86 research outputs found
Transverse Momentum Evolution of Hadron-V0 Correlations in Proton-Proton Collisions at = 7 TeV
No full textThe Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN) in Geneva, Switzerland, is capable of accelerating beams of protons (pp) and heavy-ions (Pb+Pb) up to nearly the speed of light, which corresponds to center of mass energies of sqrt(s_NN) = 7 TeV and sqrt(s_NN) = 2.76 TeV, respectively. The goal of the pp program is to investigate physics of and beyond the standard model, while the heavy-ion program attempts to characterize the properties of a new state of matter, called the Quark Gluon Plasma. The main aim of this dissertation is to identify particle production mechanisms in pp collisions, also as a reference for possible modifications due to the plasma formation in heavy-ion collisions. Two-particle azimuthal correlation measurements were employed, which allow the study of high-pT parton fragmentation without full jet reconstruction. We present the results of correlations between charged trigger particles and associated strange baryons (Lambda) and mesons (K0S). Enhancements of the azimuthal correlations are seen at delta-phi = 0 and delta-phi = pi, resulting from back-to-back jet fragmentation in the parton center-of-mass system. Two model fit functions were introduced to characterize the properties of the jet peaks. Hard and soft yields were separated using the ZYAM method and extracted yields were compared with pQCD inspired models and inclusive spectra. The analysis was performed in different multiplicity bins to detect possible enhancements of Lambda or K0S yields and the Lambda/K0S ratio. The latter was observed in high multiplicity Pb+Pb collisions and interpreted as a novel production mechanism in the deconfined medium produced at the LHC. A novel data-driven feed-down correction for Lambdas is also introduced, which could allow a more accurate calculation of the primary Lambda
Strangeness production in two-particle azimuthal correlations on the near and away side measured with ALICE in pp collisions at = 7 TeV
No full textTwo-particle azimuthal correlations allow one to study high- parton fragmentation without full jet reconstruction. Enhancements of the azimuthal correlations are seen at and , resulting from back-to-back jet fragmentation in the parton center-of-mass system. We present the current status of the study of correlations between charged trigger particles and associated strange baryons () and mesons (K) in pp collisions at = 7 TeV. A data-driven feeddown correction for is also presented, which could allow a more accurate calculation of the primary K ratio in jets and the underlying event
Deep learning based rapid X-ray fluorescence signal extraction and image reconstruction for preclinical benchtop X-ray fluorescence computed tomography applications
No full textAbstract Recent research advances have resulted in an experimental benchtop X-ray fluorescence computed tomography (XFCT) system that likely meets the imaging dose/scan time constraints for benchtop XFCT imaging of live mice injected with gold nanoparticles (GNPs). For routine in vivo benchtop XFCT imaging, however, additional challenges, most notably the need for rapid/near-real-time handling of X-ray fluorescence (XRF) signal extraction and XFCT image reconstruction, must be successfully addressed. Here we propose a novel end-to-end deep learning (DL) framework that integrates a one-dimensional convolutional neural network (1D CNN) for rapid XRF signal extraction with a U-Net model for XFCT image reconstruction. We trained the models using a comprehensive dataset including experimentally-acquired and augmented XRF/scatter photon spectra from various GNP concentrations and imaging scenarios, including phantom and synthetic mouse models. The DL framework demonstrated exceptional performance in both tasks. The 1D CNN achieved a high coefficient-of-determination (R² > 0.9885) and a low mean-absolute-error (MAE < 0.6248) in XRF signal extraction. The U-Net model achieved an average structural-similarity-index-measure (SSIM) of 0.9791 and a peak signal-to-noise ratio (PSNR) of 39.11 in XFCT image reconstruction, closely matching ground truth images. Notably, the DL approach (vs. the conventional approach) reduced the total post-processing time per slice from approximately 6 min to just 1.25 s
Use of the Fully Spectroscopic Pixelated Cadmium Telluride Detector for Benchtop X-Ray Fluorescence Computed Tomography
