Cardiac MRI in Front Line for the Diagnosis of Coronary Artery Disease as the Etiology of Left Ventricular Dysfunction

Overview

When a patient is newly diagnosed of systolic dysfunction without obvious etiology (such as rhythmic, ischemic, or valvular disease), most of the time a coronary angiography is performed. In this situation, the investigators aim to evaluate a strategy with CMR as the front line exam, and invasive coronary angiography performed only in case of ischemic scar on CMR Additionally, a secondary analysis of the collected CMR images will be performed by the MIRACL.AI core lab (AP-HP, Paris) using artificial intelligence (AI) algorithms. This analysis aims to enhance the diagnostic accuracy of coronary artery disease (CAD) detection in patients with reduced left ventricular ejection fraction (rLVEF).

Reduced Left Ventricular Ejection Fraction (LVEF) is estimated to be present in 3-7% of the population. With a survival rate between 25-40% at 5 years after a first hospitalization, prognosis of heart failure is similar to that of most cancers. Its treatment and prognosis strongly depend on the etiology, and coronary artery disease is the most frequent one. Identifying coronary artery disease determines care, including medical treatment (aspirin, statins) and revascularization strategies (stent implantation, coronary artery bypass grafting). Once an echocardiography has revealed an LV reduction, with no clear etiology at clinical or echographical examination, coronary angiography is almost systematically performed. But among the 260,000 invasive coronary angiographies performed each year in France (all indications included), 30-60% are "normal" (no obstructive coronary artery). And among patients with unexplained LV dysfunction, this rate reaches 70-74%… Thus the efficiency of systematic coronary angiography is questionable for these latter. Besides, angiography is invasive, and associated with multiple risks and costs. Cardiac Magnetic Resonance Imaging (CMR) is very specific and sensitive for detecting myocardial infarction. Small series concluded that a reduction of LVEF due to coronary artery stenosis should have at least one myocardial scar, detected on CMR. But the available data was not enough to change guidelines and clinical practice. In our retrospective study performed on 305 patients, the sensibility of CMR for coronary stenosis was 96%. Furthermore, CMR as a first-line exam would have avoided 71% of coronary angiography, saving 216 days of hospitalization and 329.054 € (1.079€/patient). These results reinforce the previous data but are not definitive. The aim of this study is to provide a high level of evidence of the benefits and safety of a strategy based on CMR as the front line exam for newly diagnosed systolic dysfunctions. The primary objective is to evaluate the sensitivity of CMR for predicting the presence of angiographically significant coronary artery stenosis in patients with reduced LVEF. The primary endpoint is the sensitivity of CMR for predicting the presence of significant coronary artery stenosis on coronary angiography in patients with reduced LVEF. The objective of the economic evaluation is to estimate the incremental (or decremental) cost effectiveness of using CMR first compared to coronary angiography first. As part of the secondary analysis, CMR images from the CAMAREC study will be transferred to the Multimodality Imaging for Research and Analysis Core Laboratory for Artificial Intelligence (MIRACL.AI) at AP-HP, Paris. The MIRACL.AI team, led by Dr. Theo Pezel, will apply advanced AI algorithms to detect ischemic patterns and quantify myocardial scarring. This AI analysis aims to improve the sensitivity and specificity of CMR in identifying significant CAD and non-ischemic cardiomyopathies. For unexplained LV dysfunction, patient will be addressed for CMR first and coronary angiography within 2 weeks after (instead of systematic coronary angiography and unsystematic CMR). CMR and coronary angiography will be performed in all patients. Independent committees will blindly review CMRs and coronary angiographies at the end of the study. Data from the CAMAREC study will be securely transferred to MIRACL.AI for AI-based analysis. This transfer does not affect the data flow to Lariboisière, nor the confidentiality or the study\'s timeline. MIRACL.AI will solely focus on the AI-enhanced interpretation of the CMR images.