Explore the vast range of titles available.

Purpose PET quantification based on standardized uptake values (SUV) is hampered by several factors, in particular by variability in PET acquisition settings and data analysis methods. Quantitative PET/CT studies acquired during a multicentre trial require harmonization of imaging procedures to maximize study power. The aims of this study were to determine which phantoms are most suitable for detecting differences in image quality and quantification, and which methods for defining volumes of interest (VOI) are least sensitive to these differences. Methods The most common accreditation phantoms used in oncology FDG PET/CT trials were scanned on the same scanner. These phantoms were those used by the Society of Nuclear Medicine Clinical Trials Network (SNM-CTN), the European Association of Nuclear Medicine/National Electrical Manufacturers Association (EANM/NEMA) and the American College of Radiology (ACR). In addition, tumour SUVs were derived from ten oncology whole-body examinations performed on the same PET/CT system. Both phantom and clinical data were reconstructed using different numbers of iterations, subsets and time-of-flight kernel widths. Subsequently, different VOI methods (VOI A50%, VOI max , VOI 3Dpeak, VOI 2Dpeak ) were applied to assess the impact of changes in image reconstruction settings on SUV and recovery coefficients (RC). Results All phantoms demonstrated sensitivity for detecting changes in SUV and RC measures in response to changes in image reconstruction settings and VOI analysis methods. The SNM-CTN and EANM/NEMA phantoms showed almost equal sensitivity in detecting RC differences with changes in image characteristics. Phantom and clinical data demonstrated that the VOI analysis methods VOI A50% and VOI max gave SUV and RC values with large variability in relation to image characteristics, whereas VOI 3Dpeak and VOI 2Dpeak were less sensitive to these differences. Conclusion All three phantoms may be used to harmonize parameters for data acquisition, processing and analysis. However, the SNM-CTN and EANM/NEMA phantoms are the most sensitive to parameter changes and are suitable for harmonizing SUV quantification based on 3D VOIs, such as VOI A50% and VOI 3Dpeak , and VOI max . Variability in SUV quantification after harmonization could be further minimized using VOI 3Dpeak analysis, which was least sensitive to residual variability in image quality and quantification.

In oncology drug development, measuring drug concentrations at the tumor site and at the targeted receptor remains an ongoing challenge. Positron emission tomography (PET)‐imaging is a promising noninvasive method to quantify intratumor exposure of a radiolabeled drug (biodistribution data) and target saturation by treatment doses in vivo. Here, we present the development and application of a minimal physiologically‐based pharmacokinetic (mPBPK) modeling approach to integrate biodistribution data in a quantitative platform to characterize and predict intratumor exposure and receptor occupancy (RO) of BI 754111, an IgG‐based anti‐lymphocyte‐activation gene 3 (LAG‐3) monoclonal antibody (mAb). Specifically, calibration and qualification of the predictions were performed using 89Zr‐labeled BI 754111 biodistribution data, that is, PET‐derived intratumor drug concentration data, tumor‐to‐plasma ratios, and data from Patlak analyses. The model predictions were refined iteratively by the inclusion of additional biological processes into the model structure and the use of sensitivity analyses to assess the impact of model assumptions and parameter uncertainty on the predictions and model robustness. The developed mPBPK model allowed an adequate description of observed tumor radioactivity concentrations and tumor‐to‐plasma ratios leading to subsequent adequate prediction of LAG‐3 RO at different dose levels. In the future, the developed model could be used as a platform for the prediction and analysis of biodistribution data for other mAbs and may ultimately support dose optimization by identifying dosages resulting in saturated RO.

