WALINET: A water and lipid identification convolutional neural network for nuisance signal removal in MR spectroscopic imaging.

Purpose: Proton magnetic resonance spectroscopic imaging ( -MRSI) provides noninvasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain -MRSI are spectral overlap of metabolite peaks with large lipid signal from scalp, and overwhelming water signal that distorts spectra. Fast and effective methods are needed for high-resolution -MRSI to accurately remove lipid and water signals while preserving the metabolite signal.

Mevalonate kinase deficiency: an updated clinical overview and revision of the SHARE recommendations.

Mevalonate kinase deficiency (MKD), a rare auto-inflammatory disorder, arises from mutations in the gene, disrupting isoprenoid biosynthesis, and affecting cellular processes. This comprehensive review provides an updated perspective on MKD, including its aetiology, pathogenesis, diagnostic modalities, and therapeutic strategies. Based on recent research and clinical advances, our objective is to bridge the knowledge gaps in the 2015 SHARE guidelines.

Role of DOCK8 in cytokine storm syndromes.

Background: Cytokine storm syndromes (CSSs), including hemophagocytic lymphohistiocytosis (HLH), are increasingly recognized as hyperinflammatory states leading to multiorgan failure and death. Familial HLH in infancy results from homozygous genetic defects in perforin-mediated cytolysis by CD8 T lymphocytes and natural killer (NK) cells. Later-onset CSSs are often associated with heterozygous defects in familial HLH genes, but genetic etiologies for most are unknown.

Predicting dynamic, motion-related changes in B field in the brain at a 7T MRI using a subject-specific fine-trained U-net.

Purpose: Subject movement during the MR examination is inevitable and causes not only image artifacts but also deteriorates the homogeneity of the main magnetic field (B ), which is a prerequisite for high quality data. Thus, characterization of changes to B , for example induced by patient movement, is important for MR applications that are prone to B inhomogeneities.

Methods: We propose a deep learning based method to predict such changes within the brain from the change of the head position to facilitate retrospective or even real-time correction.

Majority of new patient referrals to a large pediatric rheumatology center result in non-rheumatic diagnosis.

Objective: Pediatric rheumatology faces a looming supply-demand crisis. While strategies have been proposed to address the supply shortfall, investigation into the increased demand for pediatric rheumatic care has been limited. Herein, we analyze new patient visits to a large tertiary care pediatric rheumatology center to identify emerging trends in referrals and areas for potential intervention to meet this increased demand.