Effect of autofrettage in the thick-walled cylinder with a radial cross-bore

The effect of autofrettage on the stress level in thick-walled cylinders with a radial cross-bore is investigated by applying inelastic finite element analysis with cyclic pressure loading. A macro is created in ANSYS to calculate the equivalent alternating stress intensity, S-eq, based on the ASME Boiler and Pressure Vessel Code. The value of S-eq is used to evaluate the fatigue life of the vessel. For a specific cyclic load level, a distinct optimum autofrettage pressure is identified by plotting autofrettage pressure against the number of cycles from design fatigue data. The fatigue life of the autofrettaged vessel with such an optimum pressure is increased compared with the case where no autofrettage is used

Training End-to-End Unrolled Iterative Neural Networks for SPECT Image Reconstruction

Training end-to-end unrolled iterative neural networks for SPECT image reconstruction requires a memory-efficient forward-backward projector for efficient backpropagation. This paper describes an open-source, high performance Julia implementation of a SPECT forward-backward projector that supports memory-efficient backpropagation with an exact adjoint. Our Julia projector uses only ~5% of the memory of an existing Matlab-based projector. We compare unrolling a CNN-regularized expectation-maximization (EM) algorithm with end-to-end training using our Julia projector with other training methods such as gradient truncation (ignoring gradients involving the projector) and sequential training, using XCAT phantoms and virtual patient (VP) phantoms generated from SIMIND Monte Carlo (MC) simulations. Simulation results with two different radionuclides (90Y and 177Lu) show that: 1) For 177Lu XCAT phantoms and 90Y VP phantoms, training unrolled EM algorithm in end-to-end fashion with our Julia projector yields the best reconstruction quality compared to other training methods and OSEM, both qualitatively and quantitatively. For VP phantoms with 177Lu radionuclide, the reconstructed images using end-to-end training are in higher quality than using sequential training and OSEM, but are comparable with using gradient truncation. We also find there exists a trade-off between computational cost and reconstruction accuracy for different training methods. End-to-end training has the highest accuracy because the correct gradient is used in backpropagation; sequential training yields worse reconstruction accuracy, but is significantly faster and uses much less memory.Comment: submitted to IEEE TRPM

Advanced three-dimensional tailored RF pulse for signal recovery in T 2 *-weighted functional magnetic resonance imaging

T 2 * -weighted functional MR images are plagued by signal loss artifacts caused by susceptibility-induced through-plane dephasing. We present major advances to the original three-dimensional tailored RF (3DTRF) pulse method that pre-compensates the dephasing using three-dimensional selective excitation. The proposed 3DTRF pulses are designed iteratively with off-resonance incorporation and with a novel echo-volumar trajectory that frequency-encodes in z and phase-encodes in x,y . We also propose a computational scheme to accelerate the pulse design process. We demonstrate effective signal recovery in a 5-mm slice in both phantom and inferior brain, using 3DTRF pulses that are only 15.4 ms long. Compared to the original method, the new approach leads to significantly reduced pulse length and enhancement in slice selectivity. 3D images of the slice volume confirm fidelity of the excited phase pattern and slice profile. Magn Reson Med, 2006. © 2006 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55837/1/21048_ftp.pd

Effect of Including Detector Response in SPECT Quantification of Focal I-131 Therapy

With a regularized strip-integral (1D) SAGE reconstruction, circular-orbit SPECT estimates of phantom focal 131-I activity vary with changes in the level of uniform background. They also vary with changes in image resolution due to different settings of the radius of rotation. To solve these problems, we investigated the effect of employing two different depth-dependent detector-response models. A regularized plane-by-plane (2D) SAGE algorithm reduced dependence of the counts-to-activity conversion factor on relative background concentration by 37% compared to the 1D SAGE. With unregularized multi-plane (3D) OSEM reconstruction, initial results showed: 1) a conversion factor that was independent of relative background concentration, and 2) a recovery coefficient that was approximately 1 for any sphere volume down to 20cc. We conclude that using a 3D detector-response model has the potential to eliminate bias problems. For a patient, the preliminary activity-estimate changes using 3D OSEM compared to 1D SAGE were: 1) +16% for a large tumor, and 2) -35% for a small tumor for which recovery-coefficient-based-correction-factor errors can be large.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85991/1/Fessler170.pd

Time of flight PET reconstruction using nonuniform update for regional recovery uniformity

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147742/1/mp13321.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147742/2/mp13321_am.pd

Detection and Genetic Environment of Pleuromutilin-Lincosamide-Streptogramin A Resistance Genes in Staphylococci Isolated from Pets

Increasing emergence of staphylococci resistant to pleuromutilins, lincosamides, and streptogramin A (PLSA) and isolated from humans and pets is a growing public health concern worldwide. Currently, there was only one published study regarding one of the PLSA genes, vga(A) detected in staphylococci isolated from cat. In this study, eleven pleuromutilin-resistant staphylococci from pets and two from their owners were isolated and further characterized for their antimicrobial susceptibilities, plasmid profiles, genotypes, and genetic context of the PLSA resistance genes. The gene sal(A) identified in 11 staphylococcal isolates was found for the first time in Staphylococcus haemolyticus, Staphylococcus epidermidis, and Staphylococcus xylosus. Moreover, these 11 isolates shared the identical regions flanking the sal(A) gene located in the chromosomal DNA. Two S. haemolyticus isolates from a cat and its owner carried similar vga(A)LC plasmids and displayed indistinguishable PFGE patterns. A novel chromosomal multidrug resistance genomic island (MDRGI) containing 13 resistance genes, including lsa(E), was firstly identified in S. epidermidis. In addition, vga(A)LC, sal(A), and lsa(E) were for the first time identified in staphylococcal isolates originating from pet animals. The plasmids, chromosomal DNA region, and MDRGI associated with the PLSA resistance genes vga(A), vga(A)LC, sal(A), and lsa(E) are present in staphylococci isolated from pets and humans and present significant challenges for the clinical management of infections by limiting therapeutic options

