title: National Cancer Institute initiative: Lung image database resource for imaging research.
abstract: Preliminary clinical studies suggest that spiral computed tomography (CT) of the lungs can improve early detection of lung cancer in high-risk individuals. More clinical studies are needed, however, before public health recommendations can be proposed for population-based screening. Spiral CT generates large-volume data sets and thus poses problems in terms of implementation of efficient and cost-effective screening methods. Image processing algorithms such as computer assisted diagnostic (CAD) methods have the potential to assist in lesion (eg, nodule) detection on spiral CT studies. CAD methods may also be used to characterize nodules by either assessing the stability or change in size of lesions based on evaluation of serial CT studies, or quantitatively measuring the temporal parameters related to contrast dynamics when using contrast material-enhanced CT studies. CAD methods therefore have the potential to enhance the sensitivity and specificity of spiral CT lung screening studies. Lung cancer screening studies now under investigation create an opportunity to develop an image database that will allow comparison and optimization of CAD algorithms. This database could serve as an important national resource for the academic and industrial research community that is currently involved in the development of CAD methods. The National Cancer Institute request for applications (RFA) (CA-01-001) has already been announced (April 2000) to establish and support a consortium of academic centers to develop this database, the consortium to be referred to as the Lung Image Database Consortium (LIDC). This RFA is now closed. Five academic sites have been selected to be members of the LIDC, the first meeting of this consortium is planned for spring of 2001, and a public meeting is to be held in 2002. This report is abstracted from the previously published RFA to serve as an example of how an initiative is developed by the National Cancer Institute to support a research resource. For specific details of the RFA, please access the following Internet site: http://www. nci.nih.gov/bip/NCI-DIPinisumm.htm#a11.
authors.affiliation: Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD 20852, USA.
authors.forename: L P
authors.initials: LP
authors.lastname: Clarke
authors.forename: B Y
authors.initials: BY
authors.lastname: Croft
authors.forename: E
authors.initials: E
authors.lastname: Staab
authors.forename: H
authors.initials: H
authors.lastname: Baker
authors.forename: D C
authors.initials: DC
authors.lastname: Sullivan
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging*; D008175:Lung Neoplasms / Q000175:diagnosis*; D009316:National Institutes of Health (U.S.); D014057:Tomography, X-Ray Computed; D014481:United States