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DOE OSTI2024

Static actuator-sharing algorithm for concurrent control of multiple plasma properties

Simultaneous regulation of multiple properties in next-generation tokamaks like ITER and fusion pilot plant may require the integration of different plasma control algorithms. Such integration requires the conversion of individual controller commands into physical actuator requests while accounting for the coupling between different plasma properties. This work proposes a tokamak and scenario-agnostic actuator-sharing algorithm (ASA) to perform the above-mentioned command-request conversion and, hence, integrate multiple plasma controllers. The proposed algorithm implicitly solves a quadratic programming (QP) problem formulated to account for the saturation limits and the relation between the controller commands and physical actuator requests. Since the constraints arising in the QP program are linear, the proposed ASA is highly computationally efficient and can be implemented in the tokamak plasma control system in real time. Furthermore, the proposed algorithm is designed to handle real-time changes in the control objectives and actuators’ availability. Nonlinear simulations carried out using the Control Oriented Transport SIMulator illustrate the effectiveness of the proposed algorithm in achieving multiple control objectives simultaneously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Quantum Davidson algorithm for excited states

Abstract Excited state properties play a pivotal role in various chemical and physical phenomena, such as charge separation and light emission. However, the primary focus of most existing quantum algorithms has been the ground state, as seen in quantum phase estimation and the variational quantum eigensolver (VQE). Although VQE-type methods have been extended to explore excited states, these methods grapple with optimization challenges. In contrast, the quantum Krylov subspace (QKS) method has been introduced to address both ground and excited states, positioning itself as a cost-effective alternative to quantum phase estimation. However, conventional QKS methodologies depend on a pre-generated subspace through real or imaginary-time evolutions. This subspace is inherently expansive and can be plagued with issues like slow convergence or numerical instabilities, often leading to relatively deep circuits. Our research presents an economic QKS algorithm, which we term the quantum Davidson (QDavidson) algorithm. This innovation hinges on the iterative expansion of the Krylov subspace and the incorporation of a pre-conditioner within the Davidson framework. By using the residues of eigenstates to expand the Krylov subspace, we manage to formulate a compact subspace that aligns closely with the exact solutions. This iterative subspace expansion paves the way for a more rapid convergence in comparison to other QKS techniques, such as the quantum Lanczos. Using quantum simulators, we employ the novel QDavidson algorithm to delve into the excited state properties of various systems, spanning from the Heisenberg spin model to real molecules. Compared to the existing QKS methods, the QDavidson algorithm not only converges swiftly but also demands a significantly shallower circuit. This efficiency establishes the QDavidson method as a pragmatic tool for elucidating both ground and excited state properties on quantum computing platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Convex Decreasing Algorithms: Distributed Synthesis and Finite-Time Termination in Higher Dimension

Here we establish finite time termination algorithms for consensus algorithms based on geometric properties that yield finite-time guarantees, suited for use in high dimension and in the absence of a central authority. These pursuits motivate a new peer to peer convex hull algorithm which is utilized for one stopping algorithm. Further an alternative lightweight norm based stopping criteria is also developed. The practical utility of the algorithm is illustrated through MATLAB simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Data association algorithm for large-scale multi-object tracking with complex interactions

We present an online multi-object tracking algorithm to track multiple objects across a large number of image frames. Our work is motivated by the need to study evolution of nanoscale objects by transmission electron microscopy. The proposed approach is based on the existing multi-way data association tracking algorithm that is capable of tracking interacting objects with complex behaviors (i.e., merge, split, overlap, and appearance or disappearance). The multi-way data association is an offline algorithm to associate objects across all image frames at one step with a global optimization, which does not scale very well for large number of image frames. The proposed online tracking algorithm processes image frames as they arrive by detecting all objects in the newly arrived image frame and making the associations of the objects to those detected from the previous frame by the multi-way data association. This frameby-frame association scheme can cause fragmented traces of the objects that are occasionally misdetected for some image frames. We overcome this issue by allowing previously unassociated objects to be associated when the objects reappear within a fixed number of future image frames, namely the frame-delayed association. We combine the multi-way data association with the frame-delayed association to be able to track interacting objects with accurate handling of object disappearance events. The proposed method is validated through applications to simulated multi-object tracking problem and a real multi-object tracking problem. Here, the outcome of the proposed method is compared with four state-of-the-art algorithms.

