Biodistribution and dosimetry for combined [177Lu]Lu-PSMA-I&T/[225Ac]Ac-PSMA-I&T therapy using multi-isotope quantitative SPECT imaging.

PURPOSE: Quantitative SPECT for patient-specific dosimetry is a valuable tool in the scope of radionuclide therapy, although its clinical application for 225Ac-based treatments may be limited due to low therapeutic activities. Therefore, the aim of this study was to demonstrate the feasibility of clinical quantitative low-count SPECT imaging during [177Lu]Lu-PSMA-I&T/[225Ac]Ac-PSMA-I&T treatment. METHODS: Eight prostate cancer patients (1000 MBq/8 MBq [177Lu]Lu-PSMA-I&T/[225Ac]Ac-PSMA-I&T) received a single-bed quantitative 177Lu/225Ac SPECT/CT acquisition (1 h) at 24 h post treatment (high-energy collimator, 16 projections p. head à 3.5 min, 128 × 128 pixel). The gamma peak at 440 keV (width: 10%) of the progeny 213Bi was imaged along with the peak at 208 keV (width: 15%) of 177Lu. Quantification included CT-based attenuation and window-based scatter correction plus resolution modelling. Gaussian post-filtering with a full-width-half-maximum of 30 mm and 40-45 mm was employed to match the signal-to-noise ratio of 225Ac and 177Lu, respectively. RESULTS: Kidney (r = 0.96, p < 0.01) and lesion (r = 0.94, p < 0.01) SUV for [177Lu]Lu-PSMA-I&T and [225Ac]Ac-PSMA-I&T showed a strong and significant correlation. Kidney SUV were significantly higher (p < 0.01) for [225Ac]Ac-PSMA-I&T (2.5 ± 0.8 vs. 2.1 ± 0.9), while for [177Lu]Lu-PSMA-I&T lesion SUV were significantly higher (p = 0.03; 1.8 ± 1.1 vs. 2.1 ± 1.5). For absorbed dose estimates, significant differences regarding the kidneys remained, while no significant differences for lesion dosimetry were found. CONCLUSION: Quantitative low-count SPECT imaging of the peak at 440 keV during [225Ac]Ac-PSMA-I&T therapy is feasible. Multi-isotope imaging for [177Lu]Lu-PSMA-I&T/[225Ac]Ac-PSMA-I&T therapy indicates accumulation of free 213Bi in the kidneys.

Spatial and Annual Variation in Microbial Abundance, Community Composition, and Diversity Associated With Alpine Surface Snow.

Understanding microbial community dynamics in the alpine cryosphere is an important step toward assessing climate change impacts on these fragile ecosystems and meltwater-fed environments downstream. In this study, we analyzed microbial community composition, variation in community alpha and beta diversity, and the number of prokaryotic cells and virus-like particles (VLP) in seasonal snowpack from two consecutive years at three high altitude mountain summits along a longitudinal transect across the European Alps. Numbers of prokaryotic cells and VLP both ranged around 104 and 105 per mL of snow meltwater on average, with variation generally within one order of magnitude between sites and years. VLP-to-prokaryotic cell ratios spanned two orders of magnitude, with median values close to 1, and little variation between sites and years in the majority of cases. Estimates of microbial community alpha diversity inferred from Hill numbers revealed low contributions of common and abundant microbial taxa to the total taxon richness, and thus low community evenness. Similar to prokaryotic cell and VLP numbers, differences in alpha diversity between years and sites were generally relatively modest. In contrast, community composition displayed strong variation between sites and especially between years. Analyses of taxonomic and phylogenetic community composition showed that differences between sites within years were mainly characterized by changes in abundances of microbial taxa from similar phylogenetic clades, whereas shifts between years were due to significant phylogenetic turnover. Our findings on the spatiotemporal dynamics and magnitude of variation of microbial abundances, community diversity, and composition in surface snow may help define baseline levels to assess future impacts of climate change on the alpine cryosphere.

Application of High-Z Gold Nanoparticles in Targeted Cancer Radiotherapy-Pharmacokinetic Modeling, Monte Carlo Simulation and Radiobiological Effect Modeling.

