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Purpose Monoclonal antibody (mAb)-based PET (immunoPET) imaging can characterise tumour lesions non-invasively. It may be a valuable tool to determine which patients may benefit from treatment with a specific monoclonal antibody (mAb) and evaluate treatment response. For 89Zr immunoPET imaging, higher sensitivity of state-of-the art PET/CT systems equipped with silicon photomultiplier (SiPM)-based detector elements may be beneficial as the low positron abundance of 89Zr causes a low signal-to-noise level. Moreover, the long physical half-life limits the amount of activity that can be administered to the patients leading to poor image quality even when using long scan durations. Here, we investigated the difference in semiquantitative performance between the PMT-based Biograph mCT, our clinical reference system, and the SiPM-based Biograph Vision PET/CT in 89Zr immunoPET imaging. Furthermore, the effects of scan duration reduction using the Vision on semiquantitative imaging parameters and its influence on image quality assessment were evaluated. Methods Data were acquired on day 4 post 37 MBq 89Zr-labelled mAb injection. Five patients underwent a double scan protocol on both systems. Ten patients were scanned only on the Vision. For PET image reconstruction, three protocols were used, i.e. one camera-dependent protocol and European Association of Nuclear Medicine Research Limited (EARL) standards 1 and 2 compliant protocols. Vision data were acquired in listmode and were reprocessed to obtain images at shorter scan durations. Semiquantitative PET image parameters were derived from tumour lesions and healthy tissues to assess differences between systems and scan durations. Differently reconstructed images obtained using the Vision were visually scored regarding image quality by two nuclear medicine physicians. Results When images were reconstructed using 100% acquisition time on both systems following EARL standard 1 compliant reconstruction protocols, results regarding semiquantification were comparable. For Vision data, reconstructed images that conform to EARL1 standards still resulted in comparable semiquantification at shorter scan durations (75% and 50%) regarding 100% acquisition time. Conclusion Scan duration of 89Zr immunoPET imaging using the Vision can be decreased up to 50% compared with using the mCT while maintaining image quality using the EARL1 compliant reconstruction protocol.

Background and purpose: Xerostomia remains a common side effect of radiotherapy (RT) for patients with head and neck (H&N) cancer despite advancements in treatment planning and delivery. Secretory salivary gland cells express the prostate-specific membrane antigen (PSMA), and show significant uptake on PET scans using 68Ga/18F-PSMA-ligands. We aimed to objectively quantify the dose–response of salivary glands to RT using PSMA PET. Methods and materials: 28H&N cancer patients received RT with 70 Gy in 35 fractions over 7 weeks. PSMA PET/CT was acquired at baseline (BL), during treatment (DT) and at 1-&6-months post-treatment (PT1M/PT6M). Dose, BL- PT1M- and PT6M-SUV were extracted for every voxel inside each parotid (PG) and submandibular (SMG) gland. The PT1M/6M data was analysed using a generalised linear mixed effects model. Patient-reported xerostomia and DT-PSMA loss was also analysed. Results: Dose had a relative effect on BL SUV. For a population average gland (BL-SUV of 10), every 1 Gy increment, decreased the PT1M/PT6M-SUV by 1.6 %/1.6 % for PGs and by 0.9 %/1.8 % for SMGs. TD50 of the population curves was 26.5/31.3 Gy for PGs, and 22.9/27.8 Gy for SMGs at PT1M /PT6M. PSMA loss correlated well with patient-reported xerostomia at DT/PT1M (Spearman's ρ = -0.64, −0.50). Conclusion: A strong relationship was demonstrated between radiation dose and loss of secretory cells in salivary glands derived using PSMA PET/CT. The population curve could potentially be used as a dose planning objective, by maximising the predicted post-treatment SUV. BL scans could be used to further tailor this to individual patients.

Purpose As novel tracers are continuously under development, it is important to obtain reliable radiation dose estimates to optimize the amount of activity that can be administered while keeping radiation burden within acceptable limits. Organ segmentation is required for quantification of specific uptake in organs of interest and whole-body dosimetry but is a time-consuming task which induces high interobserver variability. Therefore, we explored using manual segmentations versus an artificial intelligence (AI)-based automated segmentation tool as a pre-processing step for calculating whole-body effective doses to determine the influence of variability in volumetric whole-organ segmentations on dosimetry. Procedures PET/CT data of six patients undergoing imaging with 89Zr-labelled pembrolizumab were included. Manual organ segmentations were performed, using in-house developed software, and biodistribution information was obtained. Based on the activity biodistribution information, residence times were calculated. The residence times served as input for OLINDA/EXM version 1.0 (Vanderbilt University, 2003) to calculate the whole-body effective dose (mSv/MBq). Subsequently, organ segmentations were performed using RECOMIA, a cloud-based AI platform for nuclear medicine and radiology research. The workflow for calculating residence times and whole-body effective doses, as described above, was repeated. Results Data were acquired on days 2, 4, and 7 post-injection, resulting in 18 scans. Overall analysis time per scan was approximately 4 h for manual segmentations compared to ≤ 30 min using AI-based segmentations. Median Jaccard similarity coefficients between manual and AI-based segmentations varied from 0.05 (range 0.00–0.14) for the pancreas to 0.78 (range 0.74–0.82) for the lungs. Whole-body effective doses differed minimally for the six patients with a median difference in received mSv/MBq of 0.52% (range 0.15–1.95%). Conclusion This pilot study suggests that whole-body dosimetry calculations can benefit from fast, automated AI-based whole organ segmentations.

