Prof. Lluís Donoso-Bach, PhD, former president of the European Society of Radiology (ESR), has received an honorary membership from Brazil's Paulista Society of Radiology and Diagnostic Imaging.
Prof. Lluís Donoso-Bach, PhD.Donoso-Bach received the honor at the 49th meeting of the Jornada Paulista de Radiologia last month in São Paulo. The Paulista Society of Radiology and Diagnostic Imaging was founded in 1968 in the city of Jaú, Brazil, and has more than 7,000 associates.
Since 2006, Donoso-Bach has served as chairman of the diagnostic imaging department at the Hospital Clínic of Barcelona in Spain, where he is also a professor of radiology. Early in his career, his research involved abdominal imaging, with a concentration on liver disease. His attention later shifted to digital imaging and the development and implementation of IT in diagnostic radiology.
![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)
