Digital tools like SIVQ can help pathologists to quickly, accurately and efficiently identify features on a slide with just a few clicks; to quickly calculate the area of an irregularly shaped feature; or to eliminate the slow and painstaking tallying of tiny elements.
Still, the authors stress, the program isn't intended to replace the skill and art of human pathologists, but to provide an additional resource.
"Not only do our findings show that SIVQ has the potential to be a useful tool in surgical pathologists' toolkits when optimized to aid detection of such a highly variable disease, but the case is an excellent example for how the same approach might be applied to a variety of clinical areas," says Ulysses Balis, M.D., director of the division of pathology informatics at U-M and the paper's senior author.
Balis led the software's design at U-M along with Hipp and former informatics fellow Jerome Cheng, M.D.
Unlike other pattern recognition software, SIVQ bases its matches on a set of concentric rings rather than the usual square block. This allows features to be identified no matter how they're rotated or whether they're flipped, as in a mirror.
An example of the program's flexibility was recently demonstrated by Bruce P. Levy, M.D., a research fellow in pathology at Harvard Medical School. Testing the program's utility in a forensic pathology setting, SIVQ was used to calculate the area of bullet wounds and to identify and quantify stippling, which are small scrapes surrounding some gunshot wounds that help to determine the distance from which a gun was fired.
"Being able to use software like SIVQ to analyze forensic images helps to bring the practice of forensic pathology closer to the high-tech fictional world of CSI," Levy says.
Since the computer-aided analysis of micropapillary urothelial carcinoma might contribute to patie
|Contact: Ian Demsky|
University of Michigan Health System