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Background: [18F]FDG PET denoising by SubtlePET™ using deep learning artificial intelligence (AI) was previously found to induce slight modifications in lesion and reference organs' quantification and in lesion detection. As a next step, we aimed to evaluate its clinical impact on [18F]FDG PET solid tumour treatment response assessments, while comparing "standard PET" to "AI denoised half-duration PET" ("AI PET") during follow-up. Results: 110 patients referred for baseline and follow-up standard digital [18F]FDG PET/CT were prospectively included. "Standard" EORTC and, if applicable, PERCIST response classifications by 2 readers between baseline standard PET1 and follow-up standard PET2 as a "gold standard" were compared to "mixed" classifications between standard PET1 and AI PET2 (group 1; n = 64), or between AI PET1 and standard PET2 (group 2; n = 46). Separate classifications were established using either standardized uptake values from ultra-high definition PET with or without AI denoising (simplified to "UHD") or EANM research limited v2 (EARL2)-compliant values (by Gaussian filtering in standard PET and using the same filter in AI PET). Overall, pooling both study groups, in 11/110 (10%) patients at least one EORTCUHD or EARL2 or PERCISTUHD or EARL2 mixed vs. standard classification was discordant, with 369/397 (93%) concordant classifications, unweighted Cohen's kappa = 0.86 (95% CI: 0.78–0.94). These modified mixed vs. standard classifications could have impacted management in 2% of patients. Conclusions: Although comparing similar PET images is preferable for therapy response assessment, the comparison between a standard [18F]FDG PET and an AI denoised half-duration PET is feasible and seems clinically satisfactory. [ABSTRACT FROM AUTHOR]

Background: Small-animal PET imaging is an important tool in preclinical oncology. This study evaluated the ability of a clinical SiPM-PET camera to image several rats simultaneously and to perform quantification data analysis. Methods: Intrinsic spatial resolution was measured using 18F line sources, and image quality was assessed using a NEMA NU 4-2018 phantom. Quantification was evaluated using a fillable micro-hollow sphere phantom containing 4 spheres of different sizes (ranging from 3.95 to 7.86 mm). Recovery coefficients were computed for the maximum (Amax) and the mean (A50) pixel values measured on a 50% isocontour drawn on each sphere. Measurements were performed first with the phantom placed in the centre of the field of view and then in the off-centre position with the presence of three scattering sources to simulate the acquisition of four animals simultaneously. Quantification accuracy was finally validated using four 3D-printed phantoms mimicking rats with four subcutaneous tumours each. All experiments were performed for both 18F and 68Ga radionuclides. Results: Radial spatial resolutions measured using the PSF reconstruction algorithm were 1.80 mm and 1.78 mm for centred and off-centred acquisitions, respectively. Spill-overs in air and water and uniformity computed with the NEMA phantom centred in the FOV were 0.05, 0.1 and 5.55% for 18F and 0.08, 0.12 and 2.81% for 68Ga, respectively. Recovery coefficients calculated with the 18F-filled micro-hollow sphere phantom for each sphere varied from 0.51 to 1.43 for Amax and from 0.40 to 1.01 for A50. These values decreased from 0.28 to 0.92 for Amax and from 0.22 to 0.66 for A50 for 68 Ga acquisition. The results were not significantly different when imaging phantoms in the off-centre position with 3 scattering sources. Measurements performed with the four 3D-printed phantoms showed a good correlation between theoretical and measured activity in simulated tumours, with r2 values of 0.99 and 0.97 obtained for 18F and 68Ga, respectively. Conclusion: We found that the clinical SiPM-based PET system was close to that obtained with a dedicated small-animal PET device. This study showed the ability of such a system to image four rats simultaneously and to perform quantification analysis for radionuclides commonly used in oncology. [ABSTRACT FROM AUTHOR]

