Two of our top stories from the past month dealt with research to make CT colonography (CTC), an already attractive option compared to standard colonoscopy, even better. One dealt with an algorithm to aid in the detection of polyps, while the other investigated a technique to reduce tube voltage that cut radiation doses to a level lower than a typical abdominal radiograph.
The first study, published online July 4 in Radiology, involved an algorithm for automatic endoluminal coregistration at initial CT colonography to help predict polyp location at subsequent CT colonography. Authors Emma Helbren, MBChB, FRCR, of the Centre for Medical Imaging at University College London, and colleagues wanted to improve on standard polyp surveillance, which typically involves a radiologists manually matching polyps between an initial CTC and a subsequent study.
The algorithm was designed to coregister the coordinates of endoluminal colonic surfaces of images from prone and supine CT colonographic acquisitions to match polyps in sequential studies in patients undergoing polyp surveillance. A total of 26 patients with 35 polyps were selected for the study.
Using two different testing methods, Helbren and colleagues reported the mean standard deviation of registration error for the algorithm was between 17.4 mm and 26.9 mm. They suggested that by bringing an observer’s attention immediately to within a couple centimeters of where a polyp would be, identification of known polyps for patient undergoing CTC surveillance can be made more efficient.
The other headline CTC study focused on reducing tube voltage to in turn cut effective dose. Cheong-Il Shin, MD, of Seoul National University Hospital, and colleagues reduced peak tube voltage for CTC to 80 kVp, and compared it with 100 and 120 kVp peak voltages.
Results published online July 11 in Radiology demonstrated median effective radiation dose of CT colonography at 80 kVp and 10 mAs was only 0.167 mSv, which is lower than doses from plain abdominal radiography. However, this low dose also increased image noise and per-polyp sensitivity. Shin and colleagues explained that this can be ameliorated with the use of full knowledge-based iterative reconstruction (IR), the next generation of IR algorithms.
“Unlike previous IR algorithms, it does not involve blending with [filtered back projection] images, and it is mathematically more complex but also more accurate,” wrote the authors. “The knowledge-based approach accurately determines data, image statistics, and system models, which depict the geometry and physical characteristics of the CT scanner.”
CTC use is gaining steam, and as advanced visualization capabilities continue to expand, the procedure will become an even more powerful tool for patient care.
Editor – Health Imaging