Deep learning-based whole-brain B -mapping at 7T.

Purpose: This study investigates the feasibility of using complex-valued neural networks (NNs) to estimate quantitative transmit magnetic RF field (B ) maps from multi-slice localizer scans with different slice orientations in the human head at 7T, aiming to accelerate subject-specific B -calibration using parallel transmission (pTx).

Methods: Datasets containing channel-wise B -maps and corresponding multi-slice localizers were acquired in axial, sagittal, and coronal orientation in 15 healthy subjects utilizing an eight-channel pTx transceiver head coil. Training included five-fold cross-validation for four network configurations: used transversal, sagittal, coronal data, and was trained on all slice orientations.

Robust Myocardial Perfusion MRI Quantification with DeepFermi.

Stress perfusion cardiac magnetic resonance is an important technique for examining and assessing the blood supply of the myocardium. Currently, the majority of clinical perfusion scans are evaluated based on visual assessment by experienced clinicians. This makes the process subjective, and to this end, quantitative methods have been proposed to offer a more user-independent assessment of perfusion.

Long-term lipoprotein apheresis reduces cardiovascular events in high-risk patients with isolated lipoprotein(a) elevation.

Background: Elevated lipoprotein(a) (Lp(a)) is an established risk factor for cardiovascular disease (CVD). To date, the only approved treatment to lower Lp(a) is lipoprotein apheresis (LA). Previous studies have demonstrated that LA is effective in reducing cardiovascular (CV) risk in patients with elevated low-density lipoprotein cholesterol (LDL-C) and/or Lp(a).