Given the constant pressure to increase patient throughput while respecting radiation protection, global body PET image quality (IQ) is not satisfactory in all patients. We first studied the association between IQ and other variables, in particular body habitus, on a digital PET/CT. Second, to improve and homogenize IQ, we evaluated a deep learning PET denoising solution (Subtle PETTM) using convolutional neural networks. We analysed retrospectively in 113 patients visual IQ (by a 5-point Likert score in two readers) and semi-quantitative IQ (by the coefficient of variation in the liver, CVliv) as well as lesion detection and quantification in native and denoised PET. In native PET, visual and semi-quantitative IQ were lower in patients with larger body habitus (p < 0.0001 for both) and in men vs. women (p ≤ 0.03 for CVliv). After PET denoising, visual IQ scores increased and became more homogeneous between patients (4.8 ± 0.3 in denoised vs. 3.6 ± 0.6 in native PET; p < 0.0001). CVliv were lower in denoised PET than in native PET, 6.9 ± 0.9% vs. 12.2 ± 1.6%; p < 0.0001. The slope calculated by linear regression of CVliv according to weight was significantly lower in denoised than in native PET (p = 0.0002), demonstrating more uniform CVliv. Lesion concordance rate between both PET series was 369/371 (99.5%), with two lesions exclusively detected in native PET. SUVmax and SUVpeak of up to the five most intense native PET lesions per patient were lower in denoised PET (p < 0.001), with an average relative bias of −7.7% and −2.8%, respectively. DL-based PET denoising by Subtle PETTM allowed [18F]FDG PET global image quality to be improved and homogenized, while maintaining satisfactory lesion detection and quantification. DL-based denoising may render body habitus adaptive PET protocols unnecessary, and pave the way for the improvement and homogenization of PET modalities. [ABSTRACT FROM AUTHOR]

This study aimed to investigate if combining clinical characteristics with pre-therapeutic 18 F-fluorodeoxyglucose (18 F-FDG) positron emission tomography (PET) radiomics could predict the presence of molecular alteration(s) in key molecular targets in lung adenocarcinoma. This non-interventional monocentric study included patients with newly diagnosed lung adenocarcinoma referred for baseline PET who had tumour molecular analyses. The data were randomly split into training and test datasets. LASSO regression with 100-fold cross-validation was performed, including sex, age, smoking history, AJCC cancer stage and 31 PET variables. In total, 109 patients were analysed, and it was found that 63 (57.8%) patients had at least one molecular alteration. Using the training dataset (n = 87), the model included 10 variables, namely age, sex, smoking history, AJCC stage, excessKustosis_HISTO, sphericity_SHAPE, variance_GLCM, correlation_GLCM, LZE_GLZLM, and GLNU_GLZLM. The ROC analysis for molecular alteration prediction using this model found an AUC equal to 0.866 (p < 0.0001). A cut-off value set to 0.48 led to a sensitivity of 90.6% and a positive likelihood ratio (LR+) value equal to 2.4. After application of this cut-off value in the unseen test dataset of patients (n = 22), the test presented a sensitivity equal to 90.0% and an LR+ value of 1.35. A clinico-metabolic 18 F-FDG PET phenotype allows the detection of key molecular target alterations with high sensitivity and negative predictive value. Hence, it opens the way to the selection of patients for molecular analysis. [ABSTRACT FROM AUTHOR]

Purpose: We investigated whether artificial intelligence (AI)-based denoising halves PET acquisition time in digital PET/CT. Methods: One hundred ninety-five patients referred for [18F]FDG PET/CT were prospectively included. Body PET acquisitions were performed in list mode. Original "PET90" (90 s/bed position) was compared to reconstructed ½-duration PET (45 s/bed position) with and without AI-denoising, "PET45AI and PET45". Denoising was performed by SubtlePET™ using deep convolutional neural networks. Visual global image quality (IQ) 3-point scores and lesion detectability were evaluated. Lesion maximal and peak standardized uptake values using lean body mass (SULmax and SULpeak), metabolic volumes (MV), and liver SULmean were measured, including both standard and EARL1 (European Association of Nuclear Medicine Research Ltd) compliant SUL. Lesion-to-liver SUL ratios (LLR) and liver coefficients of variation (CVliv) were calculated. Results: PET45 showed mediocre IQ (scored poor in 8% and moderate in 68%) and lesion concordance rate with PET90 (88.7%). In PET45AI, IQ scores were similar to PET90 (P = 0.80), good in 92% and moderate in 8% for both. The lesion concordance rate between PET90 and PET45AI was 836/856 (97.7%), with 7 lesions (0.8%) only detected in PET90 and 13 (1.5%) exclusively in PET45AI. Lesion EARL1 SULpeak was not significantly different between both PET (P = 0.09). Lesion standard SULpeak, standard and EARL1 SULmax, LLR and CVliv were lower in PET45AI than in PET90 (P < 0.0001), while lesion MV and liver SULmean were higher (P < 0.0001). Good to excellent intraclass correlation coefficients (ICC) between PET90 and PET45AI were observed for lesion SUL and MV (ICC ≥ 0.97) and for liver SULmean (ICC ≥ 0.87). Conclusion: AI allows [18F]FDG PET duration in digital PET/CT to be halved, while restoring degraded ½-duration PET image quality. Future multicentric studies, including other PET radiopharmaceuticals, are warranted. [ABSTRACT FROM AUTHOR]

