Atrial function provided incremental prognostic value for major adverse cardiovascular event prediction beyond established clinical and cardiac MRI parameters, including ventricular function and in... Background The role of left atrial (LA) performance in acute myocardial infarction (AMI) remains controversial. Cardiac MRI myocardial feature tracking (hereafter, MRI-FT) is a method used to quant...

Background: Right ventricular (RV) function is a known predictor of adverse events in heart failure and following acute myocardial infarction (AMI). While right atrial (RA) involvement is well characterized in pulmonary arterial hypertension, its relative contributions to adverse events following AMI especially in patients with heart failure and congestion need further evaluation. Methods: In this cardiovascular magnetic resonance (CMR)-substudy of AIDA STEMI and TATORT NSTEMI, 1235 AMI patients underwent CMR after primary percutaneous coronary intervention (PCI) in 15 centers across Germany (n = 795 with ST-elevation myocardial infarction and 440 with non-ST-elevation MI). Right atrial (RA) performance was evaluated using CMR myocardial feature tracking (CMR-FT) for the assessment of RA reservoir (total strain ε_s), conduit (passive strain ε_e), booster pump function (active strain ε_a), and associated strain rates (SR) in a blinded core-laboratory. The primary endpoint was the occurrence of major adverse cardiac events (MACE) 12 months post AMI. Results: RA reservoir (ε_s p = 0.061, SRs p = 0.049) and conduit functions (ε_e p = 0.006, SRe p = 0.030) were impaired in patients with MACE as opposed to RA booster pump (ε_a p = 0.579, SRa p = 0.118) and RA volume index (p = 0.866). RA conduit function was associated with the clinical onset of heart failure and MACE independently of RV systolic function and atrial fibrillation (AF) (multivariable analysis hazard ratio 0.95, 95% confidence interval 0.92 to 0.99, p = 0.009), while RV systolic function and AF were not independent prognosticators. Furthermore, RA conduit strain identified low- and high-risk groups within patients with reduced RV systolic function (p = 0.019 on log rank testing). Conclusions: RA impairment is a distinct feature and independent risk factor in patients following AMI and can be easily assessed using CMR-FT-derived quantification of RA strain.

This study evaluates the diagnostic performance of radiomic features and machine learning algorithms for renal tumor subtype assessment in venous computed tomography (CT) studies from clinical routine. Patients undergoing surgical resection and histopathological assessment of renal tumors at a tertiary referral center between 2012 and 2019 were included. Preoperative venous-phase CTs from multiple referring imaging centers were segmented, and standardized radiomic features extracted. After preprocessing, class imbalance handling, and feature selection, machine learning algorithms were used to predict renal tumor subtypes using 10-fold cross validation, assessed as multiclass area under the curve (AUC). In total, n = 201 patients were included (73.7% male; mean age 66 ± 11 years), with n = 131 clear cell renal cell carcinomas (ccRCC), n = 29 papillary RCC, n = 11 chromophobe RCC, n = 16 oncocytomas, and n = 14 angiomyolipomas (AML). An extreme gradient boosting algorithm demonstrated the highest accuracy (multiclass area under the curve (AUC) = 0.72). The worst discrimination was evident for oncocytomas vs. AML and oncocytomas vs. chromophobe RCC (AUC = 0.55 and AUC = 0.45, respectively). In sensitivity analyses excluding oncocytomas, a random forest algorithm showed the highest accuracy, with multiclass AUC = 0.78. Radiomic feature analyses from venous-phase CT acquired in clinical practice with subsequent machine learning can discriminate renal tumor subtypes with moderate accuracy. The classification of oncocytomas seems to be the most complex with the lowest accuracy.

Gadolinium-based contrast agents used in cardiac MRI have an acute adverse event rate of 0.38%; in Europe, macrocyclic contrast agents are primarily used and demonstrate a favorable safety profile ... Purpose To assess current use and acute safety profiles of gadolinium-based contrast agents (GBCAs) in cardiac MRI given recent suspensions of GBCA approval. Materials and Methods Patients were ret...