Deep-learning and MR images to target hypoxic habitats with evofosfamide in preclinical models of sarcoma.

Rationale: Hypoxic regions (habitats) within tumors are heterogeneously distributed and can be widely variant. Hypoxic habitats are generally pan-therapy resistant. For this reason, hypoxia-activated prodrugs (HAPs) have been developed to target these resistant volumes. The HAP evofosfamide (TH-302) has shown promise in preclinical and early clinical trials of sarcoma. However, in a phase III clinical trial of non-resectable soft tissue sarcomas, TH-302 did not improve survival in combination with doxorubicin (Dox), possibly due to a lack of patient stratification based on hypoxic status. Therefore, we used magnetic resonance imaging (MRI) to identify hypoxic habitats and non-invasively follow therapies response in sarcoma mouse models. Methods: We developed deep-learning (DL) models to identify hypoxia, using multiparametric MRI and co-registered histology, and monitored response to TH-302 in a patient-derived xenograft (PDX) of rhabdomyosarcoma and a syngeneic model of fibrosarcoma (radiation-induced fibrosarcoma, RIF-1). Results: A DL convolutional neural network showed strong correlations (>0.76) between the true hypoxia fraction in histology and the predicted hypoxia fraction in multiparametric MRI. TH-302 monotherapy or in combination with Dox delayed tumor growth and increased survival in the hypoxic PDX model (p<0.05), but not in the RIF-1 model, which had a lower volume of hypoxic habitats. Control studies showed that RIF-1 resistance was due to hypoxia and not other causes. Notably, PDX tumors developed resistance to TH-302 under prolonged treatment that was not due to a reduction in hypoxic volumes. Conclusion: Artificial intelligence analysis of pre-therapy MR images can predict hypoxia and subsequent response to HAPs. This approach can be used to monitor therapy response and adapt schedules to forestall the emergence of resistance.

Lipophilicity Determines Routes of Uptake and Clearance, and Toxicity of an Alpha-Particle-Emitting Peptide Receptor Radiotherapy.

Lipophilicity is explored in the biodistribution (BD), pharmacokinetics (PK), radiation dosimetry (RD), and toxicity of an internally administered targeted alpha-particle therapy (TAT) under development for the treatment of metastatic melanoma. The TAT conjugate is comprised of the chelator DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate), conjugated to melanocortin receptor 1 specific peptidic ligand (MC1RL) using a linker moiety and chelation of the 225Ac radiometal. A set of conjugates were prepared with a range of lipophilicities (log D 7.4 values) by varying the chemical properties of the linker. Reported are the observations that higher log D 7.4 values are associated with decreased kidney uptake, decreased absorbed radiation dose, and decreased kidney toxicity of the TAT, and the inverse is observed for lower log D 7.4 values. Animals administered TATs with lower lipophilicities exhibited acute nephropathy and death, whereas animals administered the highest activity TATs with higher lipophilicities lived for the duration of the 7 month study and exhibited chronic progressive nephropathy. Changes in TAT lipophilicity were not associated with changes in liver uptake, dose, or toxicity. Significant observations include that lipophilicity correlates with kidney BD, the kidney-to-liver BD ratio, and weight loss and that blood urea nitrogen (BUN) levels correlated with kidney uptake. Furthermore, BUN was identified as having higher sensitivity and specificity of detection of kidney pathology, and the liver enzyme alkaline phosphatase (ALKP) had high sensitivity and specificity for detection of liver damage associated with the TAT. These findings suggest that tuning radiopharmaceutical lipophilicity can effectively modulate the level of kidney uptake to reduce morbidity and improve both safety and efficacy.

Preclinical evaluation of [225Ac]Ac-DOTA-TATE for treatment of lung neuroendocrine neoplasms.