Purpose To evaluate the Dutch integrated nuclear medicine and radiology residency program from the perspective of nuclear medicine physicians and radiologists. Methods A survey was distributed among nuclear medicine physicians and radiologists in hospitals that participate in the Dutch integrated nuclear medicine and radiology training program. Results A total of 139 completed questionnaires were included. Nuclear medicine physicians (n = 36) assigned a mean score of 5.7 ± 2.0, and radiologists (n = 103) assigned a mean score of 6.5 ± 2.8 (on a 1–10 scale) to the success of the integrated training program in their hospital. On multiple regression, female gender of the survey participant (B = 2.22, P = 0.034), musculoskeletal radiology as subspecialty of the survey participant (B = 3.36, P = 0.032), and the survey participant’s expectancy of resident’s ability to handle workload after completion of residency were significantly associated with perceived success of the integrated training program (B = 1.16, P = 0.023). Perceived strengths of the integrated training program included broadening of expertise, a better preparation of future imaging specialists for hybrid imaging, increased efficiency in training residents, and increased efficiency in multidisciplinary meetings. Perceived weaknesses of the integrated training program included reduced exposure to nuclear medicine, less time for research and innovation, and concerns about its international recognition. Conclusion This study provided insights into the experiences of nuclear medicine physicians and radiologists with the Dutch integrated nuclear medicine and radiology residency program, which may be helpful to improve the program and similar residency programs in other countries.

In this contribution, several opportunities and challenges for long axial field of view (LAFOV) PET are described. It is an anthology in which the main issues have been highlighted. A consolidated overview of the camera system implementation, business and financial plan, opportunities and challenges is provided. What the nuclear medicine and molecular imaging community can expect from these new PET/CT scanners is the delivery of more comprehensive information to the clinicians for advancing diagnosis, therapy evaluation and clinical research.

Purpose Current 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. Methods EARL 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. Results Phantom 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. Conclusion Images 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.

Purpose: To explore reasons that influence a resident's choice for the nuclear medicine subspecialty in the integrated nuclear medicine and radiology residency program in the Netherlands. Methods: A web questionnaire was developed and distributed among residents in the Dutch integrated nuclear medicine and radiology training. Results: A total of 114 residents were included. The survey results revealed four categories of incentives to choose the nuclear medicine subspecialty: 1) Expertise of nuclear medicine physicians and their quality of supervision in the training hospital, 2) Opportunities to do scientific research during and after residency, 3) Diversity of pathology, radiotracers, examinations and therapies in the training hospital, and 4) The expectation that the role of hybrid imaging will increase in the future. They also revealed four groups of disincentives to choose the nuclear medicine subspecialty: 1) Lack of collaboration and integration between nuclear medicine and radiology in some training hospitals, 2) Imbalance between nuclear medicine and radiology during the first 2.5 years of basic training during residency at the expense of nuclear medicine, 3) Uncertainty regarding the international recognition of the nuclear medicine subspecialty training, and 4) Uncertain future of nuclear medicine regarding the chances of employment and the ratio of work activities of nuclear medicine to radiology. Conclusion: This study provided insight into residents' motives to pursue or refrain from nuclear medicine subspecialization in an integrated nuclear medicine and radiology residency program. Medical imaging specialists in training hospitals and developers of curricula for nuclear medicine and radiology training should take these motives into account to ensure a sufficient outflow of newly graduated nuclear medicine specialists.