This article is part of the Topical Collection on Technology Introduction Thanks to companies' research and development processes, frequently involving fruitful partnerships with academic centres, and what could be acknowledged as welcome competition between PET vendors, new PET hardware and software technologies are regularly innovated and released as clinic-ready products. Advanced PET detectors Pushing the limit of detectability More recently, silicon photomultiplier (SiPM) technology has become available from the major PET vendors. Another important consideration is that PET technology is in constant development and rapidly evolving, the latest to date being SiPM PETs system and total-body PET. There were lesions only identified using the SiPM PET/CT showing that SiPM PET/CT has superior performance compared to a conventional PET/CT scanner [[41]]. Total-body PET Anybody involved in designing or analysing PET studies recognizes that limited detection sensitivity, and its consequence of image noise, is by far the biggest technical limitation in PET imaging, whether that be in clinical PET or in research studies. [Extracted from the article]

Background: The common endocrine disorder primary hyperparathyroidism (PHPT) can be cured by surgery. Preoperative localization of parathyroid adenoma (PTA) by imaging is a prerequisite for outpatient minimally invasive parathyroidectomy (MIP). Compared to inpatient bilateral cervical exploration (BCE) which is performed if imaging is inconclusive, MIP is superior in terms of cure and complication rates and less costly. The imaging procedure F18-choline (FCH) PET/CT outperforms Tc99m-sestaMIBI (MIBI) SPECT/CT for PTA localization, but it is much costlier. The aim of this study is to identify the most efficient first-line imaging modality for optimal patient care in PHPT without added cost to society. Methods: We will conduct a multicenter open diagnostic intervention randomized phase III trial comparing two diagnostic strategies in patients with PHPT: upfront FCH PET/CT versus MIBI SPECT/CT. The primary endpoint is the proportion of patients in whom the first-line imaging method results in successful MIP and cure. Follow-up including biological tests will be performed 1 and 6 months after surgery. The main secondary endpoint is the social cost of both strategies. Other secondary endpoints are as follows: FCH PET/CT and MIBI SPECT/CT diagnostic performance, performance of surgical procedure and complication rate, FCH PET/CT inter- and intra-observer variability and optimization of FCH PET/CT procedure. Fifty-eight patients will be enrolled and randomized 1:1. Discussion: FCH PET/CT is a highly efficient but expensive imaging test for preoperative PTA localization and costs three to four times more than MIBI SPECT/CT. Whether FCH PET/CT improves patient outcomes compared to the reference standard MIBI SPECT/CT is unknown. To justify its added cost, FCH PET/CT-guided parathyroid surgery should lead to improved patient management, resulting in higher cure rates and fewer BCEs and surgical complications. In the previous phase II APACH1 study, we showed that second-line FCH PET/CT led to a cure in 88% of patients with negative or inconclusive MIBI SPECT/CT. BCE could be avoided in 75% of patients and surgical complication rates were low. We therefore hypothesize that upfront FCH PET/CT would improve patient care in PHPT and that the reduction in clinical costs would offset the increase in imaging costs. Trial registration: NCT04040946, registered August 1, 2019. Protocol version Version 2.1 dated from 2020/04/23. [ABSTRACT FROM AUTHOR]