PURPOSE: There is significant interest in the development of targeted alpha-particle therapies (TATs) for treatment of solid tumors. The metal chelator-peptide conjugate, DOTA-TATE, loaded with the ß-particle emitting radionuclide 177Lu ([177Lu]Lu-DOTA-TATE) is now standard care for neuroendocrine tumors that express the somatostatin receptor 2 (SSTR2) target. A recent clinical study demonstrated efficacy of the corresponding [225Ac]Ac-DOTA-TATE in patients that were refractory to [177Lu]Lu-DOTA-TATE. Herein, we report the radiosynthesis, toxicity, biodistribution (BD), radiation dosimetry (RD), and efficacy of [225Ac]Ac-DOTA-TATE in small animal models of lung neuroendocrine neoplasms (NENs). METHODS: [225Ac]Ac-DOTA-TATE was synthesized and characterized for radiochemical yield, purity and stability. Non-tumor-bearing BALB/c mice were tested for toxicity and BD. Efficacy was determined by single intravenous injection of [225Ac]Ac-DOTA-TATE into SCID mice-bearing human SSTR2 positive H727 and H69 lung NENs. RD was calculated using the BD data. RESULTS: [225Ac]Ac-DOTA-TATE was synthesized with 98% yield, 99.8% purity, and displayed 97% stability after 2 days incubation in human serum at 37 °C. All animals in the toxicity study appeared healthy 5 months post injection with no indications of toxicity, except that animals that received ≥111 kBq of [225Ac]Ac-DOTA-TATE had chronic progressive nephropathy. BD studies revealed that the primary route of elimination is by the renal route. RD calculations determined pharmacokinetics parameters and absorbed α-emission dosages from 225Ac and its daughters. For both tumor models, a significant tumor growth delay and time to experimental endpoint were observed following a single administration of [225Ac]Ac-DOTA-TATE relative to controls. CONCLUSIONS: These results suggest significant potential for the clinical translation of [225Ac]Ac-DOTA-TATE for lung NENs.

Biodistribution and Multicompartment Pharmacokinetic Analysis of a Targeted α Particle Therapy.

Targeted α particle therapy (TAT) is ideal for treating disease while minimizing damage to surrounding nontargeted tissues due to short path length and high linear energy transfer (LET). We developed a TAT for metastatic uveal melanoma, targeting the melanocortin-1 receptor (MC1R), which is expressed in 94% of uveal melanomas. Two versions of the therapy are being investigated: 225Ac-DOTA-Ahx-MC1RL (225Ac-Ahx) and 225Ac-DOTA-di-d-Glu-MC1RL (225Ac-di-d-Glu). The biodistribution (BD) from each was studied and a multicompartment pharmacokinetic (PK) model was developed to describe drug distribution rates. Two groups of 16 severe combined immunodeficient (SCID) mice bearing high MC1R expressing tumors were intravenously injected with 225Ac-Ahx or 225Ac-di-d-Glu. After injection, four groups (n = 4) were euthanized at 24, 96, 144, and 288 h time points for each cohort. Tumors and 13 other organs were harvested at each time point. Isomeric γ spectra were measured in tissue samples using a scintillation γ detector and converted to α activity using factors for γ ray abundance per α decay. Time activity curves were calculated for each organ. A five-compartment PK model was built with the following compartments: blood, tumor, normal tissue, kidney, and liver. This model is characterized by a system of five ordinary differential equations using mass action kinetics, which describe uptake, intercompartmental transitions, and clearance rates. The ordinary differential equations were simultaneously solved and fit to experimental data using a genetic algorithm for optimization. The BD data show that both compounds have minimal distribution to organs at risk other than the kidney and liver. The PK parameter estimates had less than 5% error. From these data, 225Ac-Ahx showed larger and faster uptake in the liver. Both compounds had comparable uptake and clearance rates for other compartments. The BD and PK behavior for two targeted radiopharmaceuticals were investigated. The PK model fit the experimental data and provided insight into the kinetics of the compounds systematically.

Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images.

