Search NASA⌕ Search

SEARCH · Search NASA

Results for “Image coding”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

Daily QA of linear accelerators using only EPID and OBI

Purpose: As treatment delivery becomes more complex, there is a pressing need for robust quality assurance (QA) tools to improve efficiency and comprehensiveness while simultaneously maintaining high accuracy and sensitivity. This work aims to present the hardware and software tools developed for comprehensive QA of linear accelerator (LINAC) using only electronic portal imaging devices (EPIDs) and kV flat panel detectors. Methods: A daily QA phantom, which includes two orthogonally positioned phantoms for QA of MV-beams and kV onboard imaging (OBI) is suspended from the gantry accessory holder to test both geometric and dosimetric components of a LINAC and an OBI. The MV component consists of a 0.5 cm water-equivalent plastic sheet incorporating 11 circular steel plugs for transmission measurements through multiple thicknesses and one resolution plug for MV-image quality testing. The kV-phantom consists of a Leeds phantom (TOR-18 FG phantom supplied by Varian) for testing low and high contrast resolutions. In the developed process, the existing LINAC tools were used to automate daily acquisition of MV and kV images and software tools were developed for simultaneous analysis of these images. A method was developed to derive and evaluate traditional QA parameters from these images [output, flatness, symmetry, uniformity, TPR{sub 20/10}, and positional accuracy of the jaws and multileaf collimators (MLCs)]. The EPID-based daily QA tools were validated by performing measurements on a detuned 6 MV beam to test its effectiveness in detecting errors in output, symmetry, energy, and MLC positions. The developed QA process was clinically commissioned, implemented, and evaluated on a Varian TrueBeam LINAC (Varian Medical System, Palo Alto, CA) over a period of three months. Results: Machine output constancy measured with an EPID (as compared against a calibrated ion-chamber) is shown to be within ±0.5%. Beam symmetry and flatness deviations measured using an EPID and a 2D ion-chamber array agree within ±0.5% and ±1.2% for crossline and inline profiles, respectively. MLC position errors of 0.5 mm can be detected using a picket fence test. The field size and phantom positioning accuracy can be determined within 0.5 mm. The entire daily QA process takes ∼15 min to perform tests for 5 photon beams, MLC tests, and imaging checks. Conclusions: The exclusive use of EPID-based QA tools, including a QA phantom and simultaneous analysis software tools, has been demonstrated as a viable, efficient, and comprehensive process for daily evaluation of LINAC performance.

60 APPLIED LIFE SCIENCES↗

2D lag and signal nonlinearity correction in an amorphous silicon EPID and their impact on pretreatment dosimetric verification

Purpose: This investigation provides measurements of signal lag and nonlinearity separately for the Varian aS500 electronic portal imaging device (EPID), and an algorithm to correct for these effects in 2D; their potential impact on intensity modulated radiation therapy (IMRT) verification is also investigated. The authors quantify lag, as a function of both delivered monitor units (MU) and time, by using a range of MUs delivered at a clinically used rate of 400 MU/min. Explicit cumulative lag curves are thus determined for a range of MUs and times between the end of irradiation and the end of image acquisition. Signal nonlinearity is also investigated as a function of total MUs delivered. The family of cumulative lag curves and signal nonlinearity are then used to determine their effects on dynamic multileaf collimator (MLC) (IMRT) deliveries, and to correct for theses effects in 2D. Methods: Images acquired with an aS500 EPID and Varis Portal-Vision software were used to quantify detector lag and signal-nonlinearity. For the signal lag investigation, Portal-Vision's service monitor was used to acquire EPID images at a rate of 8 frames/s. The images were acquired during irradiation and 66 s thereafter, by inhibiting the M-holdoff-In signal of the Linac for a range of 4.5-198.5 MUs. Relative cumulative lag was calculated by integrating the EPID signal for a time after beam-off, and normalizing this to the integrated EPID signal accumulated during radiation. Signal nonlinearity was studied by acquiring 10 Multiplication-Sign 10 cm{sup 2} open-field EPID images in 'integrated image' mode for a range of 2-500 MUs, and normalized to the 100 MU case. All data were incorporated into in-house written software to create a 2D correction map for these effects, using the field's MLC file and a field-specific calculated 2D 'time-map,' which keeps track of the time elapsed from the last fluence delivered at each given point in the image to the end of the beam delivery. Results: Relative cumulative lag curves reveal that the lag alone can deviate the EPID's perceived dose by as large as 6% (1 MU delivery, 60 s postirradiation). For signal nonlinearity relative to 100 MU, EPID signals per MU of 0.84 and 1.01 were observed for 2 and 500 MUs, respectively. Correction maps were applied to a 1 cm sweeping-window 14 Multiplication-Sign 14 cm{sup 2} field and clinical head-and-neck IMRT field. A mean correction of 1.028 was implemented in the head-and-neck field, which significantly reduced lag-related asymmetries in the EPID images, and restored linearity to the EPID imager's dose response. Corrections made to the sweeping-field showed good agreement with the treatment planning system-predicted field, yielding an average percent difference of 0.05%{+-} 0.91%, compared to the -1.32%{+-} 1.02% before corrections, or 1.75%{+-} 1.04% when only a signal nonlinearity correction is made. Conclusions: Lag and signal-nonlinearity have been quantified for an aS500 EPID imager, and an effective 2D correction method has been developed which effectively removes nonlinearity and lag effects. Both of these effects were shown to negatively impact IMRT verifications. Especially fields that involve prolonged irradiation and small overall MUs should be corrected for in 2D.

