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Published byDomenic Bradley Modified over 9 years ago
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Function BIRN: Quality Assurance Practices Introduction: Conclusion: Function BIRN In developing a common fMRI protocol for a multi-center study of schizophrenia, site-specific factors, such as scanner hardware and software versions lead to differences in image quality, distortions, and the dynamic signal to noise measurements needed for measuring cortical activity using fMRI methods. To adjust for these differences, the Function BIRN has created detailed scanning protocols that are performed at each participating Function BIRN site. Common gel cylinders, called “phantoms,” have been manufactured for each site so that the same methods are used for quality assurance across sites. Phantom scans are used to (1) perform a one time system check to test a scanner’s geometric accuracy using a specialized cylindrical geometry phantom and (2) perform ongoing quality assurance scans using a spherical agar phantom to verify inter-image stability and drift over time. These data, collected over time and across sites, are a valuable and unique resource: Most fMRI sites around the world have their own QA methods, but there is no common way of comparing whether one site’s images are the same as another. These data for the first time allow a comparison of basic image measurements across sites and over time. The multi-site functional magnetic resonance imaging effort is leading to a novel sharing of basic fMRI image characteristics across scanner manufacturers and imaging methods. These initial protocols and data are being used to improve calibration methods in the existing scanners and to calibrate new scanners as they are being installed at various sites. The meaning of these statistics across time are clear, indicating changes in the scanner’s capabilities. Comparisons across sites are being considered and improved as needed to give the most meaningful measures possible. A significant impact on the field of functional MRI is already occurring, as scanner manufacturers have become aware of the performance of their instruments in the BIRN protocols. Infrastructure for QA data sharing 3 The BIRN portal has been used to construct a single point of entry for processing, uploading, viewing and interacting with the QA phantom data. Workflow management links are available to simplify the QA analysis and SRB uploading process. Considerable effort and attention has been given to making the interface intuitive and user friendly. A user logged into the portal can select to upload their local site QA phantom data and generate an analysis. The user is abstracted from the complexities of native scanner format conversions, XML image format descriptor, and meta-data creation. The portal interface allows the user to browse intra-site and inter-site summary statistics. All data can be exported as comma separated values allowing seamless integration with common statistical packages. Function BIRN QA portal site provides workflow management, data uploads, and automated QA analysis pathways. Statistical measures 2 Sampling Region: The sampling region is a 20x20 voxel region centered in the volume’s central slice (slice #18). Mean: Simple mean calculated from the average of each sampling region over 198 volumes. The first 2 volumes are skipped to allow for signal instabilities during ramping of the gradient electronics. Standard Deviation (std): Calculated in the same fashion as the mean. Signal-to-noise ratio (SNR): The noise measurement is calculated by subtracting the average of the even numbered volumes from the odd numbered volumes using the sampling region. The signal measurement is calculated from the sampling region applied to the mean image. The SNR is calculated from the ratio of these. Signal-to-noise fluctuation ratio (SFNR): The SFNR measurement is calculated by dividing the sampling region from the mean image by the sampling region of the standard deviation image. Percent fluctuation (% fluc): Percent fluctuation or root mean square stability is calculated from the sampling region after applying a second order detrending fit. Drift: Drift is calculated from the second order detrending fit as 100*(max-min)/mean. Central slice and 20x20 voxel sampling region from 200 volumes and statistical measures plot Intra-site results 4 (A) Function BIRN phantom QA portal site showing interactive tabular summaries of QA results by site. (B) Excel pivot table template conforming to portal export data format for quick QA comparisons and analysis. Intra-site comparisons and analysis of QA phantom data provides useful information about scanner differences and drift in measurements over time. The online tabular data display allows interactive critical value thresholding and color coding for each QA measure to quickly and visually indicate malfunctioning systems. Additionally, tabular data within site and across sites can be downloaded, graphed, and analyzed using a pre-defined pivot table template. A B Function BIRN Brigham and Women’s Hospital Brain Imaging and Analysis Center UCLA Stanford Phantom scans 1 The BIRN Quality Assurance (BIRN QA) scans are performed on a routine basis. They are used to verify and measure the scanner stability during a typical fMRI scanning sequence. The scans are performed on a 17cm spherical phantom filled with an agar gel (Figure 1). The scans consist of 200 separate image volumes captured over roughly a 10 minute interval. Post acquisition analyses consist of mean and standard deviation measurements, drift and percent fluctuation in signal, signal-to-noise (SNR), and signal-to-fluctuation-noise (SFNR) ratios calculated over all volumes (Figure 2). Figure 1: Agar QA Phantom Figure 2: Images of QA agar gel phantom time series maps. (A) mean, (B) standard deviation, (C) noise average, (D) SFNR.
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