Objectives: To explore the prognostic value of positron emission tomography (PET) radiomic features in the field of diffuse large B cell lymphoma (DLBCL) treated with a first-line immunochemotherapy.Methods: One-hundred thirty-two patients newly diagnosed with DLBCL were retrospectively included. PET studies were reconstructed using an ordered subset expectation maximisation algorithm with point spread function modelling. The total metabolic tumour volume (MTV) was recorded for each patient, and the volume of interest structure of the largest target lesion was used to compute 18F-FDG textural parameters. Data was randomly split into training and validation datasets. Optimal cutoff values were determined by means of 2-year event-free survival (EFS) ROC analyses. Two-year EFS analyses were performed using Kaplan-Meier survival analyses and univariable and multivariable Cox regression models.Results: The median follow-up was 27 months, and the 2-year event-free survival (2y-EFS) was 77.3% in the entire population. ROC analyses for the 2y-EFS reached statistical significance for total MTV as well as four second-order metrics (homogeneity, contrast, correlation, dissimilarity) and five third-order metrics (LZE (Long-Zone Emphasis), LZLGE (Long-Zone Low-Grey Level Emphasis), LZHGE (Long-Zone High-Grey Level Emphasis), GLNU (Grey-Level Non-Uniformity) and ZP (Zone Percentage)). LZHGE displayed the highest ROC analysis accuracy (acc. = 0.76) and the best discriminant value on univariable Kaplan-Meier analysis (p < 0.0001, HR = 4.54). On multivariable analysis, including IPIaa, total MTV and LZHGE, LZHGE was the only independent predictor of 2y-EFS. These results were confirmed on the validation dataset.Conclusions: Baseline 18F-FDG PET heterogeneity of the largest lymphoma lesion is a promising predictor of 2y-EFS in newly diagnosed DLBCL treated with immunochemotherapy.Key Points: •18F-FDG metabolic heterogeneity emerges as a new tool for survival prognostication of patients and has been explored in many solid tumours with promising results. • Baseline18F-FDG PET heterogeneity of the largest lymphoma lesion is an independent predictor of 2y-EFS in newly diagnosed DLBCL treated with immunochemotherapy. • DLBCL patients presenting with a heterogeneous tumour displayed a worse prognosis. [ABSTRACT FROM AUTHOR]

Purpose Our purpose was to evaluate the diagnostic and prognostic value of skeletal textural features (TFs) on baseline FDG PET in diffuse large B cell lymphoma (DLBCL) patients. Methods Eighty-two patients with DLBCL who underwent a bone marrow biopsy (BMB) and a PET scan between December 2008 and December 2015 were included. Two readers blinded to the BMB results visually assessed PET images for bone marrow involvement (BMI) in consensus, and a third observer drew a volume of interest (VOI) encompassing the axial skeleton and the pelvis, which was used to assess skeletal TFs. ROC analysis was used to determine the best TF able to diagnose BMI among four first-order, six second-order and 11 third-order metrics, which was then compared for diagnosis and prognosis in disease-free patients (BMB--/PET-) versus patients considered to have BMI (BMB+/PET-, BMB--/PET+, and BMB+/PET+). Results Twenty-two out of 82 patients (26.8%) had BMI: 13 BMB--/PET+, eight BMB+/PET+ and one BMB+/PET-. Among the nine BMB+ patients, one had discordant BMI identified by both visual and TF PET assessment. ROC analysis showed that SkewnessH, a first-order metric, was the best parameter for identifying BMI with sensitivity and specificity of 81.8% and 81.7%, respectively. SkewnessH demonstrated better discriminative power over BMB and PET visual analysis for patient stratification: hazard ratios (HR), 3.78 (P = 0.02) versus 2.81 (P = 0.06) for overall survival (OS) and HR, 3.17 (P = 0.03) versus 1.26 (P = 0.70) for progression-free survival (PFS). In multivariate analysis accounting for IPI score, bulky status, haemoglobin and SkewnessH, the only independent predictor of OS was the IPI score, while the only independent predictor of PFS was SkewnessH. Conclusion The better discriminative power of skeletal heterogeneity for risk stratification compared to BMB and PET visual analysis in the overall population, and more specifically in BMB--/PET- patients, suggests that it can be useful to identify diagnostically overlooked BMI. [ABSTRACT FROM AUTHOR]

