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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-T-141: Automated Dose Point Placement for Cervical Cancer Brachytherapy Using Tandem and Ovoid Applicators

Purpose: To develop a standalone application, which automatically and consistently calculates the coordinates of points A and H based solely on the implanted applicator geometry for cervical cancer HDR brachytherapy. Methods: Manchester point A and ABS point H are both located 2cm lateral from the central tandem plane. While both points are located 2cm above the cervical os, surrogates for the os differ. Point A is defined relative to the anatomical cervical os. Point H is defined relative to the intersection of the tandem with the superior aspects of the ovoids. The application takes an input text file generated by the treatment planning system (TPS, BrachyVision, Varian) that specifies the source geometries. It then outputs the 3D coordinates of points A and H in both the left and right directions. The algorithm was implemented and tested on 34 CT scans of 7 patients treated with HDR brachytherapy delivered using tandem and ovoids. A single experienced user retrospectively and manually placed points A and H on the CT scans, whose coordinates were used as the gold standard for the comparison to the automatically calculated points. Results: The automatically calculated coordinates of points A and H agree within 0.7mm with the gold standard. The averages and standard deviations of the 3D coordinate difference between points placed by the two methods are 0.3±0.1 and 0.4±0.1mm for points A and H, respectively. The maximum difference in 3D magnitude is 0.7mm. Conclusion: The algorithm consistently calculates dose point coordinates independently of the planner for cervical cancer brachytherapy treated with tandem and ovoids. Automated point placement based on the geometry of the implanted applicators agrees in sub-millimeter with careful manual placements by an experienced user. This algorithm expedites the planning process and eliminates dependencies on either user input or TPS visualization tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-436: Fluence-Based Trajectory Optimization for Non-Coplanar VMAT

Purpose: To investigate a fluence-based trajectory optimization technique for non-coplanar VMAT for brain cancer. Methods: Single-arc non-coplanar VMAT trajectories were determined using a heuristic technique for five patients. Organ at risk (OAR) volume intersected during raytracing was minimized for two cases: absolute volume and the sum of relative volumes weighted by OAR importance. These trajectories and coplanar VMAT formed starting points for the fluence-based optimization method. Iterative least squares optimization was performed on control points 24° apart in gantry rotation. Optimization minimized the root-mean-square (RMS) deviation of PTV dose from the prescription (relative importance 100), maximum dose to the brainstem (10), optic chiasm (5), globes (5) and optic nerves (5), plus mean dose to the lenses (5), hippocampi (3), temporal lobes (2), cochleae (1) and brain excluding other regions of interest (1). Control point couch rotations were varied in steps of up to 10° and accepted if the cost function improved. Final treatment plans were optimized with the same objectives in an in-house planning system and evaluated using a composite metric - the sum of optimization metrics weighted by importance. Results: The composite metric decreased with fluence-based optimization in 14 of the 15 plans. In the remaining case its overall value, and the PTV and OAR components, were unchanged but the balance of OAR sparing differed. PTV RMS deviation was improved in 13 cases and unchanged in two. The OAR component was reduced in 13 plans. In one case the OAR component increased but the composite metric decreased - a 4 Gy increase in OAR metrics was balanced by a reduction in PTV RMS deviation from 2.8% to 2.6%. Conclusion: Fluence-based trajectory optimization improved plan quality as defined by the composite metric. While dose differences were case specific, fluence-based optimization improved both PTV and OAR dosimetry in 80% of cases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-AB-303-03: A Scheme for Real-Time, Marker-Less and Low-Dose Tumor Tracking Using Scattering Imaging: Monte Carlo Simulation Study

