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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Joint Roman Space Telescope and Rubin Observatory Synthetic Wide-Field Imaging Survey

We present and validate 20 deg(2) of overlapping synthetic imaging surveys representing the full depth of the Nancy Grace Roman Space Telescope High-Latitude Imaging Survey (HLIS) and 5 yr of observations of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The two synthetic surveys are summarized, with reference to the existing 300 deg(2) of LSST simulated imaging produced as part of Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2). Both synthetic surveys observe the same simulated DESC DC2 universe. For the synthetic Roman survey, we simulate for the first time fully chromatic images along with the detailed physics of the Sensor Chip Assemblies derived from lab measurements using the flight detectors. The simulated imaging and resulting pixel-level measurements of photometric properties of objects span a wavelength range of similar to 0.3-2.0 mu m. We also describe updates to the Roman simulation pipeline, changes in how astrophysical objects are simulated relative to the original DC2 simulations, and the resulting simulated Roman data products. We use these simulations to explore the relative fraction of unrecognized blends in LSST images, finding that 20-30 per cent of objects identified in LSST images with i-band magnitudes brighter than 25 can be identified as multiple objects in Roman images. These simulations provide a unique testing ground for the development and validation of joint pixel-level analysis techniques of ground- and space-based imaging data sets in the second half of the 2020s - in particular the case of joint Roman-LSST analyses.

gravitational lensing↗
DOE OSTI2013

Feasibility of an image planning system for kilovoltage image-guided radiation therapy

Purpose: Image guidance has become a standard of care for many treatment scenarios in radiation therapy. This is most typically accomplished by use of kV x-ray devices mounted onto the linear accelerator (Linac) gantry that yield planar, fluoroscopic, and cone-beam computed tomography (CBCT) images. Image acquisition parameters are chosen via preset techniques that rely on broad categorizations in patient anatomy and imaging goal. However, the optimal imaging technique results in detectability of the features of interest while exposing the patient to minimum dose. Herein, the authors present an investigation into the feasibility of developing an image planning system (IPS) for radiotherapy.Methods: In this first phase, the authors focused on developing an algorithm to predict tissue contrast produced by a common radiotherapy planar imaging chain. Input parameters include a CT dataset and simulated planar imaging technique settings that include kV and mAs. Energy-specific attenuation through each voxel of the CT dataset was calculated in the algorithm to derive a net transmitted intensity. The response of the flat panel detector was integrated into the image simulation algorithm. Verification was conducted by comparing simulated and measured images using four phantoms. Comparisons were made in both high and low contrast settings, as well as changes in the geometric appearance due to image saturation. Results: The authors studied a lung nodule test object to assess the planning system's ability to predict object contrast and detectability. Verification demonstrated that the slope of the pixel intensities is similar, the presence of the nodule is evident, and image saturation at high mAs values is evident in both images. The appearance of the lung nodule is a function of the image detector saturation. The authors assessed the dimensions of the lung nodule in measured and simulated images. Good quantitative agreement affirmed the algorithm's predictive capabilities. The invariance of contrast with kVp and mAs prior to saturation was predicted, as well as the gradual loss of object detectability as saturation was approached. Small changes in soft tissue density were studied using a mammography step wedge phantom. Data were acquired at beam qualities of 80 and 120 kVp and over exposure values ranging from 0.04 to 500 mAs. The data showed good agreement in terms of the absolute value of pixel intensities predicted, as well as small variations across the step wedge pattern. The saturation pixel intensity was consistent between the two beam qualities studied. Boney tissue contrast was assessed using two abdominal phantoms. Measured and calculated values agree in terms of predicting the mAs value at which detector saturation, and subsequent loss of contrast occurs. The lack of variation in contrast over mAs values lower than 10 suggests that there is wide latitude for minimizing patient dose. Conclusions: The authors developed and tested an algorithm that can be used to assist in kV imaging technique selection during localization for radiotherapy. Phantom testing demonstrated the algorithm's predictive accuracy for both low and high contrast imaging scenarios. Detector saturation with subsequent loss of imaging detail, both in terms of object size and contrast were accurately predicted by the algorithm.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Onboard functional and molecular imaging: A design investigation for robotic multipinhole SPECT