Background Distribution of mAbs into tumour tissue may occur via different processes contributing differently to the 89 Zr-mAb uptake on PET. Target-specific binding in tumours is of main interest; however, non-specific irreversible uptake may also be present, which influences quantification. The aim was to investigate the presence of non-specific irreversible uptake in tumour tissue using Patlak linearization on 89 Zr-immuno-PET data of biopsy-proven target-negative tumours. Data of two studies, including target status obtained from biopsies, were retrospectively analysed, and Patlak linearization provided the net rate of irreversible uptake ( K i ). Results Two tumours were classified as CD20-negative and two as CD20-positive. Four tumours were classified as CEA-negative and nine as CEA-positive. K i values of CD20-negative (0.43 µL/g/h and 0.92 µL/g/h) and CEA-negative tumours (mdn = 1.97 µL/g/h, interquartile range (IQR) = 1.50–2.39) were higher than zero. Median K i values of target-negative tumours were lower than CD20-positive (1.87 µL/g/h and 1.90 µL/g/h) and CEA-positive tumours (mdn = 2.77 µL/g/h, IQR = 2.11–3.65). Conclusion Biopsy-proven target-negative tumours showed irreversible uptake of 89 Zr-mAbs measured in vivo using 89 Zr-immuno-PET data, which suggests the presence of non-specific irreversible uptake in tumours. Consequently, for 89 Zr-immuno-PET, even if the target is absent, a tumour-to-plasma ratio always increases over time.

Immune-based treatment approaches are successfully used for the treatment of patients with cancer. While such therapies can be highly effective, many patients fail to benefit. To provide optimal therapy choices and to predict treatment responses, reliable biomarkers for the assessment of immune features in patients with cancer are of significant importance. Biomarkers (BM) that enable a comprehensive and repeatable assessment of the tumor microenvironment (TME), the lymphoid system, and the dynamics induced by drug treatment can fill this gap. Medical imaging, notably positron emission tomography (PET) and magnetic resonance imaging (MRI), providing whole-body imaging BMs, might deliver such BMs. However, those imaging BMs must be well characterized as being ‘fit for purpose’ for the intended use. This review provides an overview of the key steps involved in the development of ‘fit-for-purpose’ imaging BMs applicable in drug development, with a specific focus on pharmacodynamic biomarkers for assessing the TME and its modulation by immunotherapy. The importance of the qualification of imaging BMs according to their context of use (COU) as defined by the Food and Drug Administration ( FDA ) and National Institutes of Health Biomarkers, EndpointS, and other Tools ( BEST ) glossary is highlighted. We elaborate on how an imaging BM qualification for a specific COU can be achieved.

Background The aim of the present study was to investigate microglia activation over time following traumatic brain injury (TBI) and to relate these findings to glutamate release. Procedures Sequential dynamic (R) -[ 11 C]PK11195 PET scans were performed in rats 24 hours before (baseline), and one and ten days after TBI using controlled cortical impact, or a sham procedure. Extracellular fluid (ECF) glutamate concentrations were measured using cerebral microdialysis. Brains were processed for histopathology and (immuno)-histochemistry. Results Ten days after TBI, (R) -[ 11 C]PK11195 binding was significantly increased in TBI rats compared with both baseline values and sham controls (p < 0.05). ECF glutamate values were increased immediately after TBI (27.6 ± 14.0 μmol·L -1 ) as compared with the sham procedure (6.4 ± 3.6 μmol·L -1 ). Significant differences were found between TBI and sham for ED-1, OX-6, GFAP, Perl's, and Fluoro-Jade B. Conclusions Increased cerebral uptake of (R) -[ 11 C]PK11195 ten days after TBI points to prolonged and ongoing activation of microglia. This activation followed a significant acute posttraumatic increase in ECF glutamate levels.

PurposeZirconium-89-immuno-positron emission tomography (89Zr-immuno-PET) has enabled visualization of zirconium-89 labelled monoclonal antibody (89Zr-mAb) uptake in organs and tumors in vivo. Patlak linearization of 89Zr-immuno-PET quantification data allows for separation of reversible and irreversible uptake, by combining multiple blood samples and PET images at different days. As one can obtain only a limited number of blood samples and scans per patient, choosing the optimal time points is important. Tissue activity concentration curves were simulated to evaluate the effect of imaging time points on Patlak results, considering different time points, input functions, noise levels and levels of reversible and irreversible uptake.MethodsBased on 89Zr-mAb input functions and reference values for reversible (VT) and irreversible (Ki) uptake from literature, multiple tissue activity curves were simulated. Three different 89Zr-mAb input functions, five time points between 24 and 192 h p.i., noise levels of 5, 10 and 15%, and three reference Ki and VT values were considered. Simulated Ki and VT were calculated (Patlak linearization) for a thousand repetitions. Accuracy and precision of Patlak linearization were evaluated by comparing simulated Ki and VT with reference values.ResultsSimulations showed that Ki is always underestimated. Inclusion of time point 24 h p.i. reduced bias and variability in VT, and slightly reduced bias and variability in Ki, as compared to combinations of three later time points. After inclusion of 24 h p.i., minimal differences were found in bias and variability between different combinations of later imaging time points, despite different input functions, noise levels and reference values.ConclusionInclusion of a blood sample and PET scan at 24 h p.i. improves accuracy and precision of Patlak results for 89Zr-immuno-PET; the exact timing of the two later time points is not critical.

