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At least 883 records · Page 49
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DOE OSTI2016

Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction

Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated accelerated FISTAs for use with two nonsmooth penalty functions that will lead to further reductions in image reconstruction times while preserving image quality. Moreover, with the help of a mixed sparsity-regularization, better preservation of soft-tissue structures can be potentially obtained. The algorithms were systematically evaluated by use of computer-simulated and clinical data sets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A model-based scatter artifacts correction for cone beam CT

Purpose: Due to the increased axial coverage of multislice computed tomography (CT) and the introduction of flat detectors, the size of x-ray illumination fields has grown dramatically, causing an increase in scatter radiation. For CT imaging, scatter is a significant issue that introduces shading artifact, streaks, as well as reduced contrast and Hounsfield Units (HU) accuracy. The purpose of this work is to provide a fast and accurate scatter artifacts correction algorithm for cone beam CT (CBCT) imaging. Methods: The method starts with an estimation of coarse scatter profiles for a set of CBCT data in either image domain or projection domain. A denoising algorithm designed specifically for Poisson signals is then applied to derive the final scatter distribution. Qualitative and quantitative evaluations using thorax and abdomen phantoms with Monte Carlo (MC) simulations, experimental Catphan phantom data, and in vivo human data acquired for a clinical image guided radiation therapy were performed. Scatter correction in both projection domain and image domain was conducted and the influences of segmentation method, mismatched attenuation coefficients, and spectrum model as well as parameter selection were also investigated. Results: Results show that the proposed algorithm can significantly reduce scatter artifacts and recover the correct HU in either projection domain or image domain. For the MC thorax phantom study, four-components segmentation yields the best results, while the results of three-components segmentation are still acceptable. The parameters (iteration number K and weight β) affect the accuracy of the scatter correction and the results get improved as K and β increase. It was found that variations in attenuation coefficient accuracies only slightly impact the performance of the proposed processing. For the Catphan phantom data, the mean value over all pixels in the residual image is reduced from −21.8 to −0.2 HU and 0.7 HU for projection domain and image domain, respectively. The contrast of the in vivo human images is greatly improved after correction. Conclusions: The software-based technique has a number of advantages, such as high computational efficiency and accuracy, and the capability of performing scatter correction without modifying the clinical workflow (i.e., no extra scan/measurement data are needed) or modifying the imaging hardware. When implemented practically, this should improve the accuracy of CBCT image quantitation and significantly impact CBCT-based interventional procedures and adaptive radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-C-202-03: A Tool for Automatic Calculation of Delivered Dose Variation for Off-Line Adaptive Therapy Using Cone Beam CT

Purpose: Monitoring the delivered dose is an important task for the adaptive radiotherapy (ART) and for determining time to re-plan. A software tool which enables automatic delivered dose calculation using cone-beam CT (CBCT) has been developed and tested. Methods: The tool consists of four components: a CBCT Colleting Module (CCM), a Plan Registration Moduel (PRM), a Dose Calculation Module (DCM), and an Evaluation and Action Module (EAM). The CCM is triggered periodically (e.g. every 1:00 AM) to search for newly acquired CBCTs of patients of interest and then export the DICOM files of the images and related registrations defined in ARIA followed by triggering the PRM. The PRM imports the DICOM images and registrations, links the CBCTs to the related treatment plan of the patient in the planning system (RayStation V4.5, RaySearch, Stockholm, Sweden). A pre-determined CT-to-density table is automatically generated for dose calculation. Current version of the DCM uses a rigid registration which regards the treatment isocenter of the CBCT to be the isocenter of the treatment plan. Then it starts the dose calculation automatically. The AEM evaluates the plan using pre-determined plan evaluation parameters: PTV dose-volume metrics and critical organ doses. The tool has been tested for 10 patients. Results: Automatic plans are generated and saved in the order of the treatment dates of the Adaptive Planning module of the RayStation planning system, without any manual intervention. Once the CTV dose deviates more than 3%, both email and page alerts are sent to the physician and the physicist of the patient so that one can look the case closely. Conclusion: The tool is capable to perform automatic dose tracking and to alert clinicians when an action is needed. It is clinically useful for off-line adaptive therapy to catch any gross error. Practical way of determining alarming level for OAR is under development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-206-01: Employing a Novel Consensus Optimization Strategy to Achieve Iterative Cone Beam CT Reconstruction On a Multi-GPU Platform

