Multicentre analysis of PET SUV using vendor-neutral software: the Japanese Harmonization Technology (J-Hart) study

Prognostic value of combining clinical factors, 18F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study

OBJECTIVE

To investigate the prognostic value of 18F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma receiving tyrosine kinase inhibitor (TKI) treatment.

METHODS

We retrospectively analyzed the pre-treatment 18F-FDG PET of 217 patients with advanced-stage lung adenocarcinoma and actionable EGFR mutations who received TKI as first-line treatment. Patients were separated into analog (n = 166) and digital (n = 51) PET cohorts. 18F-FDG PET-derived intensity, volumetric features, ResNet-50 DL of the primary tumor, and clinical variables were used to predict progression-free survival (PFS). Independent prognosticators were used to develop prediction model. Model was developed and validated in the analog and digital PET cohorts, respectively.

RESULTS

In the analog PET cohort, female sex, stage IVB status, exon 19 deletion, SUVmax, metabolic tumor volume, and positive DL prediction independently predicted PFS. The model devised from these six prognosticators significantly predicted PFS in the analog (HR = 1.319, p < 0.001) and digital PET cohorts (HR = 1.284, p = 0.001). Our model provided incremental prognostic value to staging status (c-indices = 0.738 vs. 0.558 and 0.662 vs. 0.598 in the analog and digital PET cohorts, respectively). Our model also demonstrated a significant prognostic value for overall survival (HR = 1.198, p < 0.001, c-index = 0.708 and HR = 1.256, p = 0.021, c-index = 0.664 in the analog and digital PET cohorts, respectively).

CONCLUSIONS

Combining 18F-FDG PET-based intensity, volumetric features, and DL with clinical variables may improve the survival stratification in patients with advanced EGFR-mutated lung adenocarcinoma receiving TKI treatment. Implementing the prediction model across different generations of PET scanners may be feasible and facilitate tailored therapeutic strategies for these patients.

A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study

OBJECTIVE

The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathological regional nodal metastasis (pN+) in resectable lung adenocarcinoma varies, and their use across different generations of PET machines has not been thoroughly investigated. We compared handcrafted radiomics and deep learning using different PET scanners to predict pN+ in resectable lung adenocarcinoma.

METHODS

We retrospectively analyzed pretreatment 18 F-FDG PET from 148 lung adenocarcinoma patients who underwent curative surgery. Patients were separated into analog (n = 131) and digital (n = 17) PET cohorts. Handcrafted radiomics and a ResNet-50 deep-learning model of the primary tumor were used to predict pN+ status. Models were trained in the analog PET cohort, and the digital PET cohort was used for cross-scanner validation.

RESULTS

In the analog PET cohort, entropy, a handcrafted radiomics, independently predicted pN+. However, the areas under the receiver-operating-characteristic curves (AUCs) and accuracy for entropy were only 0.676 and 62.6%, respectively. The ResNet-50 model demonstrated a better AUC and accuracy of 0.929 and 94.7%, respectively. In the digital PET validation cohort, the ResNet-50 model also demonstrated better AUC (0.871 versus 0.697) and accuracy (88.2% versus 64.7%) than entropy. The ResNet-50 model achieved comparable specificity to visual interpretation but with superior sensitivity (83.3% versus 66.7%) in the digital PET cohort.

CONCLUSION

Applying deep learning across different generations of PET scanners may be feasible and better predict pN+ than handcrafted radiomics. Deep learning may complement visual interpretation and facilitate tailored therapeutic strategies for resectable lung adenocarcinoma.

Variability in PET image quality and quantification measured with a permanently filled 68Ge-phantom: a multi-center study

BACKGROUND

This study evaluated, as a snapshot, the variability in quantification and image quality (IQ) of the clinically utilized PET [¹⁸F]FDG whole-body protocols in Finland using a NEMA/IEC IQ phantom permanently filled with ⁶⁸Ge.

METHODS

The phantom was imaged on 14 PET-CT scanners, including a variety of models from two major vendors. The variability of the recovery coefficients (RC_max, RC_mean and RC_peak) of the hot spheres as well as percent background variability (PBV), coefficient of variation of the background (COV_BG) and accuracy of corrections (AOC) were studied using images from clinical and standardized protocols with 20 repeated measurements. The ranges of the RCs were also compared to the limits of the EARL ¹⁸F standards 2 accreditation (EARL2). The impact of image noise on these parameters was studied using averaged images (AVIs).