Purpose: In-treatment tumor localization is critical for the management of tumor motion in lung cancer radiotherapy. Conventional tumor-tracking methods using a kV or MV x-ray projection has limited contrast. To facilitate real-time, marker-less and low-dose in-treatment image tumor tracking, we propose a novel scheme using Compton scatter imaging. This study reports Monte Carlo (MC) simulations on this scheme for the purpose of proof-of-principle. Methods: A slit x-ray beam along the patient superior-inferior (SI) direction is directed to the patient, intersecting the patient lung at a 2D plane containing majority part of the tumor motion trajectory. X-ray photons are scattered due to Compton effect from this plane, which are spatially collimated by, e.g., a pinhole, on one side of the plane and then captured by a detector behind it. The captured image, after correcting for x-ray attenuation and scatter angle variation, reflects the electron density, which allows visualization of the instantaneous anatomy on this plane. We performed MC studies on a phantom and a patient case for the initial test of this proposed method. Results: In the phantom case, the contrast-resolution calculated using tumor/lung as foreground/background for kV fluoroscopy, cone-beam CT, and scattering image were 0.0625, 0.6993, and 0.5290, respectively. In the patient case, tumor motion can be clearly observed in the scatter images. Compared to fluoroscopy, scattering imaging also significantly reduced imaging dose because of its narrower beam design. Conclusion: MC simulation studies demonstrated the potential of the proposed scheme in terms of capturing the instantaneous anatomy of a patient on a 2D plane. Clear visualization of the tumor will probably facilitate ‘marker-less’ and ‘real-time’ tumor tracking with low imaging dose. NIH (1R01CA154747-01, 1R21CA178787-01A1 and 1R21EB017978-01A1)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-G-207-02: Full Sequential Projection Onto Convex Sets (FS-POCS) for X-Ray CT Reconstruction

Purpose: To develop an iterative reconstruction method for X-ray CT, in which the reconstruction can quickly converge to the desired solution with much reduced projection views. Methods: The reconstruction is formulated as a convex feasibility problem, i.e. the solution is an intersection of three convex sets: 1) data fidelity (DF) set – the L2 norm of the difference of observed projections and those from the reconstructed image is no greater than an error bound; 2) non-negativity of image voxels (NN) set; and 3) piecewise constant (PC) set - the total variation (TV) of the reconstructed image is no greater than an upper bound. The solution can be found by applying projection onto convex sets (POCS) sequentially for these three convex sets. Specifically, the algebraic reconstruction technique and setting negative voxels as zero are used for projection onto the DF and NN sets, respectively, while the projection onto the PC set is achieved by solving a standard Rudin, Osher, and Fatemi (ROF) model. The proposed method is named as full sequential POCS (FS-POCS), which is tested using the Shepp-Logan phantom and the Catphan600 phantom and compared with two similar algorithms, TV-POCS and CP-TV. Results: Using the Shepp-Logan phantom, the root mean square error (RMSE) of reconstructed images changing along with the number of iterations is used as the convergence measurement. In general, FS- POCS converges faster than TV-POCS and CP-TV, especially with fewer projection views. FS-POCS can also achieve accurate reconstruction of cone-beam CT of the Catphan600 phantom using only 54 views, comparable to that of FDK using 364 views. Conclusion: We developed an efficient iterative reconstruction for sparse-view CT using full sequential POCS. The simulation and physical phantom data demonstrated the computational efficiency and effectiveness of FS-POCS.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Monte Carlo modeling of ultrasound probes for image guided radiotherapy