Purpose: While compressed sensing-based cone-beam CT (CBCT) iterative reconstruction techniques have demonstrated tremendous capability of reconstructing high-quality images from undersampled noisy data, its long computation time still hinders wide application in routine clinic. The purpose of this study is to develop a reconstruction framework that employs modern consensus optimization techniques to achieve CBCT reconstruction on a multi-GPU platform for improved computational efficiency. Methods: Total projection data were evenly distributed to multiple GPUs. Each GPU performed reconstruction using its own projection data with a conventional total variation regularization approach to ensure image quality. In addition, the solutions from GPUs were subject to a consistency constraint that they should be identical. We solved the optimization problem with all the constraints considered rigorously using an alternating direction method of multipliers (ADMM) algorithm. The reconstruction framework was implemented using OpenCL on a platform with two Nvidia GTX590 GPU cards, each with two GPUs. We studied the performance of our method and demonstrated its advantages through a simulation case with a NCAT phantom and an experimental case with a Catphan phantom. Result: Compared with the CBCT images reconstructed using conventional FDK method with full projection datasets, our proposed method achieved comparable image quality with about one third projection numbers. The computation time on the multi-GPU platform was ∼55 s and ∼ 35 s in the two cases respectively, achieving a speedup factor of ∼ 3.0 compared with single GPU reconstruction. Conclusion: We have developed a consensus ADMM-based CBCT reconstruction method which enabled performing reconstruction on a multi-GPU platform. The achieved efficiency made this method clinically attractive.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-206-02: Evaluation of Partial Storage of the System Matrix for Cone Beam Computed Tomography Using a GPU Platform

Purpose: Iterative reconstruction algorithms in computed tomography (CT) require a fast method for computing the intersections between the photons’ trajectories and the object, also called ray-tracing or system matrix computation. This work evaluates different ways to store the system matrix, aiming to reconstruct dense image grids in reasonable time. Methods: We propose an optimized implementation of the Siddon’s algorithm using graphics processing units (GPUs) with a novel data storage scheme. The algorithm computes a part of the system matrix on demand, typically, for one projection angle. The proposed method was enhanced with accelerating options: storage of larger subsets of the system matrix, systematic reuse of data via geometric symmetries, an arithmetic-rich parallel code and code configuration via machine learning. It was tested on geometries mimicking a cone beam CT acquisition of a human head. To realistically assess the execution time, the ray-tracing routines were integrated into a regularized Poisson-based reconstruction algorithm. The proposed scheme was also compared to a different approach, where the system matrix is fully pre-computed and loaded at reconstruction time. Results: Fast ray-tracing of realistic acquisition geometries, which often lack spatial symmetry properties, was enabled via the proposed method. Ray-tracing interleaved with projection and backprojection operations required significant additional time. In most cases, ray-tracing was shown to use about 66 % of the total reconstruction time. In absolute terms, tracing times varied from 3.6 s to 7.5 min, depending on the problem size. The presence of geometrical symmetries allowed for non-negligible ray-tracing and reconstruction time reduction. Arithmetic-rich parallel code and machine learning permitted a modest reconstruction time reduction, in the order of 1 %. Conclusion: Partial system matrix storage permitted the reconstruction of higher 3D image grid sizes and larger projection datasets at the cost of additional time, when compared to the fully pre-computed approach. This work was supported in part by the Fonds de recherche du Quebec - Nature et technologies (FRQ-NT). The authors acknowledge partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council of Canada (Grant No. 432290).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT

Purpose: Total Variation (TV) based iterative reconstruction (IR) methods enable accurate CT image reconstruction from low-dose measurements with sparse projection acquisition, due to the sparsifiable feature of most CT images using gradient operator. However, conventional solutions require large amount of iterations to generate a decent reconstructed image. One major reason is that the expected piecewise constant property is not taken into consideration at the optimization starting point. In this work, we propose an iterative reconstruction method for cone-beam CT (CBCT) using image segmentation to guide the optimization path more efficiently on the regularization term at the beginning of the optimization trajectory. Methods: Our method applies general knowledge that one tissue component in the CT image contains relatively uniform distribution of CT number. This general knowledge is incorporated into the proposed reconstruction using image segmentation technique to generate the piecewise constant template on the first-pass low-quality CT image reconstructed using analytical algorithm. The template image is applied as an initial value into the optimization process. Results: The proposed method is evaluated on the Shepp-Logan phantom of low and high noise levels, and a head patient. The number of iterations is reduced by overall 40%. Moreover, our proposed method tends to generate a smoother reconstructed image with the same TV value. Conclusion: We propose a computationally efficient iterative reconstruction method for CBCT imaging. Our method achieves a better optimization trajectory and a faster convergence behavior. It does not rely on prior information and can be readily incorporated into existing iterative reconstruction framework. Our method is thus practical and attractive as a general solution to CBCT iterative reconstruction. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-206-06: Task-Specific Optimization of Scintillator Thickness for CMOS-Detector Based Cone-Beam Breast CT

Purpose: To optimize the cesium iodide (CsI:Tl) scintillator thickness in a complimentary metal-oxide semiconductor (CMOS)-based detector for use in dedicated cone-beam breast CT. Methods: The imaging task considered was the detection of a microcalcification cluster comprising six 220µm diameter calcium carbonate spheres, arranged in the form of a regular pentagon with 2 mm spacing on its sides and a central calcification, similar to that in ACR-recommended mammography accreditation phantom, at a mean glandular dose of 4.5 mGy. Generalized parallel-cascades based linear systems analysis was used to determine Fourier-domain image quality metrics in reconstructed object space, from which the detectability index inclusive of anatomical noise was determined for a non-prewhitening numerical observer. For 300 projections over 2π, magnification-associated focal-spot blur, Monte Carlo derived x-ray scatter, K-fluorescent emission and reabsorption within CsI:Tl, CsI:Tl quantum efficiency and optical blur, fiberoptic plate transmission efficiency and blur, CMOS quantum efficiency, pixel aperture function and additive noise, and filtered back-projection to isotropic 105µm voxel pitch with bilinear interpolation were modeled. Imaging geometry of a clinical prototype breast CT system, a 60 kV Cu/Al filtered x-ray spectrum from 0.3 mm focal spot incident on a 14 cm diameter semi-ellipsoidal breast were used to determine the detectability index for 300–600 µm thick (75µm increments) CsI:Tl. The CsI:Tl thickness that maximized the detectability index was considered optimal. Results: The limiting resolution (10% modulation transfer function, MTF) progressively decreased with increasing CsI:Tl thickness. The zero-frequency detective quantum efficiency, DQE(0), in projection space increased with increasing CsI:Tl thickness. The maximum detectability index was achieved with 525µm thick CsI:Tl scintillator. Reduced MTF at mid-to-high frequencies for 600µm thick CsI:Tl lowered the detectability index than 525µm CsI:Tl. Conclusion: For the x-ray spectrum and imaging conditions considered, a 525µm thick CsI:Tl scintillator integrated with the CMOS detector is optimal for detecting microcalcification cluster. Funding support: Supported in part by NIH R01 CA195512. The contents are solely the responsibility of the authors and do not reflect the official views of the NIH or the NCI. Disclosures: SV, GV and AK - Research collaboration, Koning Corp., West Henrietta, NY.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-I-03: Correction of Intra-Fractional Set-Up Errors and Target Coverage Based On Cone-Beam Computed Tomography for Cervical Cancer Patients