RESULTS

The largest variability in RC values of the routine protocols was found for the RC_max with a range of 68% and with 10% intra-scanner variability, decreasing to 36% when excluding protocols with suspected cross-calibration failure or without point-spread-function (PSF) correction. The RC ranges of individual hot spheres in routine or standardized protocols or AVIs fulfilled the EARL2 ranges with two minor exceptions, but fulfilling the exact EARL2 limits for all hot spheres was variable. RC_peak was less dependent on averaging and reconstruction parameters than RC_max and RC_mean. The PBV, COV_BG and AOC varied between 2.3-11.8%, 9.6-17.8% and 4.8-32.0%, respectively, for the routine protocols. The RC ranges, PBV and COV_BG were decreased when using AVIs. With AOC, when excluding routine protocols without PSF correction, the maximum value dropped to 15.5%.

CONCLUSION

The maximum variability of the RC values for the [¹⁸F]FDG whole-body protocols was about 60%. The RC ranges of properly cross-calibrated scanners with PSF correction fitted to the EARL2 RC ranges for individual sphere sizes, but fulfilling the exact RC limits would have needed further optimization. RC_peak was the most robust RC measure. Besides COV_BG, also RCs and PVB were sensitive to image noise.

Prognostic role of preoperative fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography with an image-based harmonization technique: A multicenter retrospective study

Objectives

Despite the prognostic impacts of preoperative fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography examination, fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography-based prognosis prediction has not been used clinically because of the disparity in data between institutions. By applying an image-based harmonized approach, we evaluated the prognostic roles of fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography parameters in clinical stage I non-small cell lung cancer.

Methods

We retrospectively examined 495 patients with clinical stage I non-small cell lung cancer who underwent fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography examinations before pulmonary resection between 2013 and 2014 at 4 institutions. Three different harmonization techniques were applied, and an image-based harmonization, which showed the best-fit results, was used in the further analyses to evaluate the prognostic roles of fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography parameters.

Results

Cutoff values of image-based harmonized fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography parameters, maximum standardized uptake, metabolic tumor volume, and total lesion glycolysis were determined using receiver operating characteristic curves that distinguish pathologic high invasiveness of tumors. Among these parameters, only the maximum standardized uptake was an independent prognostic factor in recurrence-free and overall survivals in univariate and multivariate analyses. High image-based maximum standardized uptake value was associated with squamous histology or lung adenocarcinomas with higher pathologic grades. In subgroup analyses defined by ground-glass opacity status and histology or by clinical stages, the prognostic impact of image-based maximum standardized uptake value was always the highest compared with other fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography parameters.

Conclusions

The image-based fluorine-18 fluorodeoxyglucose-positron emission tomography/computed tomography harmonization was the best fit, and the image-based maximum standardized uptake was the most important prognostic marker in all patients and in subgroups defined by ground-glass opacity status and histology in surgically resected clinical stage I non-small cell lung cancers.

A review of harmonization strategies for quantitative PET

PET can reveal in vivo biological processes at the molecular level. PET-derived quantitative values have been used as a surrogate marker for clinical decision-making in numerous clinical studies and trials. However, quantitative values in PET are variable depending on technical, biological, and physical factors. The variability may have a significant impact on a study outcome. Appropriate scanner calibration and quality control, standardization of imaging protocols, and any necessary harmonization strategies are essential to make use of PET as a biomarker with low bias and variability. This review summarizes benefits, limitations, and remaining challenges for harmonization of quantitative PET, including whole-body PET in oncology, brain PET in neurology, PET/MR, and non-¹⁸F PET imaging. This review is expected to facilitate harmonization of quantitative PET and to promote the contribution of PET-derived biomarkers to research and development in medicine.

Harmonization based on quantitative analysis of standardized uptake value variations across PET/CT scanners: a multicenter phantom study

OBJECTIVES

This study aimed to measure standardized uptake value (SUV) variations across different PET/computed tomography (CT) scanners to harmonize quantification across systems.

METHODS

We acquired images using the National Electrical Manufacturers Association International Electrotechnical Commission phantom from three PET/CT scanners operated using routine imaging protocols at each site. The SUVs of lesions were assessed in the presence of reference values by a digital reference object (DRO) and recommendations by the European Association of Nuclear Medicine (EANM/EARL) to measure inter-site variations. For harmonization, Gaussian filters with tuned full width at half maximum (FWHM) values were applied to images to minimize differences in SUVs between reference and images. Inter-site variation of SUVs was evaluated in both pre- and postharmonization situations. Test-retest analysis was also carried out to evaluate repeatability.

