Background: Targeted α particle therapy using long-lived in vivo α particle generators is cytotoxic to target tissues. However, the redistribution of released radioactive daughters through the circulation should be considered. A mathematical model was developed to describe the physicochemical kinetics of 212Pb-labeled pharmaceuticals and its radioactive daughters. Materials and Methods: A bolus of 212Pb-labeled pharmaceuticals injected in a developed compartmental model was simulated. The contributions of chelated and free radionuclides to the total released energy were investigated for different dissociation fractions of 212Bi for different chelators, for example, 36% for DOTA. The compartmental model was applied to describe a 212Bi retention study and to assess the stability of the 212Bi-1,4,7,10-tetrakis(carbamoylmethyl)-1,4,7,10-tetraazacyclododecane (212Bi-DOTAM) complex after β- decay of 212Pb. Results: The simulation of the injection showed that α emissions contribute 75% to the total released energy, mostly from 212Po (72%). The simulation of the 212Bi retention study showed that (16 ± 5)% of 212Bi atoms dissociate from the 212Bi-DOTAM complexes. The fractions of energies released by free radionuclides were 21% and 38% for DOTAM and DOTA chelators, respectively. Conclusion: The developed α particle generator model allows for simulating the radioactive kinetics of labeled and unlabeled pharmaceuticals being released from the chelating system due to a preceding disintegration.

For patients with acute myeloid leukemia, myelodysplastic syndrome, or acute lymphoblastic leukemia, allogeneic hematopoietic cell transplantation (HCT) is a potentially curative treatment. In addition to standard conditioning regimens for HCT, high-dose radioimmunotherapy (RIT) offers the unique opportunity to selectively deliver a high dose of radiation to the bone marrow while limiting side effects. Modification of a CD66b-specific monoclonal antibody (mAb) with a DTPA-based chelating agent should improve the absorbed dose distribution during therapy. The stability and radioimmunoreactive fraction of the radiolabeled mAbs were determined. Before RIT, all patients underwent dosimetry to determine absorbed doses to bone marrow, kidneys, liver, and spleen. Scans were performed twenty-four hours after therapy for quality control. A radiochemical purity of >95% and acceptable radioimmunoreactivity was achieved. Absorbed organ doses for the liver and kidney were consequently improved compared to reported historical data. All patients tolerated RIT well with no treatment-related acute adverse events. Complete remission could be observed in 4/5 of the patients 3 months after RIT. Two patients developed delayed liver failure unrelated to the radioimmunotherapy. The improved conjugation and radiolabeling procedure resulted in excellent stability, radiochemical purity, and CD66-specific radioimmunoreactivity of 90Y-labeled anti-CD66 mAb. RIT followed by conditioning and HCT was well tolerated. Based on these promising initial data, further prospective studies of [90Y]Y-DTPA-Bn-CHX-A″-anti-CD66-mAb-assisted conditioning in HCT are warranted.

Purpose The recent developments of tau-positron emission tomography (tau-PET) enable in vivo assessment of neuropathological tau aggregates. Among the tau-specific tracers, the application of 11C-pyridinyl-butadienyl-benzothiazole 3 (11C-PBB3) in PET shows high sensitivity to Alzheimer disease (AD)-related tau deposition. The current study investigates the regional tau load in patients within the AD continuum, biomarker-negative individuals (BN) and patients with suspected non-AD pathophysiology (SNAP) using 11C-PBB3-PET. Materials and methods A total of 23 memory clinic outpatients with recent decline of episodic memory were examined using 11C-PBB3-PET. Pittsburg compound B (11C-PIB) PET was available for 17, 18F-flurodeoxyglucose (18F-FDG) PET for 16, and cerebrospinal fluid (CSF) protein levels for 11 patients. CSF biomarkers were considered abnormal based on Aβ42 (< 600 ng/L) and t-tau (> 450 ng/L). The PET biomarkers were classified as positive or negative using statistical parametric mapping (SPM) analysis and visual assessment. Using the amyloid/tau/neurodegeneration (A/T/N) scheme, patients were grouped as within the AD continuum, SNAP, and BN based on amyloid and neurodegeneration status. The 11C-PBB3 load detected by PET was compared among the groups using both atlas-based and voxel-wise analyses. Results Seven patients were identified as within the AD continuum, 10 SNAP and 6 BN. In voxel-wise analysis, significantly higher 11C-PBB3 binding was observed in the AD continuum group compared to the BN patients in the cingulate gyrus, tempo-parieto-occipital junction and frontal lobe. Compared to the SNAP group, patients within the AD continuum had a considerably increased 11C-PBB3 uptake in the posterior cingulate cortex. There was no significant difference between SNAP and BN groups. The atlas-based analysis supported the outcome of the voxel-wise quantification analysis. Conclusion Our results suggest that 11C-PBB3-PET can effectively analyze regional tau load and has the potential to differentiate patients in the AD continuum group from the BN and SNAP group.

