The European Association of Nuclear Medicine (EANM) has announced that Victor Hvingelby is the recipient of this year's Sanjiv Sam Gambhir Young Investigator Award.
Hvingelby is a doctoral student in the Department of Clinical Medicine -- Nuclear Medicine and PET, Aarhus, Denmark. He is working on molecular imaging aspects of Parkinson's disease.
Hvingelby will now follow in the footsteps of David Kersting, who was the winner of the 2022 award, by spending up to three months at Stanford University as part of a scheme supported by Telix Pharmaceuticals.
Also during the EANM annual congress, held in Vienna from 9 to 13 September, the three Young Authors Award winners were revealed: Magdalena Mileva, Bastiaan Prive, and Chrysoula Vraka.
![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)
