Qualification of National Cancer Institute–Designated Cancer Centers for Quantitative PET/CT Imaging in Clinical Trials

Abstract

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 Radiologyapproved 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.

The Gamma Characteristic of Reconstructed PET Images: Implications for ROI Analysis

“…Classical linear 3-D Fourier rebinning filtered-backprojection reconstructions (FBP) are also produced. In our study, an uniform cylindrical phantom filled with F-18 radiotracer is placed in the scanner and imaged in accordance with a standard dynamic PET-FDG brain imaging protocol established by the CQIE project of the American College of Radiology Imaging Network (ACRIN) [20]. The brain imaging field of view (FOV) for PET is 700 mm trans-axially and 157 mm axially.…”

Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network

“…The need to control SUV bias has been partially addressed through consensus documents, which provide operating guidelines, [9][10][11] and accreditation organizations, which validate instrument performance. [12][13][14] Additionally, recent efforts have looked at the dependence of bias on reconstruction settings to find "harmonized" settings that match biases for small lesions. 14,15 A key area that is still lacking, though, is a characterization of bias stability that is due not to user-selected settings and clinical workflows, but to hardware performance and calibration.…”

Performance Observations of Scanner Qualification of NCI-Designated Cancer Centers: Results From the Centers of Quantitative Imaging Excellence (CQIE) Program

“…It is hard to quantitatively estimate the impact of such errors, but we note that Doot et al noted that to maintain study power in an example scenario, the required sample size increased from 8 to 126 as PET measurement precision worsened from 10% to 40% (16). Because the PET component collected more quantitative information with multiple SUV measures, a more detailed analysis of the PET data is ongoing (17). …”