Background PSMA-TO-1 (“Tumor-Optimized-1”) is a novel PSMA ligand with longer circulation time than PSMA-617. We compared the biodistribution in subcutaneous tumor-bearing mice of PSMA-TO-1, PSMA-617 and PSMA-11 when labeled with 68 Ga and 177 Lu, and the survival after treatment with 225 Ac-PSMA-TO-1/-617 in a murine model of disseminated prostate cancer. We also report dosimetry data of 177 Lu-PSMA-TO1/-617 in prostate cancer patients. Methods First, PET images of 68 Ga-PSMA-TO-1/-617/-11 were acquired on consecutive days in three mice bearing subcutaneous C4-2 xenografts. Second, 50 subcutaneous tumor-bearing mice received either 30 MBq of 177 Lu-PSMA-617 or 177 Lu-PSMA-TO-1 and were sacrificed at 1, 4, 24, 48 and 168 h for ex vivo gamma counting and biodistribution. Third, mice bearing disseminated lesions via intracardiac inoculation were treated with either 40 kBq of 225 Ac-PSMA-617, 225 Ac-PSMA-TO-1, or remained untreated and followed for survival. Additionally, 3 metastatic castration-resistant prostate cancer patients received 500 MBq of 177 Lu-PSMA-TO-1 under compassionate use for dosimetry purposes. Planar images with an additional SPECT/CT acquisition were acquired for dosimetry calculations. Results Tumor uptake measured by PET imaging of 68 Ga-labeled agents in mice was highest using PSMA-617, followed by PSMA-TO-1 and PSMA-11. 177 Lu-PSMA tumor uptake measured by ex vivo gamma counting at subsequent time points tended to be greater for PSMA-TO-1 up to 1 week following treatment ( p > 0.13 at all time points). This was, however, accompanied by increased kidney uptake and a 26-fold higher kidney dose of PSMA-TO-1 compared with PSMA-617 in mice. Mice treated with a single-cycle 225 Ac-PSMA-TO-1 survived longer than those treated with 225 Ac-PSMA-617 and untreated mice, respectively (17.8, 14.5 and 7.7 weeks, respectively; p < 0.0001). Kidney, salivary gland, bone marrow and mean ± SD tumor dose coefficients (Gy/GBq) for 177 Lu-PSMA-TO-1 in patients #01/#02/#03 were 2.5/2.4/3.0, 1.0/2.5/2.3, 0.14/0.11/0.10 and 0.42 ± 0.03/4.45 ± 0.07/1.8 ± 0.57, respectively. Conclusions PSMA-TO-1 tumor uptake tended to be greater than that of PSMA-617 in both preclinical and clinical settings. Mice treated with 225 Ac-PSMA-TO-1 conferred a significant survival benefit compared to 225 Ac-PSMA-617 despite the accompanying increased kidney uptake. In humans, PSMA-TO-1 dosimetry estimates suggest increased tumor absorbed doses; however, the kidneys, salivary glands and bone marrow are also exposed to higher radiation doses. Thus, additional preclinical studies are needed before further clinical use.

Ziel/Aim Ziel dieser Studie war es, die Genauigkeit der zeitintegrierten Aktivitätskoeffizienten (TIAC) für die Therapieplanung vor PRRT bzw. der Dosimetrie bei PPRT zu untersuchen, die mit einem Messwert und einem physiologisch basierten pharmakokinetischen (PBPK) Modell im Rahmen der NLME („non-linear mixed effects“)-Modellierung bestimmt wurden.

Ziel/Aim Bi-213-markierte PSMA Liganden sind interessante Kandidaten für die intra-arterielle Radioligandentherapie, da sie eine hohe Affinität für PSMA aufweisen und kleinere Mengen von Alpha-Emitter-markiertem Liganden bereits therapeutische Energiedosen (ED) liefern könnten. Ziel dieser Arbeit war es, das Potenzial der intra-arteriellen Prostatakrebstherapie mit Bi-213-PSMA-Liganden anhand eines PBPK-Modells und dynamischer PET/MR-Daten quantitativ zu untersuchen.

