The U.K. Society of Radiographers (SoR) has vowed to support members affected by what it described as the "shocking" collapse and liquidation of Rutherford Health, a private diagnostics and therapeutics provider.
Dean Rogers, SoR's director of industrial strategy and member relations, said the organization would do all that it could to support radiographers affected by the failure, in a post on SoR's website.
"This is shocking news for those who work at Rutherford and patients who will be worried about their care pathways. Our priority now is to support members caught up in this. We are asking for urgent talks with the National Health Service (NHS) about how they can step in to offer work and continue to support patients," Dean said.
An announcement was made June 6 that Rutherford Health was in financial difficulties and had entered administration, with the loss of hundreds of jobs. The company operates Rutherford Cancer Centres, a network of oncology facilities located in South Wales, Northumberland, Liverpool, and the Thames Valley.
Recently, the group opened the first community diagnostics center of its kind in Taunton, Somerset, U.K., under contract with the NHS.
![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)
