The radiology department at Hamad Medical Corporation in Doha, Qatar, received an Excellence in Radiology Award on 28 January at Arab Health 2014 in Dubai, United Arab Emirates.
The Arab Health Innovation and Achievement Awards have been given for seven years, honoring exceptional healthcare professionals across the Middle East.
This year, the judging panel included:
- Dr. Fadi El-Jardali of the American University of Beirut
- Dr. Joel J. Nobel, founder and president emeritus of the ECRI
- Dr. Lena Low, acting chief executive of the Australian Council on Healthcare Standards
- Ashraf Ismail, managing director, Middle East International Office, of the Joint Commission International
- Jan Schmitz-Huebsch, director for Business Development and Projects, Munich Health Daman Holding
The Excellence in Radiology award was one of nine given at the meeting.
![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)