36 MATERIALS SCIENCE↗
DOE OSTI2012

A nonlinear lag correction algorithm for a-Si flat-panel x-ray detectors

Purpose: Detector lag, or residual signal, in a-Si flat-panel (FP) detectors can cause significant shading artifacts in cone-beam computed tomography reconstructions. To date, most correction models have assumed a linear, time-invariant (LTI) model and correct lag by deconvolution with an impulse response function (IRF). However, the lag correction is sensitive to both the exposure intensity and the technique used for determining the IRF. Even when the LTI correction that produces the minimum error is found, residual artifact remains. A new non-LTI method was developed to take into account the IRF measurement technique and exposure dependencies. Methods: First, a multiexponential (N = 4) LTI model was implemented for lag correction. Next, a non-LTI lag correction, known as the nonlinear consistent stored charge (NLCSC) method, was developed based on the LTI multiexponential method. It differs from other nonlinear lag correction algorithms in that it maintains a consistent estimate of the amount of charge stored in the FP and it does not require intimate knowledge of the semiconductor parameters specific to the FP. For the NLCSC method, all coefficients of the IRF are functions of exposure intensity. Another nonlinear lag correction method that only used an intensity weighting of the IRF was also compared. The correction algorithms were applied to step-response projection data and CT acquisitions of a large pelvic phantom and an acrylic head phantom. The authors collected rising and falling edge step-response data on a Varian 4030CB a-Si FP detector operating in dynamic gain mode at 15 fps at nine incident exposures (2.0%-92% of the detector saturation exposure). For projection data, 1st and 50th frame lag were measured before and after correction. For the CT reconstructions, five pairs of ROIs were defined and the maximum and mean signal differences within a pair were calculated for the different exposures and step-response edge techniques. Results: The LTI corrections left residual 1st and 50th frame lag up to 1.4% and 0.48%, while the NLCSC lag correction reduced 1st and 50th frame residual lags to less than 0.29% and 0.0052%. For CT reconstructions, the NLCSC lag correction gave an average error of 11 HU for the pelvic phantom and 3 HU for the head phantom, compared to 14-19 HU and 2-11 HU for the LTI corrections and 15 HU and 9 HU for the intensity weighted non-LTI algorithm. The maximum ROI error was always smallest for the NLCSC correction. The NLCSC correction was also superior to the intensity weighting algorithm. Conclusions: The NLCSC lag algorithm corrected for the exposure dependence of lag, provided superior image improvement for the pelvic phantom reconstruction, and gave similar results to the best case LTI results for the head phantom. The blurred ring artifact that is left over in the LTI corrections was better removed by the NLCSC correction in all cases.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Application of activity pencil beam algorithm using measured distribution data of positron emitter nuclei for therapeutic SOBP proton beam