Quantitative imaging biomarkers (QIBs) provide medical image-derived intensity, texture, shape, and size features that may help characterize cancerous tumors and predict clinical outcomes. Successful clinical translation of QIBs depends on the robustness of their measurements. Biomarkers derived from positron emission tomography images are prone to measurement errors owing to differences in image processing factors such as the tumor segmentation method used to define volumes of interest over which to calculate QIBs. We illustrate a new Bayesian statistical approach to characterize the robustness of QIBs to different processing factors. Study data consist of 22 QIBs measured on 47 head and neck tumors in 10 positron emission tomography/computed tomography scans segmented manually and with semiautomated methods used by 7 institutional members of the NCI Quantitative Imaging Network. QIB performance is estimated and compared across institutions with respect to measurement errors and power to recover statistical associations with clinical outcomes. Analysis findings summarize the performance impact of different segmentation methods used by Quantitative Imaging Network members. Robustness of some advanced biomarkers was found to be similar to conventional markers, such as maximum standardized uptake value. Such similarities support current pursuits to better characterize disease and predict outcomes by developing QIBs that use more imaging information and are robust to different processing factors. Nevertheless, to ensure reproducibility of QIB measurements and measures of association with clinical outcomes, errors owing to segmentation methods need to be reduced.

Development of Targeted Alpha Particle Therapy for Solid Tumors.

Targeted alpha-particle therapy (TAT) aims to selectively deliver radionuclides emitting α-particles (cytotoxic payload) to tumors by chelation to monoclonal antibodies, peptides or small molecules that recognize tumor-associated antigens or cell-surface receptors. Because of the high linear energy transfer (LET) and short range of alpha (α) particles in tissue, cancer cells can be significantly damaged while causing minimal toxicity to surrounding healthy cells. Recent clinical studies have demonstrated the remarkable efficacy of TAT in the treatment of metastatic, castration-resistant prostate cancer. In this comprehensive review, we discuss the current consensus regarding the properties of the α-particle-emitting radionuclides that are potentially relevant for use in the clinic; the TAT-mediated mechanisms responsible for cell death; the different classes of targeting moieties and radiometal chelators available for TAT development; current approaches to calculating radiation dosimetry for TATs; and lead optimization via medicinal chemistry to improve the TAT radiopharmaceutical properties. We have also summarized the use of TATs in pre-clinical and clinical studies to date.

A Monte Carlo Method for Determining the Response Relationship between Two Commonly Used Detectors to Indirectly Measure Alpha Particle Radiation Activity.

Using targeted ligands to deliver alpha-emitting radionuclides directly to tumor cells has become a promising therapeutic strategy. To calculate the radiation dose to patients, activities of parent and daughter radionuclides must be measured. Scintillation detectors can be used to quantify these activities; however, activities found in pre-clinical and clinical studies can exceed their optimal performance range. Therefore, a method of correcting scintillation detector measurements at higher activities was developed using Monte Carlo modeling. Because there are currently no National Institute of Standards and Technology traceable Actinium-225 (225Ac) standards available, a well-type ionization chamber was used to measure 70.3 ± 7.0, 144.3 ± 14.4, 222.0 ± 22.2, 299.7 ± 30.0, 370.0 ± 37.0, and 447.7 ± 44.7 kBq samples of 225Ac obtained from Oak Ridge National Lab. Samples were then placed in a well-type NaI(Tl) scintillation detector and spectra were obtained. Alpha particle activity for each species was calculated using gamma abundance per alpha decay. MCNP6 Monte Carlo software was used to simulate the 4π-geometry of the NaI(Tl) detector. Using the ionization chamber reading as activity input to the Monte Carlo model, spectra were obtained and compared to NaI(Tl) spectra. Successive simulations of different activities were run until a spectrum minimizing the mean percent difference between the two was identified. This was repeated for each sample activity. Ionization chamber calibration measurements showed increase in error from 3% to 10% as activities decreased, resulting from decreasing detection efficiency. Measurements of 225Ac using both detector types agreed within 7% of Oak Ridge stated activities. Simulated Monte Carlo spectra of 225Ac were successfully generated. Activities obtained from these spectra differed with ionization chamber readings up to 156% at 147.7 kBq. Simulated spectra were then adjusted to correct NaI(Tl) measurements to be within 1%. These were compared to ionization chamber readings and a response relationship was determined between the two instruments. Measurements of 225Ac and daughter activity were conducted using a NaI(Tl) scintillation detector calibrated for energy and efficiency and an ionization chamber calibrated for efficiency using a surrogate calibration reference. Corrections provided by Monte Carlo modeling improve the accuracy of activity quantification for alpha-particle emitting radiopharmaceuticals in pre-clinical and clinical studies.

