Cleerly, Inc.

Cornell University

James K Min

Hugo Miguel Rodrigues Marques

James P Earls

Ben Hootnick

Shant Malkasian

Bobak Mosadegh

Simon Dunham

Shai Ronen

Chung Chan

Kranthi Kumar Kolli

Amir Ali Amiri Moghadam

Seyedhamidreza Alaie

Robert F Shepherd

Varun Umesh Kashyap

Sanlin S Robinson

Benjamin C Mac Murray

Alexandre Caprio

Nazanin Farokhnia

Tracey Lustig

Subhi Al'Aref

Subhi Al' Aref

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, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, 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.

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

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

Systems, devices, and methods for non-invasive image-based plaque analysis and risk determination

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

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.

This application is directed to systems, methods, and devices for image based analysis of plaque. In some embodiments, the approaches herein can be used for developing treatment plans, which can include local treatment, systemic treatment, or both. In some embodiments, the approaches herein can be used for stent selection. In some embodiments, the approaches herein can be used for surgical planning, which can include robotic surgical planning. In some embodiments, the approaches herein can be used for image normalization. In some embodiments, the approaches herein can be used for identifying plaque calcification thresholds. In some embodiments, the approaches herein can be used for identifying thin cap fibroatheroma. In some embodiments, the approaches herein can be used for coronary artery tree reconstruction. Some embodiments are directed to coronary artery disease risk stratification.

Systems, methods, and devices for image-based plaque analysis and risk determination

The present disclosure describes a system that can enable the prediction of coronary flow without invasive medical procedure. The system can generate physical models that can provide an accurate assessment of coronary mechanics and enable realistic simulation of coronary procedures. The models can enable the hemodynamic measurement of flow through the model and the study of flow dynamics through the model and the biomechanics of the model.

Assessment of coronary function via advanced 3D printed models

The present disclosure describes a replacement valve that can remove or lacerate the anterior mitral leaflet (or other portion of the heart) to reduce the obstruction of the left ventricular outflow tract (LVOT). The replacement valve can include integrated cutting features to lacerate a leaflet of a heart valve. For example, the cutting features can include blades or electrosurgical features that can cut the leaflets to reduce obstruction of the LVOT. As the cutting features are integrated components of the replacement valve, the laceration of the leaflet can follow implantation of the replacement valve and enables for clinical decisions to be made based on the degree of obstruction to the LVOT following the implantation procedure.

Mitral valves with integrated cutting features

Implanted medical devices need a mechanism of immobilization to surrounding tissues, which minimizes tissue damage while providing reliable long-term anchoring. This disclosure relates to techniques for patterning arbitrarily shaped 3D objects and to patterned balloon devices having micro- or nano-patterning on an outer surface of an inflatable balloon. The external pattern can provide enhanced friction and anchoring in an aqueous environment. Examples of these types of patterns are hexagonal arrays inspired by tree frogs, corrugated patterns, and microneedle patterns. The patterned balloon devices can be disposed between an implant and surrounding tissues to facilitate anchoring of the implant.

Growing community of inventors

Brooklyn, NY, United States of America

James K Min