Purpose: Recently, much research on imaging the clinical proton-irradiated volume using positron emitter nuclei based on target nuclear fragment reaction has been carried out. The purpose of this study is to develop an activity pencil beam (APB) algorithm for a simulation system for proton-activated positron-emitting imaging in clinical proton therapy using spread-out Bragg peak (SOBP) beams.Methods: The target nuclei of activity distribution calculations are {sup 12}C nuclei, {sup 16}O nuclei, and {sup 40}Ca nuclei, which are the main elements in a human body. Depth activity distributions with SOBP beam irradiations were obtained from the material information of ridge filter (RF) and depth activity distributions of compounds of the three target nuclei measured by BOLPs-RGp (beam ON-LINE PET system mounted on a rotating gantry port) with mono-energetic Bragg peak (MONO) beam irradiations. The calculated data of depth activity distributions with SOBP beam irradiations were sorted in terms of kind of nucleus, energy of proton beam, SOBP width, and thickness of fine degrader (FD), which were verified. The calculated depth activity distributions with SOBP beam irradiations were compared with the measured ones. APB kernels were made from the calculated depth activity distributions with SOBP beam irradiations to construct a simulation system using the APB algorithm for SOBP beams.Results: The depth activity distributions were prepared using the material information of RF and the measured depth activity distributions with MONO beam irradiations for clinical therapy using SOBP beams. With the SOBP width widening, the distal fall-offs of depth activity distributions and the difference from the depth dose distributions were large. The shapes of the calculated depth activity distributions nearly agreed with those of the measured ones upon comparison between the two. The APB kernels of SOBP beams were prepared by making use of the data on depth activity distributions with SOBP beam irradiations that were made from the depth activity distributions with MONO beam irradiations and sorted in terms of energy, SOBP width, and thickness of FD. The data on APB kernels of SOBP beams were determined as installment data for the simulation system using the APB algorithm for SOBP beam irradiations.Conclusions: A method of obtaining the depth activity distributions and the APB algorithm for clinical use of SOBP beams have been developed. It is suggested that the simulation system for imaging the clinical irradiated volume with the APB algorithm can be used in clinical proton therapy using SOBP beams by preparing and investigating the data on APB kernels of SOBP beams.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR values were found to increase with decreasing RMSE values of projection angular gaps with strong correlations (r ≈ −0.7) regardless of the reconstruction algorithm used. Conclusions: Based on the authors’ results, displacement-based binning methods, better reconstruction algorithms, and the acquisition of even projection angular views are the most important factors to consider for improving thoracic 4D-CBCT image quality. In view of the practical issues with displacement-based binning and the fact that projection angular spacing is not currently directly controllable, development of better reconstruction algorithms represents the most effective strategy for improving image quality in thoracic 4D-CBCT for IGRT applications at the current stage.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Assessing image quality and dose reduction of a new x-ray computed tomography iterative reconstruction algorithm using model observers

Purpose: A number of different techniques have been developed to reduce radiation dose in x-ray computed tomography (CT) imaging. In this paper, the authors will compare task-based measures of image quality of CT images reconstructed by two algorithms: conventional filtered back projection (FBP), and a new iterative reconstruction algorithm (IR). Methods: To assess image quality, the authors used the performance of a channelized Hotelling observer acting on reconstructed image slices. The selected channels are dense difference Gaussian channels (DDOG).A body phantom and a head phantom were imaged 50 times at different dose levels to obtain the data needed to assess image quality. The phantoms consisted of uniform backgrounds with low contrast signals embedded at various locations. The tasks the observer model performed included (1) detection of a signal of known location and shape, and (2) detection and localization of a signal of known shape. The employed DDOG channels are based on the response of the human visual system. Performance was assessed using the areas under ROC curves and areas under localization ROC curves. Results: For signal known exactly (SKE) and location unknown/signal shape known tasks with circular signals of different sizes and contrasts, the authors’ task-based measures showed that a FBP equivalent image quality can be achieved at lower dose levels using the IR algorithm. For the SKE case, the range of dose reduction is 50%–67% (head phantom) and 68%–82% (body phantom). For the study of location unknown/signal shape known, the dose reduction range can be reached at 67%–75% for head phantom and 67%–77% for body phantom case. These results suggest that the IR images at lower dose settings can reach the same image quality when compared to full dose conventional FBP images. Conclusions: The work presented provides an objective way to quantitatively assess the image quality of a newly introduced CT IR algorithm. The performance of the model observers using the IR images was always higher than that seen using the FBP images in the authors’ SKE and SKE location unknown detection tasks. To achieve a FBP-equivalent image quality in CT systems, the authors can lower the radiation dose by using this IR image reconstruction algorithm. Further studies are warranted using clinical data and human observer to validate these results for more complicated and realistic tasks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

