• Joshua S Scheuermann, Janet S Reddin, Adam Opanowski, Paul E Kinahan, Barry A Siegel, Lalitha K Shankar, and Joel S Karp.
• Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania jscheu@mail.med.upenn.edu.
• J. Nucl. Med. 2017 Jul 1; 58 (7): 1065-1071.

AbstractThe National Cancer Institute developed the Centers for Quantitative Imaging Excellence (CQIE) initiative in 2010 to prequalify imaging facilities at all of the National Cancer Institute-designated comprehensive and clinical cancer centers for oncology trials using advanced imaging techniques, including PET. Here we review the CQIE PET/CT scanner qualification process and results in detail. Methods: Over a period of approximately 5 y, sites were requested to submit a variety of phantoms, including uniform and American College of Radiology-approved phantoms, PET/CT images, and examples of clinical images. Submissions were divided into 3 distinct time periods: initial submission (T0) and 2 requalification submissions (T1 and T2). Images were analyzed using standardized procedures, and scanners received a pass or fail designation. Sites had the opportunity to submit new data for scanners that failed. Quantitative results were compared across scanners within a given time period and across time periods for a given scanner. Results: Data from 65 unique PET/CT scanners across 56 sites were submitted for CQIE T0 qualification; 64 scanners passed the qualification. Data from 44 (68%) of those 65 scanners were submitted for T2. From T0 to T2, the percentage of scanners passing the CQIE qualification on the first attempt rose from 38% for T1 to 67% for T2. The most common reasons for failure were SUV outside specifications, incomplete submission, and uniformity issues. Uniform phantom and American College of Radiology-approved phantom results between scanner manufacturers were similar. Conclusion: The results of the CQIE process showed that periodic requalification may decrease the frequency of deficient data submissions. The CQIE project also highlighted the concern within imaging facilities about the burden of maintaining different qualifications and accreditations. Finally, for quantitative imaging-based trials, further evaluation of the relationships between the level of the qualification (e.g., bias or precision) and the quality of the image data, accrual rates, and study power is needed.© 2017 by the Society of Nuclear Medicine and Molecular Imaging.

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