Abstract Background The calculation of time-integrated activities (TIAs) for tumours and organs is required for dosimetry in molecular radiotherapy. The accuracy of the calculated TIAs is highly dependent on the chosen fit function. Selection of an adequate function is therefore of high importance. However, model (i.e. function) selection works more accurately when more biokinetic data are available than are usually obtained in a single patient. In this retrospective analysis, we therefore developed a method for population-based model selection that can be used for the determination of individual time-integrated activities (TIAs). The method is demonstrated at an example of [177Lu]Lu-PSMA-I&T kidneys biokinetics. It is based on population fitting and is specifically advantageous for cases with a low number of available biokinetic data per patient. Methods Renal biokinetics of [177Lu]Lu-PSMA-I&T from thirteen patients with metastatic castration-resistant prostate cancer acquired by planar imaging were used. Twenty exponential functions were derived from various parameterizations of mono- and bi-exponential functions. The parameters of the functions were fitted (with different combinations of shared and individual parameters) to the biokinetic data of all patients. The goodness of fits were assumed as acceptable based on visual inspection of the fitted curves and coefficients of variation CVs < 50%. The Akaike weight (based on the corrected Akaike Information Criterion) was used to select the fit function most supported by the data from the set of functions with acceptable goodness of fit. Results The function $$A_{1} { }\beta { }e^{{ - \left( {\lambda_{1} + \lambda_{{{\text{phys}}}} } \right)t}} + A_{1} { }\left( {1 - \beta } \right){ }e^{{ - \left( {\lambda_{{{\text{phys}}}} } \right)t}}$$ A 1 β e - λ 1 + λ phys t + A 1 1 - β e - λ phys t with shared parameter $$\beta$$ β was selected as the function most supported by the data with an Akaike weight of 97%. Parameters $$A_{1}$$ A 1 and $$\lambda_{1}$$ λ 1 were fitted individually for every patient while parameter $$\beta { }$$ β was fitted as a shared parameter in the population yielding a value of 0.9632 ± 0.0037. Conclusions The presented population-based model selection allows for a higher number of parameters of investigated fit functions which leads to better fits. It also reduces the uncertainty of the obtained Akaike weights and the selected best fit function based on them. The use of the population-determined shared parameter for future patients allows the fitting of more appropriate functions also for patients for whom only a low number of individual data are available.

1435 Aim: Model selection is important to ensure that the used function could approximate the reality given by the observed data [1,2]. In this study, we develop an algorithm to be used to perform model selection for the determination of the time-integrated activity coefficients (TIACs) and demonstrate it at an example of 177Lu-PSMA kidneys biokinetics. The algorithm is based on population fitting, i.e. simultaneous fitting of all patients together, and is specifically advantageous for cases with a low number of available biokinetic data. Methods: Biokinetic data of 177Lu-PSMA in kidneys were collected from 13 patients with metastatic prostate cancer. Twenty exponential functions derived from various parameterizations of a mono- (A1e-λ1+λphyst) and a bi-exponential function (A1e-λ1+λphyst+A2e-λphyst ) were used as the model set for the model selection. The parameters of the functions with different combinations of shared parameters and individual parameter estimations were fitted to the data simultaneously. The goodness of the fits (visual inspection and coefficient of variation CV<50% [3]) were used to test the quality of the fits. The corrected Akaike Information Criterion (AICc) weight [2] was used to select the fit function most supported by the data from the set of functions with acceptable goodness of fit. Results: The function A1 αe-λ1+λphyst+A1 1-αe-λphyst with a shared parameter α was selected as the model best supported by the data (AICc weight=97%) from those fit functions found to have an acceptable fit based on the goodness of fit criteria. In this function, the A1 and λ1 parameters were fitted individually for each patient while parameter α was fitted as a shared parameter in the population with the estimated value of 0.963±0.004. Conclusions: An algorithm to define an adequate fit function (to be used for future patients) based on a relatively low number of data was developed. Based on our results, the function A1 αe-λ1+λphyst+A1 1-αe-λphyst with a fix parameter α can be used to estimate the TIACs for patients with a low number of data, e.g. three biokinetic data, with an individual estimation of A1 and λ1 and fixing α to 0.963. References: 1. Burnham KP, Anderson DR. Model Selection and Multimodel Inference: Springer-Verlag New York; 2002. 2. Glatting G, Kletting P, Reske SN, Hohl K, Ring C. Choosing the optimal fit function: comparison of the Akaike information criterion and the F-test. Med Phys. 2007;34(11):4285-92. 3. Kletting P, Schimmel S, Kestler HA, Hanscheid H, Luster M, Fernandez M, Broer JH, Nosske D, Lassmann M, Glatting G. Molecular radiotherapy: the NUKFIT software for calculating the time-integrated activity coefficient. Med Phys. 2013;40(10):102504.

