Investigation of dose perturbations and the radiographic visibility of potential fiducials for proton radiation therapy of the prostate

Image guidance using implanted fiducial markers is commonly used to ensure accurate and reproducible target positioning in radiation therapy for prostate cancer. The ideal fiducial marker is clearly visible in kV imaging, does not perturb the therapeutic dose in the target volume and does not cause any artifacts on the CT images used for treatment planning. As yet, ideal markers that fully meet all three of these criteria have not been reported. In this study, 12 fiducial markers were evaluated for their potential clinical utility in proton radiation therapy for prostate cancer. In order to identify the good candidates, each fiducial was imaged using a CT scanner as well as a kV imaging system. Additionally, the dose perturbation caused by each fiducial was quantified using radiochromic film and a clinical proton beam. Based on the results, three fiducials were identified as good candidates for use in proton radiotherapy of prostate cancer. © 2011 Institute of Physics and Engineering in Medicine

2D vs 3D gamma analysis: Establishment of comparable clinical action limits

Purpose: As clinics begin to use 3D metrics for intensity-modulated radiation therapy (IMRT) quality assurance; these metrics will often produce results different from those produced by their 2D counterparts. 3D and 2D gamma analyses would be expected to produce different values, because of the different search space available. We compared the results of 2D and 3D gamma analysis (where both datasets were generated the same way) for clinical treatment plans.                    Methods: 50 IMRT plans were selected from our database and recalculated using Monte Carlo. Treatment planning system-calculated (“evaluated”) and Monte Carlo-recalculated (“reference”) dose distributions were compared using 2D and 3D gamma analysis. This analysis was performed using a variety of dose-difference (5%, 3%, 2%, and 1%) and distance-to-agreement (5, 3, 2, and 1 mm) acceptance criteria, low-dose thresholds (5%, 10%, and 15% of the prescription dose), and data grid sizes (1.0, 1.5, and 3.0 mm). Each comparison was evaluated to determine the average 2D and 3D gamma and percentage of pixels passing gamma.Results: Average gamma and percentage of passing pixels for each acceptance criterion demonstrated better agreement for 3D than for 2D analysis for every plan comparison. Average difference in the percentage of passing pixels between the 2D and 3D analyses with no low-dose threshold ranged from 0.9% to 2.1%. Similarly, using a low-dose threshold resulted in a differences ranging from 0.8% to 1.5%. No appreciable differences in gamma with changes in the data density (constant difference: 0.8% for 2D vs. 3D) were observed.Conclusion: We found that 3D gamma analysis resulted in up to 2.9% more pixels passing than 2D analysis.  Factors such as inherent dosimeter differences may be an important additional consideration to the extra dimension of available data that was evaluated in this study.------------------------------------Cite this article as: Pulliam KB, Huang JY, Bosca R, Followill D, Kry SF. 2D vs. 3D gamma analysis: Establishment of comparable clinical action limits. Int J Cancer Ther Oncol 2014; 2(2):020231. DOI: 10.14319/ijcto.0202.3

Gamma Lines without a Continuum: Thermal Models for the Fermi-LAT 130 GeV Gamma Line

Recent claims of a line in the Fermi-LAT photon spectrum at 130 GeV are suggestive of dark matter annihilation in the galactic center and other dark matter-dominated regions. If the Fermi feature is indeed due to dark matter annihilation, the best-fit line cross-section, together with the lack of any corresponding excess in continuum photons, poses an interesting puzzle for models of thermal dark matter: the line cross-section is too large to be generated radiatively from open Standard Model annihilation modes, and too small to provide efficient dark matter annihilation in the early universe. We discuss two mechanisms to solve this puzzle and illustrate each with a simple reference model in which the dominant dark matter annihilation channel is photonic final states. The first mechanism we employ is resonant annihilation, which enhances the annihilation cross-section during freezeout and allows for a sufficiently large present-day annihilation cross section. Second, we consider cascade annihilation, with a hierarchy between p-wave and s-wave processes. Both mechanisms require mass near-degeneracies and predict states with masses closely related to the dark matter mass; resonant freezeout in addition requires new charged particles at the TeV scale.Comment: 17 pages, 8 figure

