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Quantitative quality assurance in a multicenter HARDI clinical trial at 3 T
Institution:1. Imaging Institute, Cleveland Clinic, Cleveland, OH, 44195, USA;2. Barrow Neurological Institute, St. Joseph''s Hospital and Medical Center, Phoenix, AZ, 85013,USA;3. Siemens Medical Solutions, Cary, NC, 27511, USA;4. Department of Neurology, Case Western Reserve University, Cleveland, OH, 44106, USA;5. Neurological Institute, Cleveland Clinic, Cleveland, OH, 44195, USA;1. Center for Advanced Imaging Innovation and Research, Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY 10016, USA;2. Department of Radiology, Duke University Medical Center, Durham, NC, 27710, USA;1. Department of Surgery, Academic Medical Center, Amsterdam, the Netherlands;1. New Zealand Brain Research Institute, Christchurch 8011, New Zealand;2. Department of Medicine, University of Otago, Christchurch 8011, New Zealand;3. Department of Psychological Medicine, University of Otago, Christchurch 8011, New Zealand;4. School of Health Sciences, University of Canterbury, Christchurch 8041, New Zealand;5. Department of Paediatrics, University of Otago, Christchurch 8011, New Zealand
Abstract:A phantom-based quality assurance (QA) protocol was developed for a multicenter clinical trial including high angular resolution diffusion imaging (HARDI). A total of 27 3 T MR scanners from 2 major manufacturers, GE (Discovery and Signa scanners) and Siemens (Trio and Skyra scanners), were included in this trial. With this protocol, agar phantoms doped to mimic relaxation properties of brain tissue are scanned on a monthly basis, and quantitative procedures are used to detect spiking and to evaluate eddy current and Nyquist ghosting artifacts. In this study, simulations were used to determine alarm thresholds for minimal acceptable signal-to-noise ratio (SNR). Our results showed that spiking artifact was the most frequently observed type of artifact. Overall, Trio scanners exhibited less eddy current distortion than GE scanners, which in turn showed less distortion than Skyra scanners. This difference was mainly caused by the different sequences used on these scanners. The SNR for phantom scans was closely correlated with the SNR from volunteers. Nearly all of the phantom measurements with artifact-free images were above the alarm threshold, suggesting that the scanners are stable longitudinally. Software upgrades and hardware replacement sometimes affected SNR substantially but sometimes did not. In light of these results, it is important to monitor longitudinal SNR with phantom QA to help interpret potential effects on in vivo measurements. Our phantom QA procedure for HARDI scans was successful in tracking scanner performance and detecting unwanted artifacts.
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