SUV variability in EARL-accredited conventional and digital PET.
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ABSTRACT:
SUBMITTER: Koopman D
PROVIDER: S-EPMC6904705 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature
Publications
SUV variability in EARL-accredited conventional and digital PET.
Koopman Daniëlle D Jager Pieter L PL Slump Cornelis H CH Knollema Siert S van Dalen Jorn A JA
EJNMMI research 20191210 1
<h4>Background</h4>A high SUV-reproducibility is crucial when different PET scanners are in use. We evaluated the SUV variability in whole-body FDG-PET scans of patients with suspected or proven cancer using an EARL-accredited conventional and digital PET scanner. In a head-to-head comparison we studied images of 50 patients acquired on a conventional scanner (cPET, Ingenuity TF PET/CT, Philips) and compared them with images acquired on a digital scanner (dPET, Vereos PET/CT, Philips). The PET s ...[more]
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Project description:PURPOSE:From 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. 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.
| S-EPMC5787222 | biostudies-literature
Project description:BACKGROUND:Today, the standardized uptake value (SUV) is essentially the only means for quantitative evaluation of static [18F-]fluorodeoxyglucose (FDG) positron emission tomography (PET) investigations. However, the SUV approach has several well-known shortcomings which adversely affect the reliability of the SUV as a surrogate of the metabolic rate of glucose consumption. The standard uptake ratio (SUR), i.e., the uptake time-corrected ratio of tumor SUV to image-derived arterial blood SUV, has been shown in the first clinical studies to overcome most of these shortcomings, to decrease test-retest variability, and to increase the prognostic value in comparison to SUV. However, it is unclear, to what extent the SUR approach is vulnerable to observer variability of the additionally required blood SUV (BSUV) determination. The goal of the present work was the investigation of the interobserver variability of image-derived BSUV. METHODS:FDG PET/CT scans from 83 patients (72 male, 11 female) with non-small cell lung cancer (N = 46) or head and neck cancer (N = 37) were included. BSUV was determined by 8 individuals, each applying a dedicated delineation tool for the BSUV determination in the aorta. Two of the observers applied two further tools. Altogether, five different delineation tools were used. With each used tool, delineation was performed for the whole patient group, resulting in 12 distinct observations per patient. Intersubject variability of BSUV determination was assessed using the fractional deviations for the individual patients from the patient group average and was quantified as standard deviation (SD is), 95% confidence interval, and range. Interobserver variability of BSUV determination was assessed using the fractional deviations of the individual observers from the observer-average for the considered patient and quantified as standard deviations (SD p, SD d) or root mean square (RMS), 95% confidence interval, and range in each patient, each observer, and the pooled data respectively. RESULTS:Interobserver variability in the pooled data amounts to RMS = 2.8% and is much smaller than the intersubject variability of BSUV (SD is= 16%). Averaged over the whole patient group, deviations of individual observers from the observer average are very small and fall in the range [ -?0.96, 1.05]%. However, interobserver variability partly differs distinctly for different patients, covering a range of [0.7, 7.4]% in the investigated patient group. CONCLUSION:The present investigation demonstrates that the image-based manual determination of BSUV in the aorta is sufficiently reproducible across different observers and delineation tools which is a prerequisite for accurate SUR determination. This finding is in line with the already demonstrated superior prognostic value of SUR in comparison to SUV in the first clinical studies.
| S-EPMC6399366 | biostudies-literature
Project description: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 tumor-to-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.
