Samuel George Armato PhD, Presenter: Nothing to Disclose

Poonam Batra MD, Abstract Co-Author: Nothing to Disclose

Philip Caligiuri MD, Abstract Co-Author: Nothing to Disclose

Cecilia Matilda Jude MD, Abstract Co-Author: Nothing to Disclose

Leslie Eisenbud Quint MD, Abstract Co-Author: Nothing to Disclose

Baskaran Sundaram MBBS, Abstract Co-Author: Research grant, Bayer AG

Michael F. McNitt-Gray PhD, Abstract Co-Author: Member, Physics Committee, American College of Radiology Imaging Network (ACRIN) Consultant, ACRIN ACR Image Metrix Consultant, Rapiscan Systems UCLA Radiological Sciences has a research agreement with Siemens Medical Solutions Research grants from National Cancer Institute (NCI) and National Institute of Biomedical Imaging and Bioengineering (NIBIB).

Charles R. Meyer PhD, Abstract Co-Author: Nothing to Disclose

Geoffrey McLennan MD, PhD, Abstract Co-Author: Shareholder, VIDA Diagnostics

Anthony P. Reeves PhD, Abstract Co-Author: Research grant, GlaxoSmithKline plc Research grant, AstraZeneca PLC Stockholder, VisionGate, Inc Consultant, VisionGate, Inc Patent agreement, General Electric Company

Laurence P. Clarke PhD, Abstract Co-Author: Nothing to Disclose

Barbara Yoder Croft PhD, Abstract Co-Author: Nothing to Disclose

Denise Ru Aberle MD, Abstract Co-Author: Nothing to Disclose

Ella A. Kazerooni MD, Abstract Co-Author: Consultant, General Electric Company Consultant, Vital Images, Inc Research funded, General Electric Company

Heber M. MacMahon MD, Abstract Co-Author: Consultant, Riverain Medical Research support, MEDIAN Technologies Stockholder, Hologic, Inc

Edwin J.R. Van Beek MD, PhD, Abstract Co-Author: Consultant, Schering-Plough Corporation Medical Advisory Board, EDDA Technology, Inc Medical Advisory Board, Vital Images, Inc Speakers Bureau, Koninklijke Philips Electronics NV Research support, General Electric Company Research support, Siemens AG Founder and owner, Quantitative Imaging of Iowa, Inc

David F. Yankelevitz MD, Abstract Co-Author: Researcher, OSI Pharmaceuticals, Inc Researcher, Carestream Health, Inc Researcher, GlaxoSmithKline plc Researcher, AstraZeneca PLC Medical Advisor, PneumRx, Inc Shareholder, PneumRx, Inc Patent agreement, General Electric Company

et al, Abstract Co-Author: Nothing to Disclose

The Lung Image Database Consortium (LIDC) has developed a database of thoracic computed tomography (CT) scans as a research resource. The scans have been marked by experienced thoracic radiologists to indicate the presence of lung nodules. Potential uses of the database include the training and testing of computer-aided diagnosis (CAD) systems, the development of volumetric nodule analyses, and the teaching of radiology residents. Users of the database should be aware of assumptions that went into the creation of the database, practical design issues, and best-use practices that have evolved through the LIDC experience.

To date, 85 publicly available CT scans have been reviewed through a two-phase process. During the initial "blinded read," each of four thoracic radiologists independently marked lesions they identified as "nodule > 3mm," "nodule 3mm." During the subsequent "unblinded read," the anonymous blinded read results of all radiologists were revealed, and each radiologist independently reviewed these marks to render a final opinion. Radiologists also subjectively evaluated nine characteristics for "nodules > 3mm."

The unblinded read has an intentionally different purpose from the blinded read; the distinction between these two reads and their impact on the overall annotation process will be described. From among the first 30 LIDC cases, 59 lesions were marked as “nodule > 3mm” by at least one radiologist; however, only 27 of these lesions (45.8%) were marked as such by all four radiologists. The reasons for this variability will be explained, and the implications of this finding for CAD development will be explored. Details of the radiologist nodule outlining procedure will be examined to understand the impact on nodule segmentation studies. The subjective rating of nodule characteristics used a fixed five-point scale for each characteristic; this approach is appreciably different from how radiologists function clinically.

Proper interpretation of results obtained using the LIDC database requires an understanding of how the database was created.

The LIDC database will become a research resource for the medical imaging research community. An understanding of how the database was created is required for proper use.

Armato, S, Batra, P, Caligiuri, P, Jude, C, Quint, L, Sundaram, B, McNitt-Gray, M, Meyer, C, McLennan, G, Reeves, A, Clarke, L, Croft, B, Aberle, D, Kazerooni, E, MacMahon, H, Van Beek, E, Yankelevitz, D, et al, , The Lung Image Database Consortium (LIDC): Lessons Learned from the Development of a Consensus-based Public Resource.  Radiological Society of North America 2008 Scientific Assembly and Annual Meeting, February 18 - February 20, 2008 ,Chicago IL. http://archive.rsna.org/2008/6022510.html