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At least 577 records · Page 32

A Method for Assessing Ground-Truth Accuracy of the 5DCT Technique

Purpose: To develop a technique that assesses the accuracy of the breathing phase-specific volume image generation process by patient-specific breathing motion model using the original free-breathing computed tomographic (CT) scans as ground truths. Methods: Sixteen lung cancer patients underwent a previously published protocol in which 25 free-breathing fast helical CT scans were acquired with a simultaneous breathing surrogate. A patient-specific motion model was constructed based on the tissue displacements determined by a state-of-the-art deformable image registration. The first image was arbitrarily selected as the reference image. The motion model was used, along with the free-breathing phase information of the original 25 image datasets, to generate a set of deformation vector fields that mapped the reference image to the 24 nonreference images. The high-pitch helically acquired original scans served as ground truths because they captured the instantaneous tissue positions during free breathing. Image similarity between the simulated and the original scans was assessed using deformable registration that evaluated the pointwise discordance throughout the lungs. Results: Qualitative comparisons using image overlays showed excellent agreement between the simulated images and the original images. Even large 2-cm diaphragm displacements were very well modeled, as was sliding motion across the lung–chest wall boundary. The mean error across the patient cohort was 1.15 ± 0.37 mm, and the mean 95th percentile error was 2.47 ± 0.78 mm. Conclusion: The proposed ground truth–based technique provided voxel-by-voxel accuracy analysis that could identify organ-specific or tumor-specific motion modeling errors for treatment planning. Despite a large variety of breathing patterns and lung deformations during the free-breathing scanning session, the 5-dimensionl CT technique was able to accurately reproduce the original helical CT scans, suggesting its applicability to a wide range of patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-E-J-141: Comparison of Dose Calculation On Automatically Generated MRBased ED Maps and Corresponding Patient CT for Clinical Prostate EBRT Plans

Purpose: To analyze the effect of computing radiation dose on automatically generated MR-based simulated CT images compared to true patient CTs. Methods: Six prostate cancer patients received a regular planning CT for RT planning as well as a conventional 3D fast-field dual-echo scan on a Philips 3.0T Achieva, adding approximately 2 min of scan time to the clinical protocol. Simulated CTs (simCT) where synthesized by assigning known average CT values to the tissue classes air, water, fat, cortical and cancellous bone. For this, Dixon reconstruction of the nearly out-of-phase (echo 1) and in-phase images (echo 2) allowed for water and fat classification. Model based bone segmentation was performed on a combination of the DIXON images. A subsequent automatic threshold divides into cortical and cancellous bone. For validation, the simCT was registered to the true CT and clinical treatment plans were re-computed on the simCT in pinnacle{sup 3}. To differentiate effects related to the 5 tissue classes and changes in the patient anatomy not compensated by rigid registration, we also calculate the dose on a stratified CT, where HU values are sorted in to the same 5 tissue classes as the simCT. Results: Dose and volume parameters on PTV and risk organs as used for the clinical approval were compared. All deviations are below 1.1%, except the anal sphincter mean dose, which is at most 2.2%, but well below clinical acceptance threshold. Average deviations are below 0.4% for PTV and risk organs and 1.3% for the anal sphincter. The deviations of the stratifiedCT are in the same range as for the simCT. All plans would have passed clinical acceptance thresholds on the simulated CT images. Conclusion: This study demonstrated the clinical usability of MR based dose calculation with the presented Dixon acquisition and subsequent fully automatic image processing. N. Schadewaldt, H. Schulz, M. Helle and S. Renisch are employed by Phlips Technologie Innovative Techonologies, a subsidiary of Royal Philips NV.