Purpose: The purpose of this study is to investigate the patient set-up error and interfraction target coverage in cervical cancer using image-guided adaptive radiotherapy (IGART) with cone-beam computed tomography (CBCT). Methods: Twenty cervical cancer patients undergoing intensity modulated radiotherapy (IMRT) were randomly selected. All patients were matched to the isocenter using laser with the skin markers. Three dimensional CBCT projections were acquired by the Varian Truebeam treatment system. Set-up errors were evaluated by radiation oncologists, after CBCT correction. The clinical target volume (CTV) was delineated on each CBCT, and the planning target volume (PTV) coverage of each CBCT-CTVs was analyzed. Results: A total of 152 CBCT scans were acquired from twenty cervical cancer patients, the mean set-up errors in the longitudinal, vertical, and lateral direction were 3.57, 2.74 and 2.5mm respectively, without CBCT corrections. After corrections, these were decreased to 1.83, 1.44 and 0.97mm. For the target coverage, CBCT-CTV coverage without CBCT correction was 94% (143/152), and 98% (149/152) with correction. Conclusion: Use of CBCT verfication to measure patient setup errors could be applied to improve the treatment accuracy. In addition, the set-up error corrections significantly improve the CTV coverage for cervical cancer patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-14: Kilovoltage Cone-Beam CT Dose Estimation of Varian On-Board Imager Using GMctdospp Monte Carlo Framework

Purpose: Although cone-beam CT (CBCT) imaging became popular in radiation oncology, its imaging dose estimation is still challenging. The goal of this study is to assess the kilovoltage CBCT doses using GMctdospp - an EGSnrc based Monte Carlo (MC) framework. Methods: Two Varian OBI x-ray tube models were implemented in the GMctpdospp framework of EGSnrc MC System. The x-ray spectrum of 125 kVp CBCT beam was acquired from an EGSnrc/BEAMnrc simulation and validated with IPEM report 78. Then, the spectrum was utilized as an input spectrum in GMctdospp dose calculations. Both full and half bowtie pre-filters of the OBI system were created by using egs-prism module. The x-ray tube MC models were verified by comparing calculated dosimetric profiles (lateral and depth) to ion chamber measurements for a static x-ray beam irradiation to a cuboid water phantom. An abdominal CBCT imaging doses was simulated in GMctdospp framework using a 5-year-old anthropomorphic phantom. The organ doses and effective dose (ED) from the framework were assessed and compared to the MOSFET measurements and convolution/superposition dose calculations. Results: The lateral and depth dose profiles in the water cuboid phantom were well matched within 6% except a few areas - left shoulder of the half bowtie lateral profile and surface of water phantom. The organ doses and ED from the MC framework were found to be closer to MOSFET measurements and CS calculations within 2 cGy and 5 mSv respectively. Conclusion: This study implemented and validated the Varian OBI x-ray tube models in the GMctdospp MC framework using a cuboid water phantom and CBCT imaging doses were also evaluated in a 5-year-old anthropomorphic phantom. In future study, various CBCT imaging protocols will be implemented and validated and consequently patient CT images will be used to estimate the CBCT imaging doses in patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-40: Evaluation of Sensitivity of the Automatic Matching Between Cone-Beam CT Image and Simulation CT Image in TrueBeam 2.0 Imaging System 6DoF Considering Different Uncertainty Sources