Multiparametric MRI and Coregistered Histology Identify Tumor Habitats in Breast Cancer Mouse Models.

It is well-recognized that solid tumors are genomically, anatomically, and physiologically heterogeneous. In general, more heterogeneous tumors have poorer outcomes, likely due to the increased probability of harboring therapy-resistant cells and regions. It is hypothesized that the genomic and physiologic heterogeneity are related, because physiologically distinct regions will exert variable selection pressures leading to the outgrowth of clones with variable genomic/proteomic profiles. To investigate this, methods must be in place to interrogate and define, at the microscopic scale, the cytotypes that exist within physiologically distinct subregions ("habitats") that are present at mesoscopic scales. MRI provides a noninvasive approach to interrogate physiologically distinct local environments, due to the biophysical principles that govern MRI signal generation. Here, we interrogate different physiologic parameters, such as perfusion, cell density, and edema, using multiparametric MRI (mpMRI). Signals from six different acquisition schema were combined voxel-by-voxel into four clusters identified using a Gaussian mixture model. These were compared with histologic and IHC characterizations of sections that were coregistered using MRI-guided 3D printed tumor molds. Specifically, we identified a specific set of MRI parameters to classify viable-normoxic, viable-hypoxic, nonviable-hypoxic, and nonviable-normoxic tissue types within orthotopic 4T1 and MDA-MB-231 breast tumors. This is the first coregistered study to show that mpMRI can be used to define physiologically distinct tumor habitats within breast tumor models. SIGNIFICANCE: This study demonstrates that noninvasive imaging metrics can be used to distinguish subregions within heterogeneous tumors with histopathologic correlation.

Cochlear pharmacokinetics - Micro-computed tomography and learning-prediction modeling for transport parameter determination.

Inner ear disorders such as sensorineural deafness and genetic diseases may one day be treated with local drug delivery to the inner ear. Current pharmacokinetic models have been based on invasive methods to measure drug concentrations, limiting them in spatial resolution, and restricting the research to larger rodents. We developed an intracochlear pharmacokinetic model based on an imaging, learning-prediction (LP) paradigm for learning transport parameters in the murine cochlea. This was achieved using noninvasive micro-computed tomography imaging of the cochlea during in vivo infusion of a contrast agent at the basal end of scala tympani through a cochleostomy. Each scan was registered in 3-D to a cochlear atlas to segment the cochlear regions with high accuracy, enabling concentrations to be extracted along the length of each scala. These spatio-temporal concentration profiles were used to learn a concentration dependent diffusion coefficient, and transport parameters between the major scalae and to clearance. The LP model results are comparable to the current state of the art model, and can simulate concentrations for cases involving different infusion molecules and different drug delivery protocols. Forward simulation results with pulsatile delivery suggest the pharmacokinetic model can be used to optimize drug delivery protocols to reduce total drug delivered and the potential for toxic side effects. While developed in the challenging murine cochlea, the processes are scalable to larger animals and different drug infusion paradigms.

Melanocortin 1 Receptor-Targeted α-Particle Therapy for Metastatic Uveal Melanoma.

