DUBAI - On Monday at Arab Health, GE Healthcare took the green silk wraps off its PET/MRI scanner, a work-in-progress being displayed for the time in the Middle East.
The scanner was introduced by Richard Hausmann, president and CEO for MRI at GE Healthcare, who noted that the machine represents a major breakthrough in oncology. GE also discussed its investigational work in PET/MRI at the RSNA 2013 meeting.
Richard Hausmann, president and CEO for MRI, introduced the new work-in-progress scanner at Arab Health 2014.The vendor is promoting the scanner as an integrated PET/MRI system. Development machines are already based in Zurich; the University of California, San Francisco; and Stanford University. The hope is to have a first installation in the Middle East within the next two years, according to Tom Gentile, president and CEO of GE Healthcare.
The new system successfully combines mature, robust technologies with new breakthroughs, and represents an excellent investment for researchers and multispecialty hospitals, he added.
![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)