Oil accumulation in the model green alga Chlamydomonas reinhardtii: characterization, variability between common laboratory strains and relationship with starch reserves

International audienceBackground: When cultivated under stress conditions, many microalgae species accumulate both starch and oil (triacylglycerols). The model green microalga Chlamydomonas reinhardtii has recently emerged as a model to test genetic engineering or cultivation strategies aiming at increasing lipid yields for biodiesel production. Blocking starch synthesis has been suggested as a way to boost oil accumulation. Here, we characterize the triacylglycerol (TAG) accumulation process in Chlamydomonas and quantify TAGs in various wild-type and starchless strains. Results: In response to nitrogen deficiency, Chlamydomonas reinhardtii produced TAGs enriched in palmitic, oleic and linoleic acids that accumulated in oil-bodies. Oil synthesis was maximal between 2 and 3 days following nitrogen depletion and reached a plateau around day 5. In the first 48 hours of oil deposition, a~80% reduction in the major plastidial membrane lipids occurred. Upon nitrogen re-supply, mobilization of TAGs started after starch degradation but was completed within 24 hours. Comparison of oil content in five common laboratory strains (CC124, CC125, cw15, CC1690 and 11-32A) revealed a high variability, from 2 μg TAG per million cell in CC124 to 11 μg in 11-32A. Quantification of TAGs on a cell basis in three mutants affected in starch synthesis (cw15sta1-2, cw15sta6 and cw15sta7-1) showed that blocking starch synthesis did not result in TAG over-accumulation compared to their direct progenitor, the arginine auxotroph strain 330. Moreover, no significant correlation was found between cellular oil and starch levels among the twenty wild-type, mutants and complemented strains tested. By contrast, cellular oil content was found to increase steeply with salt concentration in the growth medium. At 100 mM NaCl, oil level similar to nitrogen depletion conditions could be reached in CC124 strain. Conclusion: A reference basis for future genetic studies of oil metabolism in Chlamydomonas is provided. Results highlight the importance of using direct progenitors as control strains when assessing the effect of mutations on oil content. They also suggest the existence in Chlamydomonas of complex interplays between oil synthesis, genetic background and stress conditions. Optimization of such interactions is an alternative to targeted metabolic engineering strategies in the search for high oil yields

Volumetry of low-contrast liver lesions with CT: Investigation of estimation uncertainties in a phantom study

Purpose: To evaluate the performance of lesion volumetry in hepatic CT as a function of various imaging acquisition parameters. Methods: An anthropomorphic abdominal phantom with removable liver inserts was designed for this study. Two liver inserts, each containing 19 synthetic lesions with varying diameter (6–40 mm), shape, contrast (10–65 HU), and both homogenous and mixed-density were designed to have background and lesion CT values corresponding to arterial and portal-venous phase imaging, respectively. The two phantoms were scanned using two commercial CT scanners (GE 750 HD and Siemens Biograph mCT) across a set of imaging protocols (four slice thicknesses, three effective mAs, two convolution kernels, two pitches). Two repeated scans were collected for each imaging protocol. All scans were analyzed using a matched-filter estimator for volume estimation, resulting in 6080 volume measurements across all of the synthetic lesions in the two liver phantoms. A subset of portal venous phase scans was also analyzed using a semi-automatic segmentation algorithm, resulting in about 900 additional volume measurements. Lesions associated with large measurement error (quantified by root mean square error) for most imaging protocols were considered not measurable by the volume estimation tools and excluded for the statistical analyses. Imaging protocols were grouped into distinct imaging conditions based on ANOVA analysis of factors for repeatability testing. Statistical analyses, including overall linearity analysis, grouped bias analysis with standard deviation evaluation, and repeatability analysis, were performed to assess the accuracy and precision of the liver lesion volume biomarker. Results: Lesions with lower contrast and size ≤10 mm were associated with higher measurement error and were excluded from further analysis. Lesion size, contrast, imaging slice thickness, dose, and scanner were found to be factors substantially influencing volume estimation. Twenty-four distinct repeatable imaging conditions were determined as protocols for each scanner with a fixed slice thickness and dose. For the matched-filter estimation approach, strong linearity was observed for all imaging data for lesions ≥20 mm. For the Siemens scanner with 50 mAs effective dose at 0.6 mm slice thickness, grouped bias was about −10%. For all other repeatable imaging conditions with both scanners, grouped biases were low (−3%–3%). There was a trend of increasing standard deviation with decreasing dose. For each fixed dose, the standard deviations were similar among the three larger slice thicknesses (1.25, 2.5, 5 mm for GE, 1.5, 3, 5 mm for Siemens). Repeatability coefficients ranged from about 8% to 75% and showed similar trend to grouped standard deviation. For the segmentation approach, the results led to similar conclusions for both lesion characteristic factors and imaging factors but with increasing magnitude in all the error metrics assessed. Conclusions: Results showed that liver lesion volumetry was strongly dependent on lesion size, contrast, acquisition dose, and their interactions. The overall performances were similar for images reconstructed with larger slice thicknesses, clinically used pitches, kernels, and doses. Conditions that yielded repeatable measurements were identified and they agreed with the Quantitative Imaging Biomarker Alliance’s (QIBA) profile requirements in general. The authors’ findings also suggest potential refinements to these guidelines for the tumor volume biomarker, especially for soft-tissue lesions