RESULTS

SUVs from different scanners became significantly more consistent, and inter-site differences decreased for SUVmean, SUVmax and SUVpeak from 17.3, 20.7, and 15.5% to 4.8, 4.7, and 2.7%, respectively, by harmonization (P values <0.05 for all). The values for contrast-to-noise ratio in the smallest lesion of the phantom verified preservation of image quality following harmonization (>2.8%).

CONCLUSIONS

Harmonization significantly lowered variations in SUV measurements across different PET/CT scanners, improving reproducibility while preserving image quality.

Impact of patient body habitus on image quality and quantitative value in bone SPECT/CT

OBJECTIVE

The first edition of guidelines for standardization of bone single photon emission computed tomography (SPECT) imaging was published in 2017, and the optimization and standardization are widely promoted. To the purpose, clarification of the factors related to image quality and quantitative values and their influence are required. The present study aimed to clarify and optimize the influence of patient body habitus on image quality and quantitative values in bone SPECT/CT.

METHODS

National Electrical Manufacturers Association body phantom (S-size) and custom-made large body phantoms (M-size and L-size) that simulate the abdomens of Japanese patients weighing 60, 80, and 100 kg, were used. Each phantom was filled with ^99mTc-solutions of 108  and 18 kBq/mL for the hot spheres and background, respectively. Dynamic SPECT acquisition was performed for 6000 s (150 s /rotation × 40 rotation). The data were divided into six projection data and reconstructed each acquisition time (150, 300, 450, 600, 750, 900 s, and single projection 6000 s). Image quality was evaluated for contrast (Q_{H, 17 mm}), background noise (N_{B, 17 mm}), contrast-to-noise ratio (CNR), maximum standardized uptake value (SUV_{max, 17 mm}), and visual assessment for a 17 mm hot sphere.

RESULTS

Image quality in the 300 s acquisition showed that values of Q_{H, 17 mm}, CNR, and SUV_{max, 17 mm} decreased (-16.7%, -11.8%, and -11.3%) for M-size and (-28.2%, -30.1%, and -21.7%) for L-size compared with S-size, respectively. No significant difference was observed in N_{B, 17 mm} values. M-size and L-size required 1.2 and 2.3 times longer acquisition, to achieve same CNR as S-size. In visual assessment, 17 mm hot sphere could not be detected only in the L-size. When the Japanese bone SPECT guidelines criteria were applied in 600 s, the sphere could be detected between all phantoms.

CONCLUSIONS

Patient body habitus significantly affects image quality and decreases the quantitative value in bone SPECT/CT. For the optimization, extend acquisition time according to the patient body habitus is effective for image quality. And for the standardization, it is important to achieve imaging conditions that meet the Japanese bone SPECT guidelines criteria to ensure adequate detectability.

Reliability of Quantitative 18F-FDG PET/CT Imaging Biomarkers for Classifying Early Response to Chemoradiotherapy in Patients With Locally Advanced Non-Small Cell Lung Cancer

PURPOSE OF THE REPORT

We evaluated the reliability of 18F-FDG PET imaging biomarkers to classify early response status across observers, scanners, and reconstruction algorithms in support of biologically adaptive radiation therapy for locally advanced non-small cell lung cancer.

PATIENTS AND METHODS

Thirty-one patients with unresectable locally advanced non-small cell lung cancer were prospectively enrolled on a phase 2 trial (NCT02773238) and underwent 18F-FDG PET on GE Discovery STE (DSTE) or GE Discovery MI (DMI) PET/CT systems at baseline and during the third week external beam radiation therapy regimens. All PET scans were reconstructed using OSEM; GE-DMI scans were also reconstructed with BSREM-TOF (block sequential regularized expectation maximization reconstruction algorithm incorporating time of flight). Primary tumors were contoured by 3 observers using semiautomatic gradient-based segmentation. SUVmax, SUVmean, SUVpeak, MTV (metabolic tumor volume), and total lesion glycolysis were correlated with midtherapy multidisciplinary clinical response assessment. Dice similarity of contours and response classification areas under the curve were evaluated across observers, scanners, and reconstruction algorithms. LASSO logistic regression models were trained on DSTE PET patient data and independently tested on DMI PET patient data.

