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Abstract 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.

Abstract Background The clinical validation of the EARL harmonization program for standardised uptake value (SUV) metrics is well documented; however, its potential for defining metabolic active tumour volume (MATV) has not yet been investigated. We aimed to compare delineation of MATV on images reconstructed using conventional ordered subset expectation maximisation (OSEM) with those reconstructed using point spread function modelling (PSF-reconstructed images), and either optimised for diagnostic potential (PSF) or filtered to meet the EANM/EARL harmonising standards (PSF7). Methods Images from 18 stage IIIA-IIIB lung cancer patients were reconstructed using all the three methods. MATVs were then delineated using both a 40% isocontour and a gradient-based method. MATVs were compared by means of Bland–Altman analyses, and Dice coefficients and concordance indices based on the unions and intersections between each pair of reconstructions (PSF vs OSEM, PSF7 vs PSF and PSF7 vs OSEM). Results Using the 40% isocontour method and taking the MATVs delineated on OSEM images as a reference standard, the use of PSF7 images led to significantly higher Dice coefficients (median value = 0.96 vs 0.77; P

Background: Radiomics analysis usually involves, especially in multicenter and large hospital studies, different imaging protocols for acquisition, reconstruction, and processing of data. Differences in protocols can lead to differences in the quantification of the biomarker distribution, leading to radiomic feature variability. The aim of our study was to identify those radiomic features robust to the different degrading factors in positron emission tomography (PET) studies. We proposed the use of the standardized measurements of the European Association Research Ltd. (EARL) accreditation to retrospectively identify the radiomic features having low variability to the different systems and reconstruction protocols. In addition, we presented a reproducible procedure to identify PET radiomic features robust to PET/CT imaging metal artifacts. In 27 heterogeneous homemade phantoms for which ground truth was accurately defined by CT segmentation, we evaluated the segmentation accuracy and radiomic feature reliability given by the contrast-oriented algorithm (COA) and the 40% threshold PET segmentation. In the comparison of two data sets, robustness was defined by Wilcoxon rank tests, bias was quantified by Bland–Altman (BA) plot analysis, and strong correlations were identified by Spearman correlation test (r > 0.8 and p satisfied multiple test Bonferroni correction). Results: Forty-eight radiomic features were robust to system, 22 to resolution, 102 to metal artifacts, and 42 to different PET segmentation tools. Overall, only 4 radiomic features were simultaneously robust to all degrading factors. Although both segmentation approaches significantly underestimated the volume with respect to the ground truth, with relative deviations of −62 ± 36% for COA and −50 ± 44% for 40%, radiomic features derived from the ground truth were strongly correlated and/or robust to 98 radiomic features derived from COA and to 102 from 40%. Conclusion: In multicenter studies, we recommend the analysis of EARL accreditation measurements in order to retrospectively identify the robust PET radiomic features. Furthermore, 4 radiomic features (area under the curve of the cumulative SUV volume histogram, skewness, kurtosis, and gray-level variance derived from GLRLM after application of an equal probability quantization algorithm on the voxels within lesion) were robust to all degrading factors. In addition, the feasibility of 40% and COA segmentations for their use in radiomics analysis has been demonstrated. [ABSTRACT FROM AUTHOR]

Background: Machine learning studies require a large number of images often obtained on different PET scanners. When merging these images, the use of harmonized images following EARL-standards is essential. However, when including retrospective images, EARL accreditation might not have been in place. The aim of this study was to develop a convolutional neural network (CNN) that can identify retrospectively if an image is EARL compliant and if it is meeting older or newer EARL-standards. Materials and methods: 96 PET images acquired on three PET/CT systems were included in the study. All images were reconstructed with the locally clinically preferred, EARL1, and EARL2 compliant reconstruction protocols. After image pre-processing, one CNN was trained to separate clinical and EARL compliant reconstructions. A second CNN was optimized to identify EARL1 and EARL2 compliant images. The accuracy of both CNNs was assessed using fivefold cross-validation. The CNNs were validated on 24 images acquired on a PET scanner not included in the training data. To assess the impact of image noise on the CNN decision, the 24 images were reconstructed with different scan durations. Results: In the cross-validation, the first CNN classified all images correctly. When identifying EARL1 and EARL2 compliant images, the second CNN identified 100% EARL1 compliant and 85% EARL2 compliant images correctly. The accuracy in the independent dataset was comparable to the cross-validation accuracy. The scan duration had almost no impact on the results. Conclusion: The two CNNs trained in this study can be used to retrospectively include images in a multi-center setting by, e.g., adding additional smoothing. This method is especially important for machine learning studies where the harmonization of images from different PET systems is essential. [ABSTRACT FROM AUTHOR]