Purpose: Onboard imaging—currently performed primarily by x-ray transmission modalities—is essential in modern radiation therapy. As radiation therapy moves toward personalized medicine, molecular imaging, which views individual gene expression, may also be important onboard. Nuclear medicine methods, such as single photon emission computed tomography (SPECT), are premier modalities for molecular imaging. The purpose of this study is to investigate a robotic multipinhole approach to onboard SPECT. Methods: Computer-aided design (CAD) studies were performed to assess the feasibility of maneuvering a robotic SPECT system about a patient in position for radiation therapy. In order to obtain fast, high-quality SPECT images, a 49-pinhole SPECT camera was designed which provides high sensitivity to photons emitted from an imaging region of interest. This multipinhole system was investigated by computer-simulation studies. Seventeen hot spots 10 and 7 mm in diameter were placed in the breast region of a supine female phantom. Hot spot activity concentration was six times that of background. For the 49-pinhole camera and a reference, more conventional, broad field-of-view (FOV) SPECT system, projection data were computer simulated for 4-min scans and SPECT images were reconstructed. Hot-spot localization was evaluated using a nonprewhitening forced-choice numerical observer. Results: The CAD simulation studies found that robots could maneuver SPECT cameras about patients in position for radiation therapy. In the imaging studies, most hot spots were apparent in the 49-pinhole images. Average localization errors for 10-mm- and 7-mm-diameter hot spots were 0.4 and 1.7 mm, respectively, for the 49-pinhole system, and 3.1 and 5.7 mm, respectively, for the reference broad-FOV system. Conclusions: A robot could maneuver a multipinhole SPECT system about a patient in position for radiation therapy. The system could provide onboard functional and molecular imaging with 4-min scan times.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-I-74: Image-Matching Technique of Computed Tomography Images for Personal Identification: A Preliminary Study Using Anthropomorphic Chest Phantoms

Purpose: Fingerprints, dental impressions, and DNA are used to identify unidentified bodies in forensic medicine. Cranial Computed tomography (CT) images and/or dental radiographs are also used for identification. Radiological identification is important, particularly in the absence of comparative fingerprints, dental impressions, and DNA samples. The development of an automated radiological identification system for unidentified bodies is desirable. We investigated the potential usefulness of bone structure for matching chest CT images. Methods: CT images of three anthropomorphic chest phantoms were obtained on different days in various settings. One of the phantoms was assumed to be an unidentified body. The bone image and the bone image with soft tissue (BST image) were extracted from the CT images. To examine the usefulness of the bone image and/or the BST image, the similarities between the two-dimensional (2D) or threedimensional (3D) images of the same and different phantoms were evaluated in terms of the normalized cross-correlation value (NCC). Results: For the 2D and 3D BST images, the NCCs obtained from the same phantom assumed to be an unidentified body (2D, 0.99; 3D, 0.93) were higher than those for the different phantoms (2D, 0.95 and 0.91; 3D, 0.89 and 0.80). The NCCs for the same phantom (2D, 0.95; 3D, 0.88) were greater compared to those of the different phantoms (2D, 0.61 and 0.25; 3D, 0.23 and 0.10) for the bone image. The difference in the NCCs between the same and different phantoms tended to be larger for the bone images than for the BST images. These findings suggest that the image-matching technique is more useful when utilizing the bone image than when utilizing the BST image to identify different people. Conclusion: This preliminary study indicated that evaluating the similarity of bone structure in 2D and 3D images is potentially useful for identifying of an unidentified body.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