No full textIn this work, we integrated a commercially-available fully-spectroscopic pixelated cadmium telluride (CdTe) detector system as a two-dimensional (2D) array detector into our existing benchtop cone-beam x-ray fluorescence computed tomography (XFCT) system. After integrating this detector, known as High-Energy X-ray Imaging Technology (HEXITEC), we performed quantitative imaging of gold nanoparticle (GNP) distribution in a small animal-sized phantom using our benchtop XFCT system. Owing to the upgraded detector component within our benchtop XFCT system, we were able to conduct this phantom imaging in an unprecedented manner by volumetric XFCT scans followed by XFCT image reconstruction in 3D. The current results showed that adoption of HEXITEC, in conjunction with a custom-made parallel-hole collimator, drastically reduced the XFCT scan time/dose. Compared with the previous work performed with our original benchtop XFCT system adopting a single crystal CdTe detector, the currently observed reduction was up to a factor of 5, while achieving comparable GNP detection limit under similar experimental conditions. Overall, we demonstrated, for the first time to the best our knowledge, the feasibility of benchtop XFCT imaging of small animal-sized objects containing biologically relevant GNP concentrations (on the order of 0.1 mg Au/cm(3) or 100 parts-per-million/ppm), with the scan time (on the order of 1 minute)/x-ray dose (on the order of 10 cGy) that are likely meeting the minimum requirements for routine preclinical imaging applications
Sensitivity Enhancement of an Experimental Benchtop X-Ray Fluorescence Imaging System by Deploying a Single Crystal Cadmium Telluride Detector System Optimized for High Flux X-Ray Operations
No full textIn this work, an energy-resolving thermoelectrically cooled single crystal cadmium telluride (CdTe) detector system upgraded with the latest firmware was optimized for high x-ray flux operations using high bias voltage and fast peaking time. This detector system was deployed into an experimental benchtop x-ray fluorescence (XRF) imaging/computed tomography (XFCT) system developed for quantitative imaging of metal nanoprobes such as gold nanoparticles (GNPs). Using the firmware-upgraded and existing/old CdTe detector systems, the Compton/XRF spectra from small (8 mm diameter) GNP-containing phantoms were acquired. The phantoms were irradiated with 1.8 mm Sn-filtered 125 kVp cone beam x-rays at 24 mA. The firmware-upgraded detector system produced relatively lower dead time under high x-ray flux, compared with the old detector system, and performed well with the spectral resolution of ~0.7 keV (in full width at half maximum) at 69 keV photon energy. Given the same 2 mm aperture detector collimator and irradiation time of 10 s, this detector system managed to score nearly 50% more gold XRF signals than the existing one at all GNP concentrations tested. This improvement resulted in the GNP detection limit of 0.02 wt. % which was lower than that (0.03 wt. %) achievable with the existing detector system. When combined with the detector collimator containing a larger (3 mm) aperture, the firmware-upgraded detector system produced drastically more gold XRF signal at a given GNP concentration (e.g., 9 times more for 1 wt. % GNP solution and irradiation time of 10 s), leading to further reduction in the GNP detection limit (i.e., 0.01 wt. %). The present investigation showed that the firmware upgraded CdTe detector system optimized for high x-ray flux operations allowed for better photon counting efficiency, thus leading to sensitivity enhancement of an experimental benchtop XRF/XFCT imaging system
TRANSVERSE MOMENTUM EVOLUTION OF HADRON-V0 CORRELATIONS IN PP COLLISIONS AT 7 TEV
No full textThe Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN) in Geneva, Switzerland, is capable of accelerating beams of protons (pp) and heavy-ions (Pb+Pb) up to nearly the speed of light, which corresponds to center of mass energies of 7 TeV and 2.76 TeV, respectively. The goal of the pp program is to investigate physics of and beyond the standard model, while the heavy-ion program attempts to characterize the properties of a new state of matter, called the Quark Gluon Plasma. The main aim of this dissertation is to identify particle production mechanisms in pp collisions, also as a reference for possible modifications due to the plasma formation in heavy-ion collisions. Two-particle azimuthal correlation measurements were employed, which allow the study of high-pT parton fragmentation without full jet reconstruction. We present the results of correlations between charged trigger particles and associated strange baryons and mesons. Enhancements of the azimuthal correlations are seen at dphi= 0 and dphi= pi, resulting from back-to-back jet fragmentation
in the parton center-of-mass system. Two model fit functions were