New effective therapies are greatly needed for metastatic uveal melanoma, which has a very poor prognosis with a median survival of less than 1 y. The melanocortin 1 receptor (MC1R) is expressed in 94% of uveal melanoma metastases, and a MC1R-specific ligand (MC1RL) with high affinity and selectivity for MC1R was previously developed. Methods: The 225Ac-DOTA-MC1RL conjugate was synthesized in high radiochemical yield and purity and was tested in vitro for biostability and for MC1R-specific cytotoxicity in uveal melanoma cells, and the lanthanum-DOTA-MC1RL analog was tested for binding affinity. Non-tumor-bearing BALB/c mice were tested for maximum tolerated dose and biodistribution. Severe combined immunodeficient mice bearing uveal melanoma tumors or engineered MC1R-positive and -negative tumors were studied for biodistribution and efficacy. Radiation dosimetry was calculated using mouse biodistribution data and blood clearance kinetics from Sprague-Dawley rat data. Results: High biostability, MC1R-specific cytotoxicity, and high binding affinity were observed. Limiting toxicities were not observed at even the highest administered activities. Pharmacokinetics and biodistribution studies revealed rapid blood clearance (<15 min), renal and hepatobillary excretion, MC1R-specific tumor uptake, and minimal retention in other normal tissues. Radiation dosimetry calculations determined pharmacokinetics parameters and absorbed α-emission dosages from 225Ac and its daughters. Efficacy studies demonstrated significantly prolonged survival and decreased metastasis burden after a single administration of 225Ac-DOTA-MC1RL in treated mice relative to controls. Conclusion: These results suggest significant potential for the clinical translation of 225Ac-DOTA-MC1RL as a novel therapy for metastatic uveal melanoma.

Structure and properties of DOTA-chelated radiopharmaceuticals within the 225Ac decay pathway.

The successful delivery of toxic cargo directly to tumor cells is of primary importance in targeted (α) particle therapy. Complexes of radioactive atoms with the 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) chelating agent are considered as effective materials for such delivery processes. The DOTA chelator displays high affinity to radioactive metal isotopes and retains this capability after conjugation to tumor targeting moieties. Although the α-decay chains are well defined for many isotopes, the stability of chelations during the decay process and the impact of released energy on their structures remain unknown. The radioactive isotope 225Ac is an α-particle emitter that can be easily chelated by DOTA. However, 225Ac has a complex decay chain with four α-particle emissions during decay of each radionuclide. To advance our fundamental understanding of the consequences of α-decay on the stability of tumor-targeted 225Ac-DOTA conjugate radiopharmaceuticals, we performed first principles calculations of the structure, stability, and electronic properties of the DOTA chelator to the 225Ac radioactive isotope, and the initial daughters in the decay chain, 225Ac, 221Fr, 217At and 213Bi. Our calculations show that the atomic positions, binding energies, and electron localization functions are affected by the interplay between spin-orbit coupling, weak dispersive interactions, and environmental factors. Future empirical measurements may be guided and interpreted in light of these results.

Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data.

