VIDI, the leading private radiology group in France, on 2 September announced the launch of its teleradiology service, TéléVidi, which aims to offer local teleradiology solutions to medical centers across the country.
The network, which comprises 850 radiologists and 270 imaging centers across the country, has partnered with CTM Group, the latter specializing in digital organizational solutions for the medical community.
Local VIDI radiologists will offer face-to-face locum services, supported by the network's other radiologists where necessary, the imaging group stated, adding that its members represented the entire range of imaging and organ subspecialties.
Different types of institutions -- such as university hospitals, regional cancer centers, and private clinics -- will be able to outsource their image management and interpretation, both temporarily and permanently, according to Dr. Nicolas Puech, medical director of TéléVidi. He said that this dedicated locum intervention would allow the continuation of replacement services and coverage of busy periods, while ensuring emergency care and the management of urgent requests.
![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)