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A Practical, Automated Quality Assurance Method for Measuring Spatial Resolution in PET

¹ Division of Nuclear Medicine, Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland; and ² Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Johns Hopkins University School of Medicine, Baltimore, Maryland

Correspondence: For correspondence or reprints contact: Martin Lodge, Radiology/Nuclear Medicine Department, Johns Hopkins Hospital, Nelson B1-160, 600 N. Wolfe St., Baltimore, MD 21287. E-mail: mlodge1{at}jhmi.edu

The use of different scanners, acquisition protocols, and reconstruction algorithms has been identified as a problem that limits the use of PET in multicenter trials. The aim of this project was to aid standardization of data collection by developing a quality assurance method for measuring the spatial resolution achieved with clinical imaging protocols. Methods: A commercially available ⁶⁸Ge cylinder phantom (diameter, 20 cm) with a uniform activity concentration was positioned in the center of the PET field of view, and an image was acquired using typical clinical parameters. Spatial resolution was measured by artificially generating an object function (O) with uniform activity within a 20-cm-diameter cylinder, assuming no noise and perfect spatial resolution, centered on the original image (I); dividing F[I] by F[O], where F indicates a 2-dimensional Fourier transform, to produce a modulation transfer function; and taking the inverse Fourier transform of the modulation transfer function to produce a point-spread function in image space. The method was validated using data acquired on 4 different commercial PET systems. Results: Spatial resolution on the Discovery LS was measured at 5.75 ± 0.58 mm, compared with 5.54 ± 0.19 mm from separate point source measurements. Variability of the resolution measurements differed between scanners and protocols, but the typical SD was approximately 0.15 mm when iterative reconstruction was used. The potential for predicting resolution recovery coefficients for small objects was also demonstrated. Conclusion: The proposed method does not require elaborate phantom preparation and is practical to perform, and data analysis is fully automated. This approach is useful for evaluating clinical reconstruction protocols across varying scanners and reconstruction algorithms and should greatly aid standardization of data collection between centers.

Key Words: spatial resolution • quality assurance • multicenter trials • PET

COPYRIGHT © 2009 by the Society of Nuclear Medicine, Inc.

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JNM 2009 50: 11A-12A. [Full Text]