60 APPLIED LIFE SCIENCES↗

Simulation: Moving from Technology Challenge to Human Factors Success

Recognition of the many limitations of traditional apprenticeship training is driving new approaches to learning medical procedural skills. Among simulation technologies and methods available today, computer-based systems are topical and bring the benefits of automated, repeatable, and reliable performance assessments. Human factors research is central to simulator model development that is relevant to real-world imaging-guided interventional tasks and to the credentialing programs in which it would be used.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Environmental fog/rain visual display system for aircraft simulators

An environmental fog/rain visual display system for aircraft simulators is described. The electronic elements of the system include a real time digital computer, a caligraphic color display which simulates landing lights of selective intensity, and a color television camera for producing a moving color display of the airport runway as depicted on a model terrain board. The mechanical simulation elements of the system include an environmental chamber which can produce natural fog, nonhomogeneous fog, rain and fog combined, or rain only. A pilot looking through the aircraft wind screen will look through the fog and/or rain generated in the environmental chamber onto a viewing screen with the simulated color image of the airport runway thereon, and observe a very real simulation of actual conditions of a runway as it would appear through actual fog and/or rain.

Chase, W. D.↗

Spectral optimization for micro-CT

Purpose: To optimize micro-CT protocols with respect to x-ray spectra and thereby reduce radiation dose at unimpaired image quality. Methods: Simulations were performed to assess image contrast, noise, and radiation dose for different imaging tasks. The figure of merit used to determine the optimal spectrum was the dose-weighted contrast-to-noise ratio (CNRD). Both optimal photon energy and tube voltage were considered. Three different types of filtration were investigated for polychromatic x-ray spectra: 0.5 mm Al, 3.0 mm Al, and 0.2 mm Cu. Phantoms consisted of water cylinders of 20, 32, and 50 mm in diameter with a central insert of 9 mm which was filled with different contrast materials: an iodine-based contrast medium (CM) to mimic contrast-enhanced (CE) imaging, hydroxyapatite to mimic bone structures, and water with reduced density to mimic soft tissue contrast. Validation measurements were conducted on a commercially available micro-CT scanner using phantoms consisting of water-equivalent plastics. Measurements on a mouse cadaver were performed to assess potential artifacts like beam hardening and to further validate simulation results. Results: The optimal photon energy for CE imaging was found at 34 keV. For bone imaging, optimal energies were 17, 20, and 23 keV for the 20, 32, and 50 mm phantom, respectively. For density differences, optimal energies varied between 18 and 50 keV for the 20 and 50 mm phantom, respectively. For the 32 mm phantom and density differences, CNRD was found to be constant within 2.5% for the energy range of 21-60 keV. For polychromatic spectra and CMs, optimal settings were 50 kV with 0.2 mm Cu filtration, allowing for a dose reduction of 58% compared to the optimal setting for 0.5 mm Al filtration. For bone imaging, optimal tube voltages were below 35 kV. For soft tissue imaging, optimal tube settings strongly depended on phantom size. For 20 mm, low voltages were preferred. For 32 mm, CNRD was found to be almost independent of tube voltage. For 50 mm, voltages larger than 50 kV were preferred. For all three phantom sizes stronger filtration led to notable dose reduction for soft tissue imaging. Validation measurements were found to match simulations well, with deviations being less than 10%. Mouse measurements confirmed simulation results. Conclusions: Optimal photon energies and tube settings strongly depend on both phantom size and imaging task at hand. For in vivo CE imaging and density differences, strong filtration and voltages of 50-65 kV showed good overall results. For soft tissue imaging of animals the size of a rat or larger, voltages higher than 65 kV allow to greatly reduce scan times while maintaining dose efficiency. For imaging of bone structures, usage of only minimum filtration and low tube voltages of 40 kV and below allow exploiting the high contrast of bone at very low energies. Therefore, a combination of two filtrations could prove beneficial for micro-CT: a soft filtration allowing for bone imaging at low voltages, and a variable stronger filtration (e.g., 0.2 mm Cu) for soft tissue and contrast-enhanced imaging.

