more regions of plaque. ### Claim 7 (depends on 1) The system of claim 1, wherein the heterogeneity index of the one or more regions of plaque is determined by generating a mathematical transform of radiodensity values within a geometric shape of the one or more regions of plaque. ### Claim 8 (depends on 1) The system of claim 1, wherein the system is further caused to determine a change in a ratio or function of volume and radiodensity of the one or more regions of plaque between the first point in time and the second point in time, wherein the change in calcium level of the subject is further characterized based at least in part the determined change in the ratio or function of volume and radiodensity of one or more regions between the first point in time and the second point in time. ### Claim 9 (depends on 1) The system of claim 1, wherein the change in calcium level of the subject is characterized for one or more of a vessel, segment, or region of plaque of the subject. ### Claim 10 (depends on 1) The system of claim 1, wherein the change in calcium level of the subject is characterized for a vessel segment of the subject. ### Claim 11 (depends on 1) The system of claim 1, wherein the one or more regions of plaque are within a coronary region of the subject. ### Claim 12 (depends on 1) The system of claim 1, wherein the first set of plaque parameters and the second set of plaque parameters further comprise a diffuseness of the one or more regions of plaque. ### Claim 13 (depends on 1) The system of claim 1, wherein the system is further caused to: analyze the one or more medical images of the subject to identify one or more new regions of plaque; and characterize the change in calcium level of the subject between the first point in time and the second point in time further based at least in part on the analysis to identify one or more new regions of plaque. ### Claim 14 (depends on 1) The system of claim 1, wherein the second calcium level of the subject is determined by analyzing the one or more medical images of the subject. ### Claim 15 (depends on 1) The system of claim 1, wherein the one or more medical images of the subject comprises an image obtained from a non-contrast Computed Tomography (CT) scan. ### Claim 16 (depends on 1) The system of claim 1, wherein the one or more medical images of the subject comprises an image obtained from a contrast-enhanced CT scan. ### Claim 17 (depends on 1) The system of claim 1, wherein the change in calcium level between the first point in time and the second point in time is characterized as one of positive, neutral, or negative. ### Claim 18 (depends on 17) The system of claim 17, wherein positive characterization of the change in calcium score is indicative of plaque stabilization. ### Claim 19 (depends on 1) The system of claim 1, wherein the change in calcium level of the subject is characterized using machine learning. ### Claim 20 (depends on 1) The system of claim 1, wherein the first weighted measure is generated by weighting the accessed first set of plaque parameters logarithmically or algebraically. ### Claim 21 A computer-implemented method of characterizing a change in calcium level based on image analysis of one or more medical images of a subject, the method comprising: accessing, by a computer system, a first calcium level of the subject and a first weighted measure of a first set of plaque parameters for the subject, the first calcium level and the first set of plaque parameters obtained at a first point in time, wherein the first set of plaque parameters comprises one or more of a ratio or function of volume or surface area, heterogeneity index, geometry, radiodensity, or location of one or more regions of plaque of the subject at the first point in time; accessing, by the computer system, a second calcium level of the subject and one or more medical images of the subject, the second calcium level and the one or more medical images obtained at a second point in time, wherein the one or more medical images of the subject comprises the one or more regions of plaque; determining, by the computer system, a change in calcium level of the subject between the first point in time and the second point in time; generating, by the computer system, a second weighted measure of a second set of plaque parameters for the subject, the second set of plaque parameters derived from analyzing the one or more medical images, wherein the second set of plaque parameters comprises one or more of a ratio or function of volume or surface area, heterogeneity index, geometry, radiodensity, or location of the one or more regions of plaque at the second point in time; analyzing, by the computer system, a change between the first weighted measure and the second weighted measure; and characterizing, by the computer system, the change in calcium level of the subject between the first point in time and the second point in time based at least in part on the analyzed change between the first weighted measure and the second weighted measure, wherein the computer system comprises a computer processor and an electronic storage medium. ### Claim 22 (depends on 21) The method of claim 21, further comprising generating, by the computer system, a proposed treatment for the subject based at least in part on the characterized change in calcium level of the subject between the first point in time and the second point in time. ### Claim 23 (depends on 21) The method of claim 21, wherein a decrease in a ratio of volume to surface area of the one or more regions of plaque between the first point in time and the second point in time is indicative of a positive characterization of the change in calcium level of the subject between the first point in time and the second point in time. ### Claim 24 (depends on 21) The method of claim 21, wherein a decrease in the heterogeneity index of the one or more regions of plaque between the first point in time and the second point in time is indicative of a positive characterization of the change in calcium level of the subject between the first point in time and the second point in time. ### Claim 25 (depends on 21) The method of claim 21, wherein the heterogeneity index of the one or more regions of plaque is determined by generating a spatial mapping of radiodensity values within the one or more regions of plaque. ### Claim 26 (depends on 21) The method of claim 21, wherein the heterogeneity index of the one or more regions of plaque is determined by generating a three-dimensional histogram of radiodensity values within a geometric shape of the one or more regions of plaque. ### Claim 27 (depends on 21) The method of claim 21, further comprising determining, by the computer system, a change in a ratio or function of volume and radiodensity of the one or more regions of plaque between the first point in time and the second point in time, wherein the change in calcium level of the subject is further characterized based at least in part the determined change in the ratio or function of volume and radiodensity of one or more regions between the first point in time and the second point in time. ### Claim 28 (depends on 21) The method of claim 21, wherein the change in calcium level of the subject is characterized using machine learning. ### Claim 29 (depends on 21) The method of claim 21, wherein the change in calcium level between the first point in time and the second point in time is characterized as one of positive, neutral, or negative. ### Claim 30 (depends on 29) The method of claim 29, wherein positive characterization of the change in calcium score is indicative of plaque stabilization.