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Introduction Although visual and quantitative assessments of [18F]FDG PET/CT studies typically rely on liver uptake value as a reference or normalisation factor, consensus or consistency in measuring [18F]FDG uptake is lacking. Therefore, we evaluate the variation of several liver standardised uptake value (SUV) measurements in lymphoma [18F]FDG PET/CT studies using different uptake metrics. Methods PET/CT scans from 34 lymphoma patients were used to calculate SUVmaxliver, SUVpeakliver and SUVmeanliver as a function of (1) volume-of-interest (VOI) size, (2) location, (3) imaging time point and (4) as a function of total metabolic tumour volume (MTV). The impact of reconstruction protocol on liver uptake is studied on 15 baseline lymphoma patient scans. The effect of noise on liver SUV was assessed using full and 25% count images of 15 lymphoma scans. Results Generally, SUVmaxliver and SUVpeakliver were 38% and 16% higher compared to SUVmeanliver. SUVmaxliver and SUVpeakliver increased up to 31% and 15% with VOI size while SUVmeanliver remained unchanged with the lowest variability for the largest VOI size. Liver uptake metrics were not affected by VOI location. Compared to baseline, liver uptake metrics were 15–18% and 9–18% higher at interim and EoT PET, respectively. SUVliver decreased with larger total MTVs. SUVmaxliver and SUVpeakliver were affected by reconstruction protocol up to 62%. SUVmax and SUVpeak moved 22% and 11% upward between full and 25% count images. Conclusion SUVmeanliver was most robust against VOI size, location, reconstruction protocol and image noise level, and is thus the most reproducible metric for liver uptake. The commonly recommended 3 cm diameter spherical VOI-based SUVmeanliver values were only slightly more variable than those seen with larger VOI sizes and are sufficient for SUVmeanliver measurements in future studies. Trial registration EudraCT: 2006–005,174-42, 01–08-2008.

Purpose: To compare the predictive value of new immunotherapy-specific fluorine-18-labeled glucose Positron Emission Tomography/Computed Tomography ([18F]FDG PET/CT) response criteria to conventional PET/CT criteria for overall survival (OS) in melanoma and lung cancer patients treated with immunotherapy. Methods: MEDLINE (Ovid), Embase, Scopus, Web of Science and the Cochrane Library databases were searched until June 4, 2021, in line with the PRISMA statement. Two reviewers independently screened resulting records. Quality assessment was performed according to Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and/or Quality in Prognostic Studies (QUIPS) criteria. PET/CT response assessment was divided in immunotherapy PET/CT response criteria, conventional PET/CT response criteria, and individual Δ[18F]FDG/PET CT metrics. The main outcome measure extracted was the univariate hazard ratio (HR) for OS. Results: Fifteen studies (n = 565) were included, with ten studies (225 NSCLC, 178 melanoma cases) reporting on PET/CT response criteria and five studies (126 NSCLC, 36 melanoma cases) on individual Δ[18F]FDG PET/CT metrics. Until 2016, conventional criteria: EORTC and PERCIST1.0 were applied; since then, several new, modified criteria emerged: imPERCIST, PERCIMT, PECRIT and iPERCIST. For both NSCLC and melanoma, univariate HRs did not show substantial differences between immunotherapy and conventional PET/CT response criteria, with overlapping confidence intervals. No individual Δ[18F]FDG PET/CT metric can yet be recommended. ΔTMTV in melanoma and ΔSUVmax in NSCLC showed the highest univariate HRs. Conclusion: There is insufficient evidence to decide whether the predictive value of immunotherapy PET/CT criteria is superior to conventional ones for OS, in melanoma and lung cancer treated with immunotherapy. A different research strategy is needed to reach the answer: PET/CT research should focus on directly comparing (modifications of) immunotherapy and conventional PET/CT criteria within a homogenous population with standardized PET timing, immunotherapy categories and OS definition. A consortium-based comprehensive database with individual patient data could be the solution.

Although visual and quantitative assessments of [18F]FDG PET/CT studies typically rely on liver uptake value as a reference or normalisation factor, consensus or consistency in measuring [18F]FDG uptake is lacking. Therefore, we evaluate the variation of several liver standardised uptake value (SUV) measurements in lymphoma [18F]FDG PET/CT studies using different uptake metrics.PET/CT scans from 34 lymphoma patients were used to calculate SUVmaxGenerally, SUVmaxSUVmeanEudraCT: 2006-005,174-42, 01-08-2008.