Purpose: To build Monte Carlo (MC) models of two ultrasound (US) probes and to quantify the effect of beam attenuation due to the US probes for radiation therapy delivered under real-time US image guidance. Methods: MC models of two Philips US probes, an X6-1 matrix-array transducer and a C5-2 curved-array transducer, were built based on their megavoltage (MV) CT images acquired in a Tomotherapy machine with a 3.5 MV beam in the EGSnrc, BEAMnrc, and DOSXYZnrc codes. Mass densities in the probes were assigned based on an electron density calibration phantom consisting of cylinders with mass densities between 0.2 and 8.0 g/cm{sup 3}. Beam attenuation due to the US probes in horizontal (for both probes) and vertical (for the X6-1 probe) orientation was measured in a solid water phantom for 6 and 15 MV (15 × 15) cm{sup 2} beams with a 2D ionization chamber array and radiographic films at 5 cm depth. The MC models of the US probes were validated by comparison of the measured dose distributions and dose distributions predicted by MC. Attenuation of depth dose in the (15 × 15) cm{sup 2} beams and small circular beams due to the presence of the probes was assessed by means of MC simulations. Results: The 3.5 MV CT number to mass density calibration curve was found to be linear with R{sup 2} > 0.99. The maximum mass densities in the X6-1 and C5-2 probes were found to be 4.8 and 5.2 g/cm{sup 3}, respectively. Dose profile differences between MC simulations and measurements of less than 3% for US probes in horizontal orientation were found, with the exception of the penumbra region. The largest 6% dose difference was observed in dose profiles of the X6-1 probe placed in vertical orientation, which was attributed to inadequate modeling of the probe cable. Gamma analysis of the simulated and measured doses showed that over 96% of measurement points passed the 3%/3 mm criteria for both probes placed in horizontal orientation and for the X6-1 probe in vertical orientation. The X6-1 probe in vertical orientation caused the highest attenuation of the 6 and 15 MV beams, which at 10 cm depth accounted for 33% and 43% decrease compared to the respective (15 × 15) cm{sup 2} open fields. The C5-2 probe in horizontal orientation, on the other hand, caused a dose increase of 10% and 53% for the 6 and 15 MV beams, respectively, in the buildup region at 0.5 cm depth. For the X6-1 probe in vertical orientation, the dose at 5 cm depth for the 3-cm diameter 6 MV and 5-cm diameter 15 MV beams was attenuated compared to the corresponding open fields to a greater degree by 65% and 43%, respectively. Conclusions: MC models of two US probes used for real-time image guidance during radiotherapy have been built. Due to the high beam attenuation of the US probes, the authors generally recommend avoiding delivery of treatment beams that intersect the probe. However, the presented MC models can be effectively integrated into US-guided radiotherapy treatment planning in cases for which beam avoidance is not practical due to anatomy geometry.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

EUD-based biological optimization for carbon ion therapy

Purpose: Treatment planning for carbon ion therapy requires an accurate modeling of the biological response of each tissue to estimate the clinical outcome of a treatment. The relative biological effectiveness (RBE) accounts for this biological response on a cellular level but does not refer to the actual impact on the organ as a whole. For photon therapy, the concept of equivalent uniform dose (EUD) represents a simple model to take the organ response into account, yet so far no formulation of EUD has been reported that is suitable to carbon ion therapy. The authors introduce the concept of an equivalent uniform effect (EUE) that is directly applicable to both ion and photon therapies and exemplarily implemented it as a basis for biological treatment plan optimization for carbon ion therapy. Methods: In addition to a classical EUD concept, which calculates a generalized mean over the RBE-weighted dose distribution, the authors propose the EUE to simplify the optimization process of carbon ion therapy plans. The EUE is defined as the biologically equivalent uniform effect that yields the same probability of injury as the inhomogeneous effect distribution in an organ. Its mathematical formulation is based on the generalized mean effect using an effect-volume parameter to account for different organ architectures and is thus independent of a reference radiation. For both EUD concepts, quadratic and logistic objective functions are implemented into a research treatment planning system. A flexible implementation allows choosing for each structure between biological effect constraints per voxel and EUD constraints per structure. Exemplary treatment plans are calculated for a head-and-neck patient for multiple combinations of objective functions and optimization parameters. Results: Treatment plans optimized using an EUE-based objective function were comparable to those optimized with an RBE-weighted EUD-based approach. In agreement with previous results from photon therapy, the optimization by biological objective functions resulted in slightly superior treatment plans in terms of final EUD for the organs at risk (OARs) compared to voxel-based optimization approaches. This observation was made independent of the underlying objective function metric. An absolute gain in OAR sparing was observed for quadratic objective functions, whereas intersecting DVHs were found for logistic approaches. Even for considerable under- or overestimations of the used effect- or dose–volume parameters during the optimization, treatment plans were obtained that were of similar quality as the results of a voxel-based optimization. Conclusions: EUD-based optimization with either of the presented concepts can successfully be applied to treatment plan optimization. This makes EUE-based optimization for carbon ion therapy a useful tool to optimize more specifically in the sense of biological outcome while voxel-to-voxel variations of the biological effectiveness are still properly accounted for. This may be advantageous in terms of computational cost during treatment plan optimization but also enables a straight forward comparison of different fractionation schemes or treatment modalities.