RESULTS

Interobserver variability of PET contours was low for both OSEM and BSREM-TOF reconstructions; intraobserver variability between reconstructions was slightly higher. ΔSUVpeak was the most robust response predictor across observers and image reconstructions. LASSO models consistently selected ΔSUVpeak and ΔMTV as response predictors. Response classification models achieved high cross-validated performance on the DSTE cohort and more variable testing performance on the DMI cohort.

CONCLUSIONS

The variability FDG PET lesion contours and imaging biomarkers was relatively low across observers, scanners, and reconstructions. Objective midtreatment PET response assessment may lead to improved precision of biologically adaptive radiation therapy.

18F-FDG PET/CT for monitoring anti-PD-1 therapy in patients with non-small cell lung cancer using SUV harmonization of results obtained with various types of PET/CT scanners used at different centers

OBJECTIVE

The prognostic value of treatment response in patients with non-small cell lung cancer (NSCLC) treated with immune-checkpoint inhibitors (ICIs) shown by ¹⁸F-fludeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) results obtained with multiple types of PET scanners using standardized uptake value (SUV) harmonization was evaluated.

METHODS

Fifty-eight patients treated with ICIs who underwent ¹⁸F-FDG PET/CT examinations with nine types of PET scanners at six hospitals were enrolled. SUV harmonization of multiple PET scanner results was performed using the dedicated software packages "RAVAT" and "RC Tool for Harmonization". Tumor response was assessed by change in sum of harmonized SUVmax, according to the European Organization for Research and Treatment of Cancer (EORTC5) or the SUV of up to five lesions normalized to lean body mass, according to the PET Response Criteria in Solid Tumors (PERCIST5) and immunotherapy-modified PERCIST (imPERCIST5) criteria. The correlation between tumor response according to those three definitions and overall survival (OS) was evaluated and compared to known prognostic factors.

RESULTS

One-year OS in responders and non-responders for harmonized EROTC5 was 86 and 32%, for harmonized PERCIST5 was 86 and 32%, and for harmonized imPERCIST5 was 80 and 30%, respectively (each p = 0.001). Univariate analysis showed that all response criteria remained as prognostic factors. However, there was an overlap for the categories stable metabolic disease (SMD) and progression metabolic disease (PMD) in survival curves using the PET treatment response criteria.

CONCLUSION

In patients with NSCLC treated with ICIs, tumor response based on the harmonized response criteria was associated with OS. PET response criteria using harmonized metabolic parameters may be difficult to routinely employ in daily practice due to overlapping SMD and PMD, although may have a supporting role for determining prognosis.

Tumor response evaluation in patients with malignant melanoma undergoing immune checkpoint inhibitor therapy and prognosis prediction using 18F-FDG PET/CT: multicenter study for comparison of EORTC, PERCIST, and imPERCIST

OBJECTIVE

In malignant melanoma patients treated with immune checkpoint inhibitor (ICI) therapy, three different FDG-PET criteria, European Organization for Research and Treatment of Cancer (EORTC), PET Response Criteria in Solid Tumors (PERCIST), immunotherapy-modified PERCIST (imPERCIST), were compared regarding response evaluation and prognosis prediction using standardized uptake value (SUV) harmonization of results obtained with various PET/CT scanners installed at different centers.

MATERIALS AND METHODS

Malignant melanoma patients (n = 27) underwent FDG-PET/CT examinations before and again 3 to 9 months after therapy initiation (nivolumab, n = 21; pembrolizumab, n = 6) with different PET scanners at five hospitals. EORTC, PERCIST, and imPERCIST criteria were used to evaluate therapeutic response, then concordance of the results was assessed using Cohen's κ coefficient. Log-rank and Cox methods were employed to determine progression-free (PFS) and overall (OS) survival.

RESULTS

Complete metabolic response (CMR)/partial metabolic response (PMR)/stable metabolic disease (SMD)/progressive metabolic disease (PMD) with harmonized EORTC, PERCIST, and imPERCIST was seen in 3/5/4/15, 4/5/3/15, and 4/5/5/13 patients, respectively. Nearly perfect concordance between each pair of criteria was noted (κ = 0.939-0.972). Twenty patients showed progression and 14 died from malignant melanoma after a median 19.2 months. Responders (CMR/PMR) showed significantly longer PFS and OS than non-responders (SMD/PMD) (harmonized EORTC: p < 0.0001 and p = 0.011; harmonized PERCIST: p < 0.0001 and p = 0.0012; harmonized imPERCIST: p < 0.0001 and p = 0.0012, respectively).

