PurposeThe objective of this study was to explore the feasibility of harmonising performance for PET/CT systems equipped with time-of-flight (ToF) and resolution modelling/point spread function (PSF) technologies. A second aim was producing a working prototype of new harmonising criteria with higher contrast recoveries than current EARL standards using various SUV metrics.MethodsFour PET/CT systems with both ToF and PSF capabilities from three major vendors were used to acquire and reconstruct images of the NEMA NU2–2007 body phantom filled conforming EANM EARL guidelines. A total of 15 reconstruction parameter sets of varying pixel size, post filtering and reconstruction type, with three different acquisition durations were used to compare the quantitative performance of the systems. A target range for recovery curves was established such that it would accommodate the highest matching recoveries from all investigated systems. These updated criteria were validated on 18 additional scanners from 16 sites in order to demonstrate the scanners’ ability to meet the new target range.ResultsEach of the four systems was found to be capable of producing harmonising reconstructions with similar recovery curves. The five reconstruction parameter sets producing harmonising results significantly increased SUVmean (25%) and SUVmax (26%) contrast recoveries compared with current EARL specifications. Additional prospective validation performed on 18 scanners from 16 EARL accredited sites demonstrated the feasibility of updated harmonising specifications. SUVpeak was found to significantly reduce the variability in quantitative results while producing lower recoveries in smaller (≤17 mm diameter) sphere sizes.ConclusionsHarmonising PET/CT systems with ToF and PSF technologies from different vendors was found to be feasible. The harmonisation of such systems would require an update to the current multicentre accreditation program EARL in order to accommodate higher recoveries. SUVpeak should be further investigated as a noise resistant alternative quantitative metric to SUVmax.Electronic supplementary materialThe online version of this article (10.1007/s00259-018-3977-4) contains supplementary material, which is available to authorized users.

PurposeFrom 2010 until July 2016, the EANM Research Ltd. (EARL) FDG-PET/CT accreditation program has collected over 2500 phantom datasets from approximately 200 systems and 150 imaging sites worldwide. The objective of this study is to report the findings and impact of the accreditation program on the participating PET/CT systems.MethodsTo obtain and maintain EARL accredited status, sites were required to complete and submit two phantom scans - calibration quality control (CalQC), using a uniform cylindrical phantom and image quality control (IQQC), using a NEMA NU2–2007 body phantom. Average volumetric SUV bias and SUV recovery coefficients (RC) were calculated and the data evaluated on the basis of quality control (QC) type, approval status, PET/CT system manufacturer and submission order.ResultsSUV bias in 5% (n = 96) of all CalQC submissions (n = 1816) exceeded 10%. After corrective actions following EARL feedback, sites achieved 100% compliance within EARL specifications. 30% (n = 1381) of SUVmean and 23% (n = 1095) of SUVmax sphere recoveries from IQQC submissions failed to meet EARL accreditation criteria while after accreditation, failure rate decreased to 12% (n = 360) and 9% (n = 254), respectively. Most systems demonstrated longitudinal SUV bias reproducibility within ±5%, while RC values remained stable and generally within ±10% for the four largest and ±20% for the two smallest spheres.ConclusionsRegardless of manufacturer or model, all investigated systems are able to comply with the EARL specifications. Within the EARL accreditation program, gross PET/CT calibration errors are successfully identified and longitudinal variability in PET/CT performances reduced. The program demonstrates that a harmonising accreditation procedure is feasible and achievable.Electronic supplementary materialThe online version of this article (10.1007/s00259-017-3853-7) contains supplementary material, which is available to authorized users.

Purpose: Recently, updated EARL specifications (EARL2) have been developed and announced. This study aims at investigating the impact of the EARL2 specifications on the quantitative reads of clinical PET-CT studies and testing a method to enable the use of the EARL2 standards whilst still generating quantitative reads compliant with current EARL standards (EARL1). Methods: Thirteen non-small cell lung cancer (NSCLC) and seventeen lymphoma PET-CT studies were used to derive four image datasets-the first dataset complying with EARL1 specifications and the second reconstructed using parameters as described in EARL2. For the third (EARL2F6) and fourth (EARL2F7) dataset in EARL2, respectively, 6 mm and 7 mm Gaussian post-filtering was applied. We compared the results of quantitative metrics (MATV, SUVmax, SUVpeak, SUVmean, TLG, and tumorto-liver and tumor-to-blood pool ratios) obtained with these 4 datasets in 55 suspected malignant lesions using three commonly used segmentation/volume of interest (VOI) methods (MAX41, A50P, SUV4). Results: We found that with EARL2 MAX41 VOI method, MATV decreases by 22%, TLG remains unchanged and SUV values increase by 23-30% depending on the specific metric used. The EARL2F7 dataset produced quantitative metrics best aligning with EARL1, with no significant differences between most of the datasets (p>0.05). Different VOI methods performed similarly with regard to SUV metrics but differences in MATV as well as TLG were observed. No significant difference between NSCLC and lymphoma cancer types was observed. Conclusions: Application of EARL2 standards can result in higher SUVs, reduced MATV and slightly changed TLG values relative to EARL1. Applying a Gaussian filter to PET images reconstructed using EARL2 parameters successfully yielded EARL1 compliant data.