Introduction/Aim: α particle emitting bismuth (212Bi) as decay product of 212Pb-labeled pharmaceuticals has been effective in targeted α particle therapy (TAT). Estimating the contribution of 212Bi released from its chelator to the absorbed doses in nontarget tissues is challenging in TAT. Physiologically based pharmacokinetic (PBPK) modeling can help overcome this limitation. Therefore, a whole-body 212Bi-PBPK model was developed to describe the pharmacokinetics (PKs) of 212Bi in rats. Materials and Methods: The rat 212Bi-PBPK model was implemented using the modeling software SAAM II with data and parameter values from the literature. Besides other mechanisms, 212Bi interactions with red blood cells, high molecular weight plasma protein, and intracellular biological thiols are described. Important PK parameters were fitted to time-activity data. Absorbed dose coefficients (ADCs) were calculated for injecting 0.774 fmol of 212Bi. Results: 212Bi uptake rates of liver, bone, small intestine, bone marrow, skin, and muscle were (0.86 ± 0.13), (3.85 ± 0.63), (0.27 ± 0.05), (1.44 ± 0.29), (0.04 ± 0.01), and (0.007 ± 0.007) per min with corresponding ADCs of 0.09, 0.03, 0.03, 0.07, 0.01, and 0.003 mGy/kBq, respectively. An ADC of 0.70 mGy/kBq was determined for kidneys. Conclusion: Kidneys are the dose-limiting organs in 212Bi-based TAT. The 212Bi-PBPK model is an effective tool to investigate the 212Bi biodistribution in murine models. Integrating the 212Bi-PBPK model into other murine and human PBPK models of α particle generators can help study the efficacy and safety of TAT.

Ziel/Aim Die CD66-Antigen-Radioimmuntherapie (RIT) ist ein nebenwirkungsarmes Verfahren, dass vor der Stammzelltransplantation (SZT) bei Patienten mit myelodysplastischem Syndrom (MDS) oder akuter myeloischer Leukämie (AML) durchgeführt wird. Dabei wird selektiv eine hohe Strahlendosis an das rote Knochenmark (rKM) abgegeben. Hier berichten wir über die in-vitro-Charakteristika und die erfolgreiche klinische Translation des Y-90-markierten Anti-CD66-mAk.

Ziel/Aim In dieser Studie implementierten wir eine Globale Sensitivitätsanalyse (GSA) und ein physiologisch basiertes pharmakokinetisches (PBPK) Modell, um die wichtigsten physiologischen Parameter für die Bestimmung der individuellen Nieren- und Tumor-Dosen in der Lu-177-PSMA-Therapie zu identifizieren.