60 APPLIED LIFE SCIENCES↗

SU-E-T-659: Quantitative Evaluation of Patient Setup Accuracy of Stereotactic Radiotherapy with the Frameless 6D-ExacTrac System Using Statistical Modeling

Purpose: To evaluate patient setup accuracy and quantify individual and cumulative positioning uncertainties associated with different hardware and software components of the stereotactic radiotherapy (SRS/SRT) with the frameless-6D-ExacTrac system. Methods: A statistical model was used to evaluate positioning uncertainties of the different components of SRS/SRT treatment with the BrainLAB 6D-ExacTrac system using the positioning shifts of 35 patients having cranial lesions (49 total lesions treated in 1, 3, 5 fractions). All these patients were immobilized with rigid head-and-neck masks, simulated with BrainLAB-localizer and planned with iPlan treatment planning system. Infrared imaging (IR) was used initially to setup patients. Then, stereoscopic x-ray images (XC) were acquired and registered to corresponding digitally-reconstructed-radiographs using bony-anatomy matching to calculate 6D-translational and rotational shifts. When the shifts were within tolerance (0.7mm and 1°), treatment was initiated. Otherwise corrections were applied and additional x-rays were acquired (XV) to verify that patient position was within tolerance. Results: The uncertainties from the mask, localizer, IR-frame, x-ray imaging, MV and kV isocentricity were quantified individually. Mask uncertainty (Translational: Lateral, Longitudinal, Vertical; Rotational: Pitch, Roll, Yaw) was the largest and varied with patients in the range (−1.05−1.50mm, −5.06–3.57mm, −5.51−3.49mm; −1.40−2.40°, −1.24−1.74°, and −2.43−1.90°) obtained from mean of XC shifts for each patient. Setup uncertainty in IR positioning (0.88,2.12,1.40mm, and 0.64,0.83,0.96°) was extracted from standard-deviation of XC. Systematic uncertainties of the localizer (−0.03,−0.01,0.03mm, and −0.03,0.00,−0.01°) and frame (0.18,0.25,−1.27mm,−0.32,0.18, and 0.47°) were extracted from means of all XV setups and mean of all XC distributions, respectively. Uncertainties in isocentricity of the MV radiotherapy machine were (0.27,0.24,0.34mm) and kV-imager (0.15,−0.4,0.21mm). Conclusion: A statistical model was developed to evaluate the individual and cumulative systematic and random uncertainties induced by the different hardware and software components of the 6D-ExacTrac-system. The immobilization mask was associated with the largest positioning uncertainty.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Study on efficiency of time computation in x-ray imaging simulation base on Monte Carlo algorithm using graphics processing unit

Monte Carlo (MC) is one of the powerful techniques for simulation in x-ray imaging. MC method can simulate the radiation transport within matter with high accuracy and provides a natural way to simulate radiation transport in complex systems. One of the codes based on MC algorithm that are widely used for radiographic images simulation is MC-GPU, a codes developed by Andrea Basal. This study was aimed to investigate the time computation of x-ray imaging simulation in GPU (Graphics Processing Unit) compared to a standard CPU (Central Processing Unit). Furthermore, the effect of physical parameters to the quality of radiographic images and the comparison of image quality resulted from simulation in the GPU and CPU are evaluated in this paper. The simulations were run in CPU which was simulated in serial condition, and in two GPU with 384 cores and 2304 cores. In simulation using GPU, each cores calculates one photon, so, a large number of photon were calculated simultaneously. Results show that the time simulations on GPU were significantly accelerated compared to CPU. The simulations on the 2304 core of GPU were performed about 64 -114 times faster than on CPU, while the simulation on the 384 core of GPU were performed about 20 – 31 times faster than in a single core of CPU. Another result shows that optimum quality of images from the simulation was gained at the history start from 10{sup 8} and the energy from 60 Kev to 90 Kev. Analyzed by statistical approach, the quality of GPU and CPU images are relatively the same.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SU-F-I-49: Vendor-Independent, Model-Based Iterative Reconstruction On a Rotating Grid with Coordinate-Descent Optimization for CT Imaging Investigations

Purpose: Iterative reconstruction methods show promise for improving image quality and lowering the dose in helical CT. We aim to develop a novel model-based reconstruction method that offers potential for dose reduction with reasonable computation speed and storage requirements for vendor-independent reconstruction from clinical data on a normal desktop computer. Methods: In 2012, Xu proposed reconstructing on rotating slices to exploit helical symmetry and reduce the storage requirements for the CT system matrix. Inspired by this concept, we have developed a novel reconstruction method incorporating the stored-system-matrix approach together with iterative coordinate-descent (ICD) optimization. A penalized-least-squares objective function with a quadratic penalty term is solved analytically voxel-by-voxel, sequentially iterating along the axial direction first, followed by the transaxial direction. 8 in-plane (transaxial) neighbors are used for the ICD algorithm. The forward problem is modeled via a unique approach that combines the principle of Joseph’s method with trilinear B-spline interpolation to enable accurate reconstruction with low storage requirements. Iterations are accelerated with multi-CPU OpenMP libraries. For preliminary evaluations, we reconstructed (1) a simulated 3D ellipse phantom and (2) an ACR accreditation phantom dataset exported from a clinical scanner (Definition AS, Siemens Healthcare). Image quality was evaluated in the resolution module. Results: Image quality was excellent for the ellipse phantom. For the ACR phantom, image quality was comparable to clinical reconstructions and reconstructions using open-source FreeCT-wFBP software. Also, we did not observe any deleterious impact associated with the utilization of rotating slices. The system matrix storage requirement was only 4.5GB, and reconstruction time was 50 seconds per iteration. Conclusion: Our reconstruction method shows potential for furthering research in low-dose helical CT, in particular as part of our ongoing development of an acquisition/reconstruction pipeline for generating images under a wide range of conditions. Our algorithm will be made available open-source as “FreeCT-ICD”. NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.

60 APPLIED LIFE SCIENCES↗

TU-AB-202-06: Quantitative Evaluation of Deformable Image Registration in MRI-Guided Adaptive Radiation Therapy

Purpose: To assess the performance of the deformable image registration algorithm used for MRI-guided adaptive radiation therapy using image feature analysis. Methods: MR images were collected from five patients treated on the MRIdian (ViewRay, Inc., Oakwood Village, OH), a three head Cobalt-60 therapy machine with an 0.35 T MR system. The images were acquired immediately prior to treatment with a uniform 1.5 mm resolution. Treatment sites were as follows: head/neck, lung, breast, stomach, and bladder. Deformable image registration was performed using the ViewRay software between the first fraction MRI and the final fraction MRI, and the DICE similarity coefficient (DSC) for the skin contours was reported. The SIFT and Harris feature detection and matching algorithms identified point features in each image separately, then found matching features in the other image. The target registration error (TRE) was defined as the vector distance between matched features on the two image sets. Each deformation was evaluated based on comparison of average TRE and DSC. Results: Image feature analysis produced between 2000–9500 points for evaluation on the patient images. The average (± standard deviation) TRE for all patients was 3.3 mm (±3.1 mm), and the passing rate of TRE<3 mm was 60% on the images. The head/neck patient had the best average TRE (1.9 mm±2.3 mm) and the best passing rate (80%). The lung patient had the worst average TRE (4.8 mm±3.3 mm) and the worst passing rate (37.2%). DSC was not significantly correlated with either TRE (p=0.63) or passing rate (p=0.55). Conclusions: Feature matching provides a quantitative assessment of deformable image registration, with a large number of data points for analysis. The TRE of matched features can be used to evaluate the registration of many objects throughout the volume, whereas DSC mainly provides a measure of gross overlap. We have a research agreement with ViewRay Inc.

60 APPLIED LIFE SCIENCES↗

Radiology and Enterprise Medical Imaging Extensions (REMIX)

Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner Medical Center. REMIX accommodates the storage and handling of “big imaging data,” as needed for large multi-disciplinary cancer-focused programs. The evolving REMIX platform contains an array of integrated tools/software packages for the following: (1) server and storage management; (2) image reconstruction; (3) digital pathology; (4) de-identification; (5) business intelligence; (6) texture analysis; and (7) artificial intelligence. These capabilities, along with documentation and guidance, explaining how to interact with a commercial system (e.g., PACS, EHR, commercial database) that currently exists in clinical environments, are to be made freely available.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

RAY-UI: A powerful and extensible user interface for RAY

The RAY-UI project started as a proof-of-concept for an interactive and graphical user interface (UI) for the well-known ray tracing software RAY [1]. In the meantime, it has evolved into a powerful enhanced version of RAY that will serve as the platform for future development and improvement of associated tools. The software as of today supports nearly all sophisticated simulation features of RAY. Furthermore, it delivers very significant usability and work efficiency improvements. Beamline elements can be quickly added or removed in the interactive sequence view. Parameters of any selected element can be accessed directly and in arbitrary order. With a single click, parameter changes can be tested and new simulation results can be obtained. All analysis results can be explored interactively right after ray tracing by means of powerful integrated image viewing and graphing tools. Unlimited image planes can be positioned anywhere in the beamline, and bundles of image planes can be created for moving the plane along the beam to identify the focus position with live updates of the simulated results. In addition to showing the features and workflow of RAY-UI, we will give an overview of the underlying software architecture as well as examples for use and an outlook for future developments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-E-T-126: Application of PIPSpro and EPID for Quality Assurance of Medical Accelerators

Purpose: The purpose is to study applying PIPSpro and EPID for routine quality assurance of medical accelerators. Methods: (1) The coincidence of Light field and radiation field: Placed the FC-2 phantom on the treatment couch at the 100cm SSD. Using jaw set 10×10 cm{sup 2} or 15×15 cm{sup 2} field. Verified that the light field aligns with the engraved squares on the phantom. Placed the Crosshair Marker phantom on the top of the FC-2 phantom with the cross-hair and spherical marker aligned to the center of the light field. Acquired images with EPID and the images should be exported preferably in DICOM format. Analyzed Follow the recommended procedures in the radiation light field module of PIPSpro software.(2)MLC QA:Set up the MLC phantom on the treatment couch at isocenter. Positioned the EPID imager at the highest possible position without colliding with either the couch or the phantom. Created and delivered four different patterns for testing the MLC leaf position, leaf width, multi-port and leaf transmission. (3)Radiation isocenter test: Included the isocenter of collimator rotation, gantry rotation and couch rotation. Set the jaws of the collimator to create a thin field as 0.4cm x 20cm.Irradiated film or EPID using an equidistant 15° spacing angles with rotating collimator, gantry and couch respectively. Results: We analyzed imagers from EPID and film with PIPSPro software. As a Result, we acquired the specifications of medical accelerators quickly. In the meantime, the results were saved to database for trending and future analysis. Conclusion: Quality assurance of medical accelerator is very important. We used PIPSpro and EPID for routine detection, not only improved our efficiency, but also saved the cost. It is an good method.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-F-BRD-11: A Virtual Simulator Designed for Collision Prevention in Proton Therapy

Purpose: In proton therapy, collisions between patient and nozzle potentially occur in attaining minimal air gap due to the large nozzle structure. Thus, we developed software predicting the collisions of the nozzle and patient by simulating treatments. Methods: 3D modeling of a gantry inner-floor, nozzle and robotic-couch was done by using the SolidWorks based on the manufacturer’s machine data. To obtain patient body information, a 3D-scanner was utilized to scan a patient right before CT scanning. From the acquired images, a 3D-image of the patient’s body contour was reconstructed. The accuracy of the image was confirmed against the CT image for a humanoid phantom. The machine components and the virtual patient were combined on the treatment-room coordinate system, resulting in a virtual simulator. The simulator simulated the motion of its components such as rotation and translation of gantry, nozzle and couch, in real scale. Collision, if any, was examined both in static mode and dynamic mode. The static mode checks only at fixed positions of the machine’s components while dynamic mode examines while one component is in motion. Collision was notified if any voxel of two components, for example a nozzle and a patient or couch, overlapped when calculating volume locations. The event and collision point are visualized and colliding volumes are reported. Results: All components were successfully assembled and the motions could be accurately controlled. The 3D-shape of a phantom agreed with CT images within a deviation of 2 mm. Collision situations can be simulated within minutes and the results are displayed and reported. Conclusion: The developed software will be useful in improving patient safety and clinical efficiency for proton therapy. This work was supported by the National Research Foundation of Korea funded by Ministry of Science, ICT & Future Planning (2012M3A9B6055201, 2013M2A2A7043507), and Samsung Medical Center grant (GFO1130081)

60 APPLIED LIFE SCIENCES↗

Exclusive µ+Np topologies with ArgoNeuT

The Argon Neutrino Test, ArgoNeuT, is a small scale Liquid Argon Time Projection Chamber (LAr TPC) that is one step towards the construction of large scale LAr TPCs for long-baseline neutrino physics. LArTPCs provide bubble-chamber-like quality images for excellent particle ID and background rejection. Due to its superb capabilities it is well suited for topological analysis by reporting what it sees in a final state. Preliminary analysis of ArgoNeuT’s 0.1 to 10 GeV neutrino µ+Np topologies together with first ever study of proton multiplicities in neutrino-argon interactions was presented and compared with GENIE Monte Carlo generator.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-F-J-129: Verification of Geometric and Dosimetric Accuracy of Respiratory Management Systems Using Homemade Phantom

Purpose: Different placements of Infrared Cameras (IRC) in CT and treatment rooms can cause gating window level (GWL) variations leading to differences between GWL used for planning and treatments. Although, Varian Clinac DHX-OBI sytem and CT are equipped with the same kind of IRC, Truebeam STx (TB) has a different type of IRC known as banana type. In this study; geometric and dosimetric accuracy of respiratory management system (RPM) for different machines were investigated with a special homemade phantom. Methods: Special phantom was placed on the respiratory simulator machine and a CT data set was obtained at the end of the expirium phase (EOE). Conformal and IMRT plans were generated on the EOE CT image series for both DHX-OBI and TB LINACs while a VMAT plan was generated only for TB.The acquired respiratory graphs in the CT were directly sent to DHX-OBI system, and they were converted with software before sending to TB. EBT3 films were placed inside the phantom and were irradiated using RPM system with two machines for different plans. Planar dose distributions were compared with gamma analysis (GA) method (3mm, %3) to evaluate planned-measured dose differences. In addition, radio-opac marker was placed in the center of the phantom to evaluate the geometric accuracy of treatment field with gated flouroscopy (GF). Results: There were no shifts detected between planning and treeatment GWL for both DHX-OBI and TB. Difference on the GF image between digital graticule and radio-opac marker was <1mm for TB and 1mm for DHX-OBI. Although, GA agreement was 97% for conformal and IMRT techniques in TB, it was 96% for VMAT technique. While GA agreement was 98% for conformal technique in DHX-OBI, IMRT was 95%.ConclusionThis study showed that RPM can be used accurately in spite of different IRC placements or different types of ICR used.

60 APPLIED LIFE SCIENCES↗

SU-G-JeP3-15: Is the Reproducibility with Respect to Bone of Tumor Position at Simulation for Breath Hold CT Scans Correlated to the Reproducibility for Multiple Breath Hold CBCTs at Treatment in SBRT Thoracic Patients?

Purpose: To evaluate correlation between the reproducibility of tumor position under feedback guided voluntary deep inspiration breath hold gating at simulation and at treatment. Methods: All patients treated with breath hold (BH) have 3-6 BH CTs taken at simulation (sim). In addition, if the relationship between the tumor and nearby bony anatomy on treatment BH CT(or CBCT) is found to be greater than 5 mm different at treatment than it was at sim, a repeat BH CT is taken before treatment. We retrospectively analyzed the sim CTs for 19 patients who received BH SBRT lung treatments and had repeat BH CT on treatment. We evaluated the reproducibility of the tumor position during the simulation CTs and compared this to the reproducibility of the tumor position on the repeat treatment CT with our in-house CT alignment software (CT-Assisted Targeting for Radiotherapy). Results: Comparing the tumor position for multiple simulation BH CTs, we calculated: maximum difference (max) = 0.69cm; average difference (x) = 0.28cm; standard deviation (σ) = 0.18cm. Comparing the repeat BH CBCTs on treatment days we calculated: max = 0.44cm; x = 0.16cm; σ = 0.22cm. We also found that for 95% of our BH cases, the absolute variation in tumor position within the same imaging day was within 5mm of the range at the time of simulation and treatment. We found that 75% of the BH cases had less residual tumor motion on treatment days than at simulation. Conclusion: This suggests that a GTV contour based upon the residual tumor motion in multiple BH datasets plus 2 mm margin should be sufficient to cover the full range of residual tumor motion on treatment days.

60 APPLIED LIFE SCIENCES↗

WE-D-204-06: An Open Source ImageJ CatPhan Analysis Tool

Purpose: The CatPhan is a popular QA device for assessing CT image quality. There are a number of software options which perform analysis of the CatPhan. However, there is often little ability for the user to adjust the analysis if it isn’t running properly, and these are all expensive options. An open source tool is an effective solution. Methods: To use the software, the user imports the CT as an image sequence in ImageJ. The user then scrolls to the slice with the lateral dots. The user then runs the plugin. If tolerance constraints are not already created, the user is prompted to enter them or to use generic tolerances. Upon completion of the analysis, the plugin calls pdfLaTex to compile the pdf report. There is a csv version of the report as well. A log of the results from all CatPhan scans is kept as a csv file. The user can use this to baseline the machine. Results: The tool is capable of detecting the orientation of the phantom. If the CatPhan was scanned backwards, one can simply flip the stack of images horizontally and proceed with the analysis. The analysis includes Sensitometry (estimating the effective beam energy), HU values and linearity, Low Contrast Visibility (using LDPE & Polystyrene), Contrast Scale, Geometric Accuracy, Slice Thickness Accuracy, Spatial resolution (giving the MTF using the line pairs as well as the point spread function), CNR, Low Contrast Detectability (including the raw data), Uniformity (including the Cupping Effect). Conclusion: This is a robust tool that analyzes more components of the CatPhan than other software options (with the exception of ImageOwl). It produces an elegant pdf and keeps a log of analyses for long-term tracking of the system. Because it is open source, users are able to customize any component of it.

60 APPLIED LIFE SCIENCES↗

Implementation of Remote 3-Dimensional Image Guided Radiation Therapy Quality Assurance for Radiation Therapy Oncology Group Clinical Trials

Purpose: To report the process and initial experience of remote credentialing of three-dimensional (3D) image guided radiation therapy (IGRT) as part of the quality assurance (QA) of submitted data for Radiation Therapy Oncology Group (RTOG) clinical trials; and to identify major issues resulting from this process and analyze the review results on patient positioning shifts. Methods and Materials: Image guided radiation therapy datasets including in-room positioning CT scans and daily shifts applied were submitted through the Image Guided Therapy QA Center from institutions for the IGRT credentialing process, as required by various RTOG trials. A centralized virtual environment is established at the RTOG Core Laboratory, containing analysis tools and database infrastructure for remote review by the Physics Principal Investigators of each protocol. The appropriateness of IGRT technique and volumetric image registration accuracy were evaluated. Registration accuracy was verified by repeat registration with a third-party registration software system. With the accumulated review results, registration differences between those obtained by the Physics Principal Investigators and from the institutions were analyzed for different imaging sites, shift directions, and imaging modalities. Results: The remote review process was successfully carried out for 87 3D cases (out of 137 total cases, including 2-dimensional and 3D) during 2010. Frequent errors in submitted IGRT data and challenges in the review of image registration for some special cases were identified. Workarounds for these issues were developed. The average differences of registration results between reviewers and institutions ranged between 2 mm and 3 mm. Large discrepancies in the superior-inferior direction were found for megavoltage CT cases, owing to low spatial resolution in this direction for most megavoltage CT cases. Conclusion: This first experience indicated that remote review for 3D IGRT as part of QA for RTOG clinical trials is feasible and effective. The magnitude of registration discrepancy between institution and reviewer was presented, and the major issues were investigated to further improve this remote evaluation process.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-E-J-117: Verification Method for the Detection Accuracy of Automatic Winston Lutz Test

Purpose: Winston Lutz test (WLT) has been a standard QA procedure performed prior to SRS treatment, to verify the mechanical iso-center setup accuracy upon different Gantry/Couch movements. Several detection algorithms exist,for analyzing the ball-radiation field alignment automatically. However, the accuracy of these algorithms have not been fully addressed. Here, we reveal the possible errors arise from each step in WLT, and verify the software detection accuracy with the Rectilinear Phantom Pointer (RLPP), a tool commonly used for aligning treatment plan coordinate with mechanical iso-center. Methods: WLT was performed with the radio-opaque ball mounted on a MIS and irradiated onto EDR2 films. The films were scanned and processed with an in-house Matlab program for automatic iso-center detection. Tests were also performed to identify the errors arise from setup, film development and scanning process. The radioopaque ball was then mounted onto the RLPP, and offset laterally and longitudinally in 7 known positions ( 0, ±0.2, ±0.5, ±0.8 mm) manually for irradiations. The gantry and couch was set to zero degree for all irradiation. The same scanned images were processed repeatedly to check the repeatability of the software. Results: Miminal discrepancies (mean=0.05mm) were detected with 2 films overlapped and irradiated but developed separately. This reveals the error arise from film processor and scanner alone. Maximum setup errors were found to be around 0.2mm, by analyzing data collected from 10 irradiations over 2 months. For the known shift introduced using the RLPP, the results agree with the manual offset, and fit linearly (R{sup 2}>0.99) when plotted relative to the first ball with zero shift. Conclusion: We systematically reveal the possible errors arise from each step in WLT, and introduce a simple method to verify the detection accuracy of our in-house software using a clinically available tool.

60 APPLIED LIFE SCIENCES↗

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↗

Adorym: a multi-platform generic X-ray image reconstruction framework based on automatic differentiation

We describe and demonstrate an optimization-based X-ray image reconstruction framework called Adorym. Our framework provides a generic forward model, allowing one code framework to be used for a wide range of imaging methods ranging from near-field holography to fly-scan ptychographic tomography. By using automatic differentiation for optimization, Adorym has the flexibility to refine experimental parameters including probe positions, multiple hologram alignment, and object tilts. It is written with strong support for parallel processing, allowing large datasets to be processed on high-performance computing systems. We demonstrate its use on several experimental datasets to show improved image quality through parameter refinement.

36 MATERIALS SCIENCE↗