We're pleased to offer the top 10 stories of 2014 on AuntMinnieEurope.com. Hot topics in 2014 included controversy over Brazilian football star Neymar Junior's CT scan, continuing coverage of the breast screening debate, and radiology under the Nazis.
The following are the top 10 stories as measured by member traffic:
- World Cup controversy over Neymar CT scan goes viral, July 8, 2014
- Norwegians seek to add clarity to breast screening dispute, June 17, 2014
- Radiology under the Nazis, January 6, 2014
- Mammo skeptics make new bid to stop U.K. breast screening trial, September 16, 2014
- Conflict over recognition for MRI discovery resurfaces at ECR, March 10, 2014
- Some practical tips on buying a new scanner, January 22, 2014
- Guy Sebag: Europe mourns a top pediatric radiologist, December 10, 2014
- Claustrophobia, MRI, and the human factor, July 2, 2014
- French MRI waiting times are 'worst in a decade', July 16, 2014
- Scanning from Sochi: Winter Olympics medical teams are ready, February 7, 2014
![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)
