Collecting 48,000 CT exams for the lung screening study of the national lung screening trial

  • Kenneth W. Clark
  • , David S. Gierada
  • , Guillermo Marquez
  • , Stephen M. Moore
  • , David R. Maffitt
  • , Joan D. Moulton
  • , Mary A. Wolfsberger
  • , Paul Koppel
  • , Stanley R. Phillips
  • , Fred W. Prior

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

From 2002-2004, the Lung Screening Study (LSS) of the National Lung Screening Trial (NLST) enrolled 34,614 participants, aged 55-74 years, at increased risk for lung cancer due to heavy cigarette smoking. Participants, randomized to standard chest X-ray (CXR) or computed tomography (CT) arms at ten screening centers, received up to three imaging screens for lung cancer at annual intervals. Participant medical histories and radiologist-interpreted screening results were transmitted to the LSS coordinating center, while all images were retained at local screening centers. From 2005-2007, all CT exams were uniformly de-identified and delivered to a central repository, the CT Image Library (CTIL), on external hard drives (94%) or CD/DVD (5.9%), or over a secure Internet connection (0.1%). Of 48,723 CT screens performed, only 176 (0.3%) were unavailable (lost, corrupted, compressed) while 48,547 (99.7%) were delivered to the CTIL. Described here is the experience organizing, implementing, and adapting the clinical-trial workflow surrounding the image retrieval, de-identification, delivery, and archiving of available LSS-NLST CT exams for the CTIL, together with the quality assurance procedures associated with those collection tasks. This collection of CT exams, obtained in a specific, well-defined participant population under a common protocol at evenly spaced intervals, and its attending demographic and clinical information, are now available to lung-disease investigators and developers of computer-aided-diagnosis algorithms. The approach to large scale, multi-center trial CT image collection detailed here may serve as a useful model, while the experience reported should be valuable in the planning and execution of future equivalent endeavors.

Original languageEnglish
Pages (from-to)667-680
Number of pages14
JournalJournal of Digital Imaging
Volume22
Issue number6
DOIs
StatePublished - Dec 2009

Keywords

  • CT image library
  • Cancer detection
  • Chest CT
  • Clinical trial
  • Computed tomography
  • De-identification
  • Digital image management
  • Image database
  • Image libraries
  • Lung diseases
  • Lung screening study
  • National lung screening trial

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