Senior clinical radiologists cannot fulfill their job by working 100% remotely, according to the U.K. Royal College of Radiologists (RCR).
The RCR has released a statement on 17 November to indicate it will not support any job plans for consultant radiologists who are based entirely out of the hospital, unless there are genuinely exceptional circumstances.
"There should be sufficient consultant clinical radiologists physically present in the department to maintain the 'critical mass' required to support and lead imaging teams and the imaging service," the statement said.
The RCR said it is "completely aware" of the difficulty many departments have in recruiting sufficient staff to provide a comprehensive, safe clinical service and of the innovative and creative solutions needed to maintain service provision. However, it added, there is a belief that the complex role of a consultant clinical radiologist should not be delivered from an entirely remote working pattern.
The consultant role is multifaceted and involves clinical leadership, training, and interspecialty discussions on complex cases, as well as on-call duties, the RCR added.
![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)