Quantitative positron emission tomography/computed tomography (PET/CT) can be used as diagnostic or prognostic tools (i.e. single measurement) or for therapy monitoring (i.e. longitudinal studies) in multicentre studies. Use of quantitative parameters, such as standardized uptake values (SUVs), metabolic active tumor volumes (MATVs) or total lesion glycolysis (TLG), in a multicenter setting requires that these parameters be comparable among patients and sites, regardless of the PET/CT system used. This review describes the motivations and the methodologies for quantitative PET/CT performance harmonization with emphasis on the EANM Research Ltd. (EARL) Fluorodeoxyglucose (FDG) PET/CT accreditation program, one of the international harmonization programs aiming at using FDG PET as a quantitative imaging biomarker. In addition, future accreditation initiatives will be discussed. The validation of the EARL accreditation program to harmonize SUVs and MATVs is described in a wide range of tumor types, with focus on therapy assessment using either the European Organization for Research and Treatment of Cancer (EORTC) criteria or PET Evaluation Response Criteria in Solid Tumors (PERCIST), as well as liver-based scales such as the Deauville score. Finally, also presented in this paper are the results from a survey across 51 EARL-accredited centers reporting how the program was implemented and its impact on daily routine and in clinical trials, harmonization of new metrics such as MATV and heterogeneity features. [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: Quantification of tumour heterogeneity in PET images has recently gained interest, but has been shown to be dependent on image reconstruction. This study aimed to evaluate the impact of the EANM/EARL accreditation program on selected F-FDG heterogeneity metrics. Methods: To carry out our study, we prospectively analysed 71 tumours in 60 biopsy-proven lung cancer patient acquisitions reconstructed with unfiltered point spread function (PSF) positron emission tomography (PET) images (optimised for diagnostic purposes), PSF-reconstructed images with a 7-mm Gaussian filter (PSF) chosen to meet European Association of Nuclear Medicine (EANM) 1.0 harmonising standards, and EANM Research Ltd. (EARL)-compliant ordered subset expectation maximisation (OSEM) images. Delineation was performed with fuzzy locally adaptive Bayesian (FLAB) algorithm on PSF images and reported on PSF and OSEM ones, and with a 50 % standardised uptake values (SUV) threshold (SUV) applied independently to each image. Robust and repeatable heterogeneity metrics including 1st-order [area under the curve of the cumulative histogram (CH)], 2nd-order (entropy, correlation, and dissimilarity), and 3rd-order [high-intensity larger area emphasis (HILAE) and zone percentage (ZP)] textural features (TF) were statistically compared. Results: Volumes obtained with SUV were significantly smaller than FLAB-derived ones, and were significantly smaller in PSF images compared to OSEM and PSF images. PSF-reconstructed images showed significantly higher SUVmax and SUVmean values, as well as heterogeneity for CH, dissimilarity, correlation, and HILAE, and a wider range of heterogeneity values than OSEM images for most of the metrics considered, especially when analysing larger tumours. Histological subtypes had no impact on TF distribution. No significant difference was observed between any of the considered metrics (SUV or heterogeneity features) that we extracted from OSEM and PSF reconstructions. Furthermore, the distributions of TF for OSEM and PSF reconstructions according to tumour volumes were similar for all ranges of volumes. Conclusion: PSF reconstruction with Gaussian filtering chosen to meet harmonising standards resulted in similar SUV values and heterogeneity information as compared to OSEM images, which validates its use within the harmonisation strategy context. However, unfiltered PSF-reconstructed images also showed higher heterogeneity according to some metrics, as well as a wider range of heterogeneity values than OSEM images for most of the metrics considered, especially when analysing larger tumours. This suggests that, whenever available, unfiltered PSF images should also be exploited to obtain the most discriminative quantitative heterogeneity features. [ABSTRACT FROM AUTHOR]

The authors comment on the combination of a high total metabolic tumor volume (TMTV) and gene expression profiling (GEP) for a risk stratification in diffuse large B cell lymphoma (DLBCL). They determine the role of GEP in the identification of multiple genetic abnormalities in DLBCL. They also discuss the use of multiple positron emission tomography (PET) metrics in the prognosis of patients with DLBCL.