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-F-R-42: Association of Radiomic and Metabolic Tumor Volumes in Radiation Treatment of Glioblastoma Multiforme

Purpose: High-throughput extraction of imaging and metabolomic quantitative features from MRI and MR Spectroscopy Imaging (MRSI) of Glioblastoma Multiforme (GBM) results in tens of variables per patient. In radiotherapy (RT) of GBM, the relevant metabolic tumor volumes (MTVs) are related to aberrant levels of N-acetyl Aspartate (NAA) and Choline (Cho). Corresponding Clinical Target Volumes (CTVs) for RT planning are based on Contrast Enhancing T1-weighted MRI (CE-T1w) and T2-weighted/Fluid Attenuated Inversion Recovery (FLAIR) MRI. The objective is to build a framework for investigation of associations between imaging, CTV, and MTV features better understanding of the underlying information in the CTVs and dependencies between these volumes. Methods: Necrotic portions, enhancing lesion and edema were manually contoured on T1w/T2w images for 17 GBM patients. CTVs and MTVs for NAA (MTV{sub NAA}) and Cho (MTV{sub Cho}) were constructed. Tumors were scored categorically for ten semantic imaging traits by neuroradiologist. All features were investigated for redundancy. Two-way correlations between imaging and RT/MTV features were visualized as heat maps. Associations between MTV{sub NAA}, MTV{sub Cho} and imaging features were studied using Spearman correlation. Results: 39 imaging features were computed per patient. Half of the imaging traits were replaced with automatically extracted continuous variables. 21 features were extracted from MTVs/CTVs. There were a high number (43) of significant correlations of imaging with CTVs/MTV{sub NAA} while very few (10) significant correlations were with CTVs/MTV{sub Cho}. MTV{sub NAA} was found to be closely associated with MRI volumes, MTV{sub Cho} remains elusive for characterization with imaging. Conclusion: A framework for investigation of co-dependency between MRI and RT/metabolic features is established. A series of semantic imaging traits were replaced with automatically extracted continuous variables. The approach will allow for exploration of relationships between sizes and intersection of imaging features of tumors, RT volumes, metabolite concentrations and comparing those to therapy outcome, quality of life evaluation and overall survival rate. This publication was supported by Grant 10BN03 from Bankhead Coley Cancer Research Program, R01EB000822, R01EB016064, and R01CA172210 from the National Institutes of Health, and Indo-US Science & Technology Forum award #20-2009. Bhaswati Roy received financial assistance from University Grant Commission, New Delhi, India.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-113: Multi-Atlas Based Automatic Organ Segmentation for Lung Radiotherapy Planning

Purpose: Normal organ segmentation is one time-consuming and labor-intensive step for lung radiotherapy treatment planning. The aim of this study is to evaluate the performance of a multi-atlas based segmentation approach for automatic organs at risk (OAR) delineation. Methods: Fifteen Lung stereotactic body radiation therapy patients were randomly selected. Planning CT images and OAR contours of the heart - HT, aorta - AO, vena cava - VC, pulmonary trunk - PT, and esophagus – ES were exported and used as reference and atlas sets. For automatic organ delineation for a given target CT, 1) all atlas sets were deformably warped to the target CT, 2) the deformed sets were accumulated and normalized to produce organ probability density (OPD) maps, and 3) the OPD maps were converted to contours via image thresholding. Optimal threshold for each organ was empirically determined by comparing the auto-segmented contours against their respective reference contours. The delineated results were evaluated by measuring contour similarity metrics: DICE, mean distance (MD), and true detection rate (TD), where DICE=(intersection volume/sum of two volumes) and TD = {1.0 - (false positive + false negative)/2.0}. Diffeomorphic Demons algorithm was employed for CT-CT deformable image registrations. Results: Optimal thresholds were determined to be 0.53 for HT, 0.38 for AO, 0.28 for PT, 0.43 for VC, and 0.31 for ES. The mean similarity metrics (DICE[%], MD[mm], TD[%]) were (88, 3.2, 89) for HT, (79, 3.2, 82) for AO, (75, 2.7, 77) for PT, (68, 3.4, 73) for VC, and (51,2.7, 60) for ES. Conclusion: The investigated multi-atlas based approach produced reliable segmentations for the organs with large and relatively clear boundaries (HT and AO). However, the detection of small and narrow organs with diffused boundaries (ES) were challenging. Sophisticated atlas selection and multi-atlas fusion algorithms may further improve the quality of segmentations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-242: A Method for Collision Avoidance in External Beam Radiation Therapy

Purpose: We proposed a method for collision avoidance (CA) in external beam radiation therapy (EBRT). The method encompasses the analysis of all positions of the moving components of the beam delivery system such as the treatment table and gantry, including patient specific information obtained from the CT images. This method eliminates the need for time-consuming dry-runs prior to the actual treatments. Methods: The QA procedure for EBRT requires that the collision should be checked prior to treatment. We developed a system capable of a rigorous computer simulation of all moving components including positions of the couch and gantry during the delivery, position of the patients, and imaging equipment. By running this treatment simulation it is possible to quantify and graphically represent all positions and corresponding trajectories of all points of the moving parts during the treatment delivery. The development of the workflow for implementation of the CA includes several steps: a) derivation of combined dynamic equation of motion of the EBRT delivery systems, b) developing the simulation model capable of drawing the motion trajectories of the specific points, c) developing the interface between the model and the treatment plan parameters such as couch and gantry parameters for each field. Results: The patient CT images were registered to the treatment couch so the patient dimensions were included into the simulation. The treatment field parameters were structured in the xml-file which was used as the input into the dynamic equations. The trajectories of the moving components were plotted on the same graph using the dynamic equations. If the trajectories intersect that was the signal that collision exists. Conclusion: This CA method was proved to be effective in the simulation of treatment delivery. The proper implementation of this system can potentially improve the QA program and increase the efficacy in the clinical setup.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRC-01: A Data-Driven Pre-Optimization Method for Prediction of Achievability of Clinical Objectives in IMRT

Purpose: We propose a novel data-driven method to predict the achievability of clinical objectives upfront before invoking the IMRT optimization. Methods: A new metric called “Geometric Complexity (GC)” is used to estimate the achievability of clinical objectives. Here, GC is the measure of the number of “unmodulated” beamlets or rays that intersect the Region-of-interest (ROI) and the target volume. We first compute the geometric complexity ratio (GCratio) between the GC of a ROI (say, parotid) in a reference plan and the GC of the same ROI in a given plan. The GCratio of a ROI indicates the relative geometric complexity of the ROI as compared to the same ROI in the reference plan. Hence GCratio can be used to predict if a defined clinical objective associated with the ROI can be met by the optimizer for a given case. Basically a higher GCratio indicates a lesser likelihood for the optimizer to achieve the clinical objective defined for a given ROI. Similarly, a lower GCratio indicates a higher likelihood for the optimizer to achieve the clinical objective defined for the given ROI. We have evaluated the proposed method on four Head and Neck cases using Pinnacle3 (version 9.10.0) Treatment Planning System (TPS). Results: Out of the total of 28 clinical objectives from four head and neck cases included in the study, 25 were in agreement with the prediction, which implies an agreement of about 85% between predicted and obtained results. The Pearson correlation test shows a positive correlation between predicted and obtained results (Correlation = 0.82, r2 = 0.64, p < 0.005). Conclusion: The study demonstrates the feasibility of the proposed method in head and neck cases for predicting the achievability of clinical objectives with reasonable accuracy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-AB-BRC-11: Moving a GPU-OpenCL-Based Monte Carlo (MC) Dose Engine Towards Routine Clinical Use: Automatic Beam Commissioning and Efficient Source Sampling

