
The Society and College of Radiographers (SCoR) has strongly urged the U.K. government to budget for more than 4,000 new radiography staff positions, according to a press release issued on 25 September.
SCoR also encourages U.K. officials to provide ongoing financial support for the National Health Service (NHS) as it works to mitigate the effect of COVID-19 and propose new service models in need of funding, such as community-based diagnostic services and expert networks between hospitals.
Overall, SCoR demands an increase in the headcount across all levels of the clinical therapeutic radiography workforce. Current vacancy rates are 7% in England, 10% in Northern Ireland, 3% in Scotland, and 10% in Wales, according to the group.
However, the society isn't alone in requesting an increase in spending during the current review -- the Royal College of Radiologists (RCR) and the Institute of Physics and Engineering in Medicine (IPEM) is also preparing submissions urging the Treasury to spend more on hospital staff, equipment, and technology in order to protect patients. Doing so would combat the fundamental obstacles that slow down care for imaging and cancer patients, the groups believe.

















![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&fit=crop&h=112&q=70&w=112)
