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Purpose: Estrogen receptors (ER) are implicated in psychiatric disorders. We assessed if ER availability in the human brain could be quantified using 16α-[ 18 F]-fluoro-17β-estradiol ([ 18 F]FES) positron emission tomography (PET)., Procedures: Seven post‑menopausal women underwent a dynamic [ 18 F]FES PET scan with arterial blood sampling. A T1-weighted MRI was acquired for anatomical information. After one week, four subjects received a selective ER degrader (SERD), four hours before the PET scan. Pharmacokinetic analysis was performed using a metabolite-corrected plasma curve as the input function. The optimal kinetic model was selected based on the Akaike information criterion and standard error of estimated parameters. Accuracy of Logan graphical analysis and standardized uptake value (SUV) was determined via correlational analyses., Results: The reversible two-tissue compartment model (2T4k) model with fixed K 1 /k 2 was preferred. The total volume of distribution (V T ) could be more reliably estimated than the binding potential (BP ND ). A high correlation of V T with Logan graphical analysis was observed, but only a moderate correlation with SUV. SERD administration resulted in a reduced V T in the pituitary gland, but not in other regions., Conclusions: The optimal quantification method for [ 18 F]FES was the 2T4k with fixed K 1 /k 2 or Logan graphical analysis, but specific binding was only observed in the pituitary gland., (© 2024. Crown.)

Multiple sclerosis (MS) is an inflammatory demyelinating disease. Current treatments are focussed on immune suppression to modulate pathogenic activity that causes myelin damage. New treatment strategies are needed to prevent demyelination and promote remyelination. Development of such myelin repair therapies require a sensitive and specific biomarker for efficacy evaluation. Recently, it has been shown that quantification of myelin density is possible using [ 11 C]MeDAS PET. This method, however, requires arterial blood sampling to generate an arterial input function (AIF). As the invasive nature of arterial sampling will reduce clinical applicability, the purpose of this study was to assess whether an image-derived input function (IDIF) can be used as an alternative way to facilitate its routine clinical use. Six healthy controls and 11 MS patients underwent MRI and [ 11 C]MeDAS PET with arterial blood sampling. The application of both population-based whole blood-to-plasma conversion and metabolite corrections were assessed for the AIF. Next, summed images of the early time frames (0-70 s) and the frame with the highest blood-brain contrast were used to generate IDIFs. IDIFs were created using either the hottest 2, 4, 6 or 12 voxels, or an isocontour of the hottest 10% voxels of the carotid artery. This was followed by blood-to-plasma conversion and metabolite correction of the IDIF. The application of a population-based metabolite correction of the AIF resulted in high correlations of tracer binding (K i ) within subjects, but variable bias across subjects. All IDIFs had a sharper and higher peak in the blood curves than the AIF, most likely due to dispersion during blood sampling. All IDIF methods resulted in similar high correlations within subjects (r = 0.95-0.98), but highly variable bias across subjects (mean slope=0.90-1.09). Therefore, both the use of population based blood-plasma and metabolite corrections and the generation of the image-derived whole-blood curve resulted in substantial bias in [ 11 C]MeDAS PET quantification, due to high inter-subject variability. Consequently, when unbiased quantification of [ 11 C]MeDAS PET data is required, individual AIF needs to be used., (Copyright © 2022. Published by Elsevier Inc.)

Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer's Disease in-vivo. However, quantification can be affected by the image processing methodology applied. This study's goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their Native Space and Standard Space; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature. Intensity-related metrics were not substantially affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in Native Space avoiding non-rigid spatial transformations. For analyses in Standard Space, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in Native Space, while intensity-based metrics are more robust against differences in image processing pipelines., Competing Interests: The authors have declared that no competing interests exist.

The estrogen receptor (ER) is a target for endocrine therapy in breast cancer patients. Individual quantification of ERα and ERβ expression, rather than total ER levels, might enable better prediction of the response to treatment. We recently developed the tracer 2- 18 F-fluoro-6-(6-hydroxynaphthalen-2-yl)pyridin-3-ol ( 18 F-FHNP) for assessment of ERβ levels with PET. In the current study, we investigated several pharmacokinetic analysis methods to quantify changes in ERβ availability with 18 F-FHNP PET. Methods: Male nude rats were subcutaneously inoculated in the shoulder with ERα/ERβ-expressing SKOV3 human ovarian cancer cells. Two weeks after tumor inoculation, a dynamic 18 F-FHNP PET scan with arterial blood sampling was acquired from rats treated with vehicle or various concentrations of estradiol (nonspecific ER agonist) or genistein (ERβ-selective agonist). Different pharmacokinetic models were applied to quantify ERβ availability in the tumor. Results: Irreversible-uptake compartmental models fitted the kinetics of 18 F-FHNP uptake better than reversible models. The irreversible 3-tissue-compartment model, which included both the parent and the metabolite input function, gave results comparable to those of the irreversible 2-tissue-compartment model with only a parent input function, indicating that radioactive metabolites contributed little to the tumor uptake. Patlak graphical analysis gave metabolic rates ( K i , the irreversible uptake rate constant) comparable to compartment modeling. The K i values correlated well with ERβ expression but not with ERα, confirming that K i is a suitable parameter to quantify ERβ expression. SUVs at 60 min after tracer injection also correlated ( r 2 = 0.47; P = 0.04) with ERβ expression. A reduction in 18 F-FHNP tumor uptake and K i values was observed in the presence of estradiol or genistein. Conclusion: 18 F-FHNP PET enables assessment of ERβ availability in tumor-bearing rats. The most suitable parameter to quantify ERβ expression is the K i However, a simplified static imaging protocol for determining the SUVs can be applied to assess ERβ levels., (© 2017 by the Society of Nuclear Medicine and Molecular Imaging.)

In recent years, there have been multiple advances in positron emission tomography/computed tomography (PET/CT) that improve cancer imaging. The present generation of PET/CT scanners introduces new hardware, software, and acquisition methods. This review describes these new developments, which include time-of-flight (TOF), point-spread-function (PSF), maximum-a-posteriori (MAP) based reconstruction, smaller voxels, respiratory gating, metal artefact reduction, and administration of quadratic weight-dependent 18 F-fluorodeoxyglucose (FDG) activity. Also, hardware developments such as continuous bed motion (CBM), (digital) solid-state photodetectors and combined PET and magnetic resonance (MR) systems are explained. These novel techniques have a significant impact on cancer imaging, as they result in better image quality, improved small lesion detectability, and more accurate quantification of radiopharmaceutical uptake. This influences cancer diagnosis and staging, as well as therapy response monitoring and radiotherapy planning. Finally, the possible impact of these developments on the European Association of Nuclear Medicine (EANM) guidelines and EANM Research Ltd. (EARL) accreditation for FDG-PET/CT tumor imaging is discussed.