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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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868 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Imaging of moving fiducial markers during radiotherapy using a fast, efficient active pixel sensor based EPID

Purpose: The purpose of this work was to investigate the use of an experimental complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) for tracking of moving fiducial markers during radiotherapy. Methods: The APS has an active area of 5.4 x 5.4 cm and maximum full frame read-out rate of 20 frame s{sup -1}, with the option to read out a region-of-interest (ROI) at an increased rate. It was coupled to a 4 mm thick ZnWO4 scintillator which provided a quantum efficiency (QE) of 8% for a 6 MV x-ray treatment beam. The APS was compared with a standard iViewGT flat panel amorphous Silicon (a-Si) electronic portal imaging device (EPID), with a QE of 0.34% and a frame-rate of 2.5 frame s{sup -1}. To investigate the ability of the two systems to image markers, four gold cylinders of length 8 mm and diameter 0.8, 1.2, 1.6, and 2 mm were placed on a motion-platform. Images of the stationary markers were acquired using the APS at a frame-rate of 20 frame s{sup -1}, and a dose-rate of 143 MU min{sup -1} to avoid saturation. EPID images were acquired at the maximum frame-rate of 2.5 frame s{sup -1}, and a reduced dose-rate of 19 MU min{sup -1} to provide a similar dose per frame to the APS. Signal-to-noise ratio (SNR) of the background signal and contrast-to-noise ratio (CNR) of the marker signal relative to the background were evaluated for both imagers at doses of 0.125 to 2 MU. Results: Image quality and marker visibility was found to be greater in the APS with SNR {approx}5 times greater than in the EPID and CNR up to an order of magnitude greater for all four markers. To investigate the ability to image and track moving markers the motion-platform was moved to simulate a breathing cycle with period 6 s, amplitude 20 mm and maximum speed 13.2 mm s{sup -1}. At the minimum integration time of 50 ms a tracking algorithm applied to the APS data found all four markers with a success rate of {>=}92% and positional error {<=}90 {mu}m. At an integration time of 400 ms the smallest marker became difficult to detect when moving. The detection of moving markers using the a-Si EPID was difficult even at the maximum dose-rate of 592 MU min{sup -1} due to the lower QE and longer integration time of 400 ms. Conclusions: This work demonstrates that a fast read-out, high QE APS may be useful in the tracking of moving fiducial markers during radiotherapy. Further study is required to investigate the tracking of markers moving in 3D in a treatment beam attenuated by moving patient anatomy. This will require a larger sensor with ROI read-out to maintain speed and a manageable data-rate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Reducing Ground-based Astrometric Errors with Gaia and Gaussian Processes

Stochastic field distortions caused by atmospheric turbulence are a fundamental limitation to the astrometric accuracy of ground-based imaging. This distortion field is measurable at the locations of stars with accurate positions provided by the Gaia DR2 catalog; we develop the use of Gaussian process regression (GPR) to interpolate the distortion field to arbitrary locations in each exposure. We introduce an extension to standard GPR techniques that exploits the knowledge that the 2D distortion field is curl-free. Applied to several hundred 90 s exposures from the Dark Energy Survey as a test bed, we find that the GPR correction reduces the variance of the turbulent astrometric distortions ≈12× , on average, with better performance in denser regions of the Gaia catalog. The rms per-coordinate distortion in the riz bands is typically ≈7 mas before any correction and ≈2 mas after application of the GPR model. The GPR astrometric corrections are validated by the observation that their use reduces, from 10 to 5 mas rms, the residuals to an orbit fit to riz-band observations over 5 yr of the r = 18.5 trans-Neptunian object Eris. We also propose a GPR method, not yet implemented, for simultaneously estimating the turbulence fields and the 5D stellar solutions in a stack of overlapping exposures, which should yield further turbulence reductions in future deep surveys.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Effects of pulse duration on magnetostimulation thresholds