Purpose: We compared conventional filtered back-projection (FBP), two-dimensional-ordered subsets expectation maximization (OSEM) and maximum a posteriori (MAP) NEMA NU 4-optimized reconstructions for therapy assessment. Procedures: Varying reconstruction settings were used to determine the parameters for optimal image quality with two NEMA NU 4 phantom acquisitions. Subsequently, data from two experiments in which nude rats bearing subcutaneous tumors had received a dual PI3K/mTOR inhibitor were reconstructed with the NEMA NU 4-optimized parameters. Mann-Whitney tests were used to compare mean standardized uptake value (SUV) variations among groups. Results: All NEMA NU 4-optimized reconstructions showed the same 2-deoxy-2-[F]fluoro- d-glucose ([F]FDG) kinetic patterns and detected a significant difference in SUV relative to day 0 between controls and treated groups for all time points with comparable p values. Conclusion: In the framework of therapy assessment in rats bearing subcutaneous tumors, all algorithms available on the Inveon system performed equally. [ABSTRACT FROM AUTHOR]

Purpose: We prospectively evaluated whether a strategy using point spread function (PSF) reconstruction for both diagnostic and quantitative analysis in non-small cell lung cancer (NSCLC) patients meets the European Association of Nuclear Medicine (EANM) guidelines for harmonization of quantitative values. Methods: The NEMA NU-2 phantom was used to determine the optimal filter to apply to PSF-reconstructed images in order to obtain recovery coefficients (RCs) fulfilling the EANM guidelines for tumour positron emission tomography (PET) imaging (PSF). PET data of 52 consecutive NSCLC patients were reconstructed with unfiltered PSF reconstruction (PSF), PSF and with a conventional ordered subset expectation maximization (OSEM) algorithm known to meet EANM guidelines. To mimic a situation in which a patient would undergo pre- and post-therapy PET scans on different generation PET systems, standardized uptake values (SUVs) for OSEM reconstruction were compared to SUVs for PSF and PSF reconstruction. Results: Overall, in 195 lesions, Bland-Altman analysis demonstrated that the mean ratio between PSF and OSEM data was 1.03 [95 % confidence interval (CI) 0.94-1.12] and 1.02 (95 % CI 0.90-1.14) for SUV and SUV, respectively. No difference was noticed when analysing lesions based on their size and location or on patient body habitus and image noise. Ten patients (84 lesions) underwent two PET scans for response monitoring. Using the European Organization for Research and Treatment of Cancer (EORTC) criteria, there was an almost perfect agreement between OSEM/OSEM (current standard) and OSEM/PSF or PSF/OSEM with kappa values of 0.95 (95 % CI 0.91-1.00) and 0.99 (95 % CI 0.96-1.00), respectively. The use of PSF either for pre- or post-treatment (i.e. OSEM/PSF or PSF/OSEM) showed considerably less agreement with kappa values of 0.75 (95 % CI 0.67-0.83) and 0.86 (95 % CI 0.78-0.94), respectively. Conclusion: Protocol-optimized images and compliance with EANM guidelines allowed for a reliable pre- and post-therapy evaluation when using different generation PET systems. These data obtained in NSCLC patients could be extrapolated to other solid tumours. [ABSTRACT FROM AUTHOR]

The article dicusses the survey that aims to shed light on the unreported variability in the standardized uptake values ( SUVs). It mentions the significance of the SUVs as non-invasive quantitative imaging biomarkers. Strategies are proposed based on the survey including the need to systematically ask the patients to weigh themselves 2 days prior to the positron emission tomography (PET) examination.

The formulae for Dice and Jaccard indices used to assess volumes concordance should read as follows: [ABSTRACT FROM AUTHOR]

The article presents the case study of a 57-year-old male patient where his computed tomography does not visualize the bladder tumor. It adds that positron emission tomography (PET) or computed tomography (CT) were performed 60 minutes after intravenous injection of furosemide. The article discusses a case that shows the role of diuretics on medical imaging for urethelial bladder cancer.