Previously, PET image biomarkers (PET-IBMs) - the 90thpercentile standardized uptake value (P90-SUV) and the Mean SUV (Mean-SUV) ofthe contralateral parotid gland (cPG) - were identified as predictors for late-xerostomiafollowing head and neck cancer (HNC) radiotherapy. The aim of the current study wasto assess in an independent validation cohort whether these pre-treatment PET-IBMscan improve late-xerostomia prediction compared to the prediction with baselinexerostomia and mean cPG dose alone.The prediction endpoint was patient-rated moderate-to-severe xerostomia at 12 months after radiotherapy. The PET-IBMs were extracted frompre-treatment 18 F-FDG PET images. The performance of the model (base model)with baseline xerostomia and mean cPG dose alone and models with additionallyP90-SUV or Mean-SUV were tested in the current independent validation cohort.Specifically, model discrimination (area under the curve: AUC) and calibration(calibration plot) were evaluated.The current validation cohort consisted of 137 patients of which 40% developed moderate-to-severe xerostomia at 12 months. Both the PET-P90 model (AUC PET-P90 =0.71) and the PET-Mean model (AUC PET-Mean =0.70) performed well in the current validation cohort. Moreover, their performance was improved compared to the base model (AUC base =0.68). The calibration plots showed a good fit of the prediction to the actual rates for all tested models.PET-IBMs showed an improved prediction of late-xerostomia when added to the base model in this validation cohort. This contributed to the published hypothesis that PET-IBMs include individualized information and can serve as a pre- treatment risk factor for late-xerostomia.

For esophageal cancer patients, detection of residual tumor after neoadjuvant chemoradiotherapy (nCRT) is important for guiding treatment decisions regarding standard esophagectomy or active surveillance. Prediction models incorporating clinical variables and FDG-PET quantitative radiomic features have been previously developed in a single-center setting (‘development cohort’, Beukinga et al. 2018) to identify patients with residual tumor after nCRT. The aim was to improve generalizability by redeveloping the models (i.e. ‘model extension’) using a multicenter prospectively acquired cohort. The development cohort was combined with a patient cohort collected from a prospective multicenter study in four Dutch institutes. Patients underwent nCRT according to the CROSS regimen followed by esophagectomy 6–14 weeks after nCRT between 2013–2019. Outcome was tumor regression grade (TRG) 1–2 (0–10% tumor) vs TRG 3–4 (>10% tumor). FDG-PET/CT was performed 6–12 weeks after nCRT. Post-treatment FDG-PET-radiomic features were calculated from gross tumor volumes. Features were standardized per scanner. A bootstrapped least absolute shrinkage and selection (LASSO) model using clinical variables and radiomic features was developed and a model incorporating clinical variables was developed for reference. Some 262 patients were included. Median age was 65 years (IQR 60–70), 158 of 262 were male (82%) and outcomes were 129/262 TRG 1–2 (49%) and 133/262 TRG 3–4 (51%). The extended LASSO model included seven radiomic features and the clinical variables cT stage and histology (internally validated AUC, 0.59). At a probability threshold to obtain 90% sensitivity for detection of TRG 3–4 (benchmark with bite-on-bite biopsies + fine-needle aspiration of suspected lymph nodes), specificity was 36% and accuracy 63%. A LASSO clinical reference model (including cT, sex, histology) achieved an internally validated AUC of 0.58 (Fig. 1). The extended internally validated LASSO model incorporating post-treatment radiomic features and clinical variables yielded moderate discriminative ability. The improvement in predictive performance with this model compared with a model using only clinical variables was marginal. The application of radiomics to post-treatment FDG-PET/CT scans is of no help in decision-making in individual patients regarding the choice for active surveillance after nCRT.

As novel tracers are continuously under development, it is important to obtain reliable radiation dose estimates to optimize the amount of activity that can be administered while keeping radiation burden within acceptable limits. Organ segmentation is required for quantification of specific uptake in organs of interest and whole-body dosimetry but is a time-consuming task which induces high interobserver variability. Therefore, we explored using manual segmentations versus an artificial intelligence (AI)-based automated segmentation tool as a pre-processing step for calculating whole-body effective doses to determine the influence of variability in volumetric whole-organ segmentations on dosimetry.PET/CT data of six patients undergoing imaging withData were acquired on days 2, 4, and 7 post-injection, resulting in 18 scans. Overall analysis time per scan was approximately 4 h for manual segmentations compared to ≤ 30 min using AI-based segmentations. Median Jaccard similarity coefficients between manual and AI-based segmentations varied from 0.05 (range 0.00-0.14) for the pancreas to 0.78 (range 0.74-0.82) for the lungs. Whole-body effective doses differed minimally for the six patients with a median difference in received mSv/MBq of 0.52% (range 0.15-1.95%).This pilot study suggests that whole-body dosimetry calculations can benefit from fast, automated AI-based whole organ segmentations.

