Efficient and Robust Weighted Least-Squares Cell-Average Gradient Construction Methods for the Simulation of Scramjet Flows

The ability to solve the equations governing the hypersonic turbulent flow of a real gas on unstructured grids using a spatially-elliptic, 2nd-order accurate, cell-centered, finite-volume method has been recently implemented in the VULCAN-CFD code. The construction of cell-average gradients using a weighted linear least-squares method and the use of these gradients in the construction of the inviscid fluxes is the focus of this paper. A comparison of least-squares stencil construction methodologies is presented and approaches designed to minimize the number of cells used to augment/stabilize the least-squares stencil while preserving accuracy are explored. Due to our interest in hypersonic flow, a robust multidimensional cell-average gradient limiter procedure that is consistent with the stencil used to construct the cellaverage gradients is described. Canonical problems are computed to illustrate the challenges and investigate the accuracy, robustness and convergence behavior of the cell-average gradient methods on unstructured cell-centered finite-volume grids. Finally, thermally perfect, chemically frozen, Mach 7.8 turbulent flow of air through a scramjet engine flowpath is computed and compared with experimental data to demonstrate the robustness, accuracy and convergence behavior of the preferred gradient method for a realistic 3-D geometry on a non-hex-dominant grid

Callose (β-1,3 glucan) is essential for Arabidopsis pollen wall patterning, but not tube growth

BACKGROUND: Callose (β-1,3 glucan) separates developing pollen grains, preventing their underlying walls (exine) from fusing. The pollen tubes that transport sperm to female gametes also contain callose, both in their walls as well as in the plugs that segment growing tubes. Mutations in CalS5, one of several Arabidopsis β-1,3 glucan synthases, were previously shown to disrupt callose formation around developing microspores, causing aberrations in exine patterning, degeneration of developing microspores, and pollen sterility. RESULTS: Here, we describe three additional cals5 alleles that similarly alter exine patterns, but instead produce fertile pollen. Moreover, one of these alleles (cals5-3) resulted in the formation of pollen tubes that lacked callose walls and plugs. In self-pollinated plants, these tubes led to successful fertilization, but they were at a slight disadvantage when competing with wild type. CONCLUSION: Contrary to a previous report, these results demonstrate that a structured exine layer is not required for pollen development, viability or fertility. In addition, despite the presence of callose-enriched walls and callose plugs in pollen tubes, the results presented here indicate that callose is not required for pollen tube functions

Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms

PURPOSE: We develop a practical, iterative algorithm for image-reconstruction in under-sampled tomographic systems, such as digital breast tomosynthesis (DBT). METHOD: The algorithm controls image regularity by minimizing the image total $p$-variation (TpV), a function that reduces to the total variation when $p=1.0$ or the image roughness when $p=2.0$. Constraints on the image, such as image positivity and estimated projection-data tolerance, are enforced by projection onto convex sets (POCS). The fact that the tomographic system is under-sampled translates to the mathematical property that many widely varied resultant volumes may correspond to a given data tolerance. Thus the application of image regularity serves two purposes: (1) reduction of the number of resultant volumes out of those allowed by fixing the data tolerance, finding the minimum image TpV for fixed data tolerance, and (2) traditional regularization, sacrificing data fidelity for higher image regularity. The present algorithm allows for this dual role of image regularity in under-sampled tomography. RESULTS: The proposed image-reconstruction algorithm is applied to three clinical DBT data sets. The DBT cases include one with microcalcifications and two with masses. CONCLUSION: Results indicate that there may be a substantial advantage in using the present image-reconstruction algorithm for microcalcification imaging.Comment: Submitted to Medical Physic

Knowledge and self-efficacy among healthcare providers towards novel tobacco products in Japan

