The European Association of Nuclear Medicine (EANM) has updated and revised its statutes to reflect the evolving needs of the association's membership.
The updates offer guidance in fields such as theranostics, AI, and optical imaging, and "bridge thematic gaps, such as ensuring a sustainable nuclear medicine workforce for the future, standardizing guidelines and publications, and expanding ... policy initiatives with the European Union and Health Technology Assessment," EANM President Rudi Dierckx, PhD, said.
"The EANM Statutes had also been waiting an overhaul for some time, making their update and alignment with our current needs very timely," he said, expressing his gratitude to Felix Mottaghy (EANM committee coordinator 2023–2024), as well as the chairs of the EANM committees who helped in shaping this transition. "Their efforts aimed to preserve the best of our past while ensuring our readiness to meet the needs of the future."
You can access the statutes here.
![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)