PURPOSE The imaging of intestinal neuroendocrine tumours (NETs) relies on functional positron emission tomography (PET) tracers; these tumours can be studied by means of both 68 Ga-DOTA peptides and 18 F-fluorodihydroxyphenyl- l-alanine (18 F-DOPA) PET/computed tomography (CT). As yet, it is unclear which of these two modalities offers the better sensitivity. We therefore conducted a meta-analysis to assess the available data. METHODS PubMed, CENTRAL, Scopus and Web of Science were searched for studies comparing the sensitivity of 68 Ga-DOTA peptides and 18 F-DOPA PET/CT; papers up to February 2021 were considered. In each study, we considered sensitivity in terms of patient-based analysis (PBA), region-based analysis (RBA) and lesion-based analysis (LBA), and pooled the results yielded by each tracer. Multidisciplinary follow-up served as the standard of truth. RESULTS Of the 636 records identified, 6 articles published between 2008 and 2021 were finally selected, and 112 intestinal NETs patients were included. The pooled sensitivity of 18 F-DOPA PET/CT was 83%, 89% and 95% on PBA, RBA and LBA, respectively. 68 Ga-DOTA peptides PET/CT showed sensitivity of 88%, 92% and 82% on PBA, RBA and LBA, respectively. No significant differences were found between the two tracers on PBA and RBA. By contrast, a clear trend towards significance in favour of 18 F-DOPA PET/CT was identified on LBA. The presence of a significant difference in favour of 18 F-DOPA PET/CT was confirmed in a subgroup analysis conducted only on the most recent and largest studies. In all three analyses, mild-to-high heterogeneity was found; however, no publication bias was observed. CONCLUSION Both 18 F-DOPA PET/CT and 68 Ga-DOTA-peptides PET/CT are reliable diagnostic procedures in patients with intestinal NETs. However, in terms of lesion detection, a non-negligible difference in favour of 18 F-DOPA PET/CT was observed. Thus, the use of 18 F-DOPA PET/CT could be considered as a first-line molecular procedure in intestinal NETs.

PurposeThe aim of this study was to retrospectively compare F-18-FDOPA versus Ga-68-DOTATOC PET in lesion detection rates and laboratory tumor markers in patients with neuroendocrine neoplasms (NENs). Patients and MethodsAll patients with histologically proven NEN between May 2015 and February 2019 were included who underwent both F-18-DOPA and Ga-68-DOTATOC PET scans within 6 months from each other (mean, 75; median, 38; range, 2-168 days). All patients, except those with pancreatic NEN, received carbidopa before F-18-DOPA PET. Based on the number of lesions on both modalities, patients were divided into 3 categories: more lesions on F-18-DOPA (DOPA > DOTA), more lesions on Ga-68-DOTATOC (DOTA > DOPA), and equal number of lesions (DOPA = DOTA). Tumor markers chromogranin A, serotonin, and 5-hydroxyindoleacetic acid (5-HIAA) within a maximum of 3 months around either scan were retrieved from the patients' charts. ResultsF-18-DOPA revealed significantly more lesions compared with Ga-68-DOTATOC (611 vs 385, P DOTA group with 16 small intestinal (SI) NENs, 3 large intestinal, 4 pancreatic, and 1 tumor of unknown origin (TUO). For the 9 patients in the DOTA > DOPA group, 4 were SI, 2 pancreatic, 1 lung, and 2 TUOs. Twelve patients in the DOPA = DOTA group had 6 pancreatic tumors, 3 SI, 1 ovarian, and 2 TUOs. Only serotonin and 5-HIAA showed significant higher values for DOPA > DOTA compared with DOTA > DOPA (mean 24 vs 4, P DOTA patients. ConclusionsThere is an advantage of carbidopa pretreated F-18-DOPA over Ga-68-DOTATOC PET, especially for large intestinal NENs with high levels of biomarkers. There seems to be a relationship between increased biomarker value and improved lesion detection rates with the F-18-DOPA PET scan, which requires further prospective analysis.

Background and purpose: Previously, PET image biomarkers (PET-IBMs) – the 90th percentile standardized uptake value (P90-SUV) and the Mean SUV (Mean-SUV) of the contralateral parotid gland (cPG) – were identified as predictors for late-xerostomia following head and neck cancer (HNC) radiotherapy. The aim of the current study was to assess in an independent validation cohort whether these pre-treatment PET-IBM can improve late-xerostomia prediction compared to the prediction with baseline xerostomia and mean cPG dose alone. Materials and methods: The prediction endpoint was patient-rated moderate-to-severe xerostomia at 12 months after radiotherapy. The PET-IBMs were extracted from pre-treatment 18 F-FDG PET images. The performance of the model (base model) with baseline xerostomia and mean cPG dose alone and models with additionally P90-SUV or Mean-SUV were tested in the current independent validation cohort. Specifically, model discrimination (area under the curve: AUC) and calibration (calibration plot) were evaluated. Results: The current validation cohort consisted of 137 patients of which 40% developed moderate-to-severe xerostomia at 12 months. Both the PET-P90 model (AUC:PET-P90 = 0.71) and the PET-Mean model (AUC: PET-Mean = 0.70) performed well in the current validation cohort. Moreover, their performance were improved compared to the base model (AUC:base model= 0.68). The calibration plots showed a good fit of the prediction to the actual rates for all tested models. Conclusion: PET-IBMs showed an improved prediction of late-xerostomia when added to the base model in this validation cohort. This contributed to the published hypothesis that PET-IBMs include individualized information and can serve as a pre-treatment risk factor for late-xerostomia.

