18F-FDG PET/CMR in cardiac sarcoidosis: A wild card in the deck?

Multimodality imaging in arrhythmogenic cardiomyopathy - From diagnosis to management

Arrhythmogenic Cardiomyopathy (AC), an inherited cardiac disorder characterized by myocardial fibrofatty replacement, carries a significant risk of sudden cardiac death (SCD) due to ventricular arrhythmias. A comprehensive multimodality imaging approach, including echocardiography, cardiac magnetic resonance imaging (CMR), and cardiac computed tomography (CCT), allows for accurate diagnosis, effective risk stratification, vigilant monitoring, and appropriate intervention, leading to improved patient outcomes and the prevention of SCD. Echocardiography is primary tool ventricular morphology and function assessment, CMR provides detailed visualization, CCT is essential in early stages for excluding congenital anomalies and coronary artery disease. Echocardiography is preferred for follow-up, with CMR capturing changes over time. The strategic use of these imaging methods aids in confirming AC, differentiating it from other conditions, tracking its progression, managing complications, and addressing end-stage scenarios.

Review of cardiovascular imaging in the Journal of Nuclear Cardiology 2022: positron emission tomography, computed tomography, and magnetic resonance

In 2022, the Journal of Nuclear Cardiology® published many excellent original research articles and editorials focusing on imaging in patients with cardiovascular disease. In this review of 2022, we summarize a selection of articles to provide a concise recap of major advancements in the field. In the first part of this 2-part series, we addressed publications pertaining to single-photon emission computed tomography. In this second part, we focus on positron emission tomography, cardiac computed tomography, and cardiac magnetic resonance. We specifically review advances in imaging of non-ischemic cardiomyopathy, cardio-oncology, infectious disease cardiac manifestations, atrial fibrillation, detection and prognostication of atherosclerosis, and technical improvements in the field. We hope that this review will be useful to readers as a reminder to articles they have seen during the year as well as ones they have missed.

Exploring the Utility of Cardiovascular Magnetic Resonance Radiomic Feature Extraction for Evaluation of Cardiac Sarcoidosis

BACKGROUND

The aim of this study is to explore the utility of cardiac magnetic resonance (CMR) imaging of radiomic features to distinguish active and inactive cardiac sarcoidosis (CS).

METHODS

Subjects were classified into active cardiac sarcoidosis (CSactive) and inactive cardiac sarcoidosis (CSinactive) based on PET-CMR imaging. CSactive was classified as featuring patchy [18F]fluorodeoxyglucose ([18F]FDG) uptake on PET and presence of late gadolinium enhancement (LGE) on CMR, while CSinactive was classified as featuring no [18F]FDG uptake in the presence of LGE on CMR. Among those screened, thirty CSactive and thirty-one CSinactive patients met these criteria. A total of 94 radiomic features were subsequently extracted using PyRadiomics. The values of individual features were compared between CSactive and CSinactive using the Mann-Whitney U test. Subsequently, machine learning (ML) approaches were tested. ML was applied to two sub-sets of radiomic features (signatures A and B) that were selected by logistic regression and PCA, respectively.

RESULTS

Univariate analysis of individual features showed no significant differences. Of all features, gray level co-occurrence matrix (GLCM) joint entropy had a good area under the curve (AUC) and accuracy with the smallest confidence interval, suggesting it may be a good target for further investigation. Some ML classifiers achieved reasonable discrimination between CSactive and CSinactive patients. With signature A, support vector machine and k-neighbors showed good performance with AUC (0.77 and 0.73) and accuracy (0.67 and 0.72), respectively. With signature B, decision tree demonstrated AUC and accuracy around 0.7; Conclusion: CMR radiomic analysis in CS provides promising results to distinguish patients with active and inactive disease.

Prognostic value of heart rate reserve in patients with suspected coronary artery disease undergoing stress myocardial perfusion imaging

BACKGROUND

Chronotropic incompetence is common in patients with cardiovascular disease and is associated with increased risk of adverse events. We assessed the incremental prognostic value of heart rate reserve (HRR) over stress myocardial perfusion single-photon emission computed tomography (MPS) findings in patients with suspected coronary artery disease (CAD).

METHODS

We studied 866 patients with suspected CAD undergoing exercise stress-MPS as part of their diagnostic program. The primary study endpoint was all-cause mortality. All patients were followed for at least 5 years. HRR was calculated as the difference between peak exercise and resting HR, divided by the difference of age-predicted maximal and resting HR and expressed as percentage.

RESULTS

During 7 years follow-up, 61 deaths occurred, with a 7% cumulative event rate. Patients experiencing death were older (P < .001), and had a higher prevalence of male gender (P < .001) and diabetes (P < .05). Patients with event also had lower values of HRR (65% ± 27% vs 73% ± 18%, P < .0001) and higher prevalence of stress-induced myocardial ischemia (25% vs 8%, P < .0001). Male gender, HRR and stress-induced ischemia were independent predictors of all-cause mortality (all P < .01). HRR improved the prognostic power of a model including clinical data and MPS findings, increasing the global χ2 from 66 to 82 (P < .005).

CONCLUSIONS

Chronotropic incompetence has independent and incremental prognostic value in predicting all-cause mortality in patients with suspected CAD undergoing exercise stress-MPS. Hence, the evaluation of HRR may further improve patients' risk stratification.