THE SLOAN DIGITAL SKY SURVEY STRIPE 82 IMAGING DATA: DEPTH-OPTIMIZED CO-ADDS OVER 300 deg{sup 2} IN FIVE FILTERS

We present and release co-added images of the Sloan Digital Sky Survey (SDSS) Stripe 82. Stripe 82 covers an area of ∼300 deg{sup 2} on the celestial equator, and has been repeatedly scanned 70-90 times in the ugriz bands by the SDSS imaging survey. By making use of all available data in the SDSS archive, our co-added images are optimized for depth. Input single-epoch frames were properly processed and weighted based on seeing, sky transparency, and background noise before co-addition. The resultant products are co-added science images and their associated weight images that record relative weights at individual pixels. The depths of the co-adds, measured as the 5σ detection limits of the aperture (3.''2 diameter) magnitudes for point sources, are roughly 23.9, 25.1, 24.6, 24.1, and 22.8 AB magnitudes in the five bands, respectively. They are 1.9-2.2 mag deeper than the best SDSS single-epoch data. The co-added images have good image quality, with an average point-spread function FWHM of ∼1'' in the r, i, and z bands. We also release object catalogs that were made with SExtractor. These co-added products have many potential uses for studies of galaxies, quasars, and Galactic structure. We further present and release near-IR J-band images that cover ∼90 deg{sup 2} of Stripe 82. These images were obtained using the NEWFIRM camera on the NOAO 4 m Mayall telescope, and have a depth of about 20.0-20.5 Vega magnitudes (also 5σ detection limits for point sources)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SU-E-J-14: A Comparison of a 2.5MV Imaging Beam to KV and 6MV Imaging Beams

Purpose: To compare image quality metrics and dose of TrueBeam V2.0’s 2.5MV imaging beam and kV and 6MV images. Methods: To evaluate the MV image quality, the Standard Imaging QC-3 and Varian Las Vegas (LV) phantoms were imaged using the ‘quality’ and ‘low dose’ modes and then processed using RIT113 V6.3. The LEEDS phantom was used to evaluate the kV image quality. The signal to noise ratio (SNR) was also evaluated in patient images using Matlab. In addition, dose per image was evaluated at a depth of 5cm using solid water for a 28.6 cm × 28.6 cm field size, which is representative of the largest jaw settings at an SID of 150cm. Results: The 2.5MV images had lower dose than the 6 MV images and a contrast to noise ratio (CNR) about 1.4 times higher, when evaluated using the QC-3. When energy was held constant but dose varied, the different modes, ‘low dose’ and ‘quality’, showed less than an 8% difference in CNR. The ‘quality’ modes demonstrated better spatial resolution than the ‘low dose’; however, even with the ‘low dose’ all line pairs were distinct except for the 0.75lp/mm on the 2.5MV. The LV phantom was used to measure low contrast detectability and showed similar results to the QC-3. Several patient images all confirmed that SNR were highest in kV images followed by 2.5MV and then 6MV. Qualitatively, for anatomical areas with large variability in thickness, like lateral head and necks, 2.5MV images show more anatomy, such as shoulder position, than kV images. Conclusions: The kV images clearly provide the best image metrics per unit dose. The 2.5MV beam showed excellent contrast at a lower dose than 6MV and may be superior to kV for difficult to image areas that include large changes in anatomical thickness. P Balter: Varian, Sun Nuclear, Philips, CPRIT.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1994

An image assessment study of image acceptability of the Galileo low gain antenna mission