In treatment of neuroendocrine neoplasms (NENs), confirmation of somatostatin receptor expression withSeven patients with in total 89 lesions completed four infusions of 7.4 GBq [Response to PRRT with [

Background One of the challenges in the management of patients with follicular lymphoma (FL) is the identification of individuals with histological transformation, most commonly into diffuse large B-cell lymphoma (DLBCL). [F-18]FDG-PET/CT is used for staging of patients with lymphoma, but visual interpretation cannot reliably discern FL from DLBCL. This study evaluated whether radiomic features extracted from clinical baseline [F-18]FDG PET/CT and analyzed by machine learning algorithms may help discriminate FL from DLBCL.Materials and methods Patients were selected based on confirmed histopathological diagnosis of primary FL (n=44) or DLBCL (n=76) and available [F-18]FDG PET/CT with EARL reconstruction parameters within 6 months of diagnosis. Radiomic features were extracted from the volume of interest on co-registered [F-18]FDG PET and CT images. Analysis of selected radiomic features was performed with machine learning classifiers based on logistic regression and tree-based ensemble classifiers (AdaBoosting, Gradient Boosting, and XG Boosting). The performance of radiomic features was compared with a SUVmax-based logistic regression model.Results From the segmented lesions, 121 FL and 227 DLBCL lesions were included for radiomic feature extraction. In total, 79 radiomic features were extracted from the SUVmap, 51 from CT, and 6 shape features. Machine learning classifier Gradient Boosting achieved the best discrimination performance using 136 radiomic features (AUC of 0.86 and accuracy of 80%). SUVmax-based logistic regression model achieved an AUC of 0.79 and an accuracy of 70%. Gradient Boosting classifier had a significantly greater AUC and accuracy compared to the SUVmax-based logistic regression (pConclusion Machine learning analysis of radiomic features may be of diagnostic value for discriminating FL from DLBCL tumor lesions, beyond that of the SUVmax alone.

Immune checkpoint inhibitors (ICI) targeting PD-1/PD-L1 frequently induces tumor response in metastatic melanoma patients. However, tumor response often takes months and may be heterogeneous. Consequently, additional local treatment for non-responsive metastases may be needed, especially in the case of brain metastases. Non-invasive imaging may allow the characterization of (brain) metastases to predict response. This pilot study uses 18F-BMS986192 PET for PD-L1 expression to explore the variability in metastatic tracer uptake and its relation to tumor response, with a special focus on brain metastases. Methods: Metastatic melanoma patients underwent whole-body 18F-BMS986192 PET/CT scanning before and 6 weeks after starting ICI therapy. 18F-BMS986192 uptake was measured in healthy tissues, organs, and tumor lesions. Tumor response was evaluated at 12 weeks using CT thorax/abdomen and MRI brain. RECIST v 1.1 was used to define therapy response per patient. Response per lesion was measured by the percentage change in lesion diameter. Toxicity was assessed according to Common Terminology Criteria for Adverse Events version 4.0. Results: Baseline 18F-BMS986192 PET/CT was performed in 8 patients, with follow-up scans in 4 patients. The highest tracer uptake was observed in the spleen, bone marrow, kidneys, and liver. Tracer uptake in tumor lesions was heterogeneous. In total, 42 tumor lesions were identified at baseline with most lesions in the lungs (n = 21) and brain (n = 14). Tracer uptake was similar between tumor locations. 18F-BMS986192 uptake in lesions at baseline, corrected for blood pool activity, was negatively correlated with the change lesion diameter at response evaluation (r=-0.49, P = 0.005), both in intra- and extracerebral lesions. Receiver operating characteristic (ROC) analysis demonstrated that 18F-BMS986192 uptake can discriminate between responding and nonresponding lesions with an area under the curve of 0.82. At the follow-up scan an increased 18F-BMS986192 uptake compared to baseline scan was correlated with an increased lesion diameter at response evaluation. In the follow-up 18F-BMS986192-PET scan of two patients, ICI-related toxicity (thyroiditis and colitis) was detected. Conclusion: In this pilot study, 18F-BMS986192 PET showed heterogeneous uptake in intra and extracerebral metastatic lesions in melanoma patients. Baseline 18F-BMS986192 uptake was able to predict an ICI treatment-induced reduction in lesion volume, whereas the follow-up PET scan allowed the detection of treatment-induced toxicity.

