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Background: 89Zirconium-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. Methods: The 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. Results: 89Zr-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. Conclusion: The 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. [ABSTRACT FROM AUTHOR]

Background: PET scans using zirconium-89 labelled monoclonal antibodies (89Zr-mAbs), known as 89Zr-immuno-PET, are made to measure uptake in tumour and organ tissue. Uptake is related to the supply of 89Zr-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 89Zr-immuno-PET scans. Methods: PET imaging and blood sampling of two 89Zr-mAbs were included, 89Zr-cetuximab and 89Zr-durvalumab. For seven patients receiving 89Zr-cetuximab, PET scans on 1–2 h, 2 and 6 days post-injection (p.i.) were analysed. Five patients received three injections of 89Zr-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 89Zr-cetuximab and 89Zr-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 89Zr-cetuximab and 89Zr-durvalumab, respectively. Conclusions: Image-derived blood concentrations should be obtained from delineating the ascending aorta in 89Zr-immuno-PET scans, as this results in the lowest variability with respect to sample-derived blood concentrations. [ABSTRACT FROM AUTHOR]

Simple Summary: The uptake on a 89Zr-immuno-PET scan is not just the result of the binding of a radiolabeled antibody with its target (i.e., target engagement) but also includes background factors such as non-specific binding (for example, catabolism of antibodies inside endothelial cells). In this study, we wanted to isolate target engagement. We used data from five previously performed 89Zr-immuno-PET studies with immune-targeting 89Zr-radiolabeled antibodies. First, via Patlak analysis, we separated reversible from irreversible uptake, and by using a baseline of target-negative organs, we further defined target-specific irreversible uptake. Second, we compared different mass doses (ratios of labeled and unlabeled antibody) and looked for saturation effects. Evidence for target engagement was based on the following two things: (1) when the target-specific irreversible uptake exceeded the baseline, and (2) when the signal showed saturation. We found target engagement for the different antibodies in several lymphoid organs, for example, in the spleen, while the brain had close to zero target engagement. We propose a new baseline for bone marrow and brain. In conclusion, we promote the use of Patlak analysis for 89Zr-immuno-PET studies, or similar simplified outcomes such as a tissue-to-blood ratio. Introduction: 89Zr-immuno-PET (positron emission tomography with zirconium-89-labeled monoclonal antibodies ([89Zr]Zr-mAbs)) can be used to study the biodistribution of mAbs targeting the immune system. The measured uptake consists of target-specific and non-specific components, and it can be influenced by plasma availability of the tracer. To find evidence for target-specific uptake, i.e., target engagement, we studied five immune-checkpoint-targeting [89Zr]Zr-mAbs to (1) compare the uptake with previously reported baseline values for non-specific organ uptake (ns-baseline) and (2) look for saturation effects of increasing mass doses. Method: 89Zr-immuno-PET data from five [89Zr]Zr-mAbs, i.e., nivolumab and pembrolizumab (anti-PD-1), durvalumab (anti-PD-L1), BI 754,111 (anti-LAG-3), and ipilimumab (anti-CTLA-4), were analysed. For each mAb, 2–3 different mass doses were evaluated. PET scans and blood samples from at least two time points 24 h post injection were available. In 35 patients, brain, kidneys, liver, spleen, lungs, and bone marrow were delineated. Patlak analysis was used to account for differences in plasma activity concentration and to quantify irreversible uptake (Ki). To identify target engagement, Ki values were compared to ns-baseline Ki values previously reported, and the effect of increasing mass doses on Ki was investigated. Results: All mAbs, except ipilimumab, showed Ki values in spleen above the ns-baseline for the lowest administered mass dose, in addition to decreasing Ki values with higher mass doses, both indicative of target engagement. For bone marrow, no ns-baseline was established previously, but a similar pattern was observed. For kidneys, most mAbs showed Ki values within the ns-baseline for both low and high mass doses. However, with high mass doses, some saturation effects were seen, suggestive of a lower ns-baseline value. Ki values were near zero in brain tissue for all mass doses of all mAbs. Conclusion: Using Patlak analysis and the established ns-baseline values, evidence for target engagement in (lymphoid) organs for several immune checkpoint inhibitors could be demonstrated. A decrease in the Ki values with increasing mass doses supports the applicability of Patlak analysis for the assessment of target engagement for PET ligands with irreversible uptake behavior. [ABSTRACT FROM AUTHOR]

Purpose: Positron emission tomography imaging of zirconium-89-labelled monoclonal antibodies (89Zr-Immuno-PET) allows for visualisation and quantification of antibody uptake in tumours in vivo. Patlak linearization provides distribution volume (VT) and nett influx rate (Ki) values, representing reversible and irreversible uptake, respectively. Standardised uptake value (SUV) and tumour-to-plasma/tumour-to-blood ratio (TPR/TBR) are often used, but their validity depends on the comparability of plasma kinetics and clearances. This study assesses the validity of SUV, TPR and TBR against Patlak Ki for quantifying irreversible 89Zr-Immuno-PET uptake in tumours. Methods: Ten patients received 37 MBq 10 mg 89Zr-anti-EGFR with 500 mg/m2 unlabelled mAbs. Five patients received two doses of 37 MBq 89Zr-anti-HER3: 8–24 mg for the first administration and 24 mg–30 mg/kg for the second. Seven tumours from four patients showed 89Zr-anti-EGFR uptake, and 18 tumours from five patients showed 89Zr-anti-HER3 uptake. SUVpeak, TPRpeak and TBRpeak values were obtained from one to six days p.i. Patlak linearization was applied to tumour time activity curves and plasma samples to obtain Ki. Results: For 89Zr-anti-EGFR, there was a small variability along the linear regression line between SUV (− 0.51–0.57), TPR (− 0.06‒0.11) and TBR (− 0.13‒0.16) on day 6 versus Ki. Similar doses of 89Zr-anti-HER3 showed similar variability for SUV (− 1.3‒1.0), TPR (− 1.1‒0.53) and TBR (− 1.5‒0.72) on day 5 versus Ki. However, for the second administration of 89Zr-anti-HER3 with a large variability in administered mass doses, SUV showed a larger variability (− 1.4‒2.3) along the regression line with Ki, which improved when using TPR (− 0.38–0.32) or TBR (− 0.56‒0.46). Conclusion: SUV, TPR and TBR at late time points were valid for quantifying irreversible lesional 89Zr-Immuno-PET uptake when constant mass doses were administered. However, for variable mass doses, only TPR and TBR provided reliable values for irreversible uptake, but not SUV, because SUV does not take patient and mass dose-specific plasma clearance into account. [ABSTRACT FROM AUTHOR]

Purpose: Zirconium-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. Methods: Based 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. Results: Simulations 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. Conclusion: Inclusion 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. [ABSTRACT FROM AUTHOR]