This paper describes a study conducted by NASA Ames Research Center (ARC) in collaboration with the Jet Propulsion Laboratory (JPL), Pasadena, California on the image acceptability of the Galileo Low Gain Antenna mission. The primary objective of the study is to determine the impact of the Integer Cosine Transform (ICT) compression algorithm on Galilean images of atmospheric bodies, moons, asteroids and Jupiter's rings. The approach involved fifteen volunteer subjects representing twelve institutions involved with the Galileo Solid State Imaging (SSI) experiment. Four different experiment specific quantization tables (q-table) and various compression stepsizes (q-factor) to achieve different compression ratios were used. It then determined the acceptability of the compressed monochromatic astronomical images as evaluated by Galileo SSI mission scientists. Fourteen different images were evaluated. Each observer viewed two versions of the same image side by side on a high resolution monitor, each was compressed using a different quantization stepsize. They were requested to select which image had the highest overall quality to support them in carrying out their visual evaluations of image content. Then they rated both images using a scale from one to five on its judged degree of usefulness. Up to four pre-selected types of images were presented with and without noise to each subject based upon results of a previously administered survey of their image preferences. Fourteen different images in seven image groups were studied. The results showed that: (1) acceptable compression ratios vary widely with the type of images; (2) noisy images detract greatly from image acceptability and acceptable compression ratios; and (3) atmospheric images of Jupiter seem to have higher compression ratios of 4 to 5 times that of some clear surface satellite images.

Chuang, S. L.↗
DOE OSTI2019

Image quality and diagnostic accuracy of complex-averaged high b value images in diffusion-weighted MRI of prostate cancer

Purpose: To evaluate the impact of complex-averaging on image quality (IQ) and diagnostic accuracy of acquired and calculated high b value (aHBV, cHBV) images in diffusion-weighted prostate MRI. Materials and methods: This retrospective study included 84 patients who underwent multiparametric prostate MRI at 3 Tesla without endorectal coil. DWIs were acquired at three different b values which included two lower b values (b = 50,900 s/mm{sup 2}) and one higher b value (aHBV at 2000 s/mm{sup 2}). The acquired data were postprocessed to generate two different types of trace-weighted images—using conventional magnitude-averaging and complex-averaging. Using lower b values (b = 50,900 s/mm{sup 2}) from both conventional and complex-averaged image sets, cHBV images (b = 2000 s/mm{sup 2}) and ADC maps were derived. All image sets were reviewed by two radiologists in different reading sessions to assess image quality and PIRADS. The diagnostic accuracy of different image sets for the detection of prostate lesions was performed by correlating PIRADS and Gleason scores. Results: Complex-averaging did not impact ADC values of the prostate lesions compared to magnitude-averaging (P = 0.08). Complex-averaging improved image quality of acquired high b value and calculated high b value images (P < 0.0001). Complex-averaging also improved the level of confidence (LOC) of the acquired high b value for both readers (P < 0.0001, P < 0.05), but only for reader A in calculated high b value (P < 0.0001). The image quality of calculated high b value images was not significantly different than acquired high b value images. The dataset combining complex-averaging and calculated high b value provided the highest diagnostic accuracy (but not statistically significant) for detection of the significant prostate lesion compared to the magnitude-averaged acquired high b value (79.55% vs. 72.73%; P = 0.317). The mean acquisition time for b = 2000 s/mm{sup 2} sequence (aHBV) was 6 min 30 s (± 1 min 16 s) out of a total of 28 min 31 s (± 4 min 26 s) for the entire mp-MRI protocol (approximately 25% of total scan time). Conclusion: Complex-averaging provides better image quality and level of confidence without significant impact on ADC values and diagnostic accuracy for detection of the significant prostate lesions . The calculated high b value images are also comparable to (and can substitute) the acquired high b value images which can help in reducing the imaging time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SU-F-I-73: Surface Dose from KV Diagnostic Beams From An On-Board Imager On a Linac Machine Using Different Imaging Techniques and Filters