Purpose: We have previously developed a GPU-OpenCL-based MC dose engine named goMC with built-in analytical linac beam model. To move goMC towards routine clinical use, we have developed an automatic beam-commissioning method, and an efficient source sampling strategy to facilitate dose calculations for real treatment plans. Methods: Our commissioning method is to automatically adjust the relative weights among the sub-sources, through an optimization process minimizing the discrepancies between calculated dose and measurements. Six models built for Varian Truebeam linac photon beams (6MV, 10MV, 15MV, 18MV, 6MVFFF, 10MVFFF) were commissioned using measurement data acquired at our institution. To facilitate dose calculations for real treatment plans, we employed inverse sampling method to efficiently incorporate MLC leaf-sequencing into source sampling. Specifically, instead of sampling source particles control-point by control-point and rejecting the particles blocked by MLC, we assigned a control-point index to each sampled source particle, according to MLC leaf-open duration of each control-point at the pixel where the particle intersects the iso-center plane. Results: Our auto-commissioning method decreased distance-to-agreement (DTA) of depth dose at build-up regions by 36.2% averagely, making it within 1mm. Lateral profiles were better matched for all beams, with biggest improvement found at 15MV for which root-mean-square difference was reduced from 1.44% to 0.50%. Maximum differences of output factors were reduced to less than 0.7% for all beams, with largest decrease being from1.70% to 0.37% found at 10FFF. Our new sampling strategy was tested on a Head&Neck VMAT patient case. Achieving clinically acceptable accuracy, the new strategy could reduce the required history number by a factor of ∼2.8 given a statistical uncertainty level and hence achieve a similar speed-up factor. Conclusion: Our studies have demonstrated the feasibility and effectiveness of our auto-commissioning approach and new efficient source sampling strategy, implying the potential of our GPU-based MC dose engine goMC for routine clinical use.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

TU-H-206-07: Assessment of Geometric Distortion in EPI with a SPAMM Tagged Acquisition

Purpose: Echo planar imaging (EPI) is known to exhibit gross geometric distortion caused by multiple factors, including B0 inhomgeneity and transient eddy currents. However, diffusion weighted (DW) EPI has become indispensable for diagnosis and therapy assessment. We propose a methodology for quantifying distortion in EPI sequences that does not require the use of dedicated spatial accuracy phantoms, enabling flexibility in phantom design for QA of distortion effects in EPI protocols. Methods: The proposed methodology utilizes a saturation technique known as Spatial Modulation of Magnetization (SPAMM) that tags the imaging subject with saturated grid lines. Originally intended for tracking cardiac motion, these grids are applied to assess differences between diffusion weighting directions and b-values, or against a more geometrically robust sequence such as fast spin echo (FSE). The saturation preparation sequence consists of binomially weighted (e.g. 1-3-3-1) pulses interleaved with gradient blips along the frequency encode direction, followed by the same sequence with gradient blips in the phase encode direction. Three phantoms were assessed with these sequences: a spherical head-sized phantom, a large shimming phantom, and a modified PET ACR phantom that included compartments of water, air, oil, and Teflon. Each phantom was acquired with three sequences using parameters from a clinically appropriate protocol (22 cm head or 46 cm abdomen): a conventional DW-EPI sequence (3 DW directions), and both the DW-EPI and FSE sequences with tagging. Differences in grid locations were visualized with minimum intensity projection between images, and measured using intersecting locations on the grids. Results: Grid lines were clearly visualized on tagged images and enabled quantification of distortions. Maximum eddy current induced errors of 10.8 to 14.8 mm were observed in areas away from isocenter with DW gradients applied in various directions. Conclusion: SPAMM tagging provides a promising mechanism for assessing spatial distribution of distortion in EPI sequences.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-H-BRA-08: A Monte Carlo Cell Nucleus Model for Assessing Cell Survival Probability Based On Particle Track Structure Analysis

Purpose: To correlate the damage produced by particles of different types and qualities to cell survival on the basis of nanodosimetric analysis and advanced DNA structures in the cell nucleus. Methods: A Monte Carlo code was developed to simulate subnuclear DNA chromatin fibers (CFs) of 30nm utilizing a mean-free-path approach common to radiation transport. The cell nucleus was modeled as a spherical region containing 6000 chromatin-dense domains (CDs) of 400nm diameter, with additional CFs modeled in a sparser interchromatin region. The Geant4-DNA code was utilized to produce a particle track database representing various particles at different energies and dose quantities. These tracks were used to stochastically position the DNA structures based on their mean free path to interaction with CFs. Excitation and ionization events intersecting CFs were analyzed using the DBSCAN clustering algorithm for assessment of the likelihood of producing DSBs. Simulated DSBs were then assessed based on their proximity to one another for a probability of inducing cell death. Results: Variations in energy deposition to chromatin fibers match expectations based on differences in particle track structure. The quality of damage to CFs based on different particle types indicate more severe damage by high-LET radiation than low-LET radiation of identical particles. In addition, the model indicates more severe damage by protons than of alpha particles of same LET, which is consistent with differences in their track structure. Cell survival curves have been produced showing the L-Q behavior of sparsely ionizing radiation. Conclusion: Initial results indicate the feasibility of producing cell survival curves based on the Monte Carlo cell nucleus method. Accurate correlation between simulated DNA damage to cell survival on the basis of nanodosimetric analysis can provide insight into the biological responses to various radiation types. Current efforts are directed at producing cell survival curves for high-LET radiation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Sci-Fri PM: Radiation Therapy, Planning, Imaging, and Special Techniques - 09: Impact of the distance of reflective markers from linac isocenter on the positional accuracy of an infrared tracking system