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

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

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

An algorithm to estimate the object support in truncated images

Purpose: Truncation artifacts in CT occur if the object to be imaged extends past the scanner field of view (SFOV). These artifacts impede diagnosis and could possibly introduce errors in dose plans for radiation therapy. Several approaches exist for correcting truncation artifacts, but existing correction algorithms do not accurately recover the skin line (or support) of the patient, which is important in some dose planning methods. The purpose of this paper was to develop an iterative algorithm that recovers the support of the object. Methods: The authors assume that the truncated portion of the image is made up of soft tissue of uniform CT number and attempt to find a shape consistent with the measured data. Each known measurement in the sinogram is interpreted as an estimate of missing mass along a line. An initial estimate of the object support is generated by thresholding a reconstruction made using a previous truncation artifact correction algorithm (e.g., water cylinder extrapolation). This object support is iteratively deformed to reduce the inconsistency with the measured data. The missing data are estimated using this object support to complete the dataset. The method was tested on simulated and experimentally truncated CT data. Results: The proposed algorithm produces a better defined skin line than water cylinder extrapolation. On the experimental data, the RMS error of the skin line is reduced by about 60%. For moderately truncated images, some soft tissue contrast is retained near the SFOV. As the extent of truncation increases, the soft tissue contrast outside the SFOV becomes unusable although the skin line remains clearly defined, and in reformatted images it varies smoothly from slice to slice as expected. Conclusions: The support recovery algorithm provides a more accurate estimate of the patient outline than thresholded, basic water cylinder extrapolation, and may be preferred in some radiation therapy applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-D-17A-02: Four-Dimensional CBCT Using Conventional CBCT Dataset and Iterative Subtraction Algorithm of a Lung Patient

Purpose: The Iterative Subtraction Algorithm (ISA) method generates retrospectively a pre-selected motion phase cone-beam CT image from the full motion cone-beam CT acquired at standard rotation speed. This work evaluates ISA method with real lung patient data. Methods: The goal of the ISA algorithm is to extract motion and no- motion components form the full reconstruction CBCT. The workflow consists of subtracting from the full CBCT all of the undesired motion phases and obtain a motion de-blurred single-phase CBCT image, followed by iteration of this subtraction process. ISA is realized as follows: 1) The projections are sorted to various phases, and from all phases, a full reconstruction is performed to generate an image CTM. 2) Generate forward projections of CTM at the desired phase projection angles, the subtraction of projection and the forward projection will reconstruct a CTSub1, which diminishes the desired phase component. 3) By adding back the CTSub1 to CTm, no motion CBCT, CTS1, can be computed. 4) CTS1 still contains residual motion component. 5) This residual motion component can be further reduced by iteration.The ISA 4DCBCT technique was implemented using Varian Trilogy accelerator OBI system. To evaluate the method, a lung patient CBCT dataset was used. The reconstruction algorithm is FDK. Results: The single phase CBCT reconstruction generated via ISA successfully isolates the desired motion phase from the full motion CBCT, effectively reducing motion blur. It also shows improved image quality, with reduced streak artifacts with respect to the reconstructions from unprocessed phase-sorted projections only. Conclusion: A CBCT motion de-blurring algorithm, ISA, has been developed and evaluated with lung patient data. The algorithm allows improved visualization of a single phase motion extracted from a standard CBCT dataset. This study has been supported by National Institute of Health through R01CA133539.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-252: A Motion Algorithm to Extract Physical and Motion Parameters of a Mobile Target in Cone-Beam Computed Tomographic Imaging Retrospective to Image Reconstruction

Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embedded into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract actual length, size and CT-numbers distorted by motion in CBCT imaging. The model provides further information about motion of the target.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-305: Study of the Eclipse Electron Monte Carlo Algorithm for Patient Specific MU Calculations

Purpose: To evaluate the Eclipse electron Monte Carlo (eMC) algorithm based on patient specific monitor unit (MU) calculations, and to propose a new factor which quantitatively predicts the discrepancy of MUs between the eMC algorithm and hand calculations. Methods: Electron treatments were planned for 61 patients on Eclipse (Version 10.0) using the eMC algorithm for Varian TrueBeam linear accelerators. For each patient, the same treatment beam angle was kept for a point dose calculation at dmax performed with the reference condition, which used an open beam with a 15×15 cm2 size cone and 100 SSD. A patient specific correction factor (PCF) was obtained by getting the ratio between this point dose and the calibration dose, which is 1 cGy per MU delivered at dmax. The hand calculation results were corrected by the PCFs and compared with MUs from the treatment plans. Results: The MU from the treatment plans were in average (7.1±6.1)% higher than the hand calculations. The average MU difference between the corrected hand calculations and the eMC treatment plans was (0.07±3.48)%. A correlation coefficient of 0.8 was found between (1-PCF) and the percentage difference between the treatment plan and hand calculations. Most outliers were treatment plans with small beam opening (< 4 cm) and low energy beams (6 and 9 MeV). Conclusion: For CT-based patient treatment plans, the eMC algorithm tends to generate a larger MU than hand calculations. Caution should be taken for eMC patient plans with small field sizes and low energy beams. We hypothesize that the PCF ratio reflects the influence of patient surface curvature and tissue inhomogeneity to patient specific percent depth dose (PDD) curve and MU calculations in eMC algorithm.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-497: Semi-Automated in Vivo Radiochromic Film Dosimetry Using a Novel Image Processing Algorithm