PURPOSE: Radiomics utilizes a large number of image-derived features for quantifying tumor characteristics that can in turn be correlated with response and prognosis. Unfortunately, extraction and analysis of such image-based features is subject to measurement variability and bias. The challenge for radiomics is particularly acute in Positron Emission Tomography (PET) where limited resolution, a high noise component related to the limited stochastic nature of the raw data, and the wide variety of reconstruction options confound quantitative feature metrics. Extracted feature quality is also affected by tumor segmentation methods used to define regions over which to calculate features, making it challenging to produce consistent radiomics analysis results across multiple institutions that use different segmentation algorithms in their PET image analysis. Understanding each element contributing to these inconsistencies in quantitative image feature and metric generation is paramount for ultimate utilization of these methods in multi-institutional trials and clinical oncology decision making. METHODS: To assess segmentation quality and consistency at the multi-institutional level, we conducted a study of seven institutional members of the National Cancer Institute Quantitative Imaging Network. For the study, members were asked to segment a common set of phantom PET scans acquired over a range of imaging conditions as well as a second set of head and neck cancer (HNC) PET scans. Segmentations were generated at each institution using their preferred approach. In addition, participants were asked to repeat segmentations with a time interval between initial and repeat segmentation. This procedure resulted in overall 806 phantom insert and 641 lesion segmentations. Subsequently, the volume was computed from the segmentations and compared to the corresponding reference volume by means of statistical analysis. RESULTS: On the two test sets (phantom and HNC PET scans), the performance of the seven segmentation approaches was as follows. On the phantom test set, the mean relative volume errors ranged from 29.9 to 87.8% of the ground truth reference volumes, and the repeat difference for each institution ranged between -36.4 to 39.9%. On the HNC test set, the mean relative volume error ranged between -50.5 to 701.5%, and the repeat difference for each institution ranged between -37.7 to 31.5%. In addition, performance measures per phantom insert/lesion size categories are given in the paper. On phantom data, regression analysis resulted in coefficient of variation (CV) components of 42.5% for scanners, 26.8% for institutional approaches, 21.1% for repeated segmentations, 14.3% for relative contrasts, 5.3% for count statistics (acquisition times), and 0.0% for repeated scans. Analysis showed that the CV components for approaches and repeated segmentations were significantly larger on the HNC test set with increases by 112.7% and 102.4%, respectively. CONCLUSION: Analysis results underline the importance of PET scanner reconstruction harmonization and imaging protocol standardization for quantification of lesion volumes. In addition, to enable a distributed multi-site analysis of FDG PET images, harmonization of analysis approaches and operator training in combination with highly automated segmentation methods seems to be advisable. Future work will focus on quantifying the impact of segmentation variation on radiomics system performance.

Evaluation of radiofluorinated carboximidamides as potential IDO-targeted PET tracers for cancer imaging.

IDO1 is an enzyme catalyzing the initial and rate-limiting step in the catabolism of tryptophan along the kynurenine pathway. IDO1 expression could suppress immune responses by blocking T-lymphocyte proliferation locally, suggesting a role of IDO in the regulation of immune responses. The goal of this study was to evaluate the potential of radiofluorinated carboximidamides as selective PET radioligands for IDO1. Specific binding correlated with IDO1 expression as measured through in vitro, microPET experiments. Specific accumulation of the new radiotracer [18F]IDO49 was observed in IDO1-expressing tumors and confirmed by Western blot and IHC analyses. These results suggest that [18F]IDO49 has substantial potential as an imaging agent that targets IDO1 in tumors, and therefore may be utilized as a companion diagnostic for IDO1 targeted therapies.

Preclinical Modeling of KIF5B-RET Fusion Lung Adenocarcinoma.

RET fusions have been found in lung adenocarcinoma, of which KIF5B-RET is the most prevalent. We established inducible KIF5B-RET transgenic mice and KIF5B-RET-dependent cell lines for preclinical modeling of KIF5B-RET-associated lung adenocarcinoma. Doxycycline-induced CCSP-rtTA/tetO-KIF5B-RET transgenic mice developed invasive lung adenocarcinoma with desmoplastic reaction. Tumors regressed upon suppression of KIF5B-RET expression. By culturing KIF5B-RET-dependent BaF3 (B/KR) cells with increasing concentrations of cabozantinib or vandetanib, we identified cabozantinib-resistant RETV804L mutation and vandetanib-resistant-RETG810A mutation. Among cabozantinib, lenvatinib, ponatinib, and vandetanib, ponatinib was identified as the most potent inhibitor against KIF5B-RET and its drug-resistant mutants. Interestingly, the vandetanib-resistant KIF5B-RETG810A mutant displayed gain-of-sensitivity (GOS) to ponatinib and lenvatinib. Treatment of doxycycline-induced CCSP-rtTA/tetO-KIF5B-RET bitransgenic mice with ponatinib effectively induced tumor regression. These results indicate that KIF5B-RET-associated lung tumors are addicted to the fusion oncogene and ponatinib is the most effective inhibitor for targeting KIF5B-RET in lung adenocarcinoma. Moreover, this study finds a novel vandetanib-resistant RETG810A mutation and identifies lenvatinib and ponatinib as the secondary drugs to overcome this vandetanib resistance mechanism. Mol Cancer Ther; 15(10); 2521-9. ©2016 AACR.

