Colorectal cancer is the third most common form of cancer and the second leading cause of cancer-related death in the US. Yet, if polyps are detected and removed early, colorectal cancer is largely preventable. Although optical colonoscopy (OC), the current gold standard, detects more than 90% of colorectal neoplasms;it is invasive and can be uncomfortable, inconvenient, and perceived as undesirable by patients. Furthermore, even experienced endoscopists may have difficulty reaching the cecum, resulting in incomplete visualizations of the colon. As a consequence, virtual colonoscopy (VC) has emerged as an alternative to OC. During VC, a virtual camera is used to view the internal walls of a virtual colon, reconstructed from CT scans of the abdominal cavity. However, current VC systems have had limited clinical appeal, as they are limited to specific types of polyps, may generate a large number of false positives, or have poor detection rates for significant polyps in the size range of 5-9 mm. The new technology we propose to commercialize through this SBIR work is a game changing, patented, visualization technique for VC, called the "virtual fly-over" technique. The technique is sensitive, effective, and efficient for detecting colon polyps. The overall objective of this proposal is to complete the development and validation of a novel visualization technique for virtual colonoscopy, which was patented by the University of Louisville. The hypothesis is that the new visualization technique will enable better viewing of the complex colonic topology, and hence a better capability to detect polyps, especially those that may be hidden behind haustral folds. The current prototype has been utilized to evaluate twenty clinical datasets, with excellent results. However, artifact removal and user friendly features must be incorporated prior to Phase II, in which the technology will be utilized in a larg scale clinical validation trial leading to a commercial product. Also, we propose to (1) generate more convincing preliminary data in a pilot study of 160 datasets, and (2) introduce several phantom polyps, in the size range of 5-9 mm, into the clinical datasets, in order to provide statistical significance of the technology's effectiveness. The phantom polyps will be placed in traditionally difficult-to-analyze positions, which pose significant detection problems for both OC and current VC methods. According to the literature, current OC methods result in a 61-91% (average 80%) viewing of the Colon. The University of Louisville's work in the "fly-through VC method", which mimics classic OC, results in 93.4 percent viewing, and the new "fly-over" method results in 97.5% percent viewing. Even more important is the improved point of view ("eye-in-the-sky"), the lack of optical distortion, and enhanced CAD functionality that will increase polyp recognition dramatically, especially when detecting small colon polyps, polyps hidden behind haustral folds, and polyps in folded colonic segments at anatomical inflection points. We anticipate the overall improvement in the ability to visualize difficult polyps to be upwards of 30% compared to today's methods, and we are excited about commercializing this technology with the University of Louisville.

Public Health Relevance

Colorectal cancer is the third most common form of cancer and the second leading cause of cancer-related death in the US with only approximately 50% of the eligible population take advantage of current screening methods. The importance of this proposed technology is the early detection of colon cancer, in an acceptable manner that the general population will agree to, and without the associated morbidity of sedation that is required for the vast majority of endoscopic colonoscopy. We believe our technology has the potential to serve as a foundation for a huge step forward in automating and facilitating large scale screening of human colons, providing a more effective and much more acceptable method to the general population, than the currently invasive optical colonoscopy, which 50 % of the population still refuses to undergo.

Agency
National Institute of Health (NIH)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
5R43CA179911-02
Application #
8735905
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Narayanan, Deepa
Project Start
Project End
Budget Start
Budget End
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Kentucky Imaging Technologies, LLC
Department
Type
DUNS #
City
Louisville
State
KY
Country
United States
Zip Code
40245