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issn:1618-727
1.  Collecting 48,000 CT Exams for the Lung Screening Study of the National Lung Screening Trial 
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.
doi:10.1007/s10278-008-9145-9
PMCID: PMC3043737  PMID: 18777192
Cancer detection; chest CT; clinical trial; computed tomography; de-identification; lung diseases; digital image management; image database; image libraries; national lung screening trial; lung screening study; CT image library
2.  Image Quality Assurance in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Network of the National Lung Screening Trial 
Journal of Digital Imaging  2005;18(3):242-250.
The National Lung Screening Trial is evaluating the effectiveness of low-dose spiral CT and conventional chest X-ray as screening tests for persons who are at high risk for developing lung cancer. This multicenter trial requires quality assurance (QA) for the image quality and technical parameters of the scans. The electronic system described here helps manage the QA process. The system includes a workstation at each screening center that de-identifies the data, a DICOM storage service at the QA Coordinating Center, and Web-based systems for presenting images and QA evaluation forms to the QA radiologists. Quality assurance data are collated and analyzed by an independent statistical organization. We describe the design and implementation of this electronic QA system, emphasizing issues relating to data security and privacy, the various obstacles encountered in the installation of a common system at different participating screening centers, and the functional success of the system deployed.
doi:10.1007/s10278-005-5153-1
PMCID: PMC3046711  PMID: 15924251
Clinical trial; quality assurance; VPN; NLST
3.  Tools for Managing Image Flow in the Modality to Clinical-Image-Review Chain 
Journal of Digital Imaging  2003;16(3):310-317.
Web-based clinical-image viewing is commonplace in large medical centers. As demands for product and performance escalate, physicians, sold on the concept of “any image, anytime, anywhere,” fret when image studies cannot be viewed in a time frame to which they are accustomed. Image delivery pathways in large medical centers are oftentimes complicated by multiple networks, multiple picture archiving and communication systems (PACS), and multiple groups responsible for image acquisition and delivery to multiple destinations. When studies are delayed, it may be difficult to rapidly pinpoint bottlenecks. Described here are the tools used to monitor likely failure points in our modality to clinical-image-viewing chain and tools for reporting volume and throughput trends. Though perhaps unique to our environment, we believe that tools of this type are essential for understanding and monitoring image-study flow, re-configuring resources to achieve better throughput, and planning for anticipated growth. Without such tools, quality clinical-image delivery may not be what it should.
doi:10.1007/s10278-003-1724-1
PMCID: PMC3045259  PMID: 14669066
Clinical-image viewing; imaging throughput; Clinical Desktop; Imageweb

Results 1-3 (3)