VIENNA – Prior to ECR 2024, there was intense speculation that Prof. Dr. Alex Radbruch, JD, might soon be taking up a post at the Charité in Berlin. In a video interview, he comments on this speculation and also discusses the current evidence on brain retention and gadolinium-based MRI contrast agents. Do they pose a serious threat to patient safety today? And by how much can AI reduce gadolinium dose in the years to come?
Radbruch is currently chair of diagnostic and interventional neuroradiology and professor at Rheinische Friedrich Wilhelms University Bonn, Germany. He has also been an active member of the Editorial Advisory Board of AuntMinnieEurope.com since the site's launch at ECR 2011.
Video and homepage photo produced by Christof.G.Pelz | GRAFIFANT Creation | www.grafifant.at | 2024
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