| S-EPMC6933045 | biostudies-literature
Project description:INTRODUCTION:11C-acetate (ACE)-PET/CT is used for staging of high-risk prostate cancer. PET data is reconstructed with iterative algorithms, such as VUEPointHD ViP (VPHD) and VUEPoint HD Sharp IR (SharpIR), the latter with additional resolution recovery. It is expected that the resolution recovery algorithm should render more accurate maximum and mean standardized uptake values (SUVmax and SUVmean) and functional tumor volumes (FTV) than the ordinary OSEM. Performing quantitative analysis, choice of volume-of-interest delineation algorithm (SUV threshold) may influence FTV. Optimizing PET acquisition time is justified if image quality and quantitation do not deteriorate. The aim of this study is to identify the optimal reconstruction algorithm, SUV threshold and acquisition time for ACE-PET/CT. METHODS:ACE-PET/CT data acquired with a General Electric Discovery 690 PET/CT from 16 consecutive high-risk prostate cancer patients was reconstructed with VPHD and SharpIR. Forty pelvic lymph nodes (LNs) and 14 prostate glands were delineated with 42% and estimated threshold. SUVmax, SUVmean, FTV and total lesion uptake were measured. Default acquisition time was four minutes per bed position. In a subset of lesions, acquisition times of one, two and four minutes were evaluated. Structural tumor volumes (STV) of the LNs were measured with CT for correlation with functional volumetric parameters. To validate SUV quantification under different conditions with SharpIR 42%, recovery coefficients (RCs) of SUVmean and FTV were calculated from a phantom with 18F-fluoro-deoxy-glucose (FDG)-filled volumes 0.1-9.2cm3 and signal-to-background (S/B) ratios 4.3-15.9. RESULTS:With SharpIR, SUVmax and SUVmean were higher and FTV lower compared with VPHD, regardless of threshold method, in both prostates and LNs. Total lesion uptake determined with both threshold methods was lower with SharpIR compared with VPHD with both threshold methods, except in subgroup analysis of prostate targets where estimated threshold returned higher values. Longer acquisition times returned higher FTV for both threshold methods, regardless of reconstruction algorithm. The FTV difference was most pronounced with one minute's acquisition per bed position, which also produced visually the highest noise. SUV parameters were unaffected by varying acquisition times. FTV with SharpIR 42% showed the best correspondence with STV. SharpIR 42% gave higher RCs of SUVmean and FTV with increasing phantom size and S/B-ratio, as expected. CONCLUSIONS:Delineation with SharpIR 42% seems to provide the most accurate combined information from SUVmax, SUVmean, FTV and total lesion uptake. Acquisition time may be shortened to two minutes per bed position with preserved image quality.
| S-EPMC6292629 | biostudies-literature
Project description:Quantitative assessment of radio- and chemotherapy response with 18F-FDG whole-body PET has attracted increasing interest in recent years. In most published work, SUV has been used for this purpose. In the context of therapy response assessment, the reliability of lesion SUVs, notably their test-retest stability, thus becomes crucial. However, a recent study demonstrated substantial test-retest variability (TRV) in SUVs. The purpose of the present study was to investigate whether the tumor-to-blood SUV ratio (SUR) can improve TRV in tracer uptake. Methods: 73 patients with advanced non-small cell lung cancer from the prospective multicenter trials ACRIN 6678 (n = 34) and MK-0646-008 (n = 39) were included in this study. All patients underwent two 18F-FDG PET/CT investigations on two different days (time difference, 3.6 ± 2.1 d; range, 1-7 d) before therapy. For each patient, up to 7 tumor lesions were evaluated. For each lesion, SUVmax and SUVpeak were determined. Blood SUV was determined as the mean value of a 3-dimensional aortic region of interest that was delineated on the attenuation CT image and transferred to the PET image. SURs were computed as the ratio of tumor SUV to blood SUV and were uptake time-corrected to 75 min after injection. TRV was quantified as 1.96 multiplied by the root-mean-square deviation of the fractional paired differences in SUV and SUR. The combined effect of blood normalization and uptake time correction was inspected by considering RTRV (TRVSUR/TRVSUV), a ratio reflecting the reduction in the TRV in SUR relative to SUV. RTRV was correlated with the group-averaged-value difference (?) in CFmean (?CFmean) of the quantity ?CF = |CF - 1|, where CF is the numeric factor that converts individual ratios of paired SUVs into corresponding SURs. This correlation analysis was performed by successively increasing a threshold value ?CFmin and computing ?CFmean and RTRV for the remaining subgroup of patients/lesions with ?CF ? ?CFminResults: The group-averaged TRVSUV and TRVSUR were 32.1 and 29.0, respectively, which correspond to a reduction of variability in SUR by an RTRV factor of 0.9 in comparison to SUV. This rather marginal improvement can be understood to be a consequence of the atypically low intrasubject variability in blood SUV and uptake time and the accordingly small ?CF values in the investigated prospective study groups. In fact, subgroup analysis with increasing ?CFmin thresholds revealed a pronounced negative correlation (Spearman ? = -0.99, P < 0.001) between RTRV and ?CFmean, where RTRV ? 0.4 in the ?CFmin = 20% subgroup, corresponding to a more than 2-fold reduction of TRVSUR compared with TRVSUVConclusion: Variability in blood SUV and uptake time has been identified as a causal factor in the TRV in lesion SUV. Therefore, TRV in lesion uptake measurements can be reduced by replacing SUV with SUR as the uptake measure. The improvement becomes substantial for the level of variability in blood SUV and uptake time typically observed in the clinical context.