Purpose: To quantitatively investigate the surface dose deposited in patients imaged with a kV on-board-imager mounted on a radiotherapy machine using different clinical imaging techniques and filters. Methods: A high sensitivity photon diode is used to measure the surface dose on central-axis and at an off-axis-point which is mounted on the top of a phantom setup. The dose is measured for different imaging techniques that include: AP-Pelvis, AP-Head, AP-Abdomen, AP-Thorax, and Extremity. The dose measurements from these imaging techniques are combined with various filtering techniques that include: no-filter (open-field), half-fan bowtie (HF), full-fan bowtie (FF) and Cu-plate filters. The relative surface dose for different imaging and filtering techniques is evaluated quantiatively by the ratio of the dose relative to the Cu-plate filter. Results: The lowest surface dose is deposited with the Cu-plate filter. The highest surface dose deposited results from open fields without filter and it is nearly a factor of 8–30 larger than the corresponding imaging technique with the Cu-plate filter. The AP-Abdomen technique delivers the largest surface dose that is nearly 2.7 times larger than the AP-Head technique. The smallest surface dose is obtained from the Extremity imaging technique. Imaging with bowtie filters decreases the surface dose by nearly 33% in comparison with the open field. The surface doses deposited with the HF or FF-bowtie filters are within few percentages. Image-quality of the radiographic images obtained from the different filtering techniques is similar because the Cu-plate eliminates low-energy photons. The HF- and FF-bowtie filters generate intensity-gradients in the radiographs which affects image-quality in the different imaging technique. Conclusion: Surface dose from kV-imaging decreases significantly with the Cu-plate and bowtie-filters compared to imaging without filters using open-field beams. The use of Cu-plate filter does not affect image-quality and may be used as the default in the different imaging techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-DE-207A-09: Low-Dose CT Image Reconstruction Via Learning From Different Patient Normal-Dose Images

Purpose: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. Methods: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern for each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework. Quantitative evaluation of the reconstructed images was based on the signal-to-noise ratio (SNR), local binary pattern (LBP) and histogram of oriented gradients (HOG) metrics. Results: It was observed that lung and outside tissue regions have different MRF patterns predicted from the NdCT. Visual inspection showed that our method obviously outperformed the traditional FBP method. Comparing with the region-smoothing PWLS method, our method has, in average, 13% increase in SNR, 15% decrease in LBP difference, and 12% decrease in HOG difference from reference standard for all regions of interest, which indicated the superior performance of the proposed method in terms of image resolution and texture preservation. Conclusion: We proposed a novel LdCT image reconstruction method by learning similar image characteristics from a set of NdCT images, and the to-be-learnt NdCT image does not need to be scans from the same subject. This approach is particularly important for enhancing image quality in radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Demonstration of a time-integrated short line of sight neutron imaging system for inertial confinement fusion

The Neutron Imaging System (NIS) is an important diagnostic for understanding implosions of deuterium-tritium capsules at the National Ignition Facility. While the detectors for the existing system must be positioned 28 m from the source to produce sufficient imaging magnification and resolution, recent testing of a new short line of sight neutron imaging system has shown sufficient resolution to allow reconstruction of the source image with quality similar to that of the existing NIS on a 11.6 m line of sight. The new system used the existing pinhole aperture array and a stack of detectors composed of 2 mm thick high-density polyethylene converter material followed by an image plate. In these detectors, neutrons enter the converter material and interact with protons, which recoil and deposit energy within the thin active layer of the image plate through ionization losses. The described system produces time-integrated images for all neutron energies passing through the pinhole. We present details of the measurement scheme for this novel technique to produce energy-integrated neutron images as well as source reconstruction results from recent experiments at NIF.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Prospects for in vivo estimation of photon linear attenuation coefficients using postprocessing dual-energy CT imaging on a commercial scanner: Comparison of analytic and polyenergetic statistical reconstruction algorithms

