The Signal Amplification by Reversible Exchange (SABRE) has been awarded 3.6 million euros ($4.7 million U.S.) from the Wellcome Trust to develop an MRI technique to view molecular activities behind diseases, such as Alzheimer's Disease.
The new grant brings the total support for SABRE from the Wellcome Trust, the Wolfson Foundation, Bruker Biospin, the University of York, and the Engineering and Physical Sciences Research Council (EPSRC) to more than 12.5 million euros ($16.3 million U.S.) in the last three years.
A new Centre for Hyperpolarisation in Magnetic Resonance (CHyM) is being built at York to house the project. The building, which is nearing completion at York Science Park, includes a chemical laboratory, four high-field nuclear magnetic resonance systems, and space for 30 research scientists.
![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)