Background: Although most guidelines suggest performing a positron emission tomography/computed tomography (PET/CT) with somatostatin receptor (SSTR) ligands for staging of pulmonary carcinoid tumours (PC), only a limited number of studies have evaluated the role of this imaging tool in this specific patient population. The preoperative differentiation between typical carcinoid (TC) and atypical carcinoid (AC) and the extent of dissemination (N/M status) are crucial factors for treatment allocation and prognosis of these patients. Therefore, we performed a pathology-based retrospective analysis of the value of SSTR PET/CT in tumour grading and detection of nodal and metastatic involvement of PC and compared this with the previous literature and with [18F]FDG PET/CT in a subgroup of patients. Methods: SSTR PET/CT scans performed between January 2007 and May 2020 in the context of PC were included. If available, [18F]FDG PET/CT images were also evaluated. The maximum standardized uptake (SUVmax) values of the primary tumour, of the pathologically examined hilar and mediastinal lymph node stations, as well as of the distant metastases, were recorded. Tumoural SUVmax values were related to the tumour type (TC versus AC) for both SSTR and [18F]FDG PET/CT in diagnosing and differentiating both tumour types. Nodal SUVmax values were compared to the pathological status (N+ versus N−) to evaluate the diagnostic accuracy of SSTR PET/CT in detecting lymph node involvement. Finally, a mixed model analysis of all pathologically proven distant metastatic lesions was performed. Results: A total of 86 SSTR PET/CT scans performed in 86 patients with PC were retrospectively analysed. [18F]FDG PET/CT was available in 46 patients. Analysis of the SUVmax values in the primary tumour showed significantly higher SSTR uptake in TC compared with AC (median SUVmax 18.4 vs 3.8; p = 0.003) and significantly higher [18F]FDG uptake in AC compared to TC (median SUVmax 5.4 vs 3.5; p = 0.038). Receiver operating characteristic (ROC) curve analysis resulted in an area under the curve (AUC) of 0.78 for the detection of TC on SSTR PET/CT and of 0.73 for the detection of AC on [18F]FDG PET/CT. A total of 267 pathologically evaluated hilar and mediastinal lymph node stations were analysed. ROC analysis of paired SSTR/[18F]FDG SUVmax values for the detection of metastasis of TC in 83 lymph node stations revealed an AUC of 0.91 for SSTR PET/CT and of 0.74 for [18F]FDG PET/CT (difference 0.17; 95% confidence interval − 0.03 to 0.38; p = 0.10). In a sub-cohort of 10 patients with 12 distant lesions that were pathologically examined due to a suspicious aspect on SSTR PET/CT, a positive predictive value (PPV) of 100% was observed. Conclusion: Our findings confirm the higher SSTR ligand uptake in TC compared to AC and vice versa for [18F]FDG uptake. More importantly, we found a good diagnostic performance of SSTR PET/CT for the detection of hilar and mediastinal lymph node metastases of TC. Finally, a PPV of 100% for SSTR PET/CT was found in a small sub-cohort of patients with pathologically investigated distant metastatic lesions. Taken together, SSTR PET/CT has a very high diagnostic value in the TNM assessment of pulmonary carcinoids, particularly in TC, which underscores its position in European guidelines. [ABSTRACT FROM AUTHOR]

In DLBCL, the Deauville scoring system (DS) is the standard for PET/CT response assessment. An alternative system, based on the semi-quantitative change in standardized uptake values, namely ΔSUVmax, has been reported to be more objective than the DS. We aimed to compare ΔSUVmax and DS for risk stratification of DLBCL patients on end-of-treatment (EoT) PET. 108 consecutive patients were included. 2-year EFS Kaplan–Meier survival analyses and Cox regression models were performed. 2-year EFS was significantly different between favorable ΔSUVmax (favΔ < −86.5%) and unfavorable ΔSUVmax (unfavΔ ≥ −86.5%) patients: 100.0% ± 0.0 versus 58.3% ± 14.2 (p = 0.001). On Cox multivariable regression, ΔSUVmax status was the only independent predictor of 2-year EFS, outperforming DS. Therefore, ΔSUVmax should be computed for non-responder patients, especially DS4, as the 2-year EFS is not different between responders and non-responders in the case of favΔ. Further studies are needed in order to confirm this hypothesis. [ABSTRACT FROM AUTHOR]