| S-EPMC5666644 | biostudies-literature
Project description:ObjectiveIntratumoral heterogeneity is associated with poor outcomes in head and neck cancer (HNC) patients owing to chemoradiotherapy resistance. [18 F]-FDG positron emission tomography (PET) / Magnetic Resonance Imaging (MRI) provides spatial information about tumor mass, allowing intratumor heterogeneity assessment through histogram analysis. However, variability in quantitative PET/MRI parameter measurements could influence their reliability in assessing patient prognosis. Therefore, to use standardized uptake value (SUV) and apparent diffusion coefficient (ADC) parameters for assessing tumor response, this study aimed to measure SUV and ADC's variability and assess their relationship in HNC.MethodsFirst, ADC variability was measured in an in-house diffusion phantom and in five healthy volunteers. The SUV variability was only measured with the NEMA phantom using a clinical imaging protocol. Furthermore, simultaneous PET/MRI data of 11 HNC patients were retrospectively collected from the National Cyclotron and PET center in Chulabhorn Hospital. Tumor contours were manually drawn from PET images by an experienced nuclear medicine radiologist before tumor volume segmentation. Next, SUV and ADC's histogram were used to extract statistic variables of ADC and SUV: mean, median, min, max, skewness, kurtosis, and 5th , 10th , 25th , 50th , 75th , 90th , and 95th percentiles. Finally, the correlation between the statistic variables of ADC and SUV, as well as Metabolic Tumor volume and Total Lesion Glycolysis parameters was assessed using Pearson's correlation.ResultsThis pilot study showed that both parameters' maximum coefficient of variation was 13.9% and 9.8% in the phantom and in vivo, respectively. Furthermore, we found a strong and negative correlation between SUVmax and ADVmed (r = -0.75, P = 0.01).ConclusionThe SUV and ADC obtained by simultaneous PET/MRI can be potentially used as an imaging biomarker for assessing intratumoral heterogeneity in patients with HNC. The low variability and relationship between SUV and ADC could allow multimodal prediction of tumor response in future studies.
| S-EPMC10161023 | biostudies-literature
Project description:PurposeCurrent European Association of Nuclear Medicine (EANM) Research Ltd. (EARL) guidelines for the standardisation of PET imaging developed for conventional systems have not yet been adjusted for long axial field-of-view (LAFOV) systems. In order to use the LAFOV Siemens Biograph Vision Quadra PET/CT (Siemens Healthineers, Knoxville, TN, USA) in multicentre research and harmonised clinical use, compliance to EARL specifications for 18F-FDG tumour imaging was explored in the current study. Additional tests at various locations throughout the LAFOV and the use of shorter scan durations were included. Furthermore, clinical data were collected to further explore and validate the effects of reducing scan duration on semi-quantitative PET image biomarker accuracy and precision when using EARL-compliant reconstruction settings.MethodsEARL compliance phantom measurements were performed using the NEMA image quality phantom both in the centre and at various locations throughout the LAFOV. PET data (maximum ring difference (MRD) = 85) were reconstructed using various reconstruction parameters and reprocessed to obtain images at shorter scan durations. Maximum, mean and peak activity concentration recovery coefficients (RC) were obtained for each sphere and compared to EARL standards specifications. Additionally, PET data (MRD = 85) of 10 oncological patients were acquired and reconstructed using various reconstruction settings and reprocessed from 10 min listmode acquisition into shorter scan durations. Per dataset, SUVs were derived from tumour lesions and healthy tissues. ANOVA repeated measures were performed to explore differences in lesion SUVmax and SUVpeak. Wilcoxon signed-rank tests were performed to evaluate differences in background SUVpeak and SUVmean between scan durations. The coefficient of variation (COV) was calculated to characterise noise.ResultsPhantom measurements showed EARL compliance for all positions throughout the LAFOV for all scan durations. Regarding patient data, EARL-compliant images showed no clinically meaningful significant differences in lesion SUVmax and SUVpeak or background SUVmean and SUVpeak between scan durations. Here, COV only varied slightly.ConclusionImages obtained using the Vision Quadra PET/CT comply with EARL specifications. Scan duration and/or activity administration can be reduced up to a factor tenfold without the interference of increased noise.
