The European Institute for Biomedical Imaging Research (EIBIR) has kicked off its AlternativesToGD initiative, which is designed to develop a class of gadolinium-free contrast agents for MRI.
The agents would consist of small endogenous molecules, which will be hyperpolarized to ensure high sensitivities at very low doses and would completely wash out by the human body promptly after injection and imaging. Because agents rapidly decay when in a hyperpolarized state, AlternativesToGd participants will focus on three hyperpolarization techniques and agents that hold their hyperpolarization states long enough to complete contrast-enhanced MRI scans and achieve diagnostic sensitivity, according to EIBIR.
Compounds and technologies developed by the project will be tested in animal models of disease with the most promising results advancing for further clinical development, the institute stated.
The project is scheduled to run for 36 months.
![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)