60 APPLIED LIFE SCIENCES↗

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multislice simulation of transmission electron microscopy imaging of helium bubbles in Fe

Formation of nanoscale helium (He) bubbles in reduced activation ferritic/martensitic steels may lead to degradation of mechanical properties of materials. Transmission electron microscopy (TEM) has been commonly used to image the Fresnel contrast of He bubbles using a defocus of 0.5 µm ~ 1 µm. This paper presents our study of multislice simulation of the size correlation between imaged Fresnel rings and the actual He bubbles. It was found that for bubbles equal to or larger than 3 nm in diameter, the imaged bubble size, represented by its inner diameter of the first dark Fresnel ring (Din) in under-focused imaging conditions, increases with increasing electron-beam incoherency, but decreases with increasing defocus. The electron-beam accelerating voltage, bubble size, bubble position, and TEM sample thickness were found to have no significant influence on the deviation of Din from the actual bubble size (D0). For bubbles equal to or smaller than 2 nm, however, Din/Do increases dramatically with increasing defocus when it is above a threshold defocus. It was also suggested by this study that He bubbles can be differentiated from argon (Ar) bubbles by contrast differences.

Yao, Bo↗

TH-A-18C-09: Ultra-Fast Monte Carlo Simulation for Cone Beam CT Imaging of Brain Trauma

Purpose: Application of cone-beam CT (CBCT) to low-contrast soft tissue imaging, such as in detection of traumatic brain injury, is challenged by high levels of scatter. A fast, accurate scatter correction method based on Monte Carlo (MC) estimation is developed for application in high-quality CBCT imaging of acute brain injury. Methods: The correction involves MC scatter estimation executed on an NVIDIA GTX 780 GPU (MC-GPU), with baseline simulation speed of ~1e7 photons/sec. MC-GPU is accelerated by a novel, GPU-optimized implementation of variance reduction (VR) techniques (forced detection and photon splitting). The number of simulated tracks and projections is reduced for additional speed-up. Residual noise is removed and the missing scatter projections are estimated via kernel smoothing (KS) in projection plane and across gantry angles. The method is assessed using CBCT images of a head phantom presenting a realistic simulation of fresh intracranial hemorrhage (100 kVp, 180 mAs, 720 projections, source-detector distance 700 mm, source-axis distance 480 mm). Results: For a fixed run-time of ~1 sec/projection, GPU-optimized VR reduces the noise in MC-GPU scatter estimates by a factor of 4. For scatter correction, MC-GPU with VR is executed with 4-fold angular downsampling and 1e5 photons/projection, yielding 3.5 minute run-time per scan, and de-noised with optimized KS. Corrected CBCT images demonstrate uniformity improvement of 18 HU and contrast improvement of 26 HU compared to no correction, and a 52% increase in contrast-tonoise ratio in simulated hemorrhage compared to “oracle” constant fraction correction. Conclusion: Acceleration of MC-GPU achieved through GPU-optimized variance reduction and kernel smoothing yields an efficient (<5 min/scan) and accurate scatter correction that does not rely on additional hardware or simplifying assumptions about the scatter distribution. The method is undergoing implementation in a novel CBCT dedicated to brain trauma imaging at the point of care in sports and military applications. Research grant from Carestream Health. JY is an employee of Carestream Health.

60 APPLIED LIFE SCIENCES↗

SU-F-J-114: On-Treatment Imagereconstruction Using Transit Images of Treatment Beams Through Patient and Thosethrough Planning CT Images

Purpose: To reconstruct patient images at the time of radiation delivery using measured transit images of treatment beams through patient and calculated transit images through planning CT images. Methods: We hypothesize that the ratio of the measured transit images to the calculated images may provide changed amounts of the patient image between times of planning CT and treatment. To test, we have devised lung phantoms with a tumor object (3-cm diameter) placed at iso-center (simulating planning CT) and off-center by 1 cm (simulating treatment). CT images of the two phantoms were acquired; the image of the off-centered phantom, unavailable clinically, represents the reference on-treatment image in the image quality of planning CT. Cine-transit images through the two phantoms were also acquired in EPID from a non-modulated 6 MV beam when the gantry was rotated 360 degrees; the image through the centered phantom simulates calculated image. While the current study is a feasibility study, in reality our computational EPID model can be applicable in providing accurate transit image from MC simulation. Changed MV HU values were reconstructed from the ratio between two EPID projection data, converted to KV HU values, and added to the planning CT, thereby reconstructing the on-treatment image of the patient limited to the irradiated region of the phantom. Results: The reconstructed image was compared with the reference image. Except for local HU differences>200 as a maximum, excellent agreement was found. The average difference across the entire image was 16.2 HU. Conclusion: We have demonstrated the feasibility of a method of reconstructing on-treatment images of a patient using EPID image and planning CT images. Further studies will include resolving the local HU differences and investigation on the dosimetry impact of the reconstructed image.

60 APPLIED LIFE SCIENCES↗

Imaging phonon dynamics with ultrafast electron microscopy: Kinematical and dynamical simulations

Ultrafast x-ray and electron scattering techniques have proven to be useful for probing the transient elastic lattice deformations associated with photoexcited coherent acoustic phonons. Indeed, femtosecond electron imaging using an ultrafast electron microscope (UEM) has been used to directly image the influence of nanoscale structural and morphological discontinuities on the emergence, propagation, dispersion, and decay behaviors in a variety of materials. Here, we describe our progress toward the development of methods ultimately aimed at quantifying acoustic-phonon properties from real-space UEM images via conventional image simulation methods extended to the associated strain-wave lattice deformation symmetries and extents. Using a model system consisting of pristine single-crystal Ge and a single, symmetric Lamb-type guided-wave mode, we calculate the transient strain profiles excited in a wedge specimen and then apply both kinematical- and dynamical-scattering methods to simulate the resulting UEM bright-field images. While measurable contrast strengths arising from the phonon wavetrains are found for optimally oriented specimens using both approaches, incorporation of dynamical scattering effects via a multi-slice method returns better qualitative agreement with experimental observations. Contrast strengths arising solely from phonon-induced local lattice deformations are increased by nearly an order of magnitude when incorporating multiple electron scattering effects. We also explicitly demonstrate the effects of changes in global specimen orientation on the observed contrast strength, and we discuss the implications for increasing the sophistication of the model with respect to quantification of phonon properties from UEM images.

36 MATERIALS SCIENCE↗

A deep learning approach to fast analysis of collective Thomson scattering spectra

Fast analysis of collective Thomson scattering ion acoustic wave features using a deep convolutional neural network model is presented. The network was trained from spectra to predict the plasma parameters, including ion velocities, population fractions, and ion and electron temperatures. A fully kinetic particle-in-cell simulation was used to model a laboratory astrophysics experiment and simulate a diagnostic image of the ion acoustic wave feature. Network predictions were compared with Bayesian inference of the plasma model parameters for both the simulated and experimentally measured images. Both approaches were fairly accurate predicting the simulated image and the network predictions matched a good portion of the Bayesian results for the experimentally measured image. The Bayesian approach is more robust to noise and motivates future work to train deep learning models with realistic noise. The advantage of the deep learning model is making thousands of predictions in a few hundred milliseconds, compared to a few seconds to minutes per prediction for the optimization and Bayesian approaches presented here. The results demonstrate promising capabilities of deep learning models to analyze Thomson data orders of magnitude faster than conventional methods when using the neural network for standalone analysis. If more rigorous analysis is needed, neural network predictions can be used to quickly initialize other optimization methods and increase chances of success. This is especially useful when the dataset becomes very large or highly dimensional and manually refining initial conditions for the entire dataset are no longer tractable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

RhizoVision Explorer: open-source software for root image analysis and measurement standardization

Abstract Roots are central to the function of natural and agricultural ecosystems by driving plant acquisition of soil resources and influencing the carbon cycle. Root characteristics like length, diameter and volume are critical to measure to understand plant and soil functions. RhizoVision Explorer is an open-source software designed to enable researchers interested in roots by providing an easy-to-use interface, fast image processing and reliable measurements. The default broken roots mode is intended for roots sampled from pots and soil cores, washed and typically scanned on a flatbed scanner, and provides measurements like length, diameter and volume. The optional whole root mode for complete root systems or root crowns provides additional measurements such as angles, root depth and convex hull. Both modes support providing measurements grouped by defined diameter ranges, the inclusion of multiple regions of interest and batch analysis. RhizoVision Explorer was successfully validated against ground truth data using a new copper wire image set. In comparison, the current reference software, the commercial WinRhizo™, drastically underestimated volume when wires of different diameters were in the same image. Additionally, measurements were compared with WinRhizo™ and IJ_Rhizo using a simulated root image set, showing general agreement in software measurements, except for root volume. Finally, scanned root image sets acquired in different labs for the crop, herbaceous and tree species were used to compare results from RhizoVision Explorer with WinRhizo™. The two software showed general agreement, except that WinRhizo™ substantially underestimated root volume relative to RhizoVision Explorer. In the current context of rapidly growing interest in root science, RhizoVision Explorer intends to become a reference software, improve the overall accuracy and replicability of root trait measurements and provide a foundation for collaborative improvement and reliable access to all.

59 BASIC BIOLOGICAL SCIENCES↗

Poster — Thur Eve — 11: Validation of the orthopedic metallic artifact reduction tool for CT simulations at the Ottawa Hospital Cancer Centre

Metallic implants in patients can produce image artifacts in kilovoltage CT simulation images which can introduce noise and inaccuracies in CT number, affecting anatomical segmentation and dose distributions. The commercial orthopedic metal artifact reduction algorithm (O-MAR) (Philips Healthcare System) was recently made available on CT simulation scanners at our institution. This study validated the clinical use of O-MAR by investigating its effects on CT number and dose distributions. O-MAR corrected and uncorrected images were acquired with a Philips Brilliance Big Bore CT simulator of a cylindrical solid water phantom that contained various plugs (including metal) of known density. CT number accuracy was investigated by determining the mean and standard deviation in regions of interest (ROI) within each plug for uncorrected and O-MAR corrected images and comparing with no-metal image values. Dose distributions were calculated using the Monaco treatment planning system. Seven open fields were equally spaced about the phantom around a ROI near the center of the phantom. These were compared to a “correct” dose distribution calculated by overriding electron densities a no-metal phantom image to produce an image containing metal but no artifacts. An overall improvement in CT number and dose distribution accuracy was achieved by applying the O-MAR correction. Mean CT numbers and standard deviations were found to be generally improved. Exceptions included lung equivalent media, which is consistent with vendor specified contraindications. Dose profiles were found to vary by ±4% between uncorrected or O-MAR corrected images with O-MAR producing doses closer to ground truth.

60 APPLIED LIFE SCIENCES↗

A Generative Model for Realistic Galaxy Cluster X-Ray Morphologies

Abstract The X-ray morphologies of clusters of galaxies display significant variations, reflecting their dynamical histories and the nonlinear dependence of X-ray emissivity on the density of the intracluster gas. Qualitative and quantitative assessments of X-ray morphology have long been considered a proxy for determining whether clusters are dynamically active or “relaxed.” Conversely, the use of circularly or elliptically symmetric models for cluster emission can be complicated by the variety of complex features realized in nature, spanning scales from megaparsecs down to the resolution limit of current X-ray observatories. In this work, we use mock X-ray images from simulated clusters from The Three Hundred project to define a basis set of cluster image features. We take advantage of the clusters’ approximate self-similarity to minimize the differences between images before encoding the remaining diversity through a distribution of high-order polynomial coefficients. Principal component analysis then provides an orthogonal basis for this distribution, corresponding to natural perturbations from an average model. This representation allows novel, realistically complex X-ray cluster images to be easily generated, and we provide code to do so. The approach provides a simple way to generate training data for cluster image analysis algorithms and could be straightforwardly adapted to generate clusters displaying specific types of features or selected by physical characteristics available in the original simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

COSMIC SHEAR MEASUREMENT USING AUTO-CONVOLVED IMAGES

We study the possibility of using quadrupole moments of auto-convolved galaxy images to measure cosmic shear. The autoconvolution of an image corresponds to the inverse Fourier transformation of its power spectrum. The new method has the following advantages: the smearing effect due to the point-spread function (PSF) can be corrected by subtracting the quadrupole moments of the auto-convolved PSF; the centroid of the auto-convolved image is trivially identified; the systematic error due to noise can be directly removed in Fourier space; the PSF image can also contain noise, the effect of which can be similarly removed. With a large ensemble of simulated galaxy images, we show that the new method can reach a sub-percent level accuracy under general conditions, albeit with increasingly large stamp size for galaxies of less compact profiles.

79 ASTRONOMY AND ASTROPHYSICS↗

Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization

Purpose: The authors previously developed the 4D extended cardiac-torso (XCAT) phantom for multimodality imaging research. The XCAT consisted of highly detailed whole-body models for the standard male and female adult, including the cardiac and respiratory motions. In this work, the authors extend the XCAT beyond these reference anatomies by developing a series of anatomically variable 4D XCAT adult phantoms for imaging research, the first library of 4D computational phantoms. Methods: The initial anatomy of each phantom was based on chest-abdomen-pelvis computed tomography data from normal patients obtained from the Duke University database. The major organs and structures for each phantom were segmented from the corresponding data and defined using nonuniform rational B-spline surfaces. To complete the body, the authors manually added on the head, arms, and legs using the original XCAT adult male and female anatomies. The structures were scaled to best match the age and anatomy of the patient. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from the template XCAT phantom (male or female) to the target patient model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. Each new phantom was refined by checking for anatomical accuracy via inspection of the models. Results: Using these methods, the authors created a series of computerized phantoms with thousands of anatomical structures and modeling cardiac and respiratory motions. The database consists of 58 (35 male and 23 female) anatomically variable phantoms in total. Like the original XCAT, these phantoms can be combined with existing simulation packages to simulate realistic imaging data. Each new phantom contains parameterized models for the anatomy and the cardiac and respiratory motions and can, therefore, serve as a jumping point from which to create an unlimited number of 3D and 4D variations for imaging research. Conclusions: A population of phantoms that includes a range of anatomical variations representative of the public at large is needed to more closely mimic a clinical study or trial. The series of anatomically variable phantoms developed in this work provide a valuable resource for investigating 3D and 4D imaging devices and the effects of anatomy and motion in imaging. Combined with Monte Carlo simulation programs, the phantoms also provide a valuable tool to investigate patient-specific dose and image quality, and optimization for adults undergoing imaging procedures.

60 APPLIED LIFE SCIENCES↗

SU-E-J-186: Acquiring and Assessing Upright CBCT Images for Future Treatment Planning

Purpose: To acquire upright CBCT images using the onboard imager of a Varian TrueBeam. An easy to implement upright imaging protocol could allow for widespread upright radiation therapy which would greatly benefit certain patients. These include thoracic cancer patients (because lung volume increases in a seated position) and patients who experience substantial discomfort during supine treatment. Methods: To acquire upright CBCT images, the gantry head remained stationary at 0 degrees with the KV imager arms extended to their lateral positions. Phantoms were placed upright at the end of the treatment couch. During a scan, the couch rotated from 270 to 90 degrees while continuous fluoroscopic projections were taken by the onboard imager. To extend the field-of-view, this sequence was performed twice: once with the KV detector longitudinally offset +14.5cm and once with it longitudinally offset −14.5cm. The resulting two image sets were stitched together before reconstruction. The imaging beam parameters were chosen to deliver a dose similar to that given during a simulation CT. Image quality was evaluated for spatial linearity, high and low contrast resolution, and HU linearity using CatPhan and anthropomorphic phantoms. A deformable registration technique was used to evaluate HU mapping from a simulation CT. Results: Spatial linearity and high contrast resolution were maintained in upright CBCT when compared to simulation CT. However, low contrast resolution and HU linearity degraded. Streak artifacts were caused by the limited 180 degree arc of the couch, and the stitching process created a sharp artifact at the center of the reconstruction. The deformable registration was robust in the HU mapping even with these artifacts and the loss of HU linearity. Conclusions: The image quality obtained from upright CBCT was sufficient for treatment planning. The success of this novel technique is an important step towards a future clinical protocol. This project was funded in part by Varian Medical Systems, Inc.

60 APPLIED LIFE SCIENCES↗