| S-EPMC9606094 | biostudies-literature
Project description:BackgroundWe assessed and compared image quality obtained with clinical 18F-FDG whole-body oncologic PET protocols used in three different, state-of-the-art digital PET/CT and two conventional PMT-based PET/CT devices. Our goal was to evaluate an improved trade-off between administered activity (patient dose exposure/signal-to-noise ratio) and acquisition time (patient comfort) while preserving diagnostic information achievable with the recently introduced digital detector technology compared to previous analogue PET technology.MethodsWe performed list-mode (LM) PET acquisitions using a NEMA/IEC NU2 phantom, with activity concentrations of 5?kBq/mL and 25?kBq/mL for the background (9.5?L) and sphere inserts, respectively. For each device, reconstructions were obtained varying the image statistics (10, 30, 60, 90, 120, 180, and 300?s from LM data) and the number of iterations (range 1 to 10) in addition to the employed local clinical protocol setup. We measured for each reconstructed dataset: the quantitative cross-calibration, the image noise on the uniform background assessed by the coefficient of variation (COV), and the recovery coefficients (RCs) evaluated in the hot spheres. Additionally, we compared the characteristic time-activity-product (TAP) that is the product of scan time per bed position × mass-activity administered (in min·MBq/kg) across datasets.ResultsGood system cross-calibration was obtained for all tested datasets with <?6% deviation from the expected value was observed. For all clinical protocol settings, image noise was compatible with clinical interpretation (COV?<?15%). Digital PET showed an improved background signal-to-noise ratio as compared to conventional PMT-based PET. RCs were comparable between digital and PMT-based PET datasets. Compared to PMT-based PET, digital systems provided comparable image quality with lower TAP (from ~?40% less and up to 70% less).ConclusionsThis study compared the achievable clinical image quality in three state-of-the-art digital PET/CT devices (from different vendors) as well as in two conventional PMT-based PET. Reported results show that a comparable image quality is achievable with a TAP reduction of ~?40% in digital PET. This could lead to a significant reduction of the administered mass-activity and/or scan time with direct benefits in terms of dose exposure and patient comfort.
| S-EPMC6944719 | biostudies-literature
Project description:INTRODUCTION:The aim of this analysis was to investigate whether the standardized uptake value (SUV) normalized by lean body mass (SUL) is a more appropriate quantitative parameter compared to the commonly used SUV normalized by patient's weight in 68Ga-PSMA11 PET/CT. MATERIAL AND METHODS:68Ga-PSMA11 PET/CT scans of 121 patients with prostate cancer from two institutions were evaluated. Liver SUV was measured within a 3-cm volume-of-interest (VOI) in the right hepatic lobe and corrected for lean body mass using the Janmahasatian formula. SUV and SUL repeatability between baseline and follow-up scans of the same patients were assessed. RESULTS:SUV was significantly positively correlated with body weight (r = 0.35, p = 0.02). In contrast, SUL was not correlated with body weight (r = 0.23, p = 0.07). No significant differences were found between baseline and follow-up scan (p = 0.52). CONCLUSION:The Janmahasatian formula annuls the positive correlations between SUV and body weight, suggesting that SUL is preferable to SUV for quantitative analyses of 68Ga-PSMA11 PET/CT scans.
| S-EPMC6889088 | biostudies-literature
Project description:PurposeThe standardized uptake value (SUV) is widely used for quantitative evaluation in oncological FDG-PET but has well-known shortcomings as a measure of the tumor's glucose consumption. The standard uptake ratio (SUR) of tumor SUV and arterial blood SUV (BSUV) possesses an increased prognostic value but requires image-based BSUV determination, typically in the aortic lumen. However, accurate manual ROI delineation requires care and imposes an additional workload, which makes the SUR approach less attractive for clinical routine. The goal of the present work was the development of a fully automated method for BSUV determination in whole-body PET/CT.MethodsAutomatic delineation of the aortic lumen was performed with a convolutional neural network (CNN), using the U-Net architecture. A total of 946 FDG PET/CT scans from several sites were used for network training (N = 366) and testing (N = 580). For all scans, the aortic lumen was manually delineated, avoiding areas affected by motion-induced attenuation artifacts or potential spillover from adjacent FDG-avid regions. Performance of the network was assessed using the fractional deviations of automatically and manually derived BSUVs in the test data.ResultsThe trained U-Net yields BSUVs in close agreement with those obtained from manual delineation. Comparison of manually and automatically derived BSUVs shows excellent concordance: the mean relative BSUV difference was (mean ± SD) = (- 0.5 ± 2.2)% with a 95% confidence interval of [- 5.1,3.8]% and a total range of [- 10.0, 12.0]%. For four test cases, the derived ROIs were unusable (< 1 ml).ConclusionCNNs are capable of performing robust automatic image-based BSUV determination. Integrating automatic BSUV derivation into PET data processing workflows will significantly facilitate SUR computation without increasing the workload in the clinical setting.
| S-EPMC8041711 | biostudies-literature