Metastatic tumor deposits in bone marrow elicit differential bone responses that vary with the type of malignancy. This results in either sclerotic, lytic, or mixed bone lesions, which can change in morphology due to treatment effects and/or secondary bone remodeling. Hence, morphological imaging is regarded unsuitable for response assessment of bone metastases and in the current Response Evaluation Criteria In Solid Tumors 1.1 (RECIST1.1) guideline bone metastases are deemed unmeasurable. Nevertheless, the advent of functional and molecular imaging modalities such as whole-body magnetic resonance imaging (WB-MRI) and positron emission tomography (PET) has improved the ability for follow-up of bone metastases, regardless of their morphology. Both these modalities not only have improved sensitivity for visual detection of bone lesions, but also allow for objective measurements of bone lesion characteristics. WB-MRI provides a global assessment of skeletal metastases and for a one-step "all-organ" approach of metastatic disease. Novel MRI techniques include diffusion-weighted imaging (DWI) targeting highly cellular lesions, dynamic contrast-enhanced MRI (DCE-MRI) for quantitative assessment of bone lesion vascularization, and multiparametric MRI (mpMRI) combining anatomical and functional sequences. Recommendations for a homogenization of MRI image acquisitions and generalizable response criteria have been developed. For PET, many metabolic and molecular radiotracers are available, some targeting tumor characteristics not confined to cancer type (e.g. 18F-FDG) while other targeted radiotracers target specific molecular characteristics, such as prostate specific membrane antigen (PSMA) ligands for prostate cancer. Supporting data on quantitative PET analysis regarding repeatability, reproducibility, and harmonization of PET/CT system performance is available. Bone metastases detected on PET and MRI can be quantitatively assessed using validated methodologies, both on a whole-body and individual lesion basis. Both have the advantage of covering not only bone lesions but visceral and nodal lesions as well. Hybrid imaging, combining PET with MRI, may provide complementary parameters on the morphologic, functional, metabolic and molecular level of bone metastases in one examination. For clinical implementation of measuring bone metastases in response assessment using WB-MRI and PET, current RECIST1.1 guidelines need to be adapted. This review summarizes available data and insights into imaging of bone metastases using MRI and PET. [ABSTRACT FROM AUTHOR]

Background: Delineation of PSMA-positive tumor volume on PET using PSMA-ligands is of highest clinical interest as changes of PSMA-PET/CT-derived whole tumor volume (WTV) have shown to correlate with treatment response in metastatic prostate cancer patients. So far, WTV estimation was performed on PET using 68Ga-labeled ligands; nonetheless, 18F-labeled PET ligands are gaining increasing importance due to advantages over 68Ga-labeled compounds. However, standardized tumor delineation methods for 18F-labeled PET ligands have not been established so far. As correlation of PET-based information and morphological extent in osseous and visceral metastases is hampered by morphological delineation, low contrast in liver tissue and movement artefacts, we correlated CT-based volume of lymph node metastases (LNM) and different PET-based delineation approaches for thresholding on 18F-PSMA-1007 PET. Methods: Fifty patients with metastatic prostate cancer, 18F-PSMA-1007 PET/CT and non-bulky LNM (short-axis diameter ≥10mm) were included. Fifty LNM were volumetrically assessed on contrast-enhanced CT (volumetric reference standard). Different approaches for tumor volume delineation were applied and correlated with the reference standard: I) fixed SUV threshold, II) isocontour thresholding relative to SUVmax (SUV%), and thresholds relative to III) liver (SUVliver), IV) parotis (SUVparotis) and V) spleen (SUVspleen). Results: A fixed SUV of 4.0 (r=0.807, r2 = 0.651, p<0.001) showed the best overall association with the volumetric reference. 55% SUVmax (r=0.627, r2 = 0.393, p<0.001) showed highest association using an isocontour-based threshold. Best background-based approaches were 60% SUVliver (r=0.715, r2 = 0.511, p<0.001), 80% SUVparotis (r=0.762, r2 = 0.581, p<0.001) and 60% SUVspleen (r=0.645, r2 = 0.416, p<0.001). Background tissues SUVliver, SUVparotis & SUVspleen did not correlate (p>0.05 each). Recently reported cut-offs for intraprostatic tumor delineation (isocontour 44% SUVmax, 42% SUVmax and 20% SUVmax) revealed inferior association for LNM delineation. Conclusions: A threshold of SUV 4.0 for tumor delineation showed highest association with volumetric reference standard irrespective of potential changes in PSMA-avidity of background tissues (e. g. parotis). This approach is easily applicable in clinical routine without specific software requirements. Further studies applying this approach for total tumor volume delineation are initiated. [ABSTRACT FROM AUTHOR]

