An audit of imaging services in Luxembourg conducted by a team of four French radiology professors has found that 25% of submitted CT requests in 2023 were 'irrelevant', according to an article posted by media outlet RTL Today.
The audit found that CT scans were medically relevant in only 75% of cases, while MRI examination requests demonstrated a slightly higher relevance rate of 80%. The assessment included more than 1,000 CT and MRI exam requests, officials from the Luxembourg Ministry of Health said.
Compared with findings from a 2016 audit, the relevance rate for CT scans rose by 14%, while the relevance rate for MRI exams remained relatively stable, experiencing a modest 2% increase. In addition, in 14% of prescribed MRI exams, alternative diagnostic methods like ultrasound or x-ray may have been more medically appropriate, the 2023 audit found.
You can read the full article here.
![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)