BackgroundIn patients with locally advanced unresectable non-small cell lung cancer (NSCLC), durvalumab, an anti-programmed cell death ligand-1 (PD-L1) antibody, has shown improved overall survival when used as consolidation therapy following concurrent chemoradiotherapy (CRT). However, it is unclear whether CRT itself upregulates PD-L1 expression. Therefore, this study aimed to explore the changes in the uptake of the anti PD-L1 antibody [89Zr]Zr-durvalumab in tumors and healthy organs during CRT in patients with NSCLC.MethodsPatients with NSCLC scheduled to undergo CRT were scanned 7±1 days after administration of 37±1 MBq [89Zr]Zr-durvalumab at baseline, 1-week on-treatment and 1 week after finishing 6 weeks of CRT. First, [89Zr]Zr-durvalumab uptake was visually assessed in a low dose cohort with a mass dose of 2 mg durvalumab (0.13% of therapeutic dose) and subsequently, quantification was done in a high dose cohort with a mass dose of 22.5 mg durvalumab (1.5% of therapeutic dose). Tracer pharmacokinetics between injections were compared using venous blood samples drawn in the 22.5 mg cohort. Visual assessment included suspected lesion detectability. Positron emission tomography (PET) uptake in tumoral and healthy tissues was quantified using tumor to plasma ratio (TPR) and organ to plasma ratio, respectively.ResultsIn the 2 mg dose cohort, 88% of the 17 identified tumor lesions were positive at baseline, compared with 69% (9/13) for the 22.5 mg cohort. Although the absolute plasma concentrations between patients varied, the intrapatient variability was low. The ten quantitatively assessed lesions in the 22.5 mg cohort had a median TPR at baseline of 1.3 (IQR 0.7–1.5), on-treatment of 1.0 (IQR 0.7–1.4) and at the end of treatment of 0.7 (IQR 0.6–0.7). On-treatment, an increased uptake in bone marrow was seen in three out of five patients together with a decreased uptake in the spleen in four out of five patients.ConclusionsThis study successfully imaged patients with NSCLC with [89Zr]Zr-durvalumab PET before and during CRT. Our data did not show any increase in [89Zr]Zr-durvalumab uptake in the tumor 1-week on-treatment and at the end of treatment. The changes observed in bone marrow and spleen may be due to an CRT-induced effect on immune cells.Trial registration numberEudraCT number: 2019-004284-51

Background89Zirconium-immuno-positron emission tomography (89Zr-immuno-PET) is used for assessment of target status to guide antibody-based therapy. We aim to determine the relation between antibody tumor uptake and target concentration to improve future study design and interpretation. MethodsThe relation between tumor uptake and target concentration was predicted by mathematical modeling of 89Zr-labeled antibody disposition in the tumor. Literature values for trastuzumab kinetics were used to provide an example.Results89Zr-trastuzumab uptake initially increases with increasing target concentration, until it levels off to a constant value. This is determined by the total administered mass dose of trastuzumab. For a commonly used imaging dose of 50 mg 89Zr-trastuzumab, uptake can discriminate between immunohistochemistry score (IHC) 0 versus 1–2–3. ConclusionThe example for 89Zr-trastuzumab illustrates the potential to assess target expression. The pitfall of false-positive findings depends on the cut-off to define clinical target positivity (i.e., IHC 3) and the administered mass dose.

