Tributes have been paid to the U.K. musculoskeletal radiologist Dr. Asif Saifuddin, who has died at the age of 64.
Dr. Asif Saifuddin."In the realms of life, Dr Saifuddin carved his path with the precision of a skilled surgeon -- equal parts family man, devoted believer, a gifted radiologist, a prolific scientific writer and let's say, a quiet yet avid admirer of Leeds United Football club (from a distance)," wrote Dr. Sajid Butt, a student, colleague, and friend Saifuddin's.
Asif's ability to spot the relevant abnormality in a radiological image was legendary, his power of inference extraordinary, and his ability to get to the bottom of the most complex of cases, uncanny, Butt wrote.
"His departure has left us to ponder the brevity of his years while acknowledging the monumental impact he made during his relatively brief time on this earth," he wrote.
The full tribute is available on RCR's website.
![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)
