Dear AuntMinnie Insider,
Most virtual colonoscopy studies have been performed in adults, but there may be times when the procedure is appropriate for children: for example, in patients with juvenile polyposis who must be monitored frequently for signs of recurrence.
Today's Insider Exclusive looks at a study performed by Dr. Sudha Anupindi and colleagues at Massachusetts General Hospital in Boston. At last month's Society for Pediatric Radiology meeting, Anupindi discussed her team's use of the technique in patients aged 6 to 17 years.
Compared to same-day conventional colonoscopy, the researchers found the virtual procedure to be safe and highly sensitive for the detection of colorectal polyps. Still, they think more parents would consider VC if the prep were easier. You'll find the rest of our exclusive Insider story here.
And while you're in the community, you'll want to look at another new study by virtual colonoscopy investigators in Boston. Dr. Jacob Sosna and colleagues from Beth Israel Deaconess Medical Center examined the link between histologic size, grade, and CT attenuation of colorectal lesions in contrast-enhanced virtual colonoscopy, reporting their results in the latest issue of Radiology.
Just click the link below, or visit our Virtual Colonoscopy Digital Community for the lowdown on CT values and colorectal masses.
![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)