Evaluation of three commercial metal artifact reduction methods for CT simulations in radiation therapy

Purpose: To evaluate the success of three commercial metal artifact reduction methods (MAR) in the context of radiation therapy treatment planning.Methods: Three MAR strategies were evaluated: Philips O-MAR, monochromatic imaging using Gemstone Spectral Imaging (GSI) dual energy CT, and monochromatic imaging with metal artifact reduction software (GSI-MARs). The Gammex RMI 467 tissue characterization phantom with several metal rods and two anthropomorphic phantoms (pelvic phantom with hip prosthesis and head phantom with dental fillings), were scanned with and without metals (baseline). Each MAR method was evaluated based on CT number accuracy, metal size accuracy, and reduction in the severity of streak artifacts. CT number difference maps between the baseline and metal scan images were calculated, and the severity of streak artifacts was quantified using the percentage of pixels with > 40 HU error (“bad pixels”).Results: Philips O-MAR generally reduced HU errors in the RMI phantom. However, increased errors and induced artifacts were observed for lung materials. GSI monochromatic 70keV images generally showed similar HU errors as conventional 120kVp imaging, while 140keV images reduced HU errors. All the imaging techniques represented the diameter of a stainless steel rod to within ±1.6mm (2 pixels). For the hip prosthesis, O-MAR reduced the average % bad pixels from 47% to 32%. For GSI 140keV imaging, the % bad pixels was reduced from 37% to 29% compared to 120kVp imaging, and GSI-MARs further reduced it to 12%. For the head phantom, none of the MAR methods was particularly successful.Conclusion: O-MAR resulted in consistent artifact reduction but exhibited induced artifacts for metals located near lung tissue. GSI imaging at 140keV gave consistent reduction in HU errors and severity of artifacts. GSI-MARs at 140keV was the most successful MAR method for the hip prosthesis but exhibited induced artifacts at the edges of metals in some cases.---------------------------------Cite this article as: Huang JY, Kerns JR, Nute JL, Liu X, Stingo FC, Followill DS, Mirkovic D, Howell RM, Kry SF. Evaluation of three commercial metal artifact reduction methods for CT simulations in radiation therapy. Int J Cancer Ther Oncol 2014; 2(2):020224. DOI: 10.14319/ijcto.0202.2

Modeling Initiation of Ewing Sarcoma in Human Neural Crest Cells

Ewing sarcoma family tumors (ESFT) are aggressive bone and soft tissue tumors that express EWS-ETS fusion genes as driver mutations. Although the histogenesis of ESFT is controversial, mesenchymal (MSC) and/or neural crest (NCSC) stem cells have been implicated as cells of origin. For the current study we evaluated the consequences of EWS-FLI1 expression in human embryonic stem cell-derived NCSC (hNCSC). Ectopic expression of EWS-FLI1 in undifferentiated hNCSC and their neuro-mesenchymal stem cell (hNC-MSC) progeny was readily tolerated and led to altered expression of both well established as well as novel EWS-FLI1 target genes. Importantly, whole genome expression profiling studies revealed that the molecular signature of established ESFT is more similar to hNCSC than any other normal tissue, including MSC, indicating that maintenance or reactivation of the NCSC program is a feature of ESFT pathogenesis. Consistent with this hypothesis, EWS-FLI1 induced hNCSC genes as well as the polycomb proteins BMI-1 and EZH2 in hNC-MSC. In addition, up-regulation of BMI-1 was associated with avoidance of cellular senescence and reversible silencing of p16. Together these studies confirm that, unlike terminally differentiated cells but consistent with bone marrow-derived MSC, NCSC tolerate expression of EWS-FLI1 and ectopic expression of the oncogene initiates transition to an ESFT-like state. In addition, to our knowledge this is the first demonstration that EWS-FLI1-mediated induction of BMI-1 and epigenetic silencing of p16 might be critical early initiating events in ESFT tumorigenesis