1578 Aim: Alpha emitter-based peptide receptor radionuclide therapy (α-PRRT) is an effective treatment for metastatic inoperable neuroendocrine tumors (NETs). 212Pb serves as a promising in vivo source of the short-lived alpha emitter 212Bi. Application of cytotoxic alpha particles of high linear energy transfer reduces nephrotoxicity and facilitates the overcoming of radioresistance of NETs to beta emitters in PRRT. However, quantitative analysis of the biodistribution of in vivo alpha generators and cytotoxic alpha emitting daughters in the body and their contribution to the total tissue-absorbed doses is essential to assess the efficacy and safety of α-PRRT. Mathematical modeling enables cost-free, animal-free studies of the pharmacokinetics of in vivo alpha generators targeting the somatostatin receptor type 2 (sstr2). Therefore, a first physiologically-based pharmacokinetic (PBPK) model for describing the pharmacokinetics and dosimetry of in vivo alpha generators and their radioactive products is presented for xenografted mice in α-PRRT. Methods: A whole-body 212Pb-PBPK model of in vivo alpha generator in mice was developed and implemented in both modeling software SAAM II version 2.3 (The Epsilon Group, TEG, USA) and Simbiology/MATLAB (MATLAB R2020a, The MathWorks, Inc). The 212Pb-PBPK model describes all relevant physiological mechanisms (blood flow, diffusion, specific and non-specific uptakes, internalization, recycling and excretion) and physicochemical properties (physical decay and radiolabeling stability) with parameter values from the literature. For validation, the time activity data were simulated in both programs and compared for the same parameterization and model input. The PK parameters in the 212Pb-PBPK model were estimated using [212Pb]Pb-DOTAMTATE biokinetic data in mice (n = 5) bearing 300 mm3 AR42J rat xenograft after intravenous administration of 0.0013 nmol (0.169 MBq) of [212Pb]Pb-DOTAMTATE [1]. Dosimetry simulations for bound and unbound in vivo generators and free radionuclides were performed in Simbiology after integrating a 212Bi-PBPK model into the evaluated 212Pb-PBPK model. Results: The developed model could successfully describe the experimental data in both programs. The fitted curves were good by visual inspection. The simulation results of both programs were quite similar with a relative deviation of 1 %. The tumor plasma flow-rate were (0.25 ± 0.20) ml/min/g. The sstr2 densities in tumor, kidneys, liver, pancreas, spleen and lung were (6.1 ± 0.9), (3.0 ± 0.3), (0.10 ± 0.02), (4.0 ± 1.1), (0.56 ± 0.04), (1.39 ± 0.04) nmol/l, with absorbed dose coefficients (ADC) of 0.10, 0.06, 0.004, 0.06, 0.01, and 0.03 Gy/kBq, respectively. Conclusions: The developed 212Pb-PBPK model allows for simulating the biokinetics of in vivo alpha particle generators targeting sstr2. The 212Pb-PBPK model can address concerns about the fate of the distributed free radioactive daughters and their contribution to the overall absorbed dose to non-target tissues. The ability of the model to estimate important physiological parameters and subsequently predict optimal dosing regimens will reduce the required time for translation from bench to bedside. Also, the model allows for generating hypotheses for experiments leading to improve α-PRRT for NET. [1]. Stallons, T. A. R., et al. (2019). Molecular Cancer Therapeutics 18(5): 1012-1021.

Ziel/Aim Die Radioimmunreaktivität, d.h. der bindungsfähige Anteil von radiomarkierten Antikörpern, ist eine entscheidende Einflussgröße auf die Pharmakokinetik und bestimmt damit die Energiedosis des Zielorgans und der Risikoorgane bei Radioimmuntherapien. Am Beispiel eines DTPA-gekoppelten CEACAM8-spezifischen Antikörpers für die Intensivierung der Konditionierung für Hochrisiko-Leukämiepatienten wird eine optimierte Bestimmung der Radioimmunreaktivität vorgestellt.

Purpose: Quantification of tau load using C-11-PBB3-PET has the potential to improve diagnosis of neurodegenerative diseases. Although MRI-based pre-processing is used as a reference method, not all patients have MRI. The feasibility of a PET-based pre-processing for the quantification of C-11-PBB3 tracer was evaluated and compared with the MRI-based method. Materials and methods: Fourteen patients with decreased recent memory were examined with C-11-PBB3-PET and MRI. The PET scans were visually assessed and rated as either PBB3(+) or PBB3(-). The image processing based on the PET-based method was validated against the MRI-based approach. The regional uptakes were quantified using the Mesial-temporal/Temporoparietal/Rest of neocortex (MeTeR) regions. SUVR values were calculated by normalizing to the cerebellar reference region to compare both methods within the patient groups. Results: Significant correlations were observed between the SUVRs of the MRI-based and the PET-based methods in the MeTeR regions (r(Me) = 0.91; r(Te) = 0.98; r(R) = 0.96; p < 0.0001). However, the Bland-Altman plot showed a significant bias between both methods in the subcortical Me region (bias: -0.041; 95% CI: -0.061 to -0.024; p = 0.003). As in the MRI-based method, the 11C-PBB3 uptake obtained with the PET-based method was higher for the PBB3(+) group in each of the cortical regions and for the whole brain than for the PBB3(-) group (PET-based(Global): 1.11 vs. 0.96; Cliff's Delta (d) = 0.68; p = 0.04; MRI-based(Global): 1.11 vs. 0.97; d = 0.70; p = 0.03). To differentiate between positive and negative scans, Youden's index estimated the best cut-off of 0.99 from the ROC curve with good accuracy (AUC: 0.88 +/- 0.10; 95% CI: 0.67-1.00) and the same sensitivity (83%) and specificity (88%) for both methods. Conclusion: The PET-based pre-processing method developed to quantify the tau burden with 11C-PBB3 provided comparable SUVR values and effect sizes as the MRI-based reference method. Furthermore, both methods have a comparable discrimination accuracy between PBB3(+) and PBB3(-) groups as assessed by visual rating. Therefore, the presented PET-based method can be used for clinical diagnosis if no MRI image is available.