Multimodality vendor GE Healthcare of Chalfont St. Giles, U.K., has expanded a partnership with a German firm to include collaboration in the field of molecular imaging and its application to the development of cancer therapeutics.
GE and the Fraunhofer Institut für Toxikologie und Experimentelle Medizin (Fraunhofer ITEM) said they will partner on a research project that will apply toxicogenomic and pharmagenomic techniques to establish the effectiveness and side effects of potential new drugs at a very early stage in their development. GE will invest research funds for three years and provide active scientific support to Fraunhofer ITEM. Of particular focus will be immuno-nanoparticles for the treatment of lung and liver cancers.
GE and Fraunhofer ITEM have been working together since 2005, during which time Fraunhofer ITEM has used GE's eXplore Vista, eXplore Locus, and eXplore Optix devices in its research.
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![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)