Purpose: To validate an automated image processing algorithm designed to detect the center of radiochromic film used for in vivo film dosimetry against the current gold standard of manual selection. Methods: An image processing algorithm was developed to automatically select the region of interest (ROI) in *.tiff images that contain multiple pieces of radiochromic film (0.5x1.3cm{sup 2}). After a user has linked a calibration file to the processing algorithm and selected a *.tiff file for processing, an ROI is automatically detected for all films by a combination of thresholding and erosion, which removes edges and any additional markings for orientation. Calibration is applied to the mean pixel values from the ROIs and a *.tiff image is output displaying the original image with an overlay of the ROIs and the measured doses. Validation of the algorithm was determined by comparing in vivo dose determined using the current gold standard (manually drawn ROIs) versus automated ROIs for n=420 scanned films. Bland-Altman analysis, paired t-test, and linear regression were performed to demonstrate agreement between the processes. Results: The measured doses ranged from 0.2-886.6cGy. Bland-Altman analysis of the two techniques (automatic minus manual) revealed a bias of -0.28cGy and a 95% confidence interval of (5.5cGy,-6.1cGy). These values demonstrate excellent agreement between the two techniques. Paired t-test results showed no statistical differences between the two techniques, p=0.98. Linear regression with a forced zero intercept demonstrated that Automatic=0.997*Manual, with a Pearson correlation coefficient of 0.999. The minimal differences between the two techniques may be explained by the fact that the hand drawn ROIs were not identical to the automatically selected ones. The average processing time was 6.7seconds in Matlab on an IntelCore2Duo processor. Conclusion: An automated image processing algorithm has been developed and validated, which will help minimize user interaction and processing time of radiochromic film used for in vivo dosimetry.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

WE-A-17A-06: Evaluation of An Automatic Interstitial Catheter Digitization Algorithm That Reduces Treatment Planning Time and Provide Means for Adaptive Re-Planning in HDR Brachytherapy of Gynecologic Cancers

Purpose: To evaluate an automatic interstitial catheter digitization algorithm that reduces treatment planning time and provide means for adaptive re-planning in HDR Brachytherapy of Gynecologic Cancers. Methods: The semi-automatic catheter digitization tool utilizes a region growing algorithm in conjunction with a spline model of the catheters. The CT images were first pre-processed to enhance the contrast between the catheters and soft tissue. Several seed locations were selected in each catheter for the region growing algorithm. The spline model of the catheters assisted in the region growing by preventing inter-catheter cross-over caused by air or metal artifacts. Source dwell positions from day one CT scans were applied to subsequent CTs and forward calculated using the automatically digitized catheter positions. This method was applied to 10 patients who had received HDR interstitial brachytherapy on an IRB approved image-guided radiation therapy protocol. The prescribed dose was 18.75 or 20 Gy delivered in 5 fractions, twice daily, over 3 consecutive days. Dosimetric comparisons were made between automatic and manual digitization on day two CTs. Results: The region growing algorithm, assisted by the spline model of the catheters, was able to digitize all catheters. The difference between automatic and manually digitized positions was 0.8±0.3 mm. The digitization time ranged from 34 minutes to 43 minutes with a mean digitization time of 37 minutes. The bulk of the time was spent on manual selection of initial seed positions and spline parameter adjustments. There was no significance difference in dosimetric parameters between the automatic and manually digitized plans. D90% to the CTV was 91.5±4.4% for the manual digitization versus 91.4±4.4% for the automatic digitization (p=0.56). Conclusion: A region growing algorithm was developed to semi-automatically digitize interstitial catheters in HDR brachytherapy using the Syed-Neblett template. This automatic digitization tool was shown to be accurate compared to manual digitization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-E-BRE-07: Development of Dose Calculation Error Predictors for a Widely Implemented Clinical Algorithm

