The influence of the European Society of Radiology's journal European Radiology continues to expand.
According to ISI Impact Factors, European Radiology achieved an increase in its impact factor to 4.338 in 2013, compared with 3.548 in 2012. The impact factor is calculated on the basis of citations in other scientific publications to help measure the scientific importance of a journal.
ISI Impact Factors is published annually in Thomson Reuters' Journal Citation Reports.
European Radiology's impact factor has been climbing rapidly since it was registered in 1998. After a steady rise over the past three years, it has now reached its highest number yet.
In addition, the journal has moved up further in rank from number 19 to 13 out of 121 radiological journals in the radiology, nuclear medicine, and molecular imaging section, and is again the top general radiological journal in Europe.
![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)