Purpose: To estimate the sensitivity of TrueBeam 2.0 Imaging System 6DoF automatic matching tool through the acquisition of cone-beam CT images in different phantoms applying submillimeter translations and rotations of tenths of a degree and registered with image simulation CT. Methods: To evaluate overall system-wide image, we consider two uncertainties source; First, the uncertainty of the manual phantom displacement (ε-m). This uncertainty is calculated by a digital caliper (0.01 mm) for vertical (Vrt), lateral (Lat) and longitudinal (Lng). A digital inclinometer (0.01°) for the pitch and roll and the own phantom scale to evaluate the coordinate rotation (Rtn). The second uncertainty is the displacement detected by the algorithm system of matching (σ-d) that we obtain from the standard deviations of the different measurements. We use three different phantoms. The BrainLab Radiosurgery system for supporting masks with an anthropomorphic dummy adapted to allow displacements of 0.1 mm in Vrt, Lat and Lng dimensions and rotations of 0.1° in Pitch dimension. For the analysis of the Rtn and Roll dimensions we use two homemade phantoms (RinoRot and RinoRoll, La Fe Hospital, Valencia, Spain) that allow rotations of 0.3°. Results: In the case of manual displacement of 0.10 ± 0.03 mm in the translations, the system detect 0.10 ± 0.07 mm, 0.12 ± 0.07 mm and 0.13 ± 0.07 mm (mean ± SD) in Lat, Vrt and Lng respectively. In the case of rotational dimension, manual displacement of 0.3 ± 0.1° was detected with 0.19 ± 0.06°, 0.29 ± 0.03° and 0.27 ± 0.06° in Pitch, Roll and Rtn. Conclusion: We conclude that the sensitivity of the automatic matching system is within 0.10 mm in translations and 0.3° in rotations. These values are under the own sensitivity of the software.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-42: Comparison of Varian TrueBeam Cone-Beam CT and BrainLab ExacTrac X-Ray for Cranial Radiotherapy

Purpose: To compare online image registrations of TrueBeam cone-beam CT (CBCT) and BrainLab ExacTrac x-ray imaging systems for cranial radiotherapy. Method: Phantom and patient studies were performed on a Varian TrueBeam STx linear accelerator (Version 2.5), which is integrated with a BrainLab ExacTrac imaging system (Version 6.1.1). The phantom study was based on a Rando head phantom, which was designed to evaluate isocenter-location dependence of the image registrations. Ten isocenters were selected at various locations in the phantom, which represented clinical treatment sites. CBCT and ExacTrac x-ray images were taken when the phantom was located at each isocenter. The patient study included thirteen patients. CBCT and ExacTrac x-ray images were taken at each patient’s treatment position. Six-dimensional image registrations were performed on CBCT and ExacTrac, and residual errors calculated from CBCT and ExacTrac were compared. Results: In the phantom study, the average residual-error differences between CBCT and ExacTrac image registrations were: 0.16±0.10 mm, 0.35±0.20 mm, and 0.21±0.15 mm, in the vertical, longitudinal, and lateral directions, respectively. The average residual-error differences in the rotation, roll, and pitch were: 0.36±0.11 degree, 0.14±0.10 degree, and 0.12±0.10 degree, respectively. In the patient study, the average residual-error differences in the vertical, longitudinal, and lateral directions were: 0.13±0.13 mm, 0.37±0.21 mm, 0.22±0.17 mm, respectively. The average residual-error differences in the rotation, roll, and pitch were: 0.30±0.10 degree, 0.18±0.11 degree, and 0.22±0.13 degree, respectively. Larger residual-error differences (up to 0.79 mm) were observed in the longitudinal direction in the phantom and patient studies where isocenters were located in or close to frontal lobes, i.e., located superficially. Conclusion: Overall, the average residual-error differences were within 0.4 mm in the translational directions and were within 0.4 degree in the rotational directions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-47: Inherent Uncertainty in the Positional Shifts Determined by a Volumetric Cone Beam Imaging System

Purpose: To quantify inherent uncertainty associated with a volumetric imaging system in its determination of positional shifts. Methods: The study was performed on an Elekta Axesse™ linac’s XVI cone beam computed tomography (CBCT) system. A CT image data set of a Penta- Guide phantom was used as reference image by placing isocenter at the center of the phantom.The phantom was placed arbitrarily on the couch close to isocenter and CBCT images were obtained. The CBCT dataset was matched with the reference image using XVI software and the shifts were determined in 6-dimensions. Without moving the phantom, this process was repeated 20 times consecutively within 30 minutes on a single day. Mean shifts and their standard deviations in all 6-dimensions were determined for all the 20 instances of imaging. For any given day, the first set of shifts obtained was kept as reference and the deviations of the subsequent 19 sets from the reference set were scored. Mean differences and their standard deviations were determined. In this way, data were obtained for 30 consecutive working days. Results: Tabulating the mean deviations and their standard deviations observed on each day for the 30 measurement days, systematic and random errors in the determination of shifts by XVI software were calculated. The systematic errors were found to be 0.03, 0.04 and 0.03 mm while random errors were 0.05, 0.06 and 0.06 mm in lateral, craniocaudal and anterio-posterior directions respectively. For rotational shifts, the systematic errors were 0.02°, 0.03° and 0.03° and random errors were 0.06°, 0.05° and 0.05° in pitch, roll and yaw directions respectively. Conclusion: The inherent uncertainties in every image guidance system should be assessed and baseline values established at the time of its commissioning. These shall be periodically tested as part of the QA protocol.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-77: Variations in the Displacement Vector Fields Calculated by Different Deformable Image Registration Algorithms Used in Helical, Axial and Cone-Beam CT Images of a Mobile