Purpose: Accurate patient-specific photon cross-section information is needed to support more accurate model-based dose calculation for low energy photon-emitting modalities in medicine such as brachytherapy and kilovoltage x-ray imaging procedures. A postprocessing dual-energy CT (pDECT) technique for noninvasivein vivo estimation of photon linear attenuation coefficients has been experimentally implemented on a commercial CT scanner and its accuracy assessed in idealized phantom geometries. Methods: Eight test materials of known composition and density were used to compare pDECT-estimated linear attenuation coefficients to NIST reference values over an energy range from 10 keV to 1 MeV. As statistical image reconstruction (SIR) has been shown to reconstruct images with less random and systematic error than conventional filtered backprojection (FBP), the pDECT technique was implemented with both an in-house polyenergetic SIR algorithm, alternating minimization (AM), as well as a conventional FBP reconstruction algorithm. Improvement from increased spectral separation was also investigated by filtering the high-energy beam with an additional 0.5 mm of tin. The law of propagated uncertainty was employed to assess the sensitivity of the pDECT process to errors in reconstructed images. Results: Mean pDECT-estimated linear attenuation coefficients for the eight test materials agreed within 1% of NIST reference values for energies from 1 MeV down to 30 keV, with mean errors rising to between 3% and 6% at 10 keV, indicating that the method is unbiased when measurement and calibration phantom geometries are matched. Reconstruction with FBP and AM algorithms conferred similar mean pDECT accuracy. However, single-voxel pDECT estimates reconstructed on a 1 × 1 × 3 mm{sup 3} grid are shown to be highly sensitive to reconstructed image uncertainty; in some cases pDECT attenuation coefficient estimates exhibited standard deviations on the order of 20% around the mean. Reconstruction with the statistical AM algorithm led to standard deviations roughly 40% to 60% less than FBP reconstruction. Additional tin filtration of the high energy beam exhibits similar pDECT estimation accuracy as the unfiltered beam, even when scanning with only 25% of the dose. Using the law of propagated uncertainty, low Z materials are found to be more sensitive to image reconstruction errors than high Z materials. Furthermore, it is estimated that reconstructed CT image uncertainty must be limited to less than 0.25% to achieve a target linear-attenuation coefficient estimation uncertainty of 3% at 28 keV. Conclusions: That pDECT supports mean linear attenuation coefficient measurement accuracies of 1% of reference values for energies greater than 30 keV is encouraging. However, the sensitivity of the pDECT measurements to noise and systematic errors in reconstructed CT images warrants further investigation in more complex phantom geometries. The investigated statistical reconstruction algorithm, AM, reduced random measurement uncertainty relative to FBP owing to improved noise performance. These early results also support efforts to increase DE spectral separation, which can further reduce the pDECT sensitivity to measurement uncertainty.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Multimodal imaging and machine learning to enhance microscope images of shale

A machine learning based image processing workflow is presented to enhance shale source rock microscopic images obtained using diverse imaging platforms. Images were acquired from a 30 μm diameter cylindrical Vaca Muerta shale sample using both nondestructive Transmission X-Ray Microscopy (TXM, alternately referred to as nano computed tomography) and destructive Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM). Output cross-sectional images from each modality were aligned using a combination of manual and automated registration techniques to create a registered image dataset. We then apply this dataset for two image processing tasks: prediction of image cross sections with SEM-like resolution from nondestructive TXM data and repair of charged region artifacts (localized accumulation of electrons) within SEM images. The image processing algorithms for both tasks use deep learning models, specifically image-to-image Convolutional Neural Networks (CNNs) and conditional Generative Adversarial Networks (cGANs). In the image enhancement tasks, we are able to achieve significant qualitative and quantitative improvement in TXM images. Here, the best model reaches an average Peak Signal to Noise Ratio (PSNR) of 15.8 dB. Conditioning on TXM data is also shown to reduce artifacts from SEM charging, achieving an average PSNR of 25.8 dB. Furthermore, our results suggest that properly trained and validated networks are capable of significant enhancement of images obtained using nondestructive techniques, thereby improving interpretation of two- and three-dimensional images while preserving samples for future use.

