SBIR-STTR Award

Proposal There is increasing appreciation of a syndrome in which patients female patients, present with chestpain due to myocardial ischemia and have a normal or near normal coronary angiogram. Termedcoronary microvascular dysfunction (MVD) this disorder is not benign with cardiovascular event ratessimilar to those with established coronary artery disease. Clinical tools are therefore needed to bothidentify MVD patients and better understand the mechanisms causing myocardial ischemia. There isevidence that myocardial contrast echocardiography (MCE) provides incremental information in theevaluation of patients with coronary artery disease, myocardial viability, or diseases of themicrovasculature. Despite data demonstrating the diagnostic and prognostic benefit of MCE inevaluating patients with MVD, its clinical use has been limited to only a handful of experts in the field,because there are currently no widely available clinical tools to support MCE quantitative analysis andinterpretation. The overall aim of this Phase I proposal is to provide clinicians with a new tool toevaluate the myocardial flow-function relationship that is critical to identifying patients with MVD byusing echocardiography. We will develop clinical software that can rapidly process MCE data into astandardized, quantitative and easy- to- interpret format. In Aim 1, the power of image averaging andcomputer aided assessment of radial wall thickening will be used to enhance the current standard of carewhich relies solely on readers' visual estimation of segmental function. An algorithm will be developed torearrange the order of images so that images representing the same phase of the cardiac cycle aregrouped together. Functional analysis will then be developed using computer-aided tracings of epicardialand endocardial borders. In Aim 2, a software module for quantitative analysis of real-time MCEperfusion will be developed that will incorporate statistical confidence, derived from the performance ofimage processing algorithms to inform the interpreter about the data strength. Machine learning will beutilized to train and deploy a neural network for the pixel-by-pixel assessment of myocardial perfusion.In Aim 3, we will combine myocardial perfusion and function modules into a novel, perfusion-functionmode of imaging (PF-mode). This new mode will be applied to an archival sample of clinically diagnosedMVD cases to demonstrate the feasibility to detect abnormalities in the myocardial flow-functionrelationship. The composite PF-mode will include a cine-loop rendered for one cardiac cycle whereparametric images (perfusion) are superimposed over averaged ultrasound images with an overlay ofgraphic representation of wall thickness (function). This novel mode of imaging provides the means todiagnose MVD in a single clinical study.

Public Health Relevance Statement:
Project Narrative Project Title: Reading workstation for clinical contrast echocardiography Despite a wealth of evidence that myocardial contrast echocardiography imaging of myocardial perfusion provides incremental information in the evaluation of patients with diseases of the myocardial microvasculature (MVD), its clinical use has been limited to only a handful of experts in the field. In this proposal, we have created a multidisciplinary partnership between physicians-scientists and engineers with the overall aim to address this clinical gap that exists between a proven echocardiographic technique and the technology necessary to enable widespread adoption of MCE clinically. We will develop a software program enabling a new method for evaluating the myocardial flow-function relationship using echocardiography that will enable the identification of MVD using MCE studies at the level of expert readers.

