Dosimetric validation of SmART-RAD Monte Carlo modelling for x-ray cabinet radiobiology irradiators

Objective: Accuracy and reproducibility in the measurement of radiation dose and associated reporting are critically important for the validity of basic and preclinical radiobiological studies performed with kilovolt x-ray radiation cabinets. This is essential not only to enable results of radiobiological studies to be repeated, as well as enable valid comparisons between laboratories. In addition, the commonly used single point dose value hides the 3D dose heterogeneity across the irradiated sample. This is particularly true for preclinical rodent models, and is generally difficult to measure directly. Radiation transport simulations integrated in an easy to use application could help researchers improve quality of dosimetry and reporting. Approach: this paper describes the use and dosimetric validation of a newly-developed Monte Carlo (MC) tool, SmART-RAD, to simulate the x-ray field in a range of standard commercial x-ray cabinet irradiators used for preclinical irradiations. Comparisons are made between simulated and experimentally determined dose distributions for a range of configurations to assess the potential use of this tool in determining dose distributions through samples, based on more readily available air-kerma calibration point measurements. Main results: simulations gave very good dosimetric agreement with measured depth dose distributions in phantoms containing both water and bone equivalent materials. Good spatial and dosimetric agreement between simulated and measured dose distributions was obtained when using beam-shaping shielding. Significance: the MC simulations provided by SmART-RAD provide a useful tool to go from a limited number of dosimetry measurements to detailed 3D dose distributions through a non-homogeneous irradiated sample. This is particularly important when trying to determine the dose distribution in more complex geometries. The use of such a tool can improve reproducibility and dosimetry reporting in preclinical radiobiological research

Optimizing dual energy cone beam CT protocols for preclinical imaging and radiation research

Objective: The aim of this work was to investigate whether quantitative dual-energy CT (DECT) imaging is feasible for small animal irradiators with an integrated cone-beam CT (CBCT) system. Methods: The optimal imaging protocols were determined by analyzing different energy combinations and dose levels. The influence of beam hardening effects and the performance of a beam hardening correction (BHC) were investigated. In addition, two systems from different manufacturers were compared in terms of errors in the extracted effective atomic numbers (Z(eff)) and relative electron densities (rho(e)) for phantom inserts with known elemental compositions and relative electron densities. Results: The optimal energy combination was determined to be 50 and 90kVp. For this combination, Z(eff) and r rho(e) can be extracted with a mean error of 0.11 and 0.010, respectively, at a dose level of 60cGy. Conclusion: Quantitative DECT imaging is feasible for small animal irradiators with an integrated CBCT system. To obtain the best results, optimizing the imaging protocols is required. Well-separated X-ray spectra and a sufficient dose level should be used to minimize the error and noise for Z(eff) and rho(e). When no BHC is applied in the image reconstruction, the size of the calibration phantom should match the size of the imaged object to limit the influence of beam hardening effects. No significant differences in Z(eff) and rho(e) errors are observed between the two systems from different manufacturers. Advances in knowledge: This is the first study that investigates quantitative DECT imaging for small animal irradiators with an integrated CBCT system

A novel data management platform to improve image-guided precision preclinical biological research

Objective: Preclinical biological research is mandatory for developing new drugs to investigate the toxicity and efficacy of the drug. In this paper, the focus is on radiobiological research as an example of advanced preclinical biological research. In radiobiology, recent technological advances have produced novel research platforms which can precisely irradiate targets in animals and use advanced onboard image-guidance, mimicking the clinical radiotherapy environment. These platforms greatly facilitate complex research combining several agents simultaneously (in our example, radiation and non-radiation agents). Since these modern platform can produce a large amount of wide-ranging data, one of the main impediments in preclinical research platforms is a proper data management system for preclinical studies. Methods: A preclinical data management system, inspired by current radiotherapy clinical data management systems was designed. The system was designed with InterSystems technology, i.e. a programmable Enterprise Service Bus solution. New DICOM animal imaging standards are used such as DICOM suppl. 187 for storing small animal acquisition context and the DICOM second generation course model. Results: A small animal big data warehouse environment for research is designed to work with modern image-guided precision research platforms. Its modular design includes (1) a study workflow manager, (2) a data manager, and (3) a storage manager. The system provides interfaces to, e.g. preclinical treatment planning systems and data analysis plug-ins, and guides the user efficiently through the many steps involved in preclinical research. The system manages various data source locations, and arranges access to the data centrally. Conclusion: A novel preclinical data management system can be designed to improve preclinical workflow, facilitate data exchange between researchers, and support translation to clinical trials. Advances in knowledge: A preclinical data management system such as the one proposed here would greatly benefit preparation, execution and analysis of biological experiments, and will eventually facilitate translation to clinical trials

One-class Gaussian process regressor for quality assessment of transperineal ultrasound images