Several new tobacco products, including e-cigarettes and heated tobacco products (HTPs), have become highly prevalent in Japan. As safety data continues to evolve, healthcare providers are considered important sources for product use, yet little is known about provider knowledge or self-efficacy to counsel patient about novel tobacco product use. This cross-sectional study used data from a Japanese Association of Smoking Control Science (JASCS) online survey of physicians, pharmacists, nurses, and public health practitioners (N = 277) to assess provider knowledge of novel tobacco products and self-efficacy to counsel patients about product use. Correlates of knowledge and self-efficacy were also assessed. More than half the sample had received previous training in treating tobacco use, but 62% of respondents had no knowledge of HTPs; 80% of respondents indicated that they occasionally or always provide smoking cessation support. Overall knowledge of HTPs was low (41.4% correct) with higher knowledge for HTPs containing nicotine (89% correct) vs. HTPs emitting no carbon monoxide (25%). Self-efficacy to counsel patients about novel tobacco products was low on a scale ranging from 10 to 70 (Mean = 31.2; Standard Deviation = 16.7). Greater knowledge of HTPs was associated with male gender, higher rates of training at JASCS and previous learning about HTPs at JASCS. (p < 0.05). The results suggested that healthcare providers' knowledge and self-efficacy regarding novel tobacco products remains low in Japan, but additional training may improve it

Histogram Analysis of ADC in Brain Tumor Patients

At various stage of progression, most brain tumors are not homogenous. In this presentation, we retrospectively studied the distribution of ADC values inside tumor volume during the course of tumor treatment and progression for a selective group of patients who underwent an anti-VEGF trial. Complete MRI studies were obtained for this selected group of patients including pre- and multiple follow-up, post-treatment imaging studies. In each MRI imaging study, multiple scan series were obtained as a standard protocol which includes T1, T2, T1-post contrast, FLAIR and DTI derived images (ADC, FA etc.) for each visit. All scan series (T1, T2, FLAIR, post-contrast T1) were registered to the corresponding DTI scan at patient\u27s first visit. Conventionally, hyper-intensity regions on T1-post contrast images are believed to represent the core tumor region while regions highlighted by FLAIR may overestimate tumor size. Thus we annotated tumor regions on the T1-post contrast scans and ADC intensity values for pixels were extracted inside tumor regions as defined on T1-post scans. We fit a mixture Gaussian (MG) model for the extracted pixels using the Expectation-Maximization (EM) algorithm, which produced a set of parameters (mean, various and mixture coefficients) for the MG model. This procedure was performed for each visits resulting in a series of GM parameters. We studied the parameters fitted for ADC and see if they can be used as indicators for tumor progression. Additionally, we studied the ADC characteristics in the peri-tumoral region as identified by hyper-intensity on FLAIR scans. The results show that ADC histogram analysis of the tumor region supports the two compartment model that suggests the low ADC value subregion corresponding to densely packed cancer cell while the higher ADC value region corresponding to a mixture of viable and necrotic cells with superimposed edema. Careful studies of the composition and relative volume of the two compartments in tumor region may provide some insights in the early assessment of tumor response to therapy for recurrence brain cancer patients

Preliminary study on phase-contrast digital tomosynthesis: development and evaluation of experimental system

ABSTRACT The advantage of X-ray phase imaging is its ability to obtain information on soft tissues, which is difficult using conventional X-ray imaging. Moreover, a sharp X-ray image can be obtained from the edge effect resulting from phase contrast. Digital tomosynthesis is an imaging technique used to reconstruct multiple planes in a single scan. In this study, we developed an experimental system that combines the phase-contrast and digital tomosynthesis techniques. Our experimental system consists of a transmission-type micro-focus X-ray source (minimum focus size: 1 μm). We also introduced an indirect conversion-type flat panel detector (pixel pitch: 50 μm, matrix size: 2366 × 2368) as an imaging device. The sample is placed on a computer-controlled rotation table, and projection images are captured from various angles. The images are then reconstructed using the filtered back projection method. In the experiments, a tomosynthesis image of an acrylic phantom was obtained at a tube voltage of 40 kV and at a maximum projection angle of ±20°. To evaluate the edge enhancement effect by phase contrast, the resolution, degree of edge enhancement, and image contrast were measured using the acrylic phantom. A good edge enhancement effect was confirmed under the specified conditions. Furthermore, we compared to the shape between the projection image and the tomosynthesis image and found that the tomosynthesis image showed high shape reproducibility compared to the conventional projection image. These results indicate that phase-contrast digital tomosynthesis may be useful for the three-dimensional imaging of low-contrast material