Mature lymphoproliferative diseases are a heterogeneous group of neoplasms arising from different stages of B-cell and T-cell development. With improved understanding of the molecular processes in lymphoma and novel treatment options, arises a growing need for the molecular characterisation of tumours. Molecular imaging with single-photon-emission CT and PET using specific radionuclide tracers can provide whole-body information to investigate cancer biology, to evaluate phenotypic heterogeneity, to identify resistance to targeted therapy, and to assess the biodistribution of drugs in patients. In this Review, we evaluate the existing literature on molecular imaging in lymphoma, other than 18F-fluordeoxyglucose molecular imaging. The aim is to examine the contribution of molecular imaging to the understanding of the biology of lymphoma and to discuss potential implications for the diagnostics and therapy of this disease. Finally, we discuss possible applications for molecular imaging of patients with lymphoma in the clinical context.

Background: Oligometastatic prostate cancer (OMPC) is a heterogeneous disease state that is imperfectly understood, and its clinical implications are unclear. Objective: To determine the consensus of a Dutch multidisciplinary expert panel on biological aspects, treatment goals, and management of OMPC in daily clinical practice. Design, setting, and participants: The study comprised a modified Delphi method including an explorative survey with various statements and questions, followed by a consensus meeting to discuss and determine the agreement with revised statements and related items. The panel consisted of 34 Dutch representatives from urology, medical and radiation oncology, radiology, nuclear medicine, and basic research. Outcome measurements and statistical analysis: Agreement was determined with statements (five-point scale). Consensus was defined as ≥75% panel agreement with a statement. Results and limitations: Consensus existed for 56% of statements. The panel agreed that OMPC comprises a limited metastatic spread in the hormone-sensitive setting, in both the synchronous and the metachronous presentation. Limited metastatic spread was believed to involve three to five metastases and a maximum of two organs. Prostate-specific membrane antigen positron emission tomography/computed tomography scan was currently perceived as the most accurate diagnostic imaging modality. Although there was a consensus that targeted treatment of all metastases in OMPC will delay further dissemination of the disease, opinions on specific treatment regimens were divided. Panel outcomes were limited by the lack of scientific evidence on OMPC. Conclusions: A multidisciplinary panel reached a consensus that OMPC is a specific disease state requiring a tailored treatment approach. OMPC registries and clinical studies should focus on both the biology and the clinical parameters in relation to optimal treatment strategies in synchronous and metachronous OMPC. Patient summary: A group of Dutch medical specialists agreed that prostate cancer patients having few metastases may benefit from a new therapeutic approach. Clinical studies need to determine which treatment is best for each specific situation. A multidisciplinary panel reached consensus that oligometastatic prostate cancer (OMPC) is a specific disease state requiring a tailored treatment approach. OMPC registries and clinical studies should provide insight into the biology and clinical parameters in relation to optimal treatment strategies in synchronous and metachronous OMPC.

In May 2018, the Biograph Vision PET/CT system was installed at the University Medical Center Groningen. This study evaluated the initial experiences with this new PET/CT system in terms of perceived image quality and semiquantitative analysis in comparison to the Biograph mCT as a reference. Methods: In total, 20 oncologic patients were enrolled and received a single 3 MBq/kg injected dose of 18F-FDG followed by a dual-imaging PET scan. Ten patients were scanned on the Biograph mCT first, whereas the other 10 patients were scanned on the Biograph Vision first. The locally preferred clinically reconstructed images were blindly reviewed by 3 nuclear medicine physicians and scored (using a Likert scale of 1–5) on tumor lesion demarcation, overall image quality, and image noise. In addition, these clinically reconstructed images were used for semiquantitative analysis by measurement of SUVs in tumor lesions. Images acquired using reconstructions conform with the European Association of Nuclear Medicine Research Ltd. (EARL) specifications were also used for measurements of SUV in tumor lesions and healthy tissues for comparison between systems. Results: The 18F-FDG dose received by the 14 men and 6 women (age range, 36–84; mean ± SD, 61 ± 16 y) ranged from 145 to 405 MBq (mean ± SD, 268 ± 59.3). Images acquired on the Biograph Vision were scored significantly higher on tumor lesion demarcation, overall image quality, and image noise than images acquired on the Biograph mCT (P < 0.001). The overall interreader agreement showed a Fleiss κ of 0.61 (95% confidence interval, 0.53–0.70). Furthermore, the SUVs in tumor lesions and healthy tissues agreed well (within 95%) between PET/CT systems, particularly when EARL-compliant reconstructions were used on both systems. Conclusion: In this initial study, the Biograph Vision showed improved image quality compared with the Biograph mCT in terms of lesion demarcation, overall image quality, and visually assessed signal-to-noise ratio. The 2 systems are comparable in semiquantitatively assessed image biomarkers in both healthy tissues and tumor lesions. Improved quantitative performance may, however, be feasible using the clinically optimized reconstruction settings.

