French computer-assisted interventional radiology firm Imactis is bringing its CT-Navigation system to the U.S. for the first time.
University of Wisconsin Health, the academic medical center and health system of the University of Wisconsin, will be the recipient of the system. The navigation system features a dedicated instrumentation kit designed for percutaneous interventional radiology procedures performed under CT, such as tumor ablations, biopsies, musculoskeletal interventions, and other needle-based interventions.
The device allows clinicians to explore a patient's anatomy, plan the optimal needle trajectory to avoid damage to surrounding organs, and provide needle guidance and control for enhanced precision and execution.
CT-Navigation system has received both the CE Mark and 510(k) clearance from the U.S. Food and Drug Administration. It is installed in 50 hospitals in Europe and has performed more than 6,000 interventions, according to Imactis.
![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)