CONCLUSIONS

All harmonized FDG-PET criteria (EORTC, PERCIST, imPERCIST) showed accuracy for response evaluation of ICI therapy and prediction of malignant melanoma patient prognosis. Additional studies to determine their value in larger study populations will be necessary.

Differences among [18F]FDG PET-derived parameters in lung cancer produced by three software packages

Investigation of differences in derived [18F]FDG PET metabolic and volumetric parameters among three different software programs in lung cancer. A retrospective analysis was performed on a group of 98 lung cancer patients who underwent a baseline [18F]FDG PET/CT study. To assess appropriate delineation methods, the NEMA phantom study was first performed using the following software: Philips EBW (Extended Brilliance Workstation), MIM Software and Rover. Based on this study, the best cut-off methods (dependent on tumour size) were selected, extracted and applied for lung cancer delineation. Several semiquantitative [18F]FDG parameters (SUVmax, SUVmean, TLG and MTV) were assessed and compared among the three software programs. The parameters were assessed based on body weight (BW), lean body mass (LBM) and Bq/mL. Statistically significant differences were found in SUVmean (LBM) between MIM Software and Rover (4.62 ± 2.15 vs 4.84 ± 1.20; p < 0.005), in SUVmean (Bq/mL) between Rover and Philips EBW (21,852.30 ± 21,821.23 vs 19,274.81 ± 13,340.28; p < 0.005) and Rover and MIM Software (21,852.30 ± 21,821.23 vs 19,399.40 ± 10,051.30; p < 0.005), and in MTV between MIM Software and Philips EBW (19.87 ± 25.83 vs 78.82 ± 228.00; p = 0.0489). This study showed statistically significant differences in the estimation of semiquantitative parameters using three independent image analysis tools. These findings are important for performing further diagnostic and treatment procedures in lung cancer patients.

Usefulness of semi-automatic harmonization strategy of standardized uptake values for multicenter PET studies

This study assessed the possibility of semi-automatic harmonization of standardized uptake values (SUVs) in multicenter studies. Phantom data were acquired using 16 PET/CT scanners (including 3 PET/CT scanners with a silicon photomultiplier detector). PET images obtained using 30-min/bed scans for optimum harmonization filter calculations and using 90–180-s/bed scans for SUV validation under clinical conditions were obtained. Time of flight and a reconstruction method with point-spread function correction were allowed. The optimal full width at half maximum of the 3D-Gaussian filter that minimizes the root mean square error with the median value of the JSNM harmonization range was calculated semi-automatically. The SUVmax and the SUVpeak of the hot spheres were measured, and the inter-scanner coefficient of variation (COV) was calculated before and after harmonization. The harmonization filter was applied to 11 of the 15 PET/CT scanners in which the SUV calibration accuracy had been verified, but not in the remaining 4 scanners. Under noiseless conditions before harmonization, the inter-scanner COVs of the SUVmax and the SUVpeak were as high as 21.57% and 12.20%, respectively, decreasing to 8.79% and 5.73% after harmonization, respectively. Harmonization brought the SUVmax of all the hot spheres to within the harmonization range. Even under clinical conditions affected by image noise, the inter-scanner COVs for the SUVmax and SUVpeak were as high as 8.83% and 5.18% after harmonization, respectively. By applying an optimal harmonization filter that is calculated semi-automatically, the harmonization of SUVs according to the JSNM strategy is possible in multicenter studies, thereby reducing inter-scanner COVs.

Harmonized pretreatment quantitative volume-based FDG-PET/CT parameters for prognosis of stage I-III breast cancer: Multicenter study

OBJECTIVES

This study investigated harmonized pretreatment volume-based quantitative FDG-PET/CT parameters in breast cancer patients for prognostic value.

