Prognostic value of coronary plaque composition in symptomatic patients with obstructive coronary artery disease.

Objectives: To determine whether plaque composition analysis defined by cardiac CT can provide incremental prognostic value above coronary artery disease (CAD) burden markers in symptomatic patients with obstructive CAD.

Materials And Methods: Between 2009 and 2019, a multicentric registry included all consecutive symptomatic patients with obstructive CAD (at least one ≥ 50% stenosis on CCTA) and was followed for major adverse cardiovascular (MACE) defined by cardiovascular death or nonfatal myocardial infarction. Each coronary segment was scored visually for both the degree of stenosis and composition of plaque, which were classified as non-calcified, mixed, or calcified.

Unusual Cause of Ventricular Arrhythmia.

Although relatively rare, cardiac metastases represent a significant clinical challenge because of their impact on cardiac function and overall patient prognosis. This case presents a rare and atypical presentation of a patient with ventricular arrhythmia revealing a metastatic cancer in the heart. A 59-year-old man with lung cancer was admitted for chest tightness and episodes of syncope.

A Machine Learning Model Using Cardiac CT and MRI Data Predicts Cardiovascular Events in Obstructive Coronary Artery Disease.

Background Multimodality imaging is essential for personalized prognostic stratification in suspected coronary artery disease (CAD). Machine learning (ML) methods can help address this complexity by incorporating a broader spectrum of variables. Purpose To investigate the performance of an ML model that uses both stress cardiac MRI and coronary CT angiography (CCTA) data to predict major adverse cardiovascular events (MACE) in patients with newly diagnosed CAD.

Prognostic Value of Cardiac MRI Late Gadolinium Enhancement Granularity in Participants with Ischemic Cardiomyopathy.

Background Ischemic late gadolinium enhancement (LGE) assessed with cardiac MRI is a well-established prognosticator in ischemic cardiomyopathy. However, the prognostic value of additional LGE parameters, such as extent, transmurality, location, and associated midwall LGE, remains unclear. Purpose To assess the prognostic value of ischemic LGE features to predict all-cause mortality in ischemic cardiomyopathy.

Functional imaging after the "ISCHEMIA" trial.

Previous randomized trials have shown a lack of benefits from the addition of revascularization to optimal medical therapy versus optimal medical therapy alone in patients with stable ischaemic heart disease at relatively low risk (Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation [COURAGE]), and in diabetic patients with stable ischaemic heart disease (Bypass Angioplasty Revascularization Investigation in Type 2 Diabetics [BARI 2D]). More recently, the International Study of Comparative Health Effectiveness with Medical and Invasive Approaches (ISCHEMIA) randomized clinical trial showed similar results in patients with moderate-severe ischaemia on functional testing (imaging or stress electrocardiogram) and at least one significant (> 50%) coronary stenosis in a major epicardial coronary artery on coronarography computed coronary angiography. Although the ISCHEMIA trial adds pivotal knowledge regarding the management of and decision-making in stable patients, this study has prompted a great debate about the role of functional imaging for diagnosis, risk stratification and therapeutic decision-making.

Bobo-Newton acute myocarditis caused by : a case report.

Background: Capnocytophaga canimorsus is a Gram-negative bacillus commensal of the oral cavities of dogs and cats that can cause human infection after a bite or scratch. Cardiovascular manifestations have included endocarditis, heart failure, acute myocardial infarction, mycotic aortic aneurysm and prosthetic aortitis.

Case Summary: A 37-year-old male presented septic manifestations, ST-segment alterations on the electrocardiogram and troponin rise, 3 days after a dog bite.

AI-Based Fully Automated Left Atrioventricular Coupling Index as a Prognostic Marker in Patients Undergoing Stress CMR.

Background: The left atrioventricular coupling index (LACI) is a strong and independent predictor of heart failure (HF) in individuals without clinical cardiovascular disease. Its prognostic value is not established in patients with cardiovascular disease.

Objectives: This study sought to determine in patients undergoing stress cardiac magnetic resonance (CMR) whether fully automated artificial intelligence-based LACI can provide incremental prognostic value to predict HF.

Case report: Diagnosis, management and evolution of a bulky and invasive cardiac mass complicated by complete atrioventricular block.

Introduction: Cardiac lymphoma is a rare but serious disease that is usually located in the right heart. The symptoms (dyspnea, respiratory distress, fatigue, syncope…) are not specific and depend on the mass location. Cardiac magnetic resonance has a crucial role in the diagnostic strategy but biopsy is mandatory to confirm the diagnosis.

Computed Tomography/Fluoroscopy Fusion and 3D Transesophageal Echocardiography-Guided Percutaneous Paravalvular Leak Closure.

Percutaneous paravalvular leak closure seems a safe alternative to surgery in frail patients. However, it is a challenging procedure that should be tailored to each patient with optimal imaging guidance. Transesophageal echocardiography during the procedure and computed tomography scan/fluoroscopy fusion provide guidance for critical steps, such as PVL localization and crossing.

Clustering of patients with inconclusive non-invasive stress testing referred for vasodilator stress cardiovascular magnetic resonance.

Background: Inconclusive non-invasive stress testing is associated with impaired outcome. This population is very heterogeneous, and its characteristics are not well depicted by conventional methods.

Aims: To identify patient subgroups by phenotypic unsupervised clustering, integrating clinical and cardiovascular magnetic resonance data to unveil pathophysiological differences between subgroups of patients with inconclusive stress tests.

[The role of Cardiovascular Magnetic Resonance in Interventional Cardiology].

Cardiovascular magnetic resonance has emerged as a very helpful tool for the interventional cardiologists not only in the assessment and treatment of coronary artery disease, but also in the evaluation of various structural cardiac diseases. The main pulse sequences are standardised, acquired during short breath-holds, and include steady-state free precession cines, dynamic myocardial first-pass perfusion imaging during contrast injection, and late enhancement imaging for the identification of myocardial substrates. Less than 30-minute CMR studies are now available for the most common clinical indications.

Safety, feasibility, and prognostic value of stress perfusion CMR in patients with MR-conditional pacemaker.

Aims: To assess the safety, feasibility, and prognostic value of stress cardiovascular magnetic resonance (CMR) in patients with pacemaker (PM).

Methods And Results: Between 2008 and 2021, we conducted a bi-centre longitudinal study with all consecutive patients with MR-conditional PM referred for vasodilator stress CMR at 1.5 T in the Institut Cardiovasculaire Paris Sud and Lariboisiere University Hospital.

Additional prognostic value of stress cardiovascular magnetic resonance for cardiovascular risk stratification after a cryptogenic ischemic stroke.

Background: One-third of ischemic strokes are "cryptogenic" without clearly identified etiology. Although coronary artery disease (CAD) is the main cause of death after stroke, the interest in CAD screening in patients with cryptogenic stroke is still debated.

Aim: The aim of the study was to assess the incremental prognostic value of stress cardiovascular magnetic resonance (CMR) beyond traditional risk factors for predicting cardiovascular events in patients with a prior cryptogenic ischemic stroke.

Machine-Learning Score Using Stress CMR for Death Prediction in Patients With Suspected or Known CAD.

Background: In patients with suspected or known coronary artery disease, traditional prognostic risk assessment is based on a limited selection of clinical and imaging findings. Machine learning (ML) methods can take into account a greater number and complexity of variables.

Objectives: This study sought to investigate the feasibility and accuracy of ML using stress cardiac magnetic resonance (CMR) and clinical data to predict 10-year all-cause mortality in patients with suspected or known coronary artery disease, and compared its performance with existing clinical or CMR scores.