Background: Anal cancer is a relatively rare tumor of which incidence increases in developed countries. 18F-FDG PET has been increasingly used for its post radio-chemotherapy evaluation. However, several authors have reported the risk of local false-positive findings leading to low specificity and positive predictive values. These false-positive results could be due to post-radiotherapy inflammation or infection but certainly also to physiological anal canal uptake that is observed on a regular basis in clinical practice. The purpose of this prospective study (NCT03506529; HYPHYCA) was therefore to seek predictive factors of physiological anal canal hypermetabolism. Materials and methods: Over a 2-month period, patients aged 18 years old and more, referred for 18F-FDG PET-CT at two EARL-accredited PET centers were included, after obtaining their informed and written consent. They were asked to fill in a questionnaire including seven closed questions about usual intestinal transit, ongoing medications relative to intestinal transit, history of digestive, and anal and/or pelvic diseases. Age, gender, and body mass index (BMI) were recorded. A single nuclear medicine physician visually and quantitatively analyzed anal canal uptake (SUVmax_EARL) and assessed visual rectal content (air, feces, or both) and the largest rectal diameter (mm). Results: Six hundred and thirteen patients were included (sex ratio F/M = 0.99) and 545 (89%) questionnaires were entirely completed. Significantly more males presented anal canal hypermetabolism (sex ratio (M/F) = 1.18 versus 0.85, p = 0.048). Moreover, patients with anal canal hypermetabolism had higher BMI (27.6 (5.7) kg/m2 versus 23.9 (4.5) kg/m2, p < 0.0001), higher rate of hemorrhoid history (43% versus 27%, p = 0.016), and higher rate of rectum filled with only feces (21% versus 12%, p = 0.019) as compared to patients with no anal canal uptake. On logistic regression, all these variables were found to be independent predictors of the occurrence of an anal canal hypermetabolism. Odds ratio were 1.16 (1.12–1.20) per unit of BMI (kg/m2) (p < 0.0001), 1.48 (1.04–2.11) for males (p = 0.030), 1.64 (1.10–2.45) for hemorrhoids history (p = 0.016), and 1.94 (1.147–3.22) for the rectum filled with only feces (p = 0.010). Conclusion: According to our study, the predictive factors of physiological anal canal hypermetabolism are high BMI, male gender, hemorrhoid history, and rectum filled with only feces. This may pave the way to a more specific interpretation of post radio-chemotherapy PET evaluations of anal canal cancer, provided that other studies are conducted in this specific population. Trial registration: This prospective study was registered at Clinicaltrial.gov: NCT03506529; HYPHYCA on April 24, 2018 [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: Tumor response evaluated by 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) with standardized uptake value (SUV) is questionable when pre- and post-treatment PET/CT are acquired on different scanners. The aims of our study, performed in oncological patients who underwent pre- and post-treatment [18F]FDG PET/CT on different scanners, were (1) to evaluate whether EQ·PET, a proprietary SUV inter-exams harmonization tool, modifies the EORTC tumor response classification and (2) to assess which classification (harmonized and non-harmonized) better predicts clinical outcome.Procedures: We retrospectively identified 95 PET pairs (pre- and post-treatment) performed on different scanners (Biograph mCT, Siemens; GEMINI GXL, Philips) in 73 oncological patients (52F; 57.8 ± 16.3 years). An 8-mm Gaussian filter was applied for the Biograph protocol to meet the EANM/EARL harmonization standard; no filter was needed for GXL. SUVmax and SUVmaxEQ of the same target lesion in the pre- and post-treatment PET/CT were noted. For each PET pair, the metabolic response classification (responder/non-responder), derived from combining the EORTC response categories, was evaluated twice (with and without harmonization). In discordant cases, the association of each metabolic response classification with final clinical response assessment and survival data (2-year disease-free survival, DFS) was assessed.Results: On Biograph, SUVmaxEQ of all target lesions was significantly lower (p = 0.001) than SUVmax (8.5 ± 6.8 vs 12.5 ± 9.6; - 38.6 %). A discordance between the two metabolic response classifications (harmonized and non-harmonized) was found in 19/95 (20 %) PET pairs. In this subgroup (n = 19; mean follow-up, 33.9 ± 9 months), responders according to harmonized classification (n = 9) had longer DFS (47.5 months, 88.9 %) than responders (n = 10) according to non-harmonized classification (26.3 months, 50.0 %; p = 0.01). Moreover, harmonized classification showed a better association with final clinical response assessment (17/19 PET pairs).Conclusions: The harmonized metabolic response classification is more associated with the final clinical response assessment, and it is able to better predict the DFS than the non-harmonized classification. EQ·PET is a useful harmonization tool for evaluating metabolic tumor response using different PET/CT scanners, also in different departments or for multicenter studies. [ABSTRACT FROM AUTHOR]

