The development of computer-aided diagnostic(CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography(CT) scans. The LungImageDatabase Consortium (LIDC) and ImageDatabase Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.Methods:
Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (“,” “,” and “non-”). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.Results:
The Database contains 7371 lesions marked “nodule” by at least one radiologist. 2669 of these lesions were marked “” by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings.Conclusions:
The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.
This paper is dedicated to the memory of Geoffrey McLennan, M.D., Ph.D., who served as the Chair of the LIDC/IDRI Steering Committee since the inception of the project. Dr. McLennan provided the constant source of motivation, perspective, and determination that moved this database from an idea to reality. His extraordinary scientific and clinical vision, combined with his unfettered perseverance and uncompromising optimism, will be greatly missed by all his co-authors, colleagues, and friends. The authors would like express their sincere appreciation to the late Robert F. Wagner, Ph.D., whose enlightened perspective on medical image analysis performance studies provided the foundation for the statistical considerations on which the LIDC/IDRI Database was founded. Supported in part by USPHS Grant Nos. U01CA091085, U01CA091090, U01CA091099, U01CA091100, and U01CA091103 and by NCI Contract No. HHSN261200800001E. Funding was obtained through the Foundation for the National Institutes of Health from contributions provided by the medical imaging companies that participated in the IDRI. Disclosure statement: S.G.A. and H.M. receive royalties and licensing fees through the University of Chicago related to computer-aided diagnosis. H.M. is a consultant to Riverain, a company that produces software for lung nodule detection. A.P.R. is a paid consultant of and holds stock in VisionGate, Inc. A.P.R. is a coinventor on a patent and other pending patents owned by Cornell Research Foundation which are non-exclusively licensed to General Electric and are related to technology involving computer-aided diagnostic methods, including measurement of nodules. A.P.R. receives research support in the form of grants and contracts from: NCI, American Legacy Foundation, Flight Attendants' Medical Research Institute, AstraZeneca, Inc., GlaxoSmithKline and Carestream Health Inc. D.Y. is a named inventor on a number of patents and patent applications relating to the evaluation of diseases of the chest including measurement of nodules. Some of these, which are owned by Cornell Research Foundation (CRF) are nonexclusively licensed to General Electric. As an inventor of these patents, D.Y. is entitled to a share of any compensation which CRF may receive from its commercialization of these patents.
I. INTRODUCTION II. MATERIALS AND METHODS II.A. Patient image data II.B. Image annotation process II.C. Analysis of lesions II.D. Quality assurance evaluation II.E. Database access III. RESULTS IV. DISCUSSION V. CONCLUSION
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