Dear AuntMinnie Member,
In a milestone for virtual colonoscopy, the New England Journal of Medicine today published clinical results from a large multicenter trial of VC that show the imaging technique delivering comparable accuracy to optical colonoscopy -- the gold standard for detecting clinically significant colorectal polyps.
The results from the American College of Radiology Imaging Network's (ACRIN) National CT Colonography Trial are hardly breaking news -- we broke the story a year ago in our Virtual Colonoscopy Digital Community. But publication of the complete results in a prestigious academic journal such as NEJM will help solidify VC's evolution from an experimental technique into an accepted screening tool for colorectal cancer. Learn more by clicking here.
In other VC news, a new study in Radiology indicates that a comprehensive training program can produce impressive results for those reading VC exams -- even medical students. Click here to learn about how University of Chicago researchers implemented a rigorous training program for novice readers.
SPECT/CT for bone lesions
In the world of musculoskeletal imaging, a recent study by U.S. researchers indicates that SPECT/CT can help determine the exact location of bone lesions. SPECT/CT found more lesions than either SPECT alone or planar imaging and also was better able to predict a patient's final diagnosis.
Find out more about the study by clicking here, or visit the Musculoskeletal Imaging Digital Community at msk.auntminnie.com.
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)