58 GEOSCIENCES↗
DOE OSTI2016

Comparison of polystyrene scintillator fiber array and monolithic polystyrene for neutron imaging and radiography

The neutron imaging diagnostic at the National Ignition Facility has been operating since 2011 generating neutron images of deuterium-tritium (DT) implosions at peak compression. The current design features a scintillating fiber array, which allows for high imaging resolution to discern small-scale structure within the implosion. In recent years, it has become clear that additional neutron imaging systems need to be constructed in order to provide 3D reconstructions of the DT source and these additional views need to be on a shorter line of sight. As a result, there has been increased effort to identify new image collection techniques that improve upon imaging resolution for these next generation neutron imaging systems, such as monolithic deuterated scintillators. This work details measurements performed at the Weapons Neutron Research Facility at Los Alamos National Laboratory that compares the radiographic abilities of the fiber scintillator with a monolithic scintillator, which may be featured in a future short line of sight neutron imaging systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

WE-G-17A-01: Improving Tracking Image Spatial Resolution for Onboard MR Image Guided Radiation Therapy Using the WHISKEE Technique

Purpose: To evaluate the feasibility of using the weighted hybrid iterative spiral k-space encoded estimation (WHISKEE) technique to improve spatial resolution of tracking images for onboard MR image guided radiation therapy (MR-IGRT). Methods: MR tracking images of abdomen and pelvis had been acquired from healthy volunteers using the ViewRay onboard MRIGRT system (ViewRay Inc. Oakwood Village, OH) at a spatial resolution of 2.0mm*2.0mm*5.0mm. The tracking MR images were acquired using the TrueFISP sequence. The temporal resolution had to be traded off to 2 frames per second (FPS) to achieve the 2.0mm in-plane spatial resolution. All MR images were imported into the MATLAB software. K-space data were synthesized through the Fourier Transform of the MR images. A mask was created to selected k-space points that corresponded to the under-sampled spiral k-space trajectory with an acceleration (or undersampling) factor of 3. The mask was applied to the fully sampled k-space data to synthesize the undersampled k-space data. The WHISKEE method was applied to the synthesized undersampled k-space data to reconstructed tracking MR images at 6 FPS. As a comparison, the undersampled k-space data were also reconstructed using the zero-padding technique. The reconstructed images were compared to the original image. The relatively reconstruction error was evaluated using the percentage of the norm of the differential image over the norm of the original image. Results: Compared to the zero-padding technique, the WHISKEE method was able to reconstruct MR images with better image quality. It significantly reduced the relative reconstruction error from 39.5% to 3.1% for the pelvis image and from 41.5% to 4.6% for the abdomen image at an acceleration factor of 3. Conclusion: We demonstrated that it was possible to use the WHISKEE method to expedite MR image acquisition for onboard MR-IGRT systems to achieve good spatial and temporal resolutions simultaneously. Y. Hu and O. green receive travel reimbursement from ViewRay. S. Mutic has consulting and research agreements with ViewRay. Q. Zeng, R. Nana, J.L. Patrick, S. Shvartsman and J.F. Dempsey are ViewRay employees.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-J-89: Comparative Analysis of MIM and Velocity’s Image Deformation Algorithm Using Simulated KV-CBCT Images for Quality Assurance

Purpose: Deformable image registration (DIR) is used routinely in the clinic without a formalized quality assurance (QA) process. Using simulated deformations to digitally deform images in a known way and comparing to DIR algorithm predictions is a powerful technique for DIR QA. This technique must also simulate realistic image noise and artifacts, especially between modalities. This study developed an algorithm to create simulated daily kV cone-beam computed-tomography (CBCT) images from CT images for DIR QA between these modalities. Methods: A Catphan and physical head-and-neck phantom, with known deformations, were used. CT and kV-CBCT images of the Catphan were utilized to characterize the changes in Hounsfield units, noise, and image cupping that occur between these imaging modalities. The algorithm then imprinted these changes onto a CT image of the deformed head-and-neck phantom, thereby creating a simulated-CBCT image. CT and kV-CBCT images of the undeformed and deformed head-and-neck phantom were also acquired. The Velocity and MIM DIR algorithms were applied between the undeformed CT image and each of the deformed CT, CBCT, and simulated-CBCT images to obtain predicted deformations. The error between the known and predicted deformations was used as a metric to evaluate the quality of the simulated-CBCT image. Ideally, the simulated-CBCT image registration would produce the same accuracy as the deformed CBCT image registration. Results: For Velocity, the mean error was 1.4 mm for the CT-CT registration, 1.7 mm for the CT-CBCT registration, and 1.4 mm for the CT-simulated-CBCT registration. These same numbers were 1.5, 4.5, and 5.9 mm, respectively, for MIM. Conclusion: All cases produced similar accuracy for Velocity. MIM produced similar values of accuracy for CT-CT registration, but was not as accurate for CT-CBCT registrations. The MIM simulated-CBCT registration followed this same trend, but overestimated MIM DIR errors relative to the CT-CBCT registration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-AB-BRA-02: A Novel Scatter Imaging Modality for Real-Time Image Guidance During Lung SBRT

