The U.K. Royal College of Radiologists (RCR) and the College of Radiographers (CoR) have jointly published new standards for the education and training of reporting practitioners in musculoskeletal (MSK) plain radiographs.
The joint publication defines the education and training required for all members of a multiprofessional team reporting MSK plain radiographs. Clinical radiology trainees in U.K. training programs will meet these standards in the RCR curriculum approved by the General Medical Council, while diagnostic radiographers will handle the requirements through CoR-approved masters-level programs, according to the organizations.
"With a chronic shortage of both radiologists and radiographers and significant increasing demand for reporting services, intensified by the COVID-19 pandemic and the NHS COVID recovery plan, effective team working in the delivery of clinical imaging services has never been more important," the RCR said in a statement.
"The newly published standards will support this by ensuring that all members of the multi-professional team reporting MSK plain radiographs within a clinical imaging service will be trained to a standard level of overall competence in this aspect of their practice. Importantly, the document states that it is expected that other MSK plain film reporters operating outside of a clinical imaging service should also follow the same standards for education and training," the statement continued.
The standards can be downloaded free-of-charge via the 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)