Aim: Our aim was (1) to evaluate the prevalence of steatosis in lymphoma patients and its evolution during treatment; (2) to evaluate the impact of hepatic steatosis on 18F-FDG liver uptake; and (3) to study how hepatic steatosis affects the Deauville score (DS) for discriminating between responders and non-responders.Methods: Over a 1-year period, 358 PET scans from 227 patients [122 diffuse large B cell lymphoma (DLBCL), 57 Hodgkin lymphoma (HL) and 48 Follicular lymphoma (FL)] referred for baseline (n = 143), interim (n = 79) and end-of-treatment (EoT, n = 136) PET scans were reviewed. Steatosis was diagnosed on the unenhanced CT part of PET/CT examinations using a cut-off value of 42 Hounsfield units (HU). EARL-compliant SULmax were recorded on the liver and the tumour target lesion. DS were then computed.Results: Prevalence of steatosis at baseline, interim and EoT PET was 15/143 (10.5%), 6/79 (7.6%) and 16/136 (11.8%), respectively (p = 0.62).Ten out of 27 steatotic patients (37.0%) displayed a steatotic liver on all examinations. Six patients (22.2%) had a disappearance of hepatic steatosis during their time-course of treatment. Only one patient developed steatosis during his course of treatment. Liver SULmax values were significantly lower in the steatosis versus non-steatotic groups of patients for interim (1.66 ± 0.36 versus 2.15 ± 0.27) and EoT (1.67 ± 0.29 versus 2.17 ± 0.30) PET. CT density was found to be an independent factor that correlated with liver SULmax, while BMI, blood glucose level and the type of chemotherapy regimen were not. Using a method based on this correlation to correct liver SULmax, all DS4 steatotic patients on interim (n = 1) and EoT (n = 2) PET moved to DS3.Conclusions: Steatosis is actually a theoretical but not practical issue in most patients but should be recognised and corrected in appropriate cases, namely, for those patients scored DS4 with a percentage difference between the target lesion and the liver background lower than 30%. [ABSTRACT FROM AUTHOR]

Background: This study evaluates the consistency of PET evaluation response criteria in solid tumours (PERCIST) and European Organisation for Research and Treatment of Cancer (EORTC) classification across different reconstruction algorithms and whether aligning standardized uptake values (SUVs) to the European Association of Nuclear Medicine acquisition (EANM)/EARL standards provides more consistent response classification. Materials and methods: Baseline () and response assessment () scans in 61 patients with non-small cell lung cancer were acquired in protocols compliant with the EANM guidelines and were reconstructed with point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction for optimal tumour detection and with a standardized ordered subset expectation maximization (OSEM) reconstruction known to fulfil EANM harmonizing standards. Patients were recruited in three centres. Following reconstruction, EQ.PET, a proprietary software solution was applied to the PSF ± TOF data (PSF ± TOF.EQ) to harmonize SUVs to the EANM standards. The impact of differing reconstructions on PERCIST and EORTC classification was evaluated using standardized uptake values corrected for lean body mass (SUL). Results: Using OSEM/OSEM (standard scenario), responders displayed a reduction of −57.5% ± 23.4 and −63.9% ± 22.4 for SUL and SUL, respectively, while progressing tumours had an increase of +63.4% ± 26.5 and +60.7% ± 19.6 for SUL and SUL respectively. The use of PSF ± TOF reconstruction impacted the classification of tumour response. For example, taking the OSEM/PSF ± TOF scenario reduced the apparent reduction in SUL in responding tumours (−39.7% ± 31.3 and −55.5% ± 26.3 for SUL and SUL, respectively) but increased the apparent increase in SUL in progressing tumours (+130.0% ± 50.7 and +91.1% ± 39.6 for SUL and SUL, respectively). Consequently, variation in reconstruction methodology (PSF ± TOF/OSEM or OSEM /PSF ± TOF) led, respectively, to 11/61 (18.0%) and 10/61 (16.4%) PERCIST classification discordances and to 17/61 (28.9%) and 19/61 (31.1%) EORTC classification discordances. An agreement was better for these scenarios with application of the propriety filter, with kappa values of 1.00 and 0.95 compared to 0.75 and 0.77 for PERCIST and kappa values of 0.93 and 0.95 compared to 0.61 and 0.55 for EORTC, respectively. Conclusion: PERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either. [ABSTRACT FROM AUTHOR]