Purpose: A novel scatter imaging modality is developed and its feasibility for image-guided radiation therapy (IGRT) during stereotactic body radiation therapy (SBRT) for lung cancer patients is assessed using analytic and Monte Carlo models as well as experimental testing. Methods: During treatment, incident radiation interacts and scatters from within the patient. The presented methodology forms an image of patient anatomy from the scattered radiation for real-time localization of the treatment target. A radiographic flat panel-based pinhole camera provides spatial information regarding the origin of detected scattered radiation. An analytical model is developed, which provides a mathematical formalism for describing the scatter imaging system. Experimental scatter images are acquired by irradiating an object using a Varian TrueBeam accelerator. The differentiation between tissue types is investigated by imaging simple objects of known compositions (water, lung, and cortical bone equivalent). A lung tumor phantom, simulating materials and geometry encountered during lung SBRT treatments, is fabricated and imaged to investigate image quality for various quantities of delivered radiation. Monte Carlo N-Particle (MCNP) code is used for validation and testing by simulating scatter image formation using the experimental pinhole camera setup. Results: Analytical calculations, MCNP simulations, and experimental results when imaging the water, lung, and cortical bone equivalent objects show close agreement, thus validating the proposed models and demonstrating that scatter imaging differentiates these materials well. Lung tumor phantom images have sufficient contrast-to-noise ratio (CNR) to clearly distinguish tumor from surrounding lung tissue. CNR=4.1 and CNR=29.1 for 10MU and 5000MU images (equivalent to 0.5 and 250 second images), respectively. Conclusion: Lung SBRT provides favorable treatment outcomes, but depends on accurate target localization. A comprehensive approach, employing multiple simulation techniques and experiments, is taken to demonstrate the feasibility of a novel scatter imaging modality for the necessary real-time image guidance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

X-ray tests of a two-dimensional stigmatic imaging scheme with variable magnifications

A two-dimensional stigmatic x-ray imaging scheme, consisting of two spherically bent crystals, one concave and one convex, was recently proposed [M. Bitter et al., Rev. Sci. Instrum. 83, 10E527 (2012)]. The Bragg angles and the radii of curvature of the two crystals of this imaging scheme are matched to eliminate the astigmatism and to satisfy the Bragg condition across both crystal surfaces for a given x-ray energy. In this paper, we consider more general configurations of this imaging scheme, which allow us to vary the magnification for a given pair of crystals and x-ray energy. The stigmatic imaging scheme has been validated for the first time by imaging x-rays generated by a micro-focus x-ray source with source size of 8.4 μm validated by knife-edge measurements. Results are presented from imaging the tungsten Lα1 emission at 8.3976 keV, using a convex Si-422 crystal and a concave Si-533 crystal with 2d-spacings of 2.21707 Å and 1.65635 Å and radii of curvature of 500 ± 1 mm and 823 ± 1 mm, respectively, showing a spatial resolution of 54.9 μm. This imaging scheme is expected to be of interest for the two-dimensional imaging of laser produced plasmas.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