Right ventricular involvement in ST-segment elevation MI is detected more frequently with cardiac MRI than with ECG and echocardiography and is an independent prognostic indicator.

Coronary artery disease (CAD) is currently the leading cause of death in developed nations. Reflecting the complexity of cardiac function and morphology, noninvasive diagnosis of CAD represents a major challenge for medical imaging. Although coronary artery stenoses can be depicted with magnetic resonance (MR) and computed tomography (CT) techniques, its functional or hemodynamic impact frequently remains elusive. Therefore, there is growing interest in other, target organ‐specific parameters such as myocardial function at stress and first‐pass myocardial perfusion imaging to assess myocardial blood flow. This review explores the pathophysiologic background, recent technical developments, and current clinical status of first‐pass MR imaging (MRI) of myocardial perfusion. J. Magn. Reson. Imaging 2004;19:750–757. © 2004 Wiley‐Liss, Inc.

(1) Background: Epi- and Paracardial Adipose Tissue (EAT, PAT) have been spotlighted as important biomarkers in cardiological assessment in recent years. Since biomarker quantification is an increasingly important method for clinical use, we wanted to examine fully automated EAT and PAT quantification for possible use in cardiovascular risk stratification. (2) Methods: 966 patients with intermediate Framingham risk scores for Coronary Artery Disease referred for coronary calcium scans were included in clinical routine retrospectively. The Coronary Artery Calcium Score (CACS) was extracted and tissue quantification was performed by a deep learning network. (3) Results: The Computed Tomography (CT) segmentations predicted by the network indicated no significant correlation between EAT volume and EAT radiodensity when compared to Agatston score (r = 0.18, r = −0.09). CACS 0 category patients showed significantly lower levels of total EAT and PAT volumes and higher EAT and PAT densities than CACS 1–99 category patients (p < 0.01). Notably, this difference did not reach significance regarding EAT attenuation in male patients. Women older than 50 years, thus more likely to be postmenopausal, were shown to be at higher risk of coronary calcification (p < 0.01, OR = 4.59). CACS 1–99 vs. CACS ≥100 category patients remained below significance level (EAT volume: p = 0.087, EAT attenuation: p = 0.98). (4) Conclusions: Our study proves the feasibility of a fully automated adipose tissue analysis in clinical cardiac CT and confirms in a large clinical cohort that volume and attenuation of EAT and PAT are not correlated with CACS. Broadly available deep learning based rapid and reliable tissue quantification should thus be discussed as a method to assess this biomarker as a supplementary risk predictor in cardiac CT.

NR as a correlate of microvascular obstruction remains independently related to prognosis in patients with acute myocardial infarction treated by PCI.

We compared two different magnetic resonance (MR) sequences [steady-state free precession (SSFP) and gradient echo fast low-angle shot (FLASH)] for the assessment of aortic valve areas in aortic stenosis using transesophageal echocardiography (TEE) as the standard of reference. Thirty-two patients with known aortic stenosis underwent MR (1.5 T) using a cine SSFP sequence and a cine FLASH sequence. Planimetry was performed in cross-sectional images and compared to the results of the TEE. In seven patients the grade of stenosis was additionally assessed by invasive cardiac catheterization (ICC). The mean aortic valve area measured by TEE was 0.97+/-0.19 mm(2), 1.00+/-0.25 mm(2) for SSFP and 1.25+/-0.23 mm(2) based on FLASH images. The mean difference between the valve areas assessed based on SSFP and TEE images was 0.15+/-0.13 cm(2) (FLASH vs TEE: 0.29+/-0.17 cm(2)). Bland-Altman analysis demonstrated that measurements using FLASH images overestimated the aortic valve area compared to TEE. Comparing ICC with MRI and TEE, only a weak to moderate correlation was found (ICC vs TEE: R=0.52, p=0.22; ICC vs SSFP: R=0.20, p=0.65; ICC vs FLASH: R=0.16, p=0.70). Measurements of the aortic valve area based on SSFP images correlate better with TEE compared to FLASH images.