Description

Stress perfusion cardiac magnetic resonance (CMR), Cardiac Computed Tomography (CT) and Positron Emission Tomography (PET) are well-established non-invasive imaging tests that are increasingly being used for the assessment of patients with known or suspected ischemic heart disease [1]. While all of these clinically established modalities have different characteristics and thus inherent advantages and disadvantages, none of them alone allows simultaneous exclusive visualization of anatomic, functional, and metabolic features of the heart. Stress CMR provides an accu-rate assessment of cardiac function [2, 3], myocardial scar [4, 5], and myocardial ischemia [6-8]. However, stress perfusion CMR remains underutilized for the assessment of chest pain compared with other non-invasive methods [8]. This is in part due to cost, inadequate access to the technology, long scan times, and an insufficient number of physicians with expertise to interpret the images while automated analysis is not well established for CMR. On the other side, stress PET perfusion imaging can accurately assess myocardial scar and myocardial ischemia and has moreover the unique ability to quantify myocardial blood flow [9, 10].

Given this discrepancy between the professional guidelines supporting the use of stress CMR and the lack of adoption into clinical practice, there is significant interest in developing: (A) more efficient and higher quality image acquisition and (B) more automated and quantitative image analysis approaches to improve the utilization of and access to stress CMR. One such improvement is the modification of the magnetic resonance imaging (MRI) pulse sequence currently used to assess myocardial perfusion so that it can also simultaneously be used to provide the information necessary to quantify myocardial blood flow [11]. Indeed when combined with a specially designed image analysis software, this modified pulse sequence provides images that can be used to automatically quantify myocardial blood flow on a pixel-by-pixel basis [12].

Further improvements in the software used to acquire and analyse stress CMR images are needed to make this important diagnostic tool more accessible to patients that would benefit from it.

Hence, the primary goal of this study is to compare in a larger patient sample perfusion and metabolism assessed by MR or complimentary by PET and MR in terms of identifying individuals with myocardial perfusion defects. Furthermore, in those patients where cardiac CT and invasive coro-nary angiography data is available (from clinical routine examinations), complimentary anatomy and perfusion measures of CT, PET, coronary angiography, and MR measurements will be assessed as well. Within this study a comparison of various assessments and possible readouts will be compared with regards values and parameters received. Typical readouts used in clinical routine and available automated algorithms will be used. The goal is to evaluate current clinical protocols, its benefits and potential optimization.

Additionally, this study will submit data into a multicentric data registry in order to efficiently test and validate potential of future technological developments in CMR. Therefore, the de-identified images and raw data acquired will be collected from multiple centers and stored at a HIPAA-compliant repository at University of Chicago Medicine and the University of Virginia. The images which would fulfill the criteria for this register will be further processed. The de-identified imaging and clinical data will be distributed to a Core Laboratory located at McGill University (Montreal, Canada) and also to other academic partners for image processing, image analysis, and software development. Additionally, downstream testing and patient outcomes will be collected as pilot data towards determining the clinical impact of automated quantitative myocardial blood flow analysis of stress CMR images.