MYC gene rearrangements in diffuse large B cell lymphomas (DLBCLs) result in high proliferation rates and are associated with a poor prognosis. Strong proliferation is associated with high metabolic demand and tumour necrosis. The aim of this study was to investigate differences in the presence of necrosis and semiquantitative 18F-FDG PET metrics between DLBCL cases with or without a MYC rearrangement. The prognostic impact of necrosis and semiquantitative 18F-FDG PET parameters was investigated in an explorative survival analysis. Fluorescence in situ hybridisation analysis for MYC rearrangements, visual assesment, semiquantitative analysis of 18F-FDG PET scans and patient survival analysis were performed in 61 DLBCL patients, treated at a single referral hospital between 2008 and 2015. Of 61 tumours, 21 (34%) had a MYC rearrangement (MYC+). MYC status was neither associated with the presence of necrosis on 18F-FDG PET scans (necrosisPET; p = 1.0) nor associated with the investigated semiquantitative parameters maximum standard uptake value (SUVmax; p = 0.43), single highest SUVmax (p = 0.49), metabolic active tumour volume (MATV; p = 0.68) or total lesion glycolysis (TLG; p = 0.62). A multivariate patient survival analysis of the entire cohort showed necrosisPET as an independent prognostic marker for disease-specific survival (DSS) (HR = 13.9; 95% CI 3.0–65; p = 0.001). MYC rearrangements in DLBCL have no influence on the visual parameter necrosisPET or the semi-quantiative parameters SUVmax, MATV and TLG. Irrespective of MYC rearrangements, necrosisPET is an independent, adverse prognostic factor for DSS. • Retrospective analysis indicates that MYC rearrangement is not associated with necrosis on 18 F-FDG PET (necrosis PET ) scans or semiquantitative 18 F-FDG PET parameters. • Necrosis PET is a potential independent adverse prognostic factor for disease-specific survival in patients with DLBCL and is not influenced by the presence of MYC rearrangements.

Abstract Whole-body Patlak images can be obtained from an acquisition of first 6 min of dynamic imaging over the heart to obtain the arterial input function (IF), followed by multiple whole-body sweeps up to 60 min pi. The use of a population-averaged IF (PIF) could exclude the first dynamic scan and minimize whole-body sweeps to 30–60 min pi. Here, the effects of (incorrect) PIFs on the accuracy of the proposed Patlak method were assessed. In addition, the extent of mitigating these biases through rescaling of the PIF to image-derived IF values at 30–60 min pi was evaluated. Methods Using a representative IF and rate constants from the literature, various tumour time-activity curves (TACs) were simulated. Variations included multiplication of the IF with a positive and negative gradual linear bias over 60 min of 5, 10, 15, 20, and 25% (generating TACs using an IF different from the PIF); use of rate constants (K1, k3, and both K1 and k2) multiplied by 2, 1.5, and 0.75; and addition of noise (μ = 0 and σ = 5, 10 and 15%). Subsequent Patlak analysis using the original IF (representing the PIF) was used to obtain the influx constant (Ki) for the differently simulated TACs. Next, the PIF was scaled towards the (simulated) IF value using the 30–60-min pi time interval, simulating scaling of the PIF to image-derived values. Influence of variabilities in IF and rate constants, and rescaling the PIF on bias in Ki was evaluated. Results Percentage bias in Ki observed using simulated modified IFs varied from − 16 to 16% depending on the simulated amplitude and direction of the IF modifications. Subsequent scaling of the PIF reduced these Ki biases in most cases (287 out of 290) to Conclusions Simulations suggest that scaling of a (possibly incorrect) PIF to IF values seen in whole-body dynamic imaging from 30 to 60 min pi can provide accurate Ki estimates. Consequently, dynamic Patlak imaging protocols may be performed for 30–60 min pi making whole-body Patlak imaging clinically feasible.