Purpose In order to achieve comparability of image quality, harmonisation of PET system performance is imperative. In this study, prototype harmonisation criteria for PET brain studies were developed. Methods Twelve clinical PET/CT systems (4 GE, 4 Philips, 4 Siemens, including SiPM-based “digital” systems) were used to acquire 30-min PET scans of a Hoffman 3D Brain phantom filled with ~ 33 kBq·mL−1 [18F]FDG. Scan data were reconstructed using various reconstruction settings. The images were rigidly coregistered to a template (voxel size 1.17 × 1.17 × 2.00 mm3) onto which several volumes of interest (VOIs) were defined. Recovery coefficients (RC) and grey matter to white matter ratios (GMWMr) were derived for eroded (denoted in the text by subscript e) and non-eroded grey (GM) and white (WM) matter VOIs as well as a mid-phantom cold spot (VOIcold) and VOIs from the Hammers atlas. In addition, left-right hemisphere differences and voxel-by-voxel differences compared to a reference image were assessed. Results Systematic differences were observed for reconstructions with and without point-spread-function modelling (PSFON and PSFOFF, respectively). Normalising to image-derived activity, upper and lower limits ensuring image comparability were as follows: for PSFON, RCGMe = [0.97–1.01] and GMWMre = [3.51–3.91] for eroded VOI and RCGM = [0.78–0.83] and GMWMr = [1.77–2.06] for non-eroded VOI, and for PSFOFF, RCGMe = [0.92–0.99] and GMWMre = [3.14–3.68] for eroded VOI and RCGM = [0.75–0.81] and GMWMr = [1.72–1.95] for non-eroded VOI. Conclusions To achieve inter-scanner comparability, we propose selecting reconstruction settings based on RCGMe and GMWMre as specified in “Results”. These proposed standards should be tested prospectively to validate and/or refine the harmonisation criteria.

PurposeThe aim of this study was to investigate the variability in quantitative performance and feasibility of quantitative harmonisation in 89Zr PET/CT imaging.MethodsEight EANM EARL-accredited (Kaalep A et al., Eur J Nucl Med Mol Imaging 45:412–22, 2018) PET/CT systems were investigated using phantom acquisitions of uniform and NEMA NU2-2007 body phantoms. The phantoms were filled according to EANM EARL guidelines for [18F]FDG, but [18F]FDG solution was replaced by a 89Zr calibration mixture. For each system, standard uptake value (SUV) accuracy and recovery coefficients (RC) using SUVmean, SUVmax and SUVpeak metrics were determined.ResultsAll eight investigated systems demonstrated similarly shaped RC curves, and five of them exhibited closely aligning recoveries when SUV bias correction was applied. From the evaluated metrics, SUVpeak was found to be least sensitive to noise and reconstruction differences among different systems.ConclusionsHarmonisation of PET/CT scanners for quantitative 89Zr studies is feasible when proper scanner-dose calibrator cross-calibration and harmonised image reconstruction procedures are followed. An accreditation programme for PET/CT scanners would facilitate multicentre 89Zr quantitative studies.

This letter aims at explaining that adjusting the performance of PET/CT systems to a new standard also requires updating of interpretation criteria. Simply changing one aspect of the imaging procedure, i.e., PET/CT performance and image quality, and not adapting interpretation criteria will result in an increase of false positive (or negative) reads.

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Purpose: From until July 2016 EANM Research Ltd. (EARL) FDG-PET/CT accreditation program has collected over 2500 phantom datasets from approximately 200 systems and 150 imaging sites worldwide. The objective of this study is to report the findings and impact of the accreditation program on the participating PET/CT systems. Methods: To obtain and maintain EARL accredited status, sites were required to complete and submit two phantom scans-calibration quality control (CalQC), using a uniform cylindrical phantom and image quality control (IQQC), using a NEMA NU2-2007 body phantom. Average volumetric SUV bias and SUV recovery coefficients (RC) were calculated and the data evaluated on the basis of quality control (QC) type, approval status, PET/CT system manufacturer and submission order. Results: SUV bias in 5% (n=96) of all CalQC submissions (n=1816) exceeded 10%. After corrective actions following EARL feedback, sites achieved 100% compliance within EARL specifications. 30% (n=1381) of SUVmean and 23% (n=1095) of SUVmax sphere recoveries from IQQC submissions failed to meet EARL accreditation criteria while after accreditation, failure rate decreased to 12% (n=360) and 9% (n=254) respectively. Most systems demonstrated longitudinal SUV bias reproducibility within ±5%, while RC values remained stable and generally within ±10% for the four largest and ±20% for the two smallest spheres. Conclusions: Regardless of manufacturer or model, all investigated systems are able to comply with the EARL specifications. Within the EARL accreditation program gross PET/CT calibration errors are successfully identified and longitudinal variability in PET/CT performances reduced. The program demonstrates that a harmonising accreditation procedure is feasible and achievable. We would like to thank the EARL sites that provided additional reconstructions of the image quality QC phantom experiments, namely: