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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Image Guided Radiation Therapy (IGRT) Practice Patterns and IGRT's Impact on Workflow and Treatment Planning: Results From a National Survey of American Society for Radiation Oncology Members

Purpose: To survey image guided radiation therapy (IGRT) practice patterns, as well as IGRT's impact on clinical workflow and planning treatment volumes (PTVs). Methods and Materials: A sample of 5979 treatment site–specific surveys was e-mailed to the membership of the American Society for Radiation Oncology (ASTRO), with questions pertaining to IGRT modality/frequency, PTV expansions, method of image verification, and perceived utility/value of IGRT. On-line image verification was defined as images obtained and reviewed by the physician before treatment. Off-line image verification was defined as images obtained before treatment and then reviewed by the physician before the next treatment. Results: Of 601 evaluable responses, 95% reported IGRT capabilities other than portal imaging. The majority (92%) used volumetric imaging (cone-beam CT [CBCT] or megavoltage CT), with volumetric imaging being the most commonly used modality for all sites except breast. The majority of respondents obtained daily CBCTs for head and neck intensity modulated radiation therapy (IMRT), lung 3-dimensional conformal radiation therapy or IMRT, anus or pelvis IMRT, prostate IMRT, and prostatic fossa IMRT. For all sites, on-line image verification was most frequently performed during the first few fractions only. No association was seen between IGRT frequency or CBCT utilization and clinical treatment volume to PTV expansions. Of the 208 academic radiation oncologists who reported working with residents, only 41% reported trainee involvement in IGRT verification processes. Conclusion: Consensus guidelines, further evidence-based approaches for PTV margin selection, and greater resident involvement are needed for standardized use of IGRT practices.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

A 4DCT imaging-based breathing lung model with relative hysteresis

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Automatic information extraction from neutron radiography imaging to estimate axial fuel expansion in $\mathrm{EBR-II}$

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, like fuel swelling. However, due to the lack of technology or resources, many of the images have not been processed or were processed manually through visual examination. This paper represents first-attempt to develop an image processing algorithm capable of automatically extracting information regarding the degree of fuel swelling from neutron radiography imaging. The algorithm was applied to 120 images of three different metallic fuel pin compositions—U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr. The algorithm performs operations of image intensity adjustment, image binarization, region finding, and labeling to extract information about fuel swelling. The average growth for U-10Zr was found to be 8.49% with 95% Confidence Interval (CI) [8.33 –8.66%], for U-8Pu-10Zr — 7.50% with 95% CI [7.23 – 7.78%], and for U-19Pu-10Zr — 3.15%, with 95% CI [2.40 – 3.91%]. The results obtained by applying this automatic image processing algorithm are consistent with previously reported studies of the same types of fuels. The automatic image processing algorithm will be expanded to include thousands of available neutron radiography images and different types of fuels to investigate empirical dependencies of fuel swelling, which can be subsequently applied to advanced fuel modeling. Results from this study can later be compared to BISON simulations to further benchmark modeling efforts and develop assessment cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

All-optical image denoising using a diffractive visual processor

Abstract Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers, present latency due to several iterations implemented in, e.g., graphics processing units (GPUs). While deep learning-enabled methods can operate non-iteratively, they also introduce latency and impose a significant computational burden, leading to increased power consumption. Here, we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images – implemented at the speed of light propagation within a thin diffractive visual processor that axially spans <250 × λ, where λ is the wavelength of light. This all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features, causing them to miss the output image Field-of-View (FoV) while retaining the object features of interest. Our results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of ~30–40%. We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz spectrum. Owing to their speed, power-efficiency, and minimal computational overhead, all-optical diffractive denoisers can be transformative for various image display and projection systems, including, e.g., holographic displays.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Design and testing of ultrasound probe adapters for a robotic imaging platform

Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military settings. Ultrasound imaging can be used to rapidly identify free fluid in abdominal and thoracic cavities which could necessitate immediate surgical intervention. However, proper ultrasound image capture requires a skilled ultrasonography technician who is likely unavailable at the point of injury where resources are limited. Instead, robotics and computer vision technology can simplify image acquisition. As a first step towards this larger goal, here, we focus on the development of prototypes for ultrasound probe securement using a robotics platform. The ability of four probe adapter technologies to precisely capture images at anatomical locations, repeatedly, and with different ultrasound transducer types were evaluated across more than five scoring criteria. Testing demonstrated two of the adapters outperformed the traditional robot gripper and manual image capture, with a compact, rotating design compatible with wireless imaging technology being most suitable for use at the point of injury. Next steps will integrate the robotic platform with computer vision and deep learning image interpretation models to automate image capture and diagnosis. This will lower the skill threshold needed for medical imaging-based triage, enabling this procedure to be available at or near the point of injury.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Non parametric denoising methods based on wavelets: Application to electron microscopy images in low exposure time

The 3D reconstruction of the Cryo-Transmission Electron Microscopy (Cryo-TEM) and Energy Filtering TEM images (EFTEM) hampered by the noisy nature of these images, so that their alignment becomes so difficult. This noise refers to the collision between the frozen hydrated biological samples and the electrons beam, where the specimen is exposed to the radiation with a high exposure time. This sensitivity to the electrons beam led specialists to obtain the specimen projection images at very low exposure time, which resulting the emergence of a new problem, an extremely low signal-to-noise ratio (SNR). This paper investigates the problem of TEM images denoising when they are acquired at very low exposure time. So, our main objective is to enhance the quality of TEM images to improve the alignment process which will in turn improve the three dimensional tomography reconstructions. We have done multiple tests on special TEM images acquired at different exposure time 0.5s, 0.2s, 0.1s and 1s (i.e. with different values of SNR)) and equipped by Golding beads for helping us in the assessment step. We herein, propose a structure to combine multiple noisy copies of the TEM images. The structure is based on four different denoising methods, to combine the multiple noisy TEM images copies. Namely, the four different methods are Soft, the Hard as Wavelet-Thresholding methods, Bilateral Filter as a non-linear technique able to maintain the edges neatly, and the Bayesian approach in the wavelet domain, in which context modeling is used to estimate the parameter for each coefficient. To ensure getting a high signal-to-noise ratio, we have guaranteed that we are using the appropriate wavelet family at the appropriate level. So we have chosen âĂIJsym8âĂİ wavelet at level 3 as the most appropriate parameter. Whereas, for the bilateral filtering many tests are done in order to determine the proper filter parameters represented by the size of the filter, the range parameter and the spatial parameter respectively. The experiments reported in this paper demonstrate the performance of the Bilateral Filtering and the Bayesian approaches in terms of improving the SNRout and the image quality. Taken together, these results suggest that the Bayesian process has a potential to outperform all the used methods, where in the multiple noisy copies structure it gave us the best SNRout without change of the golden beads diameter. The Bayesian approach yielded enhanced average image without needing a huge amount of copies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

SDSS J2222+2745: A GRAVITATIONALLY LENSED SEXTUPLE QUASAR WITH A MAXIMUM IMAGE SEPARATION OF 15.''1 DISCOVERED IN THE SLOAN GIANT ARCS SURVEY

We report the discovery of a unique gravitational lens system, SDSS J2222+2745, producing five spectroscopically confirmed images of a z{sub s} = 2.82 quasar lensed by a foreground galaxy cluster at z{sub l} = 0.49. We also present photometric and spectroscopic evidence for a sixth lensed image of the same quasar. The maximum separation between the quasar images is 15.''1. Both the large image separations and the high image multiplicity are in themselves rare among known lensed quasars, and observing the combination of these two factors is an exceptionally unlikely occurrence in present data sets. This is only the third known case of a quasar lensed by a cluster, and the only one with six images. The lens system was discovered in the course of the Sloan Giant Arcs Survey, in which we identify candidate lenses in the Sloan Digital Sky Survey and target these for follow-up and verification with the 2.56 m Nordic Optical Telescope. Multi-band photometry obtained over multiple epochs from 2011 September to 2012 September reveals significant variability at the {approx}10%-30% level in some of the quasar images, indicating that measurements of the relative time delay between quasar images will be feasible. In this lens system, we also identify a bright (g = 21.5) giant arc corresponding to a strongly lensed background galaxy at z{sub s} = 2.30. We fit parametric models of the lens system, constrained by the redshift and positions of the quasar images and the redshift and position of the giant arc. The predicted time delays between different pairs of quasar images range from {approx}100 days to {approx}6 yr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Flattening filter removal for improved image quality of megavoltage fluoroscopy

Purpose: Removal of the linear accelerator (linac) flattening filter enables a high rate of dose deposition with reduced treatment time. When used for megavoltage imaging, an unflat beam has reduced primary beam scatter resulting in sharper images. In fluoroscopic imaging mode, the unflat beam has higher photon count per image frame yielding higher contrast-to-noise ratio. The authors’ goal was to quantify the effects of an unflat beam on the image quality of megavoltage portal and fluoroscopic images.Methods: 6 MV projection images were acquired in fluoroscopic and portal modes using an electronic flat-panel imager. The effects of the flattening filter on the relative modulation transfer function (MTF) and contrast-to-noise ratio were quantified using the QC3 phantom. The impact of FF removal on the contrast-to-noise ratio of gold fiducial markers also was studied under various scatter conditions.Results: The unflat beam had improved contrast resolution, up to 40% increase in MTF contrast at the highest frequency measured (0.75 line pairs/mm). The contrast-to-noise ratio was increased as expected from the increased photon flux. The visualization of fiducial markers was markedly better using the unflat beam under all scatter conditions, enabling visualization of thin gold fiducial markers, the thinnest of which was not visible using the unflat beam.Conclusions: The removal of the flattening filter from a clinical linac leads to quantifiable improvements in the image quality of megavoltage projection images. These gains enable observers to more easily visualize thin fiducial markers and track their motion on fluoroscopic images.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

Dose optimization in cardiac x-ray imaging

Purpose: The aim of this research was to optimize x-ray image quality to dose ratios in the cardiac catheterization laboratory. This study examined independently the effects of peak x-ray tube voltage (kVp), copper (Cu), and gadolinium (Gd) x-ray beam filtration on the image quality to radiation dose balance for adult patient sizes.Methods: Image sequences of polymethyl methacrylate (PMMA) phantoms representing two adult patient sizes were captured using a modern flat panel detector based x-ray imaging system. Tin and copper test details were used to simulate iodine-based contrast medium and stents/guide wires respectively, which are used in clinical procedures. Noise measurement for a flat field image and test detail contrast were used to calculate the contrast to noise ratio (CNR). Entrance surface dose (ESD) and effective dose measurements were obtained to calculate the figure of merit (FOM), CNR{sup 2}/dose. This FOM determined the dose efficiency of x-ray spectra investigated. Images were captured with 0.0, 0.1, 0.25, 0.4, and 0.9 mm Cu filtration and with a range of gadolinium oxysulphide (Gd{sub 2}O{sub 2}S) filtration.Results: Optimum x-ray spectra were the same for the tin and copper test details. Lower peak tube voltages were generally favored. For the 20 cm phantom, using 2 Lanex Fast Back Gd{sub 2}O{sub 2}S screens as x-ray filtration at 65 kVp provided the highest FOM considering ESD and effective dose. Considering ESD, this FOM was only marginally larger than that from using 0.4 mm Cu at 65 kVp. For the 30 cm phantom, using 0.25 mm copper filtration at 80 kVp was most optimal; considering effective dose the FOM was highest with no filtration at 65 kVp.Conclusions: These settings, adjusted for x-ray tube loading limits and clinically acceptable image quality, should provide a useful option for optimizing patient dose to image quality in cardiac x-ray imaging. The same optimal x-ray beam spectra were found for both the tin and copper details, suggesting that iodine contrast based imaging and visualization of interventional devices could potentially be optimized for dose using similar x-ray beam spectra.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Long-term stability and mechanical characteristics of kV digital imaging system for proton radiotherapy

Purpose: To quantitatively evaluate the long-term image panel positioning stability and gantry angle dependence for gantry-mounted kV imaging systems. Methods: For patient setup digital imaging systems in isocentric rotating proton beam delivery facilities, physical crosshairs are commonly inserted into the snout to define the kV x-ray beam isocenter. Utilizing an automatic detection algorithm, the authors analyzed the crosshair center positions in 2744 patient setup kV images acquired with the four imagers in two treatment rooms from January 2012 to January 2013. The crosshair position was used as a surrogate for imaging panel position, and its long-term stability at the four cardinal angles and the panel flex dependency on gantry angle was investigated. Results: The standard deviation of the panel position distributions was within 0.32 mm (with the range of variation less than ± 1.4 mm) in both the X-Z plane and Y direction. The mean panel inplane rotations were not more than 0.51° for the four panels at the cardinal angles, with standard deviations ≤0.26°. The panel position variations with gantry rotation due to gravity (flex) were within ±4 mm, and were panel-specific. Conclusions: The authors demonstrated that the kV image panel positions in our proton treatment system were highly reproducible at the cardinal angles over 13 months and also that the panel positions can be correlated to gantry angles. This result indicates that the kV image panel positions are stable over time; the amount of panel sag is predictable during gantry rotation and the physical crosshair for kV imaging may eventually be removed, with the imaging beam isocenter position routinely verified by adequate quality assurance procedures and measurements.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging

Purpose: 4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol. Methods: The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency. Results: The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3–0.5 mm for patients 1–3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1–1.5 min per phase. Conclusions: High-quality 4D-CBCT imaging based on the clinically standard 1-min 3D CBCT scanning protocol is feasible via the proposed hybrid reconstruction algorithm.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-23: An Accurate Algorithm to Match Imperfectly Matched Images for Lung Tumor Detection Without Markers

Purpose: In order to locate lung tumors on projection images without internal markers, digitally reconstructed radiograph (DRR) is created and compared with projection images. Since lung tumors always move and their locations change on projection images while they are static on DRRs, a special DRR (background DRR) is generated based on modified anatomy from which lung tumors are removed. In addition, global discrepancies exist between DRRs and projections due to their different image originations, scattering, and noises. This adversely affects comparison accuracy. A simple but efficient comparison algorithm is reported. Methods: This method divides global images into a matrix of small tiles and similarities will be evaluated by calculating normalized cross correlation (NCC) between corresponding tiles on projections and DRRs. The tile configuration (tile locations) will be automatically optimized to keep the tumor within a single tile which has bad matching with the corresponding DRR tile. A pixel based linear transformation will be determined by linear interpolations of tile transformation results obtained during tile matching. The DRR will be transformed to the projection image level and subtracted from it. The resulting subtracted image now contains only the tumor. A DRR of the tumor is registered to the subtracted image to locate the tumor. Results: This method has been successfully applied to kV fluoro images (about 1000 images) acquired on a Vero (Brainlab) for dynamic tumor tracking on phantom studies. Radiation opaque markers are implanted and used as ground truth for tumor positions. Although, other organs and bony structures introduce strong signals superimposed on tumors at some angles, this method accurately locates tumors on every projection over 12 gantry angles. The maximum error is less than 2.6 mm while the total average error is 1.0 mm. Conclusion: This algorithm is capable of detecting tumor without markers despite strong background signals.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-44: Design a Platform and Phantom Model for Photoacoustic Imaging in Combination with CT

Purpose: Our (long-term) objective is to develop a US manipulator that will provide in situ radiation response and image-guided therapy for bladder cancer based on photoacoustic molecular imaging. Methods: A platform was devised to provide a reproducible positional frame of reference for targeting anatomic structure between MDCT and US scans, in lieu of CBCT, and to fuse photoacoustic molecular imaging. US and photoacoustic scans are taken of a patient while in the CT scanner and IRMT. Through co-registration, based on anatomical positions, we identified a common coordinate system to be used in Eclipse. A bladder phantom was constructed to validate anatomical tracking via US and photoacoustic imaging. We tested the platform using phantom model to demonstrate validity once moved from the CT couch to the linear accelerator couch. Results: This platform interlocks with Varian exact couch index points for reproducibility of positioning. Construction from low Z material and sized appropriately to fit in CT/IMRT gantry. Error in conversion from cylindrical coordinates of the manipulator to X, Y, Z coordinates of the treatment couch was less than 1mm. We measured the bladder size in 3 different directions in both Eclipse from the CT and Acuson from US. The error was less than 2mm in all directions. CT and US images were co-registered in MATLAB. Co-registration of photoacoustic images is still being developed. Conclusion: For Linear Accelerators without on board imaging, MV portal images are not a viable option for the localization of soft tissue anatomy. We believe our manipulator provides an alternative using US imaging, which will be examined in an upcoming clinical trial. We plan to examine the value of hypoxia guided treatment through photoacoustic imaging during this trial.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-104: Single Photon Image From PET with Insertable SPECT Collimator for Boron Neutron Capture Therapy: A Feasibility Study

Purpose: The aim of our proposed system is to confirm the feasibility of extraction of two types of images from one positron emission tomography (PET) module with an insertable collimator for brain tumor treatment during the BNCT. Methods: Data from the PET module, neutron source, and collimator was entered in the Monte Carlo n-particle extended (MCNPX) source code. The coincidence events were first compiled on the PET detector, and then, the events of the prompt gamma ray were collected after neutron emission by using a single photon emission computed tomography (SPECT) collimator on the PET. The obtaining of full width at half maximum (FWHM) values from the energy spectrum was performed to collect effective events for reconstructed image. In order to evaluate the images easily, five boron regions in a brain phantom were used. The image profiles were extracted from the region of interest (ROI) of a phantom. The image was reconstructed using the ordered subsets expectation maximization (OSEM) reconstruction algorithm. The image profiles and the receiver operating characteristic (ROC) curve were compiled for quantitative analysis from the two kinds of reconstructed image. Results: The prompt gamma ray energy peak of 478 keV appeared in the energy spectrum with a FWHM of 41 keV (6.4%). On the basis of the ROC curve in Region A to Region E, the differences in the area under the curve (AUC) of the PET and SPECT images were found to be 10.2%, 11.7%, 8.2% (center, Region C), 12.6%, and 10.5%, respectively. Conclusion: We attempted to acquire the PET and SPECT images simultaneously using only PET without an additional isotope. Single photon images were acquired using an insertable collimator on a PET detector. This research was supported by the Leading Foreign Research Institute Recruitment Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, Information and Communication Technologies (ICT) and Future Planning (MSIP)(Grant No.2009 00420) and the Radiation Technology R and D program (Grant No.2013M2A2A7043498), Republic of Korea.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

WE-G-BRF-04: Robust Real-Time Volumetric Imaging Based On One Single Projection

Purpose: Real-time volumetric imaging is highly desirable to provide instantaneous image guidance for lung radiation therapy. This study proposes a scheme to achieve this goal using one single projection by utilizing sparse learning and a principal component analysis (PCA) based lung motion model. Methods: A patient-specific PCA-based lung motion model is first constructed by analyzing deformable vector fields (DVFs) between a reference image and 4DCT images at each phase. At the training stage, we “learn” the relationship between the DVFs and the projection using sparse learning. Specifically, we first partition the projections into patches, and then apply sparse learning to automatically identify patches that best correlate with the principal components of the DVFs. Once the relationship is established, at the application stage, we first employ a patchbased intensity correction method to overcome the problem of different intensity scale between the calculated projection in the training stage and the measured projection in the application stage. The corrected projection image is then fed to the trained model to derive a DVF, which is applied to the reference image, yielding a volumetric image corresponding to the projection. We have validated our method through a NCAT phantom simulation case and one experiment case. Results: Sparse learning can automatically select those patches containing motion information, such as those around diaphragm. For the simulation case, over 98% of the lung region pass the generalized gamma test (10HU/1mm), indicating combined accuracy in both intensity and spatial domain. For the experimental case, the average tumor localization errors projected to the imager are 0.68 mm and 0.4 mm on the axial and tangential direction, respectively. Conclusion: The proposed method is capable of accurately generating a volumetric image using one single projection. It will potentially offer real-time volumetric image guidance to facilitate lung radiotherapy. This study is supported in part by NIH (1R01CA154747-01), The Core Technology Research in Strategic Emerging Industry, Guangdong, China(2011A081402003)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

WE-G-18A-01: JUNIOR INVESTIGATOR WINNER - Low-Dose C-Arm Cone-Beam CT with Model-Based Image Reconstruction for High-Quality Guidance of Neurosurgical Intervention

Purpose: To address the challenges of image quality, radiation dose, and reconstruction speed in intraoperative cone-beam CT (CBCT) for neurosurgery by combining model-based image reconstruction (MBIR) with accelerated algorithmic and computational methods. Methods: Preclinical studies involved a mobile C-arm for CBCT imaging of two anthropomorphic head phantoms that included simulated imaging targets (ventricles, soft-tissue structures/bleeds) and neurosurgical procedures (deep brain stimulation (DBS) electrode insertion) for assessment of image quality. The penalized likelihood (PL) framework was used for MBIR, incorporating a statistical model with image regularization via an edgepreserving penalty. To accelerate PL reconstruction, the ordered-subset, separable quadratic surrogates (OS-SQS) algorithm was modified to incorporate Nesterov's method and implemented on a multi-GPU system. A fair comparison of image quality between PL and conventional filtered backprojection (FBP) was performed by selecting reconstruction parameters that provided matched low-contrast spatial resolution. Results: CBCT images of the head phantoms demonstrated that PL reconstruction improved image quality (∼28% higher CNR) even at half the radiation dose (3.3 mGy) compared to FBP. A combination of Nesterov's method and fast projectors yielded a PL reconstruction run-time of 251 sec (cf., 5729 sec for OS-SQS, 13 sec for FBP). Insertion of a DBS electrode resulted in severe metal artifact streaks in FBP reconstructions, whereas PL was intrinsically robust against metal artifact. The combination of noise and artifact was reduced from 32.2 HU in FBP to 9.5 HU in PL, thereby providing better assessment of device placement and potential complications. Conclusion: The methods can be applied to intraoperative CBCT for guidance and verification of neurosurgical procedures (DBS electrode insertion, biopsy, tumor resection) and detection of complications (intracranial hemorrhage). Significant improvement in image quality, dose reduction, and reconstruction time of ∼4 min will enable practical deployment of low-dose C-arm CBCT within the operating room. AAPM Research Seed Funding (2013-2014); NIH Fellowship F32EB017571; Siemens Healthcare (XP Division)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

WE-G-18C-08: Real Time Tumor Imaging Using a Novel Dynamic Keyhole MRI Reconstruction Technique

Purpose: To test the hypothesis that the novel Dynamic Keyhole MRI reconstruction technique can accelerate image acquisition whilst maintaining high image quality for lung cancer patients. Methods: 18 MRI datasets from 5 lung cancer patients were acquired using a 3T MRI scanner. These datasets were retrospectively reconstructed using (A) The novel Dynamic Keyhole technique, (B) The conventional keyhole technique and (C) the conventional zero filling technique. The dynamic keyhole technique in MRI refers to techniques in which previously acquired k-space data is used to supplement under sampled data obtained in real time. The novel Dynamic Keyhole technique utilizes a previously acquired a library of kspace datasets in conjunction with central k-space datasets acquired in realtime. A simultaneously acquired respiratory signal is utilized to sort, match and combine the two k-space streams with respect to respiratory displacement. Reconstruction performance was quantified by (1) comparing the keyhole size (which corresponds to imaging speed) required to achieve the same image quality, and (2) maintaining a constant keyhole size across the three reconstruction methods to compare the resulting image quality to the ground truth image. Results: (1) The dynamic keyhole method required a mean keyhole size which was 48% smaller than the conventional keyhole technique and 60% smaller than the zero filling technique to achieve the same image quality. This directly corresponds to faster imaging. (2) When a constant keyhole size was utilized, the Dynamic Keyhole technique resulted in the smallest difference of the tumor region compared to the ground truth. Conclusion: The dynamic keyhole is a simple and adaptable technique for clinical applications requiring real-time imaging and tumor monitoring such as MRI guided radiotherapy. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by a factor of five compared with full k-space methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Model-based CT performance assessment and optimization for iodinated and noniodinated imaging tasks as a function of kVp and body size

Purpose: The goal of this study was to assess the comparative performance of iterative reconstruction in space (IRIS) and filtered back projection (FBP) reconstruction algorithms in terms of image quality and dose across kVps and phantom sizes. Methods: The ACR CT phantom (model 464) was supplemented with the addition of an iodinated spherical capsule (1.5 mm diameter, 3.4 mg iodine per ml) to simulate the contrast filled structures and with an additional circular attachment consisting of an array of 500 um brass beads for spatial resolution measurements. A larger sized phantom was also created by wrapping the original phantom with additional tissue equivalent material of 4 cm thickness. The phantoms were imaged on a 64 detector array multidetector computed tomography scanner (Somatom Definition, Siemens, Germany) using clinically applicable protocols (0.5 s rotation time; 80, 100, 120, and 140 kVp; 64 to 640 mA; 220 to 250 mm field of view). Images were reconstructed using the FBP and the IRIS algorithms. Combining measurements of image noise and spatial resolution with a task function, a figure of merit (FOM) for image quality was generated taking into account the type of visualization required from the image for the detection of either large or small image features with and without iodine content. The FOM was further reported in terms of area under the receiver operating characteristic (ROC) curve (A{sub Z}) to predict the comparative diagnostic performance of the two algorithms at different dose levels. Results: For a given dose level, the predicted A{sub Z} for IRIS consistently outperformed that of FBP. At comparative A{sub Z}, depending on protocol and task, the dose requirement for the optimal technique (optimized kVp with IRIS) was 2-3 times lower than that for standard technique (120 kVp with FBP). The potential for dose reduction was found to be higher when performing small feature detection tasks in comparison to larger feature detection tasks. The optimal kVp was from 80 to 100 kVp for the small phantom, 100 to 120 kVp for the larger phantom. Conclusions: Overall, greater dose reduction may be achieved with IRIS compared to FBP, with enhanced advantage at thinner slice reconstructions. The results highlight how IRIS may offer a superior balance between image quality and dose across a range of imaging tasks, thus enabling dose reduction at constant quality or image quality improvement at constant dose. The prediction of the investigation can be used toward effective design of subsequent clinical studies.

60 APPLIED LIFE SCIENCES↗