A province in Italy is launching a new research project to screen residents for colon cancer using virtual colonoscopy and computer-aided detection (CAD) software as a primary reader.
The Proteus project will include 26,000 patients in Italy's Piedmont region as part of the province's cancer prevention efforts. Under the project, residents will undergo virtual colonoscopy scans at local clinics, with image data sent to centralized locations for CAD interpretation using the CAD-Colon software from Italian software developer im3D of Turin.
Results of the study will be compared to the existing method for colon cancer screening in Piedmont, which relies on fecal occult blood tests (FOBT) and sigmoidoscopy. The project is valued at 4.7 million euros ($7.5 million U.S.) over the next two years and is being sponsored by the Piedmont provincial government, im3D, and the University of Turin.
Related Reading
im3D launches DICOM viewer, November 21, 2007
Road to RSNA, CAD, im3D, November 1, 2007
iMed changes name to im3D, November 15, 2006
Road to RSNA, Advanced Visualization, iMed, November 17, 2005
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![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)