High-Z gold nanoparticles (AuNPs) conjugated to a targeting antibody can help to improve tumor control in radiotherapy while simultaneously minimizing radiotoxicity to adjacent healthy tissue. This paper summarizes the main findings of a joint research program which applied AuNP-conjugates in preclinical modeling of radiotherapy at the Klinikum rechts der Isar, Technical University of Munich and Helmholtz Zentrum München. A pharmacokinetic model of superparamagnetic iron oxide nanoparticles was developed in preparation for a model simulating the uptake and distribution of AuNPs in mice. Multi-scale Monte Carlo simulations were performed on a single AuNP and multiple AuNPs in tumor cells at cellular and molecular levels to determine enhancements in the radiation dose and generation of chemical radicals in close proximity to AuNPs. A biologically based mathematical model was developed to predict the biological response of AuNPs in radiation enhancement. Although simulations of a single AuNP demonstrated a clear dose enhancement, simulations relating to the generation of chemical radicals and the induction of DNA strand breaks induced by multiple AuNPs showed only a minor dose enhancement. The differences in the simulated enhancements at molecular and cellular levels indicate that further investigations are necessary to better understand the impact of the physical, chemical, and biological parameters in preclinical experimental settings prior to a translation of these AuNPs models into targeted cancer radiotherapy.

Radiopharmacokinetic modelling and radiation dose assessment of 223Ra used for treatment of metastatic castration-resistant prostate cancer.

PURPOSE: Ra-223 dichloride (223Ra, Xofigo®) is used for treatment of patients suffering from castration-resistant metastatic prostate cancer. The objective of this work was to apply the most recent biokinetic model for radium and its progeny to show their radiopharmacokinetic behaviour. Organ absorbed doses after intravenous injection of 223Ra were estimated and compared to clinical data and data of an earlier modelling study. METHODS: The most recent systemic biokinetic model of 223Ra and its progeny, developed by the International Commission on Radiological Protection (ICRP), as well as the ICRP human alimentary tract model were applied for the radiopharmacokinetic modelling of Xofigo® biodistribution in patients after bolus administration. Independent kinetics were assumed for the progeny of 223Ra. The time activity curves for 223Ra were modelled and the time integrated activity coefficients, [Formula: see text] in the source regions for each progeny were determined. For estimating the organ absorbed doses, the Specific Absorbed Fractions (SAF) and dosimetric framework of ICRP were used together with the aforementioned [Formula: see text] values. RESULTS: The distribution of 223Ra after injection showed a rapid plasma clearance and a low urinary excretion. Main elimination was via faeces. Bone retention was found to be about 30% at 4 h post-injection. Similar tendencies were observed in clinical trials of other authors. The highest absorbed dose coefficients were found for bone endosteum, liver and red marrow, followed by kidneys and colon. CONCLUSION: The biokinetic modelling of 223Ra and its progeny may help to predict their distributions in patients after administration of Xofigo®. The organ dose coefficients of this work showed some variation to the values reported from clinical studies and an earlier compartmental modelling study. The dose to the bone endosteum was found to be lower by a factor of ca. 3 than previously estimated.

Modeling of radon exhalation from soil influenced by environmental parameters.

Atmospheric radioactive noble gas radon (Rn-222) originates from soil gas exhaled in the atmospheric surface layer. Radon exhalation rates from soil as well as corresponding meteorological and soil parameters were recorded for two subsequent years. Based on long-term field data, a statistical regression model for the radon exhalation and the most important influencing parameters soil water content, temperature of soil and air, air pressure and autocorrelation of the exhalation rate was established. The fitting result showed that the multivariate model can explain up to 61% of the variation of the exhalation rate. First, the exhalation rate increases up to 80 Bq m-2 h-1 with increasing soil water content. Later, at water content >10%, increasing soil wetness suppressed the exhalation rate: at values higher than 24% to approximately one third. The air temperature had a distinct positive effect while the soil temperature had a strong negative effect on the exhalation rate, indicating their different influencing-mechanisms on the exhalation. The air pressure was negligible. The lagged values of radon exhalation had to be included in the model, as the variable shows strong autocorrelation.