Predictive computational modeling to define effective treatment strategies for bone metastatic prostate cancer.

The ability to rapidly assess the efficacy of therapeutic strategies for incurable bone metastatic prostate cancer is an urgent need. Pre-clinical in vivo models are limited in their ability to define the temporal effects of therapies on simultaneous multicellular interactions in the cancer-bone microenvironment. Integrating biological and computational modeling approaches can overcome this limitation. Here, we generated a biologically driven discrete hybrid cellular automaton (HCA) model of bone metastatic prostate cancer to identify the optimal therapeutic window for putative targeted therapies. As proof of principle, we focused on TGFß because of its known pleiotropic cellular effects. HCA simulations predict an optimal effect for TGFß inhibition in a pre-metastatic setting with quantitative outputs indicating a significant impact on prostate cancer cell viability, osteoclast formation and osteoblast differentiation. In silico predictions were validated in vivo with models of bone metastatic prostate cancer (PAIII and C4-2B). Analysis of human bone metastatic prostate cancer specimens reveals heterogeneous cancer cell use of TGFß. Patient specific information was seeded into the HCA model to predict the effect of TGFß inhibitor treatment on disease evolution. Collectively, we demonstrate how an integrated computational/biological approach can rapidly optimize the efficacy of potential targeted therapies on bone metastatic prostate cancer.

Preliminary Therapy Evaluation of (225)Ac-DOTA-c(RGDyK) Demonstrates that Cerenkov Radiation Derived from (225)Ac Daughter Decay Can Be Detected by Optical Imaging for In Vivo Tumor Visualization.

The theranostic potential of (225)Ac-based radiopharmaceuticals continues to increase as researchers seek innovative ways to harness the nuclear decay of this radioisotope for therapeutic and imaging applications. This communication describes the evaluation of (225)Ac-DOTA-c(RGDyK) in both biodistribution and Cerenkov luminescence imaging (CLI) studies. Initially, La-DOTA-c(RGDyK) was prepared as a non-radioactive surrogate to evaluate methodologies that would contribute to an optimized radiochemical synthetic strategy and estimate the radioactive conjugate's affinity for αvß3, using surface plasmon resonance spectroscopy. Surface plasmon resonance spectroscopy studies revealed the IC50 and Ki of La-DOTA-c(RGDyK) to be 33 ± 13 nM and 26 ± 11 nM, respectively, and suggest that the complexation of the La(3+) ion to the conjugate did not significantly alter integrin binding. Furthermore, use of this surrogate allowed optimization of radiochemical synthesis strategies to prepare (225)Ac-DOTA-c(RGDyK) with high radiochemical purity and specific activity similar to other (225)Ac-based radiopharmaceuticals. This radiopharmaceutical was highly stable in vitro. In vivo biodistribution studies confirmed the radiotracer's ability to target αvß3 integrin with specificity; specificity was detected in tumor-bearing animals using Cerenkov luminescence imaging. Furthermore, tumor growth control was achieved using non-toxic doses of the radiopharmaceutical in U87mg tumor-bearing nude mice. To our knowledge, this is the first report to describe the CLI of αvß3 (+) tumors in live animals using the daughter products derived from (225)Ac decay in situ. This concept holds promise to further enhance development of targeted alpha particle therapy.

Laminar, cellular, transverse, and multiheaded pulsating detonations in condensed phase energetic materials from molecular dynamics simulations.