IntroductionThe assessment of ex vivo biodistribution is the preferred method for quantification of radiotracers biodistribution in preclinical models, but is not in line with current ethics on animal research. PET imaging allows for noninvasive longitudinal evaluation of tracer distribution in the same animals, but systemic comparison with ex vivo biodistribution is lacking. Our aim was to evaluate the potential of preclinical PET imaging for accurate tracer quantification, especially in tumor models.MethodsNEMA NU 4-2008 phantoms were filled with 11C, 68Ga, 18F, or 89Zr solutions and scanned in Mediso nanoPET/CT and PET/MR scanners until decay. N87 tumor-bearing mice were i.v. injected with either [18F]FDG (~ 14 MBq), kept 50 min under anesthesia followed by imaging for 20 min, or with [89Zr]Zr-DFO-NCS-trastuzumab (~ 5 MBq) and imaged 3 days post-injection for 45 min. After PET acquisition, animals were killed and organs of interest were collected and measured in a γ-counter to determine tracer uptake levels. PET data were reconstructed using TeraTomo reconstruction algorithm with attenuation and scatter correction and regions of interest were drawn using Vivoquant software. PET imaging and ex vivo biodistribution were compared using Bland–Altman plots.ResultsIn phantoms, the highest recovery coefficient, thus the smallest partial volume effect, was obtained with 18F for both PET/CT and PET/MR. Recovery was slightly lower for 11C and 89Zr, while the lowest recovery was obtained with 68Ga in both scanners. In vivo, tumor uptake of the 18F- or 89Zr-labeled tracer proved to be similar irrespective whether quantified by either PET/CT and PET/MR or ex vivo biodistribution with average PET/ex vivo ratios of 0.8–0.9 and a deviation of 10% or less. Both methods appeared less congruent in the quantification of tracer uptake in healthy organs such as brain, kidney, and liver, and depended on the organ evaluated and the radionuclide used.ConclusionsOur study suggests that PET quantification of 18F- and 89Zr-labeled tracers is reliable for the evaluation of tumor uptake in preclinical models and a valuable alternative technique for ex vivo biodistribution. However, PET and ex vivo quantification require fully described experimental and analytical procedures for reliability and reproducibility.

Background PET scans using zirconium-89 labelled monoclonal antibodies ( 89 Zr-mAbs), known as 89 Zr-immuno-PET, are made to measure uptake in tumour and organ tissue. Uptake is related to the supply of 89 Zr-mAbs in the blood. Measuring activity concentrations in blood, however, requires invasive blood sampling. This study aims to identify the best delineation strategy to obtain the image-derived blood concentration (IDBC) from 89 Zr-immuno-PET scans. Methods PET imaging and blood sampling of two 89 Zr-mAbs were included, 89 Zr-cetuximab and 89 Zr-durvalumab. For seven patients receiving 89 Zr-cetuximab, PET scans on 1–2 h, 2 and 6 days post-injection (p.i.) were analysed. Five patients received three injections of 89 Zr-durvalumab. The scanning protocol for the first two injections consisted of PET scanning on 2, 5 and 7 days p.i. and for the third injection only on 7 days p.i. Blood samples were drawn with every PET scan and the sample-derived blood concentration (SDBC) was used as gold standard for the IDBC. According to an in-house developed standard operating procedure, the aortic arch, ascending aorta, descending aorta and left ventricle were delineated. Bland–Altman analyses were performed to assess the bias (mean difference) and variability (1.96 times the standard deviation of the differences) between IDBC and SDBC. Results Overall, the activity concentration obtained from the IDBC was lower than from the SDBC. When comparing IDBC with SDBC, variability was smallest for the ascending aorta (20.3% and 17.0% for 89 Zr-cetuximab and 89 Zr-durvalumab, respectively). Variability for the other regions ranged between 17.9 and 30.8%. Bias for the ascending aorta was − 10.9% and − 11.4% for 89 Zr-cetuximab and 89 Zr-durvalumab, respectively. Conclusions Image-derived blood concentrations should be obtained from delineating the ascending aorta in 89 Zr-immuno-PET scans, as this results in the lowest variability with respect to sample-derived blood concentrations.