Dear AuntMinnieEurope Member,
This year will mark the 40th anniversary of diffusion MRI, and our most-read story this week was actually an interview we conducted with Prof. Denis Le Bihan, PhD, who is credited with inventing the technique. Le Bihan is founder of NeuroSpin, which is part of the French Atomic Energy Commission (CEA). Click here to listen to his reflections.
The Journées Francophones de Radiologie (JFR 2024) congress was held from 4 to 7 October in Paris, and our readers took notice of our meeting coverage, which included new French recommendations for imaging endometriosis and a story on the continued expansion of France's largest network of private radiologists, VIDI.
Also of interest this week to AuntMinnieEurope members was an article on how 7-tesla MRI reveals the long-term effects of COVID-19 on the brains of those who recovered from the illness, as well as a story on how imaging can help clinicians identify specific toxins in patients with symptoms of poisoning and clarify how the toxin is affecting them.
Kate Madden Yee
Contributing Editor
AuntMinnieEurope.com
Editor-in-Chief Philip Ward is on assignment.
![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)