The development of condensed-phase detonation instabilities is simulated using moving window molecular dynamics and a generic AB model of a high explosive. It is found that an initially planar detonation front with one-dimensional flow can become unstable through development of transverse perturbations resulting in highly inhomogeneous and complex two- and three-dimensional distributions of pressure and other variables within the detonation front. Chemical reactions are initiated in localized transverse shock fronts and Mach stems with a pressure and temperature higher than those predicted by classic Zel'dovich, von Neumann, and Doering detonation theory. The two-dimensional cellular and transverse and three-dimensional pulsating detonation structures are found by varying the physico-chemical properties of AB energetic material, sample geometry, and boundary conditions. The different regimes of condensed-phase detonation that can develop from instabilities within a planar detonation front exhibit structures, although at a much smaller scale, that are similar to those observed in gases and diluted liquids.

Effects of quantum noise in 4D-CT on deformable image registration and derived ventilation data.

Quantum noise is common in CT images and is a persistent problem in accurate ventilation imaging using 4D-CT and deformable image registration (DIR). This study focuses on the effects of noise in 4D-CT on DIR and thereby derived ventilation data. A total of six sets of 4D-CT data with landmarks delineated in different phases, called point-validated pixel-based breathing thorax models (POPI), were used in this study. The DIR algorithms, including diffeomorphic morphons (DM), diffeomorphic demons (DD), optical flow and B-spline, were used to register the inspiration phase to the expiration phase. The DIR deformation matrices (DIRDM) were used to map the landmarks. Target registration errors (TRE) were calculated as the distance errors between the delineated and the mapped landmarks. Noise of Gaussian distribution with different standard deviations (SD), from 0 to 200 Hounsfield Units (HU) in amplitude, was added to the POPI models to simulate different levels of quantum noise. Ventilation data were calculated using the ΔV algorithm which calculates the volume change geometrically based on the DIRDM. The ventilation images with different added noise levels were compared using Dice similarity coefficient (DSC). The root mean square (RMS) values of the landmark TRE over the six POPI models for the four DIR algorithms were stable when the noise level was low (SD <150 HU) and increased with added noise when the level is higher. The most accurate DIR was DD with a mean RMS of 1.5 ± 0.5 mm with no added noise and 1.8 ± 0.5 mm with noise (SD = 200 HU). The DSC values between the ventilation images with and without added noise decreased with the noise level, even when the noise level was relatively low. The DIR algorithm most robust with respect to noise was DM, with mean DSC = 0.89 ± 0.01 and 0.66 ± 0.02 for the top 50% ventilation volumes, as compared between 0 added noise and SD = 30 and 200 HU, respectively. Although the landmark TRE were stable with low noise, the differences between ventilation images increased with noise level, even when the noise was low, indicating ventilation imaging from 4D-CT was sensitive to image noise. Therefore, high quality 4D-CT is essential for accurate ventilation images.

Evolution of shock-induced orientation-dependent metastable states in crystalline aluminum.

The evolution of orientation-dependent metastable states during shock-induced solid-liquid phase transitions in crystalline Al is followed using moving window molecular dynamics simulations. The orientation-dependent transition pathways towards an orientation-independent final state Hugoniot include both "cold melting" followed by recrystallization in [110]- and [111]-oriented shock waves and crystal overheating followed by melting in [100] shock waves. The orientation-dependent dynamics take place within a zone that can extend up to hundreds of nanometers behind the shock front.

Two-zone elastic-plastic single shock waves in solids.

By decoupling time and length scales in moving window molecular dynamics shock-wave simulations, a new regime of shock-wave propagation is uncovered characterized by a two-zone elastic-plastic shock-wave structure consisting of a leading elastic front followed by a plastic front, both moving with the same average speed and having a fixed net thickness that can extend to microns. The material in the elastic zone is in a metastable state that supports a pressure that can substantially exceed the critical pressure characteristic of the onset of the well-known split-elastic-plastic, two-wave propagation. The two-zone elastic-plastic wave is a general phenomenon observed in simulations of a broad class of crystalline materials and is within the reach of current experimental techniques.