Molecular Biomarkers of Vascular Dysfunction in Obstructive Sleep Apnea

Untreated and long-lasting obstructive sleep apnea (OSA) may lead to important vascular abnormalities, including endothelial cell (EC) dysfunction, hypertension, and atherosclerosis. We observed a correlation between microcirculatory reactivity and endothelium-dependent release of nitric oxide in OSA patients. Therefore, we hypothesized that OSA affects (micro)vasculature and we aimed to identify vascular gene targets of OSA that could possibly serve as reliable biomarkers of severity of the disease and possibly of vascular risk. Using quantitative RT-PCR, we evaluated gene expression in skin biopsies of OSA patients, mouse aortas from animals exposed to 4-week intermittent hypoxia (IH; rapid oscillations in oxygen desaturation and reoxygenation), and human dermal microvascular (HMVEC) and coronary artery endothelial cells (HCAEC) cultured under IH. We demonstrate a significant upregulation of endothelial nitric oxide synthase (eNOS), tumor necrosis factor-alpha-induced protein 3 (TNFAIP3; A20), hypoxia-inducible factor 1 alpha (HIF-1α?? and vascular endothelial growth factor (VEGF) expression in skin biopsies obtained from OSA patients with severe nocturnal hypoxemia (nadir saturated oxygen levels [SaO2]<75%) compared to mildly hypoxemic OSA patients (SaO2 75%–90%) and a significant upregulation of vascular cell adhesion molecule 1 (VCAM-1) expression compared to control subjects. Gene expression profile in aortas of mice exposed to IH demonstrated a significant upregulation of eNOS and VEGF. In an in vitro model of OSA, IH increased expression of A20 and decreased eNOS and HIF-1α expression in HMVEC, while increased A20, VCAM-1 and HIF-1αexpression in HCAEC, indicating that EC in culture originating from distinct vascular beds respond differently to IH stress. We conclude that gene expression profiles in skin of OSA patients may correlate with disease severity and, if validated by further studies, could possibly predict vascular risk in OSA patients

The NS1 Glycoprotein Can Generate Dramatic Antibody-Enhanced Dengue Viral Replication in Normal Out-Bred Mice Resulting in Lethal Multi-Organ Disease

Antibody-enhanced replication (AER) of dengue type-2 virus (DENV-2) strains and production of antibody-enhanced disease (AED) was tested in out-bred mice. Polyclonal antibodies (PAbs) generated against the nonstructural-1 (NS1) glycoprotein candidate vaccine of the New Guinea-C (NG-C) or NSx strains reacted strongly and weakly with these antigens, respectively. These PAbs contained the IgG2a subclass, which cross-reacted with the virion-associated envelope (E) glycoprotein of the DENV-2 NSx strain, suggesting that they could generate its AER via all mouse Fcγ-receptor classes. Indeed, when these mice were challenged with a low dose (<0.5 LD50) of the DENV-2 NSx strain, but not the NG-C strain, they all generated dramatic and lethal DENV-2 AER/AED. These AER/AED mice developed life-threatening acute respiratory distress syndrome (ARDS), displayed by diffuse alveolar damage (DAD) resulting from i) dramatic interstitial alveolar septa-thickening with mononuclear cells, ii) some hyperplasia of alveolar type-II pneumocytes, iii) copious intra-alveolar protein secretion, iv) some hyaline membrane-covered alveolar walls, and v) DENV-2 antigen-positive alveolar macrophages. These mice also developed meningo-encephalitis, with greater than 90,000-fold DENV-2 AER titers in microglial cells located throughout their brain parenchyma, some of which formed nodules around dead neurons. Their spleens contained infiltrated megakaryocytes with DENV-2 antigen-positive red-pulp macrophages, while their livers displayed extensive necrosis, apoptosis and macro- and micro-steatosis, with DENV-2 antigen-positive Kuppfer cells and hepatocytes. Their infections were confirmed by DENV-2 isolations from their lungs, spleens and livers. These findings accord with those reported in fatal human “severe dengue” cases. This DENV-2 AER/AED was blocked by high concentrations of only the NG-C NS1 glycoprotein. These results imply a potential hazard of DENV NS1 glycoprotein-based vaccines, particularly against DENV strains that contain multiple mutations or genetic recombination within or between their DENV E and NS1 glycoprotein-encoding genes. The model provides potential for assessing DENV strain pathogenicity and anti-DENV therapies in normal mice

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages