VIENNA – When Titti Owman entered the field in the early 1980s, MRI safety was rarely discussed. In a video interview at ECR 2026, the research coordinator at Lund University Hospital and chair of the International Society for MR Radiographers and Technologists (ISMRT) Safety Committee reflects on how dramatically the conversation around MRI safety has evolved.
Over time, growing awareness and several high-profile incidents pushed MRI safety to the forefront of research, education, and professional training.
Today, Owman says safety awareness is far stronger, but national guidance remains an important foundation for consistent practice. Clear frameworks, she adds, help radiology teams maintain high standards and strengthen MRI safety education across Europe.
Video produced by: Christof G. Pelz | GRAFIFANT Creation | www.grafifant.at | 2026. Homepage portrait photo by Christof G. Pelz.
![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)
