The opening day of the European Congress of Radiology (ECR) used to be a pretty relaxed affair, but that's no longer the case. Thursday is now a full congress day, and the crowds were flocking into the Austria Center from early this morning.
The scientific sessions got underway at 10:30 a.m., and our team of six editors was there bright and early to bring you news direct from the conference in Vienna. You can see the fruits of our labor in the RADCast @ ECR.
The European Society of Radiology (ESR) chose the opening day of the meeting to launch its EuroSafe Imaging campaign. In a video interview, ESR President Dr. Guy Frija explains the rationale behind the launch. And for a separate article by radiation expert Madan Rehani, PhD, that provides further insight and information about the initiative, click here.
Mobile devices and tablets also were making headlines. Italian researchers believe an iPad can be an effective tool for reading CT angiography studies in patients suspected of having acute gastrointestinal bleeding. Get the story here. Presenters from Spain and Switzerland also shared their experiences of these devices, and you can read more here.
Our live coverage from ECR 2014 will continue through Monday, so please make sure you check back to our RADCast, at radcast.auntminnieeurope.com, as often as possible.
![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)