The use of ultrasound guidance in prostate cancer radiotherapy workflows is not widespread. This can be partially attributed to the need for image interpretation by a trained operator during ultrasound image acquisition. In this work, a one-class regressor, based on DenseNet and Gaussian processes, was implemented to assess automatically the quality of transperineal ultrasound images of the male pelvic region. The implemented deep learning approach achieved a scoring accuracy of 94%, a specificity of 95% and a sensitivity of 93% with respect to the majority vote of three experts, which was comparable with the results of these experts. This is the first step towards a fully automatic workflow, which could potentially remove the need for image interpretation and thereby make the use of ultrasound imaging, which allows real-time volumetric organ tracking in the RT environment, more appealing for hospitals

An orthotopic non-small cell lung cancer model for image-guided small animal radiotherapy platforms

Objective: Lung cancer is the deadliest cancer worldwide. To increase treatment potential for lung cancer, pre-clinical models that allow testing and follow up of clinically relevant treatment modalities are essential. Therefore, we developed a single-nodule-based orthotopic non-small cell lung cancer tumor model which can be monitored using multimodal non-invasive imaging to select the optimal image-guided radiation treatment plan. Methods: An orthotopic non-small cell lung cancer model in NMRI-nude mice was established to investigate the complementary information acquired from 80 kVp microcone-beam CT (micro-CBCT) and bioluminescence imaging (BLI) using different angles and filter settings. Different micro-CBCT-based radiation-delivery plans were evaluated based on their dose-volume histogram metrics of tumor and organs at risk to select the optimal treatment plan. Results: H1299 cell suspensions injected directly into the lung render exponentially growing single tumor nodules whose CBCT-based volume quantification strongly correlated with BLI-integrated intensity. Parallel-opposed single angle beam plans through a single lung are preferred for smaller tumors, whereas for larger tumors, plans that spread the radiation dose across healthy tissues are favored. Conclusions: Closely mimicking a clinical setting for lung cancer with highly advanced preclinical radiation treatment planning is possible in mice developing orthotopic lung tumors. Advances in knowledge: BLI and CBCT imaging of orthotopic lung tumors provide complementary information in a temporal manner. The optimal radiotherapy plan is tumor volume-dependent

半鹹水魚簇ヲ中間宿主トスル吸蟲ニ就テ

Missingness of required data elements used to build the threshold and clinical action measure. (DOCX 17 kb

Mechanisms of apoptosis sensitivity and resistance to the BH3 mimetic ABT-737 in acute myeloid leukemia

SummaryBCL-2 proteins are critical for cell survival and are overexpressed in many tumors. ABT-737 is a small-molecule BH3 mimetic that exhibits single-agent activity against lymphoma and small-cell lung cancer in preclinical studies. We here report that ABT-737 effectively kills acute myeloid leukemia blast, progenitor, and stem cells without affecting normal hematopoietic cells. ABT-737 induced the disruption of the BCL-2/BAX complex and BAK-dependent but BIM-independent activation of the intrinsic apoptotic pathway. In cells with phosphorylated BCL-2 or increased MCL-1, ABT-737 was inactive. Inhibition of BCL-2 phosphorylation and reduction of MCL-1 expression restored sensitivity to ABT-737. These data suggest that ABT-737 could be a highly effective antileukemia agent when the mechanisms of resistance identified here are considered

Pharmacological inhibition of 17β-hydroxysteroid dehydrogenase impairs human endometrial cancer growth in an orthotopic xenograft mouse model

Endometrial cancer (EC) is the most common gynaecological tumor in developed countries and its incidence is increasing. Approximately 80% of newly diagnosed EC cases are estrogen-dependent. Type 1 17β-hydroxysteroid dehydrogenase (17β-HSD-1) is the enzyme that catalyzes the final step in estrogen biosynthesis by reducing the weak estrogen estrone (E1) to the potent estrogen 17β-estradiol (E2), and previous studies showed that this enzyme is implicated in the intratumoral E2 generation in EC. In the present study we employed a recently developed orthotopic and estrogen-dependent xenograft mouse model of EC to show that pharmacological in-hibition of the 17β-HSD-1 enzyme inhibits disease development. Tumors were induced in one uterine horn of athymic nude mice by  intrauterine injection of  the  well-differentiated human endometrial adenocarcinoma Ishikawa cell line, modified to express human 17β-HSD-1 in levels comparable to EC, and the luciferase and green fluorescent protein reporter genes. Controlled estrogen exposure in ovariectomized mice was achieved using subcutaneous MedRod implants that released either the low active estrone (E1) precursor or vehicle. A subgroup of E1 supplemented mice received daily oral gavage of FP4643, a well-characterized 17β-HSD-1 in-hibitor. Bioluminescence imaging (BLI) was used to measure tumor growth non-invasively. At sacrifice, mice receiving E1  and  treated with the  FP4643 inhibitor showed a  significant reduction in  tumor growth by approximately 65% compared to mice receiving E1. Tumors exhibited metastatic spread to the peritoneum, to the  lymphovascular space (LVI), and  to  the  thoracic cavity. Metastatic spread and  LVI  invasion were both significantly reduced in the inhibitor-treated group. Transcriptional profiling of tumors indicated that FP4643 treatment reduced the oncogenic potential at the mRNA level. In conclusion, we show that 17β-HSD-1 inhibition represents a promising novel endocrine treatment for EC.   </div