Purpose: Medical imaging techniques such as magnetic resonance imaging and magnetic particle imaging (MPI) utilize time-varying magnetic fields that are subject to magnetostimulation limits, which often limit the speed of the imaging process. Various human-subject experiments have studied the amplitude and frequency dependence of these thresholds for gradient or homogeneous magnetic fields. Another contributing factor was shown to be number of cycles in a magnetic pulse, where the thresholds decreased with longer pulses. The latter result was demonstrated on two subjects only, at a single frequency of 1.27 kHz. Hence, whether the observed effect was due to the number of cycles or due to the pulse duration was not specified. In addition, a gradient-type field was utilized; hence, whether the same phenomenon applies to homogeneous magnetic fields remained unknown. Here, the authors investigate the pulse duration dependence of magnetostimulation limits for a 20-fold range of frequencies using homogeneous magnetic fields, such as the ones used for the drive field in MPI. Methods: Magnetostimulation thresholds were measured in the arms of six healthy subjects (age: 27 ± 5 yr). Each experiment comprised testing the thresholds at eight different pulse durations between 2 and 125 ms at a single frequency, which took approximately 30–40 min/subject. A total of 34 experiments were performed at three different frequencies: 1.2, 5.7, and 25.5 kHz. A solenoid coil providing homogeneous magnetic field was used to induce stimulation, and the field amplitude was measured in real time. A pre-emphasis based pulse shaping method was employed to accurately control the pulse durations. Subjects reported stimulation via a mouse click whenever they felt a twitching/tingling sensation. A sigmoid function was fitted to the subject responses to find the threshold at a specific frequency and duration, and the whole procedure was repeated at all relevant frequencies and pulse durations. Results: The magnetostimulation limits decreased with increasing pulse duration (T{sub pulse}). For T{sub pulse} < 18 ms, the thresholds were significantly higher than at the longest pulse durations (p < 0.01, paired Wilcoxon signed-rank test). The normalized magnetostimulation threshold (B{sub Norm}) vs duration curve at all three frequencies agreed almost identically, indicating that the observed effect is independent of the operating frequency. At the shortest pulse duration (T{sub pulse} ≈ 2 ms), the thresholds were approximately 24% higher than at the asymptotes. The thresholds decreased to within 4% of their asymptotic values for T{sub pulse} > 20 ms. These trends were well characterized (R{sup 2} = 0.78) by a stretched exponential function given by B{sub Norm}=1+αe{sup −(T{sub p}{sub u}{sub l}{sub s}{sub e}/β){sup γ}}, where the fitted parameters were α = 0.44, β = 4.32, and γ = 0.60. Conclusions: This work shows for the first time that the magnetostimulation thresholds decrease with increasing pulse duration, and that this effect is independent of the operating frequency. Normalized threshold vs duration trends are almost identical for a 20-fold range of frequencies: the thresholds are significantly higher at short pulse durations and settle to within 4% of their asymptotic values for durations longer than 20 ms. These results emphasize the importance of matching the human-subject experiments to the imaging conditions of a particular setup. Knowing the dependence of the safety limits to all contributing factors is critical for increasing the time-efficiency of imaging systems that utilize time-varying magnetic fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A semi–automatic analytical methodology for characterizing the energy consumption of MRI systems using load duration curves

Background and purpose: Magnetic resonance imaging (MRI) scanners are a major contributor to greenhouse gas emissions from the healthcare sector, and efforts to improve energy efficiency and reduce energy consumption rely on quantification of the characteristics of energy consumption. The purpose of this work was to develop a semi-automatic analytical methodology for the characterization of the energy consumption of MRI systems using only the load duration curve (LDC). LDCs are a fundamental tool used across various fields to analyze and understand the behavior of loads over time. Methods: An electric current transformer sensor and data logger were installed on two 3T MRI scanners from two vendors, termed M1 (outpatient scanner) and M2 (inpatient/emergency scanner). Data was collected for 1 month (7/11/2023 to 8/11/2023). Active power was calculated, assuming a balanced three-phase system, using the average current measured across all three phases, a 480 V reference voltage for both machines, and vendor-provided power factors. An LDC was constructed for each system by sorting the active power values in descending order and computing the cumulative time (in units of percentage) for each data point. The first derivative of the LDC was then computed (LDC’), smoothed by convolution with a window function (sLDC’), and used to detect transitions between different system modes including (in descending power levels): scan, prepared-to-scan, idle, low-power, and off. The final, segmented LDC was used to measure time (% total time), total energy (kWh), and mean power (kW) for each system mode on both scanners. The method was validated by comparing mean power values, computed using the segmented 1-month LDC, for each nonproductive system mode (i.e., prepared-to-scan, idle, lower-power, and off) against power levels measured after a deliberate system shutdown was performed for each scanner (1 day worth of data). Results: The validation revealed differences in mean power values <1.4% for all nonproductive modes and both scanners. In the scan system mode, the mean power values ranged from 29.8 to 37.2 kW and the total energy consumed for 1 month ranged from 11 106 to 14 466 kWh depending on the scanner. Over the course of 1 month, the portion of time the scanners were in nonproductive modes ranged from 76% to 80% across scanners and the nonproductive energy consumption ranged from 8010 to 6722 kWh depending on the scanner. The M1 (outpatient) scanner consumed 99.9 and 183.9 kWh/day in idle mode for weekdays and weekends, respectively, because the scanner spent 23% more time proportionally in idle mode on the weekends. Conclusions: A semi-automatic method for quantifying energy consumption characteristics of MRI scanners was introduced and validated. This method is relatively simple to implement as it requires only power data from the scanners and avoids the technical challenges associated with extracting and processing scanner log files. Finally, the methodology enables quantitative evaluation of the power, time, and energy characteristics of MRI scanners in scan and nonproductive system modes, providing baseline data and the capability of identifying potential opportunities for enhancing the energy efficiency of MRI scanners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