Background The BULLSEYE trial is a multicenter, open-label, randomized controlled trial to test the hypothesis if 177Lu-PSMA is an effective treatment in oligometastatic hormone-sensitive prostate cancer (oHSPC) to prolong the progression-free survival (PFS) and postpone the need for androgen deprivation therapy (ADT). The original study protocol was published in 2020. Here, we report amendments that have been made to the study protocol since the commencement of the trial. Changes in methods and materials Two important changes were made to the original protocol: (1) the study will now use 177Lu-PSMA-617 instead of 177Lu-PSMA-I&T and (2) responding patients with residual disease on 18F-PSMA PET after the first two cycles are eligible to receive additional two cycles of 7.4 GBq 177Lu-PSMA in weeks 12 and 18, summing up to a maximum of 4 cycles if indicated. Therefore, patients receiving 177Lu-PSMA-617 will also receive an interim 18F-PSMA PET scan in week 4 after cycle 2. The title of this study was modified to; “Lutetium-177-PSMA in Oligo-metastatic Hormone Sensitive Prostate Cancer” and is now partly supported by Advanced Accelerator Applications, a Novartis Company. Conclusions We present an update of the original study protocol prior to the completion of the study. Treatment arm patients that were included and received 177Lu-PSMA-I&T under the previous protocol will be replaced. Trial registration ClinicalTrials.gov NCT04443062. First posted: June 23, 2020.

The imaging of intestinal neuroendocrine tumours (NETs) relies on functional positron emission tomography (PET) tracers; these tumours can be studied by means of bothPubMed, CENTRAL, Scopus and Web of Science were searched for studies comparing the sensitivity ofOf the 636 records identified, 6 articles published between 2008 and 2021 were finally selected, and 112 intestinal NETs patients were included. The pooled sensitivity ofBoth

PURPOSE: Post-transplant lymphoproliferative disorder (PTLD) is a serious complication after solid organ and hematopoietic stem cell transplantation, requiring a timely and accurate diagnosis. In this study, we evaluated the diagnostic performance of FDG-PET/CT in patients with suspected PTLD and examined if lactate dehydrogenase (LDH) levels, Epstein-Barr virus (EBV) load, or timing of FDG-PET/CT relate to detection performance of FDG-PET/CT.METHODS: This retrospective study included 91 consecutive patients with clinical suspicion of PTLD and a total of 97 FDG-PET/CT scans within an 8-year period. Pathology reports and a 2-year follow-up were used as the reference standard. Diagnostic performance of FDG-PET/CT for detection of PTLD as well as logistic regression analysis for factors expected to affect diagnostic yield were assessed.RESULTS: The diagnosis of PTLD was established in 34 patients (35%). Fifty-seven FDG-PET/CT scans (59%) were true negative, 29 (30%) were true positive, 6 (6%) false positive, and 5 (5%) false negative. Sensitivity of FDG-PET/CT for the detection of PTLD was 85%, specificity 90%, positive predictive value 83%, and negative predictive value 92%, with good inter-observer variability (k = 0.78). Of the parameters hypothesized to be associated with a true positive FDG-PET/CT result for the diagnosis of PTLD, only LDH was statistically significant (OR 1.03, p = 0.04).CONCLUSION: FDG-PET/CT has a good diagnostic performance in patients suspected of PTLD, with a good inter-observer agreement. Only LDH levels seemed to influence the detection performance of FDG-PET/CT. EBV-DNA load and timing of FDG-PET/CT after transplantation did not affect FDG-PET/CT diagnostic yield.

Objectives: The aim of this study was to investigate whether quantitative CT image-biomarkers (IBMs) can improve the prediction models with only classical prognostic factors for local-control (LC), regional-control (RC), distant metastasis-free survival (DMFS) and disease-free survival (DFS) for head and neck cancer (HNC) patients.Materials and Methods: The cohort included 240 and 204 HNC patients in the training and validation analysis, respectively. Clinical variables were scored prospectively and IBMs of the primary tumor and lymph nodes were extracted from planning CT-images. Clinical, IBM and combined models were created from multivariable Cox proportional-hazard analyses based on clinical features, IBMs, and both for LC, RC, DMFS and DFS.Results: Clinical variables identified in the multivariable analysis included tumor-site, WHO performance-score, tumor-stage and age. Bounding-box-volume describing the tumor volume and irregular shape, IBM correlation representing radiological heterogeneity, and LN_major-axis-length showing the distance between lymph nodes were included in the IBM models. The performance of IBM LC, RC, DMFS and DFS models (c-index(validated): 0.62, 0.80, 0.68 and 0.65) were comparable to that of the clinical models (0.62, 0.76, 0.70 and 0.66). The combined DFS model (0.70) including clinical features and IBMs performed significantly better than the clinical model. Patients stratified with the combined models revealed larger differences between risk groups in the validation cohort than with clinical models for LC, RC and DFS. For DMFS, the differences were similar to the clinical model.Conclusion: For prediction of HNC treatment outcomes, image-biomarkers performed as good as or slightly better than clinical variables.