Purpose: To investigate quantitatively the displacement-vector-fields (DVF) obtained from different deformable image registration algorithms (DIR) in helical (HCT), axial (ACT) and cone-beam CT (CBCT) to register CT images of a mobile phantom and its correlation with motion amplitudes and frequencies. Methods: HCT, ACT and CBCT are used to image a mobile phantom which includes three targets with different sizes that are manufactured from water-equivalent material and embedded in low density foam. The phantom is moved with controlled motion patterns where a range of motion amplitudes (0–40mm) and frequencies (0.125–0.5Hz) are used. The CT images obtained from scanning of the mobile phantom are registered with the stationary CT-images using four deformable image registration algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from DIRART software. Results: The DVF calculated by the different algorithms correlate well with the motion amplitudes that are applied on the mobile phantom where maximal DVF increase linearly with the motion amplitudes of the mobile phantom in CBCT. Similarly in HCT, DVF increase linearly with motion amplitude, however, its correlation is weaker than CBCT. In ACT, the DVF’s do not correlate well with the motion amplitudes where motion induces strong image artifacts and DIR algorithms are not able to deform the ACT image of the mobile targets to the stationary targets. Three DIR-algorithms produce comparable values and patterns of the DVF for certain CT imaging modality. However, DVF from fast-demons deviated strongly from other algorithms at large motion amplitudes. Conclusion: In CBCT and HCT, the DVF correlate well with the motion amplitude of the mobile phantom. However, in ACT, DVF do not correlate with motion amplitudes. Correlations of DVF with motion amplitude as in CBCT and HCT imaging techniques can provide information about unknown motion parameters of the mobile organs in real patients as demonstrated in this phantom visibility study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-81: Evaluation of Automated Deformable Registration Between Planning Computed Tomography (CT) and Daily Cone Beam CT Images Over the Course of Prostate Cancer Radiotherapy

Purpose: To compute daily dose delivered during radiotherapy, deformable registration needs to be relatively fast, automated, and accurate. The aim of this study was to evaluate the performance of commercial deformable registration software for deforming between two modalities: planning computed tomography (pCT) images acquired for treatment planning and cone beam (CB) CT images acquired prior to each fraction of prostate cancer radiotherapy. Methods: A workflow was designed using MIM Software™ that aligned and deformed pCT into daily CBCT images in two steps: (1) rigid shifts applied after daily CBCT imaging to align patient anatomy to the pCT and (2) normalized intensity-based deformable registration to account for interfractional anatomical variations. The physician-approved CTV and organ and risk (OAR) contours were deformed from the pCT to daily CBCT over the course of treatment. The same structures were delineated on each daily CBCT by a radiation oncologist. Dice similarity coefficient (DSC) mean and standard deviations were calculated to quantify the deformable registration quality for prostate, bladder, rectum and femoral heads. Results: To date, contour comparisons have been analyzed for 31 daily fractions of 2 of 10 of the cohort. Interim analysis shows that right and left femoral head contours demonstrate the highest agreement (DSC: 0.96±0.02) with physician contours. Additionally, deformed bladder (DSC: 0.81±0.09) and prostate (DSC: 0.80±0.07) have good agreement with physician-defined daily contours. Rectum contours have the highest variations (DSC: 0.66±0.10) between the deformed and physician-defined contours on daily CBCT imaging. Conclusion: For structures with relatively high contrast boundaries on CBCT, the MIM automated deformable registration provided accurate representations of the daily contours during treatment delivery. These findings will permit subsequent investigations to automate daily dose computation from CBCT. However, improved methods need to be investigated to improve deformable results for rectum contours.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-148: A Collapsed Cone Algorithm Can Be Used for Quality Assurance for Monaco Treatment Plans for the MR-Linac

Purpose: Treatment plans for the MR-linac, calculated in Monaco v5.19, include direct simulation of the effects of the 1.5T B{sub 0}-field. We tested the feasibility of using a collapsed-cone (CC) algorithm in Oncentra, which does not account for effects of the B{sub 0}-field, as a fast online, independent 3D check of dose calculations. Methods: Treatment plans for six patients were generated in Monaco with a 6 MV FFF beam and the B{sub 0}-field. All plans were recalculated with a CC model of the same beam. Plans for the same patients were also generated in Monaco without the B{sub 0}-field. The mean dose (Dmean) and doses to 10% (D10%) and 90% (D90%) of the volume were determined, as percentages of the prescribed dose, for target volumes and OARs in each calculated dose distribution. Student’s t-tests between paired parameters from Monaco plans and corresponding CC calculations were performed. Results: Figure 1 shows an example of the difference between dose distributions calculated in Monaco, with the B{sub 0}-field, and the CC algorithm. Figure 2 shows distributions of (absolute) difference between parameters for Monaco plans, with the B{sub 0}-field, and CC calculations. The Dmean and D90% values for the CTVs and PTVs were significantly different, but differences in dose distributions arose predominantly at the edges of the target volumes. Inclusion of the B{sub 0}-field had little effect on agreement of the Dmean values, as illustrated by Figure 3, nor on agreement of the D10% and D90% values. Conclusion: Dose distributions recalculated with a CC algorithm show good agreement with those calculated with Monaco, for plans both with and without the B{sub 0}-field, indicating that the CC algorithm could be used to check online treatment planning for the MRlinac. Agreement for a wider range of treatment sites, and the feasibility of using the γ-test as a simple pass/fail criterion, will be investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-211: Scatter Correction for Clinical Cone-Beam CT System Using An Optimized Stationary Beam Blocker with a Single Scan

Purpose: X-ray scatter photons result in significant image quality degradation of cone-beam CT (CBCT). Measurement based algorithms using beam blocker directly acquire the scatter samples and achieve significant improvement on the quality of CBCT image. Within existing algorithms, single-scan and stationary beam blocker proposed previously is promising due to its simplicity and practicability. Although demonstrated effectively on tabletop system, the blocker fails to estimate the scatter distribution on clinical CBCT system mainly due to the gantry wobble. In addition, the uniform distributed blocker strips in our previous design results in primary data loss in the CBCT system and leads to the image artifacts due to data insufficiency. Methods: We investigate the motion behavior of the beam blocker in each projection and design an optimized non-uniform blocker strip distribution which accounts for the data insufficiency issue. An accurate scatter estimation is then achieved from the wobble modeling. Blocker wobble curve is estimated using threshold-based segmentation algorithms in each projection. In the blocker design optimization, the quality of final image is quantified using the number of the primary data loss voxels and the mesh adaptive direct search algorithm is applied to minimize the objective function. Scatter-corrected CT images are obtained using the optimized blocker. Results: The proposed method is evaluated using Catphan@504 phantom and a head patient. On the Catphan©504, our approach reduces the average CT number error from 115 Hounsfield unit (HU) to 11 HU in the selected regions of interest, and improves the image contrast by a factor of 1.45 in the high-contrast regions. On the head patient, the CT number error is reduced from 97 HU to 6 HU in the soft tissue region and image spatial non-uniformity is decreased from 27% to 5% after correction. Conclusion: The proposed optimized blocker design is practical and attractive for CBCT guided radiation therapy. This work is supported by grants from Guangdong Innovative Research Team Program of China (Grant No. 2011S013), National 863 Programs of China (Grant Nos. 2012AA02A604 and 2015AA043203), the National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-212: Enabling Conventional Cone Beam CT with the Capability of Dual Energy Imaging Using a Simple Add-On Beam Modifier