Pittsburgh Center for Artificial Intelligence Innovation in Medical Imaging

We propose to create a medical imaging artificial intelligence (AI) center (name: Pittsburgh Center for Artificial Intelligence Innovation in Medical Imaging). AI is the new revolutionary technique for medical research and is reshaping tomorrow’s clinical practice in medical imaging (radiology and pathology). Our long-term vision is to build a center for innovative AI in clinical translational medical imaging by combining computational expertise and clinical resources across Pitt, UPMC, and CMU. The Center concept is a formalization of a group of researchers and clinicians that are united by the common theme: “building advanced and trustworthy imaging AI for clinical applications.” Our short-term plan is to assemble dedicated members from the School of Medicine, the School of Engineering, and the School of Computing and Information. We seek a Scaling grant from the Momentum Funds to foster collaborative activities of the Center between these three Pitt schools to provide the essential components of a competitive P41 (Biomedical Technology Resource Centers) center grant in 2 years. The National Institute of Biomedical Imaging and Bioengineering (NIBIB) P41 mechanism aligns with the overall vision of this initiative to develop specific AI imaging tools and to support the dissemination and commercialization pathways that are essential to bringing AI imaging tools to clinical practice. These projects will include key components: 1) Clinical need-driven medical imaging AI development and evaluation of tools, models, systems, and informatics, 2) Core imaging AI theory, methodology, and algorithm investigation, and 3) Linking imaging phenotypes to the biological (genomics and proteomics) underpinnings. To date, we have already 35 members for the Center. The Pitt Momentum Funds will provide critical scaling support to promote communication between the three Pitt schools to develop a competitive P41 grant application and a sustainable framework to ensure the clinical impact of these AI imaging tools

Using breast radiographers\u27 reports as a second opinion for radiologists\u27 readings of microcalcifications in digital mammography

Objective: The aim of this study was to investigate a practical method for incorporating radiographers\u27 reports with radiologists\u27 readings of digital mammograms. Methods: This simulation study was conducted using data from a free-response receiver operating characteristic observer study obtained with 75 cases (25 malignant, 25 benign and 25 normal cases) of digital mammograms. Each of the rating scores obtained by six breast radiographers was utilized as a second opinion for four radiologists\u27 readings with the radiographers\u27 reports. A logical "OR" operation with various criteria settings was simulated for deciding an appropriate method to select a radiographer\u27s report in all combinations of radiologists and radiographers. The average figure of merit (FOM) of the radiologists\u27 performances was statistically analysed using a jackknife procedure (JAFROC) to verify the clinical utility of using radiographers\u27 reports. Results: Potential improvement of the average FOM of the radiologists\u27 performances for identifying malignant microcalcifications could be expected when using radiographers\u27 reports as a second opinion. When the threshold value of 2.6 in Breast Imaging-Reporting and Data System (BI-RADS®) assessment was applied to adopt/ reject a radiographer\u27s report, FOMs of radiologists\u27 performances were further improved. Conclusion: When using breast radiographers\u27 reports as a second opinion, radiologists\u27 performances potentially improved when reading digital mammograms. It could be anticipated that radiologists\u27 performances were improved further by setting a threshold value on the BIRADS assessment provided by the radiographers. Advances in knowledge: For the effective use of a radiographer\u27s report as a second opinion, radiographers\u27 rating scores and its criteria setting for adoption/ rejection would be necessary

Definition of target antigens for naturally occurring CD4+ CD25+ regulatory T cells

The antigenic targets recognized by naturally occurring CD4+ CD25+ regulatory T cells (T reg cells) have been elusive. We have serologically defined a series of broadly expressed self-antigens derived from chemically induced mouse sarcomas by serological identification of antigens by recombinant expression cloning (SEREX). CD4+ CD25+ T cells from mice immunized with SEREX-defined self-antigens had strong suppressive activity on peptide-specific proliferation of CD4+ CD25− T cells and CD8+ T cells. The suppressive effect was observed without in vitro T cell stimulation. Foxp3 expression in these CD4+ CD25+ T cells from immunized mice was 5–10 times greater than CD4+ CD25+ T cells derived from naive mice. The suppressive effect required cellular contact and was blocked by anti-glucocorticoid–induced tumor necrosis factor receptor family–related gene antibody. In vitro suppressive activity essentially disappeared 8 wk after the last immunization. However, it was regained by in vitro restimulation with cognate self-antigen protein but not with control protein. We propose that SEREX-defined self-antigens such as those used in this study represent self-antigens that elicit naturally occurring CD4+ CD25+ T reg cells