GE Healthcare of Chalfont St. Giles, U.K., has introduced its new Discovery PET/CT 600 scanner at the annual meeting of the European Association of Nuclear Medicine (EANM) in Munich, Germany.
The system is designed primarily for oncology and combines GE's BrightSpeed CT with its Discovery PET system. It features a scintillator with bismuth germanate crystal technology for enhanced lesion detection, potentially reducing dose requirements and allowing for faster scans and increased patient throughput.
Discovery PET/CT 600 also offers a 70-cm bore that provides a full 70-cm PET and CT field-of-view, and a patient table with a capacity of 500 lb. The greater vertical scan range also is designed to provide more flexibility in radiation treatment planning and patient positioning.
Discovery PET/CT 600 has received clearance from the U.S. Food and Drug Administration (FDA).
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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)
