A report released on 11 November by National Health Service (NHS) England stated that in September 2021, more than 192,000 patients had been waiting six weeks or more for a CT, MRI, or ultrasound scan. In February 2020, the number was 11,338.
The report also said radiology departments have succeeded in bringing down long waits from the record highs of summer 2020, caused by the pause in nonurgent hospital work. However, the number of patients waiting more than 13 weeks for the same scans is now 50,348, compared with 1,636 in February 2020, the authors wrote.
The Royal College of Radiologists (RCR) has issued a response, expressing concern and calling for a concerted high-level commitment from the NHS and government officials to address radiology workforce issues, including sustainable investment in more radiologists, radiographers, and imaging support staff, as well as increasing global recruitment.
![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)