Project Terms:
Adoption ; Algorithms ; Anatomy ; Anatomic ; Anatomic Sites ; Anatomic structures ; Anatomical Sciences ; Angiography ; Angiogram ; angiographic imaging ; arteriole ; Blood ; Blood Reticuloendothelial System ; Blood Flow Velocity ; Cardiovascular system ; Cardiovascular ; Cardiovascular Body System ; Cardiovascular Organ System ; Heart Vascular ; circulatory system ; Chest Pain ; Classification ; Systematics ; Clinical Research ; Clinical Study ; Color ; Computers ; Contrast Media ; Contrast Agent ; Contrast Drugs ; Radiopaque Media ; Coronary Arteriosclerosis ; Coronary Artery Disease ; Coronary Artery Disorder ; Coronary Atherosclerosis ; atherosclerotic coronary disease ; coronary arterial disease ; Diagnosis ; Disease ; Disorder ; Echocardiography ; Echocardiogram ; Transthoracic Echocardiography ; heart sonography ; Contrast Echocardiography ; Engineering ; Eye ; Eyeball ; Female ; indexing ; Methods ; Microcirculation ; Names ; Patients ; Perfusion ; Physicians ; Reading ; Recommendation ; Rest ; Societies ; Computer software ; Software ; Software Engineering ; Computer Software Development ; Computer Software Engineering ; Standardization ; Stress ; Syndrome ; Technology ; Time ; single photon emission computed tomography ; SPECT ; SPECT imaging ; Single-Photon Emission-Computed Radionuclide Tomography ; Ultrasonography ; Echography ; Echotomography ; Medical Ultrasound ; Ultrasonic Imaging ; Ultrasonogram ; Ultrasound Diagnosis ; Ultrasound Medical Imaging ; Ultrasound Test ; diagnostic ultrasound ; sonogram ; sonography ; sound measurement ; ultrasound ; ultrasound imaging ; ultrasound scanning ; Vendor ; Imaging Techniques ; Imaging Procedures ; Imaging Technics ; Myocardial Ischemia ; Ischemic Heart ; Ischemic Heart Disease ; Ischemic myocardium ; cardiac ischemia ; coronary ischemia ; heart ischemia ; myocardial ischemia/hypoxia ; myocardium ischemia ; Guidelines ; Clip ; base ; image processing ; Apical ; Benign ; Clinical ; Phase ; Medical ; Evaluation ; prognostic ; Training ; Visual ; clinical Diagnosis ; tool ; Diagnostic ; machine learned ; Machine Learning ; programs ; mechanical ; Mechanics ; Scientist ; Myocardial perfusion ; Event ; Side ; Radius ; Radial ; Techniques ; American ; Performance ; novel ; Coding System ; Code ; Myocardial Diseases ; Myocardial Disorder ; Myocardiopathies ; myocardium disease ; myocardium disorder ; Cardiomyopathies ; Thickness ; Thick ; Address ; Data ; Reader ; Process ; Coronary ; Myocardial ; Cardiac ; Image ; imaging ; Computer Assisted ; computer aided ; multidisciplinary ; user-friendly ; standard of care ; Microvascular Dysfunction ; microvascular complications ; microvascular disease ; small vessel disease ; endothelial dysfunction ; imaging software ; perfusion imaging ; parametric imaging ; neural network ; sample archive ;

Coronary microvascular dysfunction (MVD) is increasingly being appreciated as a part of the pathophysiology ofa number of conditions including MINOCA (myocardial infarction with nonobstructive coronary arteries), hearttransplant graft vasculopathy, and heart failure with preserved ejection fraction (HFpEF). Coronary MVD occursmore commonly in women and can result in chest pain due to myocardial ischemia despite the presence ofnormal or near normal coronary angiograms. Identifying MVD in patients remains challenging and results indelayed or missed diagnoses even though cardiovascular event rates in these conditions are similar to thosewith established coronary artery disease. Clinical tools are therefore needed to both rapidly and accurately detectthese conditions. Echocardiographic imaging of the myocardial microcirculation using ultrasound contrastagents, referred to as myocardial contrast echocardiography (MCE), has decades of data demonstrating thediagnostic and prognostic benefit of MCE in evaluating patients with MVD. In many ways, MCE is the preferredmethod for perfusion assessment because it is more convenient, less expensive, and more available thancomparative techniques of nuclear imaging (SPECT), positron emission tomography (PET), and cardiac MRI.However, the clinical use of MCE has been limited to only a handful of experts in the field due in large part to theperceived experience dependence of MCE interpretation. Currently, no widely available clinical tools exist tosupport MCE quantitative analysis and interpretation. A clinical gap exists between a proven echocardiographictechnique and the technology necessary to apply MCE in an efficient, user friendly and standardized method.Narnar LLC is developing a user-friendly contrast echocardiography quantification and visualization software.This product is designed to overcome the existing critical limitations of MCE by enabling rapid interpretation.This new clinical tool will evaluate the myocardial flow-function relationship that is critical to identifying patientswith MVD by using echocardiography. The overall aim of this phase II proposal is to productionize the prototypesoftware into a comprehensive software solution that when integrated into the current workflows using alreadyavailable technologies (ultrasound, FDA approved enhancing agents) will enable a cardiologist to confidentlyassess both function and perfusion by contrast echocardiography.

Public Health Relevance Statement:
NARRATIVE The goal of this study is to establish the utility of GECHO, the analytical software Narnar has been developing, in a simulated but realistic environment. Current approaches to use enhanced ultrasound to diagnose myocardial perfusion defects are underutilized and constrained to a relatively small population of experts in this field. This proposal will address this need by developing a reading workstation for visualization and quantification of ultrasound studies that will empower much wider medical community to interpret enhanced studies with diagnostic confidence.

Project Terms: