GE Healthcare will highlight its new Revolution CT scanner and Centricity 360 image-sharing software at this week's Arab Health 2014 meeting in Dubai, United Arab Emirates.
First introduced at RSNA 2013, Revolution is GE's new CT platform that combines radiation dose reduction technologies with broader anatomic coverage. The system features 16 cm of coverage per rotation, compared with 4 cm on older GE CT scanners. Revolution is pending 510(k) clearance from the U.S. Food and Drug Administration (FDA).
Also launched at RSNA 2013, Centricity 360 is GE's new cloud-based software for the exchange of medical images. Designed to improve collaboration between physicians and patients, Centricity 360 enables caregivers to exchange images and join private communities to collaborate on diagnosis and treatment discussions in near real-time, according to the vendor.
Because all Centricity 360 applications and collaboration tools are provided via a cloud services platform, no upfront investment is required from clinical users, patients, or integrated delivery networks.
Another notable GE highlight at Arab Health 2014 will be the company's VolumeRad chest tomosynthesis system for advanced radiography studies. VolumeRad is designed for the detection of lung nodules and to provide physicians with multiple high-resolution slice images of the anatomy of interest, including the chest, abdomen, extremities, and spine.
Maher Abouzeid, president and CEO of GE Healthcare for the Middle East and Pakistan, noted that healthcare expenditures in the Gulf Cooperation Council (GCC) region have grown 7.9% per year over the past 10 years, and total healthcare expenditure in the area is expected to be $79.2 billion in 2015.
![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)