Purpose: The HexaPOD™ six degree of freedom couchtop is equipped with an optical tracking system, consisting of a stereoscopic camera and a reference frame (RF) carrying infrared reflective markers. The manufacturer recommends placing the RF within 50 cm from linac isocenter (ISO), which is a serious limitation since the RF does not fit around the shoulders of most brain patients. This study quantifies the impact of extended RF distances from ISO on positional accuracy. Methods: An in-house tool with an estimated resolution of 0.3 mm and 0.1° was used. It is a large cube and a mathematical model of HexaPOD motion to determine the intersection of room lasers with the ruled cube edges. Combinations of translations (±1 and ±3 cm) and rotations (±2.5°) were executed on two HexaPOD couchtops for multiple RF distances from ISO (35 to 77 cm). For each combination, ten laser readings were fed into a least squares algorithm to determine the executed translations and rotations while minimizing operator reading errors. Results: The usable tracking volume is up to an RF distance of 82 cm from ISO. Positional accuracy of the HexaPOD/iGuide system is 0.6 mm and 0.1° (95% confidence). Positional accuracy variations versus RF distance from ISO are statistically insignificant (p = 0.05). Our results generally confirm recent internal estimates by the manufacturer (for future release). Conclusions: RF distances up to 77 cm from ISO are clinically acceptable, provided performing a patient safety study with a verification scan.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Teaching Quantum Computing to High School Students

Quantum computing is a growing field at the intersection of physics and computer science. The goal of this article is to highlight a successfully trialled quantum computing course for high school students between the ages of 15 and 18 years old. This course was designed to bridge the gap between popular science articles and advanced undergraduate textbooks. Conceptual ideas in the text are reinforced with active learning techniques, such as interactive problem sets and simulation-based labs at various levels. The course is freely available for use and download under the Creative Commons “Attribution-NonCommercial-ShareAlike 4.0 International” license.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

BioBits™ Bright: A fluorescent synthetic biology education kit

Synthetic biology offers opportunities for experiential educational activities at the intersection of the life sciences, engineering, and design. However, implementation of hands-on biology activities in classrooms is challenging because of the need for specialized equipment and expertise to grow living cells. We present BioBits™ Bright, a shelf-stable, just-add-water synthetic biology education kit with easy visual outputs enabled by expression of fluorescent proteins in freeze-dried, cell-free reactions. We introduce activities and supporting curricula for teaching the central dogma, tunable protein expression, and design-build-test cycles and report data generated by K-12 teachers and students. We also develop inexpensive incubators and imagers, resulting in a comprehensive kit costing <US$100 per 30-person classroom. The user-friendly resources of this kit promise to enhance biology education both inside and outside the classroom.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Examining metastatic behavior within 3D bioprinted vasculature for the validation of a 3D computational flow model

Understanding the dynamics of circulating tumor cell (CTC) behavior within the vasculature has remained an elusive goal in cancer biology. To elucidate the contribution of hydrodynamics in determining sites of CTC vascular colonization, the physical forces affecting these cells must be evaluated in a highly controlled manner. To this end, we have bioprinted endothelialized vascular beds and perfused these constructs with metastatic mammary gland cells under physiological flow rates. By pairing these in vitro devices with an advanced computational flow model, we found that the bioprinted analog was readily capable of evaluating the accuracy and integrated complexity of a computational flow model, while also highlighting the discrete contribution of hydrodynamics in vascular colonization. This intersection of these two technologies, bioprinting and computational simulation, is a key demonstration in the establishment of an experimentation pipeline for the understanding of complex biophysical events.

42 ENGINEERING↗