Blood-based biomarkers are gaining interest for response evaluation in classical Hodgkin lymphoma (cHL). However, it is unknown how blood-based biomarkers relate to quantitative 18F-FDG-PET features. We correlated extracellular vesicle-associated miRNAs (EV-miRNA), serum TARC, and complete blood count (CBC) with PET features (e.g., metabolic tumor volume [MTV], dissemination and intensity features) in 30 cHL patients at baseline. EV-miR127-3p, EV-miR24-3p, sTARC, and several CBC parameters showed weak to strong correlations with MTV and dissemination features, but not with intensity features. Two other EV-miRNAs only showed weak correlations with PET features. Therefore, blood-based biomarkers may be complementary to PET features, which warrants further exploration of combining these biomarkers in prognostic models.

Purpose: To clarify and elaborate on the choices that were made in the development of the Patient Scale of the Patient and Observer Scar Assessment Scale 3.0 (POSAS 3.0), based upon the rich information obtained from patients during focus groups and pilot tests. Methods: The discussions described in this paper are a reflection of the focus group study and pilot tests that were conducted in order to develop the Patient Scale of the POSAS3.0. The focus group took place in the Netherlands and Australia and included 45 participants. Pilot test interviews were performed with 15 participants in Australia, the Netherlands, and the United Kingdom.Results: We discussed the selection and wording of 9 included items. The merging 8 characteristics into 4 items was discussed. Finally, the reasons for exclusion of 23 characteristics are given. Conclusion: Based upon the unique and rich material of patient input obtained, two versions of the Patient Scale of the POSAS3.0 were developed: the Generic version, and the Linear scar version. The discussions and decisions taken during the development are informative for a good understanding of the POSAS 3.0 and are indispensable as a background for future translations and cross-cultural adaptations.

Forensic High and Intensive Care (FHIC) has recently been developed as a new care model in Dutch forensic psychiatry. FHIC aims to provide contact-based care. To support Dutch forensic care institutions in the implementation of the model, a model fidelity scale was developed called the FHIC monitor. The aim of this study was to assess the inter-rater reliability, content validity, and construct validity of the FHIC monitor. A multi-methods design was used, combining qualitative and quantitative research. To collect data, audits and focus group meetings were organized to score care at individual wards with the monitor and get feedback from auditors and audit receiving teams about the quality of the monitor. In total, fifteen forensic mental healthcare institutions participated. The instrument showed acceptable inter-rater reliability and content validity, and a significant difference between expected high and low scoring institutions, supporting construct validity. The instrument can be used as a valid instrument to measure the level of implementation of the FHIC model on forensic psychiatric wards in the Netherlands.

Purpose Biomarkers that can accurately predict outcome in DLBCL patients are urgently needed. Radiomics features extracted from baseline [18F]-FDG PET/CT scans have shown promising results. This study aims to investigate which lesion- and feature-selection approaches/methods resulted in the best prediction of progression after 2 years. Methods A total of 296 patients were included. 485 radiomics features (n = 5 conventional PET, n = 22 morphology, n = 50 intensity, n = 408 texture) were extracted for all individual lesions and at patient level, where all lesions were aggregated into one VOI. 18 features quantifying dissemination were extracted at patient level. Several lesion selection approaches were tested (largest or hottest lesion, patient level [all with/without dissemination], maximum or median of all lesions) and compared to the predictive value of our previously published model. Several data reduction methods were applied (principal component analysis, recursive feature elimination (RFE), factor analysis, and univariate selection). The predictive value of all models was tested using a fivefold cross-validation approach with 50 repeats with and without oversampling, yielding the mean cross-validated AUC (CV-AUC). Additionally, the relative importance of individual radiomics features was determined. Results Models with conventional PET and dissemination features showed the highest predictive value (CV-AUC: 0.72–0.75). Dissemination features had the highest relative importance in these models. No lesion selection approach showed significantly higher predictive value compared to our previous model. Oversampling combined with RFE resulted in highest CV-AUCs. Conclusion Regardless of the applied lesion selection or feature selection approach and feature reduction methods, patient level conventional PET features and dissemination features have the highest predictive value. Trial registration number and date: EudraCT: 2006–005174-42, 01–08-2008.