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Cornell University

Development of a CAD Assessment of a PN Database
David Yankelevitz, M.D.
Cornell University

Grant Number: U01CA091100

Lung cancer is the leading cause of cancer death worldwide, both in men and women, with an estimate of over 164,000 new cases and over 156,000 deaths in 2000 in the United States alone. A principal reason for this high mortality is that lung cancer typically is first detected at an advanced stage where the prospects for cure are quite low. However, in those cases where it is found in an early stage, the prospects for cure are quite high. Recognition of these facts is a primary driver behind the development of improved screening and diagnostic tools. We propose to form a collaborative group of institutions to develop a large, high-quality internet-accessible spiral computed tomography (CT) image database of pulmonary nodules. This will serve as an important resource for researchers interested in developing improved methods for early detection and screening for lung cancer.

Specifically this proposal plans to 1) develop the criteria for inclusion of nodules within the database, 2) develop ground truth or pathologic diagnosis of each nodule, 3) populate the database with the appropriate nodule candidates as described above, 4) develop common data elements (CDEs) to classify each case, 5) develop criteria for measuring performance standards of various CADs, and 6) develop an overall management plan for the consortium. The database developed in this consortium will be an important resource for research and teaching purposes. It will represent a standard that can be used for testing new CAD systems. With the rapid advances in computer science and engineering, a high-quality database that is continually evolving will be an invaluable resource.

The design of this research proposal is somewhat novel in that we aim not only to collaborate with others on the design and content of the image database, but intend also to attach demographic and pathologic data to each case so that a broad community of research can be served. Our overall management plan seeks to aggressively identify collaborative partners from a variety of sources including similar or related industry, for example the Visible Human Project. Working groups will include radiology, CAD development, and informatics and our outreach efforts will include patient advocacy and early users of the database.

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