Background: The clinical validation of the EARL harmonization program for standardised uptake value (SUV) metrics is well documented; however, its potential for defining metabolic active tumour volume (MATV) has not yet been investigated. We aimed to compare delineation of MATV on images reconstructed using conventional ordered subset expectation maximisation (OSEM) with those reconstructed using point spread function modelling (PSF-reconstructed images), and either optimised for diagnostic potential (PSF) or filtered to meet the EANM/EARL harmonising standards (PSF). Methods: Images from 18 stage IIIA-IIIB lung cancer patients were reconstructed using all the three methods. MATVs were then delineated using both a 40% isocontour and a gradient-based method. MATVs were compared by means of Bland-Altman analyses, and Dice coefficients and concordance indices based on the unions and intersections between each pair of reconstructions (PSF vs OSEM, PSF vs PSF and PSF vs OSEM). Results: Using the 40% isocontour method and taking the MATVs delineated on OSEM images as a reference standard, the use of PSF images led to significantly higher Dice coefficients (median value = 0.96 vs 0.77; P < 0.0001) and concordance indices (median value = 0.92 vs 0.64; P < 0.0001) than those obtained using PSF images. The gradient-based methodology was less sensitive to reconstruction variability than the 40% isocontour method; Dice coefficients and concordance indices were superior to 0.8 for both PSF reconstruction methods. However, the use of PSF images led to narrower interquartile ranges and significantly higher Dice coefficients (median value = 0.96 vs 0.94; P = 0.01) and concordance indices (median value = 0.89 vs 0.85; P = 0.003) than those obtained with PSF images. Conclusion: This study demonstrates that automatic contouring of lung tumours on EARL-compliant PSF images using the widely adopted automatic isocontour methodology is an accurate means of overcoming reconstruction variability in MATV delineation. Although gradient-based methodology appears to be less sensitive to reconstruction variability, the use of EARL-compliant PSF images significantly improved the Dice coefficients and concordance indices, demonstrating the importance of harmonised-images, even when more advanced contouring algorithms are used. [ABSTRACT FROM AUTHOR]

Purpose: [F]UCB-H is a novel radiotracer with a high affinity for synaptic vesicle glycoprotein 2A (SV2A), a protein expressed in synaptic vesicles. SV2A is the binding site of levetiracetam, a 'first-in-class' antiepileptic drug with a distinct but still poorly understood mechanism of action. The objective of this study was to determine the biodistribution and radiation dosimetry of [F]UCB-H in a human clinical trial and to establish injection limits according to biomedical research guidelines. Additionally, the clinical radiation dosimetry results were compared to estimations in previously published preclinical data. Procedures: Dynamic whole body positron emission tomography/X-ray computed tomography (PET/CT) imaging was performed over approximately 110 min on five healthy male volunteers after injection of 144.5 ± 7.1 MBq (range, 139.1-156.5 MBq) of [F]UCB-H. Major organs were delineated on CT images, and time-activity curves were obtained from co-registered dynamic PET emission scans. The bladder could only be delineated on PET images. Time-integrated activity coefficients were calculated as area under the curve using trapezoidal numerical integration. Urinary excretion data based on PET activities including voiding was also simulated using the dynamic bladder module of OLINDA/EXM. The radiation dosimetry was calculated using OLINDA/EXM. Results: The effective dose to the OLINDA/EXM 70-kg standard male was 1.54 × 10 ± 6.84 × 10 millisieverts (mSv)/MBq, with urinary bladder wall, gallbladder wall, and the liver receiving the highest absorbed dose. The brain, the tracer's main organ of interest, received an absorbed dose of 1.89 × 10 ± 2.32 × 10 mGy/MBq. Conclusions: This first human dosimetry study of [F]UCB-H indicated that the tracer shows similar radiation burdens to widely used common clinical tracers. Single injections of at maximum 672 MBq for US practice and 649 MBq for European practice keep radiation exposure below recommended limits. Recently published preclinical dosimetry data extrapolated from mice provided satisfactory prediction of total body and effective dose but showed significant differences in organ absorbed doses compared to human data. [ABSTRACT FROM AUTHOR]