Purpose: In searching for a robust, efficient and cost-effective dual energy cone beam CT (DECBCT) solution for various radiation oncology applications, in particularly for improved proton dose planning/replanning accuracy and DE-CBCT guided radiation therapy, we investigate a novel energy modulation scheme using a beam modifier placed between the source and patient and optimize its geometric configuration for routine clinical use. Methods: The study was performed using a Hitachi CBCT scanner and the tube voltage was set at 125 kVp. The higher energy beam was obtained by filtering the incident utilizing a beam modulation layer (material: copper, thickness: 1.8 mm). To avoid the need for double scans (one with and one without the energy modulator), the modulation layer was configured to cover only the half of the X-ray beam so that two sets of sinograms corresponding low and high energies were collected after a single gantry rotation of 360 deg. The average high energy and low energy HU numbers (HUhigh and HUlow) were derived for pixels in a defined region-of-interest, respectively. Results: The beam modifier increased the threshold of the energy spectrum from ∼20 keV up to ∼50 keV. Two complete sets of images were obtained with good alignment between the high energy and low-energy cases without any artifact observed (Fig. 2). The HUlow/HUhigh is ∼0/0 (water), ∼394/238 (brain), ∼1283/1085 (cortical bone) and ∼3000/1800 (titanium). Conclusion: The feasibility of the proposed DECT implementation using a beam modifier has been demonstrated. Compared to the existing DECT solutions, the proposed scheme is much more cost-effective and requires minimum hardware modification. The work lays foundation for us to study the quantification of HU values to derive material density images and atomic number (and electron density) of substances.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-191: 4D Dose Reconstruction of Intensity Modulated Proton Therapy (IMPT) Based On Breathing Probability Density Function (PDF) From 4D Cone Beam Projection Images: A Study for Lung Treatment

Purpose: With energy repainting in lung IMPT, the dose delivered is approximate to the convolution of dose in each phase with corresponding breathing PDF. This study is to compute breathing PDF weighted 4D dose in lung IMPT treatment and compare to its initial robust plan. Methods: Six lung patients were evaluated in this study. Amsterdam shroud image were generated from pre-treatment 4D cone-beam projections. Diaphragm motion curve was extract from the shroud image and the breathing PDF was generated. Each patient was planned to 60 Gy (12GyX5). In initial plans, ITV density on average CT was overridden with its maximum value for planning, using two IMPT beams with robust optimization (5mm uncertainty in patient position and 3.5% range uncertainty). The plan was applied to all 4D CT phases. The dose in each phase was deformed to a reference phase. 4D dose is reconstructed by summing all these doses based on corresponding weighting from the PDF. Plan parameters, including maximum dose (Dmax), ITV V100, homogeneity index (HI=D2/D98), R50 (50%IDL/ITV), and the lung-GTV’s V12.5 and V5 were compared between the reconstructed 4D dose to initial plans. Results: The Dmax is significantly less dose in the reconstructed 4D dose, 68.12±3.5Gy, vs. 70.1±4.3Gy in the initial plans (p=0.015). No significant difference is found for the ITV V100, HI, and R50, 92.2%±15.4% vs. 96.3%±2.5% (p=0.565), 1.033±0.016 vs. 1.038±0.017 (p=0.548), 19.2±12.1 vs. 18.1±11.6 (p=0.265), for the 4D dose and initial plans, respectively. The lung-GTV V12.5 and V5 are significantly high in the 4D dose, 13.9%±4.8% vs. 13.0%±4.6% (p=0.021) and 17.6%±5.4% vs. 16.9%±5.2% (p=0.011), respectively. Conclusion: 4D dose reconstruction based on phase PDF can be used to evaluate the dose received by the patient. A robust optimization based on the phase PDF may even further improve patient care.

60 APPLIED LIFE SCIENCES↗