Dr. Elias Zerhouni, the well-known U.S. radiologist and former director of the U.S. National Institutes of Health, will give a lecture on "Great Trends in Medical Imaging" at this year's Journées Francophones de Radiologie (JFR 2018), to be held in Paris from 12 to 15 October.
Dr. Elias Zerhouni.Dr. Philippe Charlier, PhD, the French forensic pathologist and physical anthropologist, will give another keynote lecture. He will speak about "Imaging in the Service of History," the French Society of Radiology (SFR) has announced.
The advance program for JFR 2018 is available now. The meeting will focus on "right imaging for a targeted and personalized treatment." Also, JFR President Dr. Anne Cotten has released her president's letter.
"These days represent a privileged moment of exchanges around the latest technological and scientific advances in medical imaging," she wrote. "It is also during these conference days that clinical research, fundamental research, and industrial research mix, inseparable and complementary. This close collaboration is the essential keystone to continue to evolve toward ever-more efficient imaging and therapeutic treatment of the patient."
![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)
