The European Association of Nuclear Medicine (EAM) is seeking a new member for its physics committee. Also, the association has announced that it will be participate in an upcoming meeting on radiopharmaceuticals.
The association said the new member of the physics committee should have one or more of the following areas of experience: quantitative image analysis for PET, SPECT, and/or multimodality imaging with a particular interest or experience in cardiology. The application deadline is 15 February. More information can be found on the EANM's website.
The association also noted that it will be represented by Wolfgang Wadsak, its secretary and treasurer, at the upcoming IAEA International Symposium on Trends in Radiopharmaceuticals. The symposium, which will be held from 17-23 April at the IAEA's headquarters in Vienna, will cover topics such as development, production, and uses of diagnostic, therapeutic, and theranostic radioisotopes and radiopharmaceuticals, as well as education, certification, and training methodologies, according to the EANM.
![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)
