Although colorectal cancer is the second leading cause of cancer deaths for men and women in the United States, it would be largely preventable if its precursor lesions were detected and removed early. Most colorectal cancers develop from sessile or pedunculated polypoid neoplasms. Early removal of such neoplasms has been observed to reduce the occurrence of colorectal carcinoma. Computed tomographic colonography (CTC), or virtual colonoscopy, has become an alternative technique for providing mass screening for colorectal carcinoma due to recent large-scale, multi-center clinical trials, including the National CT Colonography Trial. However, for CTC to be truly deployed for the 70 million people eligible for screening in the U.S., it should be easy for the patients to tolerate, and should have high accuracy in detecting polyps. One of the difficulties with total colon examination, including CTC, is low patient adherence to the rigorous cathartic bowel cleansing that is used for bowel preparation prior to the examination. Laxative-free CTC (lfCTC) is an emerging technique for eliminating rigorous cathartic cleansing from the bowel preparation used in current CTC. Although promising, anticipated difficulties with lfCTC include a large amount of solid residual fecal material present in the colon, and variations in diagnostic performance among readers who interpret lfCTC images because of the distracting residual solid stool in detecting small polyps as well as flat lesions. For addressing these difficulties, the short-term goal in this project is to develop an lfCTC interpretation system that assists radiologists in detecting colorectal lesions (polyps and flat lesions) quickly and accurately. This proposal aims at developing two components in the lfCTC interpretation (1) A high-performance laxative-free computer-aided detection (lfCAD) scheme, which automatically and accurately detects polyps and flat lesions in lfCTC images;and (2) A laxative-free electronic cleansing (lfEC) scheme, which virtually cleanses the solid residual stool without prior physical bowel cleansing. Both schemes will be designed and optimized for lfCTC images. system: We hypothesize that the lfCTC interpretation (Aim 1) Establish lfCTC databases to develop and evaluate lfCAD and lfEC schemes;
(Aim 2) Develop an lfCAD scheme for detection of colorectal lesions in lfCTC;
(Aim 3) Develop an advanced lfEC scheme for artifact-free removal of the solid residual stool in lfCTC;
(Aim 4) Evaluate the clinical benefit of an integrated lfCTC system will create diagnostic quality CTC images, yield clinically acceptable high detection performance of lesions, and improve radiologists'performance in the detection of colorectal lesions in lfCTC images. To explore these hypotheses, we propose the following specific aims: interpretation Successful development of the proposed lfCTC system. interpretation system will substantially advance the clinical implementation of image-based colon cancer screening in a large population, lead to an increased screening rate, promote the early diagnosis of colon cancer, and ultimately reduce the mortality due to colon cancer.

Public Health Relevance

The significance of this proposal is that successful development of the lfCTC interpretation system will substantially improve radiologists? performance and reduce their inter-observer variability in the detection of colonic lesions in lfCTC. Such a CAD system will make lfCTC a viable option for screening of large population, lead to an increased screening rate, promote the early diagnosis of colon cancer, and ultimately reduce the mortality due to colon cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA095279-10
Application #
8511350
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Zhang, Yantian
Project Start
2002-04-01
Project End
2014-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
10
Fiscal Year
2013
Total Cost
$350,697
Indirect Cost
$152,563
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Cai, Wenli; Zhang, Da; Lee, June-Goo et al. (2013) Dual-energy index value of luminal air in fecal-tagging computed tomography colonography: findings and impact on electronic cleansing. J Comput Assist Tomogr 37:183-94
Nappi, Janne; Yoshida, Hiroyuki (2007) Fully automated three-dimensional detection of polyps in fecal-tagging CT colonography. Acad Radiol 14:287-300
Nappi, Janne; Frimmel, Hans; Yoshida, Hiroyuki (2005) Virtual endoscopic visualization of the colon by shape-scale signatures. IEEE Trans Inf Technol Biomed 9:120-31
Nappi, Janne; Okamura, Akihiko; Frimmel, Hans et al. (2005) Region-based supine-prone correspondence for the reduction of false-positive CAD polyp candidates in CT colonography. Acad Radiol 12:695-707
Frimmel, Hans; Nappi, J; Yoshida, H (2005) Centerline-based colon segmentation for CT colonography. Med Phys 32:2665-72
Frimmel, Hans; Nappi, Janne; Yoshida, Hiroyuki (2004) Fast and robust computation of colon centerline in CT colonography. Med Phys 31:3046-56
Nappi, Janne J; Frimmel, Hans; Dachman, Abraham H et al. (2004) Computerized detection of colorectal masses in CT colonography based on fuzzy merging and wall-thickening analysis. Med Phys 31:860-72