Purpose: Several shortcomings of the current implementation of the analytic anisotropic algorithm (AAA) may lead to dose calculation errors in highly modulated treatments delivered to highly heterogeneous geometries. Here we introduce a set of dosimetric error predictors that can be applied to a clinical treatment plan and patient geometry in order to identify high risk plans. Once a problematic plan is identified, the treatment can be recalculated with more accurate algorithm in order to better assess its viability. Methods: Here we focus on three distinct sources dosimetric error in the AAA algorithm. First, due to a combination of discrepancies in smallfield beam modeling as well as volume averaging effects, dose calculated through small MLC apertures can be underestimated, while that behind small MLC blocks can overestimated. Second, due the rectilinear scaling of the Monte Carlo generated pencil beam kernel, energy is not properly transported through heterogeneities near, but not impeding, the central axis of the beamlet. And third, AAA overestimates dose in regions very low density (< 0.2 g/cm{sup 3}). We have developed an algorithm to detect the location and magnitude of each scenario within the patient geometry, namely the field-size index (FSI), the heterogeneous scatter index (HSI), and the lowdensity index (LDI) respectively. Results: Error indices successfully identify deviations between AAA and Monte Carlo dose distributions in simple phantom geometries. Algorithms are currently implemented in the MATLAB computing environment and are able to run on a typical RapidArc head and neck geometry in less than an hour. Conclusion: Because these error indices successfully identify each type of error in contrived cases, with sufficient benchmarking, this method can be developed into a clinical tool that may be able to help estimate AAA dose calculation errors and when it might be advisable to use Monte Carlo calculations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-E-BRE-11: Adaptive-Beamlet Based Finite Size Pencil Beam (AB-FSPB) Dose Calculation Algorithm for Independent Verification of IMRT and VMAT

Purpose: In current IMRT and VMAT settings, the use of sophisticated dose calculation procedure is inevitable in order to account complex treatment field created by MLCs. As a consequence, independent volumetric dose verification procedure is time consuming which affect the efficiency of clinical workflow. In this study, the authors present an efficient Pencil Beam based dose calculation algorithm that minimizes the computational procedure while preserving the accuracy. Methods: The computational time of Finite Size Pencil Beam (FSPB) algorithm is proportional to the number of infinitesimal identical beamlets that constitute the arbitrary field shape. In AB-FSPB, the dose distribution from each beamlet is mathematically modelled such that the sizes of beamlets to represent arbitrary field shape are no longer needed to be infinitesimal nor identical. In consequence, it is possible to represent arbitrary field shape with combinations of different sized and minimal number of beamlets. Results: On comparing FSPB with AB-FSPB, the complexity of the algorithm has been reduced significantly. For 25 by 25 cm2 squared shaped field, 1 beamlet of 25 by 25 cm2 was sufficient to calculate dose in AB-FSPB, whereas in conventional FSPB, minimum 2500 beamlets of 0.5 by 0.5 cm2 size were needed to calculate dose that was comparable to the Result computed from Treatment Planning System (TPS). The algorithm was also found to be GPU compatible to maximize its computational speed. On calculating 3D dose of IMRT (∼30 control points) and VMAT plan (∼90 control points) with grid size 2.0 mm (200 by 200 by 200), the dose could be computed within 3∼5 and 10∼15 seconds. Conclusion: Authors have developed an efficient Pencil Beam type dose calculation algorithm called AB-FSPB. The fast computation nature along with GPU compatibility has shown performance better than conventional FSPB. This completely enables the implantation of AB-FSPB in the clinical environment for independent volumetric dose verification.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was reduced by an average of 60% in SAFIRE images compared to FBP. However, for edge pixels, noise magnitude ranged from 20% higher to 40% lower in SAFIRE images compared to FBP. SAFIRE images of the lung phantom exhibited distinct regions with varying noise texture (i.e., noise autocorrelation/power spectra). Conclusions: Quantum noise properties observed in uniform phantoms may not be representative of those in actual patients for nonlinear reconstruction algorithms. Anatomical texture should be considered when evaluating the performance of CT systems that use such nonlinear algorithms.

60 APPLIED LIFE SCIENCES↗