National Cancer Institute - NCI Division of Cancer Treatment and ...
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T O O L S , P R O D U C T S , A N D R E S O U R C E S Lung Imaging Database Consortium http://imaging.cancer.gov/ reportsandpublications/ reportsandpresentations/firstdataset The Lung Imaging Database Consortium (LIDC), funded by CIP, comprises five institutions that are developing consensus guidelines and metrics for the use of spiral CT lung images. Preliminary clinical studies show that spiral CT scanning of the lungs could play a role in improving early detection of lung cancer in high-risk individuals. However, more clinical data are needed before public health recommendations can be made for population-based spiral CT screening. Image-processing algorithms have the potential to help detect lesions in spiral CT scans and to assess changes in lesions on serial CT studies. The use of such computer-assisted algorithms could significantly enhance the sensitivity and specificity of spiral CT lung screening and lower costs by reducing physician time needed for interpretation. LIDC is in the process of constructing a database of spiral CT lung images as a test-bed and showcase. This resource will stimulate further database development and thus accelerate applications of imaging to lung cancer screening, diagnosis, and image-guided intervention and treatment. The database has wide utility as a research, teaching, and training resource. Already available on the LIDC Website via FTP download are two lung cancer cases with CT scans performed at multiple time points during treatment. Nodule markings are contained in .xml files accompanying the scans. More data sets will be presented in the future. Also available is the first data set, containing images of 23 nodules and a boundary definition of the nodules from a screening and diagnostic caseload. This preliminary database may prove to be useful for the evaluation of image segmentation methods. LIDC has plans to provide the final database of 400 cases in summer 2006. NCI Visuals Online, Bill Branson, photographer. C A N C E R I M A G I N G P R O G R A M ■ 63
Virtual Colonoscopy Training Collection http://nova.nlm.nih.gov/wramc CIP offers a virtual colonoscopy image database from the National CT Colonography Trial that can be downloaded for training, research, or development of computer-aided diagnostic applications for enhancing or interpreting images. This project is a collaboration with the Walter Reed Army Medical Center Virtual Colonoscopy Center and the NIH National Library of Medicine. The images comprising the database are DICOM-compliant, meaning that they adhere to standards for Digital Imaging and Communications in Medicine developed jointly by ACR and NEMA. 64 ■ P R O G R A M A C C O M P L I S H M E N T S 2 0 0 6 NCI Visuals Online, Bill Branson, photographer. This database currently provides 52 complete cases (26 with polyps) consisting of three-dimensional CT data, several twodimensional images, pathology reports, virtual and optical colonoscopy reports, and optical colonoscopy video. National Forum on Biomedical Imaging in Oncology http://imaging.cancer.gov/NewsAnd Meetings/meetings The National Forum on Biomedical Imaging in Oncology (NFBIO), cosponsored by NCI, NEMA, FDA, and CMS, facilitates partnerships between researchers, the imaging industry, and government agencies. The goal is to address new biomedical opportunities and challenges in oncology and to focus on the regulatory, coverage, and reimbursement issues for established technologies to improve patient diagnosis and care. The two-day meeting concentrates on a different topic each time it is held. Planning is under way for a 2007 meeting. Interagency Council on Biomedical Imaging in Oncology http://imaging.cancer.gov/ programsandresources/ specializedinitiatives/ICBIO In informal, confidential meetings, the Interagency Council on Biomedical Imaging in Oncology (ICBIO) brings representatives of NCI, FDA, and CMS together with technology developers. Developers receive advice from a multiagency perspective on the spectrum of scientific, regulatory, and reimbursement issues related to commercializing new imaging devices or technologies.
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T O O L S , P R O D U C T S , A N D R E S O U R C E S<br />
Lung Imaging Database<br />
Consortium<br />
http://imaging.cancer.gov/<br />
reports<strong>and</strong>publications/<br />
reports<strong>and</strong>presentations/firstdataset<br />
The Lung Imaging Database Consortium<br />
(LIDC), funded by CIP, comprises five institutions<br />
that are developing consensus<br />
guidelines <strong>and</strong> metrics for the use <strong>of</strong><br />
spiral CT lung images.<br />
Preliminary clinical studies show that<br />
spiral CT scanning <strong>of</strong> the lungs could play<br />
a role in improving early detection <strong>of</strong> lung<br />
cancer in high-risk individuals. However,<br />
more clinical data are needed before<br />
public health recommendations can be<br />
made for population-based spiral CT<br />
screening. Image-processing algorithms<br />
have the potential to help detect lesions<br />
in spiral CT scans <strong>and</strong> to assess changes<br />
in lesions on serial CT studies. The use <strong>of</strong><br />
such computer-assisted algorithms could<br />
significantly enhance the sensitivity <strong>and</strong><br />
specificity <strong>of</strong> spiral CT lung screening <strong>and</strong><br />
lower costs by reducing physician time<br />
needed for interpretation.<br />
LIDC is in the process <strong>of</strong> constructing<br />
a database <strong>of</strong> spiral CT lung images<br />
as a test-bed <strong>and</strong> showcase. This resource<br />
will stimulate further database development<br />
<strong>and</strong> thus accelerate applications<br />
<strong>of</strong> imaging to lung cancer screening,<br />
diagnosis, <strong>and</strong> image-guided intervention<br />
<strong>and</strong> treatment.<br />
The database has wide utility as a research,<br />
teaching, <strong>and</strong> training resource. Already<br />
available on the LIDC Website via FTP<br />
download are two lung cancer cases<br />
with CT scans performed at multiple<br />
time points during treatment. Nodule<br />
markings are contained in .xml files<br />
accompanying the scans. More data sets<br />
will be presented in the future. Also available<br />
is the first data set, containing images<br />
<strong>of</strong> 23 nodules <strong>and</strong> a boundary definition<br />
<strong>of</strong> the nodules from a screening <strong>and</strong> diagnostic<br />
caseload. This preliminary database<br />
may prove to be useful for the evaluation<br />
<strong>of</strong> image segmentation methods. LIDC<br />
has plans to provide the final database<br />
<strong>of</strong> 400 cases in summer 2006.<br />
<strong>NCI</strong> Visuals Online, Bill Branson, photographer.<br />
C A N C E R I M A G I N G P R O G R A M ■ 63
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