RESULTS

During a median overall follow-up period of 5.3 years, 91 patients had recurrence and 40 died. Multivariate analysis of ER-positive/HER2-negative patients showed high maximum standardized uptake value (SUVmax) (p = 0.018), high total lesion glycolysis (TLG) (p = 0.010), and clinical N-classification (p = 0.0027) as independent negative predictors of RFS, while high maximum SUVmax (p = 0.037), advanced clinical T-classification (p = 0.030), and advanced TNM stage (p = 0.0067) were independent negative predictors of OS. For recurrence and death in HER2-positive patients, high total TLG (p = 0.037, p = 0.0048, respectively) and advanced TNM stage (p = 0.048, p = 0.046, respectively) were independent prediction factors. In the triple-negative group, independent factors related to recurrence and death were high maximum SUVmax (p = 0.0014, p = 0.0003, respectively) and advanced TNM stage (p < 0.0001, p < 0.0001, respectively).

MATERIALS AND METHODS

Records of 546 stage I-III invasive breast cancer patients, including 344 estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative, 110 HER2-positive, and 92 triple-negative cases, treated at four institutions were reviewed retrospectively. Harmonized primary tumor and nodal maximum SUVmax, metabolic tumor volume (MTV), and TLG indicated in pretreatment FDG-PET/CT results were analyzed. Evaluations of relationships of clinicopathological factors, volume-based quantitative parameters, recurrence-free survival (RFS), and overall survival (OS) for each subtype were performed with a Cox proportional hazards model and log-rank test.

CONCLUSIONS

The results indicated that potential surrogate markers for prognosis in patients with the three main subtypes of operable breast cancer include harmonized pretreatment quantitative volume-based FDG-PET/CT parameters, particularly whole-lesion SUVmax and TLG.

Asphericity of tumor FDG uptake in non-small cell lung cancer: reproducibility and implications for harmonization in multicenter studies

Background

Asphericity (ASP) of the primary tumor’s metabolic tumor volume (MTV) in FDG-PET/CT is independently predictive for survival in patients with non-small cell lung cancer (NSCLC). However, comparability between PET systems may be limited. Therefore, reproducibility of ASP was evaluated at varying image reconstruction and acquisition times to assess feasibility of ASP assessment in multicenter studies.

Methods

This is a retrospective study of 50 patients with NSCLC (female 20; median age 69 years) undergoing pretherapeutic FDG-PET/CT (median 3.7 MBq/kg; 180 s/bed position). Reconstruction used OSEM with TOF_4/16 (iterations 4; subsets 16; in-plane filter 2.0, 6.4 or 9.5 mm), TOF_4/8 (4 it; 8 ss; filter 2.0/6.0/9.5 mm), PSF + TOF_2/17 (2 it; 17 ss; filter 2.0/7.0/10.0 mm) or Bayesian-penalized likelihood (Q.Clear; beta, 600/1750/4000). Resulting reconstructed spatial resolution (FWHM) was determined from hot sphere inserts of a NEMA IEC phantom. Data with approx. 5-mm FWHM were retrospectively smoothed to achieve 7-mm FWHM. List mode data were rebinned for acquisition times of 120/90/60 s. Threshold-based delineation of primary tumor MTV was followed by evaluation of relative ASP/SUVmax/MTV differences between datasets and resulting proportions of discordantly classified cases.

Results

Reconstructed resolution for narrow/medium/wide in-plane filter (or low/medium/high beta) was approx. 5/7/9 mm FWHM. Comparing different pairs of reconstructed resolution between TOF_4/8, PSF + TOF_2/17, Q.Clear and the reference algorithm TOF_4/16, ASP differences was lowest at FWHM of 7 versus 7 mm. Proportions of discordant cases (ASP > 19.5% vs. ≤ 19.5%) were also lowest at 7 mm (TOF_4/8, 2%; PSF + TOF_2/17, 4%; Q.Clear, 10%). Smoothing of 5-mm data to 7-mm FWHM significantly reduced discordant cases (TOF_4/8, 38% reduced to 2%; PSF + TOF_2/17, 12% to 4%; Q.Clear, 10% to 6%), resulting in proportions comparable to original 7-mm data. Shorter acquisition time only increased proportions of discordant cases at < 90 s.

Conclusions

ASP differences were mainly determined by reconstructed spatial resolution, and multicenter studies should aim at comparable FWHM (e.g., 7 mm; determined by in-plane filter width). This reduces discordant cases (high vs. low ASP) to an acceptable proportion for TOF and PSF + TOF of < 5% (Q.Clear: 10%). Data with better resolution (i.e., lower FWHM) could be retrospectively smoothed to the desired FWHM, resulting in a comparable number of discordant cases.