Journal of digital imaging
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Randomized Controlled Trial
iPad-based patient briefing for radiological examinations-a clinical trial.
To analyze if an iPad-based patient briefing can serve as a digital alternative to conventional documentations prior to radiological examinations. One hundred one patients referred for routine MRI were randomized into two groups, who underwent iPad-based and classic written briefing in opposite order. For each briefing completion time, completeness and correctness were noted. ⋯ Patient briefing on iPads transfers the information for the patients equally well compared to the classic written approach. Although iPad briefing took patients longer to perform, the majority would prefer it to written consent briefings in the future. Nevertheless, measures have to be undertaken to improve the overall acceptance and performance.
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Randomized Controlled Trial Multicenter Study
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. ⋯ 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.