introduced to characterize the properties of the jet peaks. Hard and soft yields were seperated using the ZYAM method and extracted yields were compared with pQCD inspired models and inclusive spectra. The analysis was performed in different
multiplicity bins to detect possible enhancements of baryons or meson
yields and the baryon/meson ratio. The latter was observed in high multiplicity Pb+Pb collisions and interpreted as a novel production mechanism in the deconfined medium produced at the LHC. A novel data-driven feeddown correction for Lambda is also introduced, which could allow a more accurate calculation of the primary Xi.Physics, Department o
Nanoscale Gold Nanoparticle (Gnp)-Laden Tumor Cell Model and Its Use for Estimation of Intracellular Dose From Gnp-Induced Secondary Electrons
No full textBackground: Gold nanoparticles (GNPs) accumulated within tumor cells have been shown to sensitize tumors to radiotherapy. From a physics point of view, the observed GNP-mediated radiosensitization is due to various downstream effects of the secondary electron (SE) production from internalized GNPs such as GNP-mediated dose enhancement. Over the years, numerous computational investigations on GNP-mediated dose enhancement/radiosensitization have been conducted. However, such investigations have relied mostly on simple cellular geometry models and/or artificial GNP distributions. Thus, it is at least desirable, if not necessary, to conduct further investigations using cellular geometry models that properly reflect realistic cell morphology as well as internalized GNP distributions at the nanoscale.
Purpose: The primary aim of this study was to develop a nanometer-resolution geometry model of a GNP-laden tumor cell for computational investigations of GNP-mediated dose enhancement/radiosensitization. The secondary aim was to demonstrate the utility of this model by quantifying GNP-induced SE tracks/dose distribution at sub-cellular levels for further validation of a nanoscopic dose point kernel (nDPK) method against full-fledged Geant4 Monte Carlo (MC) simulation.
Methods: A transmission electron microscopy (TEM) image of a single cell showing cytoplasm, cellular nucleus, and internalized GNPs in the cellular endosome was segmented into sub-cellular levels based on pixel value thresholding. A corresponding material density was allocated to each pixel, and, by adding a thickness, each pixel was transformed to a geometric voxel and imported as a Geant4-acceptable input geometry file. In Geant4-Penelope MC simulation, a clinical 6 MV photon beam was applied, vertically or horizontally to the cell surface, and energy deposition to the cellular nucleus and cytoplasm, due to SEs emitted by internalized GNPs, was scored. Next, nDPK calculations were performed by generating virtual electron tracks from each GNP voxel to all nucleus and cytoplasm voxels. Subsequently, another set of Geant4 simulation was performed with both Penelope and DNA physics models under the geometry closely mimicking in vitro cell irradiation with a clinical 6 MV photon beam, allowing for derivation of nDPK specific to this geometry and further comparison between Gean4 simulation and nDPK method.
Results: The Geant4-calculated SE tracks and associated energy depositions showed significant dependence on photon incidence angle. For perpendicular incidence, nDPK results showed good agreement (average percentage pixel-to-pixel difference of 0.4% for cytoplasm and 0.5% for nucleus) with Geant4 results, while, for parallel incidence, the agreement became worse (-1.7%-0.7% for cytoplasm and -5.5%-0.8% for nucleus). Under the 6 MV cell irradiation geometry, nDPK results showed reasonable agreement (pixel-to-pixel Pearson\u27s product moment correlation coefficient of 0.91 for cytoplasm and 0.98 for nucleus) with Geant4 results.
Conclusions: The currently developed TEM-based model of a GNP-laden cell offers unprecedented details of realistic intracellular GNP distributions for nanoscopic computational investigations of GNP-mediated dose enhancement/radiosensitization. A benchmarking study performed with this model showed reasonable agreement between Geant4- and nDPK-calculated intracellular dose deposition by SEs emitted from internalized GNPs, especially under perpendicular incidence - a popular cell irradiation geometry and when the Geant4-Penelope physics model was used
Geant4-based Model of a Mouse Injected with Gold Nanoparticles for X-Ray Tomography Simulation Studies
No full textFeasibility of X-ray Fluorescence Computed Tomography (XFCT) Imaging of Human Lung Tumors loaded with Gold Nanoparticles: A Monte Carlo Study
No full textThe effect of integrating knowledge‐based planning with multicriteria optimization in treatment planning for prostate SBRT
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