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At least 1,747 records · Page 97
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DOE OSTI2014

MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps

Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast irradiation case (Case II) solved with photon and electron modulated beams (IMRT + MERT); and a prostatic bed case (Case III) with a pronounced concave-shaped PTV by using volumetric modulated arc therapy. In the three cases, the required target prescription doses and constraints on organs at risk were fulfilled in a short enough time to allow routine clinical implementation. The quality assurance protocol followed to check CARMEN system showed a high agreement with the experimental measurements. Conclusions: A Monte Carlo treatment planning model exclusively based on maps performed from patient imaging data has been presented. The sequencing of these maps allows obtaining deliverable apertures which are weighted for modulation under a linear programming formulation. The model is able to solve complex radiotherapy treatments with high accuracy in an efficient computation time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Poster — Thur Eve — 35: The impact of intensity- and energy-modulated photon radiotherapy (XMRT) optimization on a variety of organ geometries

We previously reported on a novel, modulated in both energy and intensity; photon radiotherapy (XMRT) optimization technique. The purpose of this investigation was to test this XMRT optimization against conventional intensity modulated radiotherapy (IMRT) optimization on four different organ test geometries. All geometries mimicked clinically relevant scenarios. Both IMRT and XMRT were based on a linear programming approach where the objective function was the mean dose to healthy organs and organ-specific linear dose-point constraints were used. For IMRT, the beam energy was fixed to 6 MV while XMRT optimized in terms of both 6 and 18 MV beams. All plans consisted of a seven beam coplanar arrangement. All organ geometries were contoured on a 25cm diameter cylindrical water phantom in open source radiotherapy research software known as CERR. Solutions for both IMRT and XMRT were obtained for each geometry using a numerical solver Gurobi. Analyzing the quality of the solutions was done by comparing dose distributions and dose volume histograms calculated using CERR. For all four geometries, IMRT and XMRT solutions were comparable in terms of target coverage. For two of the geometries, IMRT provided an advantage in terms of reduced dose to the healthy structures. XMRT showed improved dose reduction to healthy organs for one geometry and a comparable dose distribution to IMRT for the remaining geometry. The inability to exploit the benefits of using multiple energies may be attributed to limited water phantom diameter and having the majority of the organs in close proximity to the transverse axis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Poster — Thur Eve — 69: Computational Study of DVH-guided Cancer Treatment Planning Optimization Methods

Purpose: To compare methods to incorporate the Dose Volume Histogram (DVH) curves into the treatment planning optimization. Method: The performance of three methods, namely, the conventional Mixed Integer Programming (MIP) model, a convex moment-based constrained optimization approach, and an unconstrained convex moment-based penalty approach, is compared using anonymized data of a prostate cancer patient. Three plans we generated using the corresponding optimization models. Four Organs at Risk (OARs) and one Tumor were involved in the treatment planning. The OARs and Tumor were discretized into total of 50,221 voxels. The number of beamlets was 943. We used commercially available optimization software Gurobi and Matlab to solve the models. Plan comparison was done by recording the model runtime followed by visual inspection of the resulting dose volume histograms. Conclusion: We demonstrate the effectiveness of the moment-based approaches to replicate the set of prescribed DVH curves. The unconstrained convex moment-based penalty approach is concluded to have the greatest potential to reduce the computational effort and holds a promise of substantial computational speed up.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Multiple anatomy optimization of accumulated dose

Purpose: To investigate the potential advantages of multiple anatomy optimization (MAO) for lung cancer radiation therapy compared to the internal target volume (ITV) approach. Methods: MAO aims to optimize a single fluence to be delivered under free-breathing conditions such that the accumulated dose meets the plan objectives, where accumulated dose is defined as the sum of deformably mapped doses computed on each phase of a single four dimensional computed tomography (4DCT) dataset. Phantom and patient simulation studies were carried out to investigate potential advantages of MAO compared to ITV planning. Through simulated delivery of the ITV- and MAO-plans, target dose variations were also investigated. Results: By optimizing the accumulated dose, MAO shows the potential to ensure dose to the moving target meets plan objectives while simultaneously reducing dose to organs at risk (OARs) compared with ITV planning. While consistently superior to the ITV approach, MAO resulted in equivalent OAR dosimetry at planning objective dose levels to within 2% volume in 14/30 plans and to within 3% volume in 19/30 plans for each lung V20, esophagus V25, and heart V30. Despite large variations in per-fraction respiratory phase weights in simulated deliveries at high dose rates (e.g., treating 4/10 phases during single fraction beams) the cumulative clinical target volume (CTV) dose after 30 fractions and per-fraction dose were constant independent of planning technique. In one case considered, however, per-phase CTV dose varied from 74% to 117% of prescription implying the level of ITV-dose heterogeneity may not be appropriate with conventional, free-breathing delivery. Conclusions: MAO incorporates 4DCT information in an optimized dose distribution and can achieve a superior plan in terms of accumulated dose to the moving target and OAR sparing compared to ITV-plans. An appropriate level of dose heterogeneity in MAO plans must be further investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A method of surface marker location optimization for tumor motion estimation in lung stereotactic body radiation therapy

Purpose: Accurately localizing lung tumor localization is essential for high-precision radiation therapy techniques such as stereotactic body radiation therapy (SBRT). Since direct monitoring of tumor motion is not always achievable due to the limitation of imaging modalities for treatment guidance, placement of fiducial markers on the patient’s body surface to act as a surrogate for tumor position prediction is a practical alternative for tracking lung tumor motion during SBRT treatments. In this work, the authors propose an innovative and robust model to solve the multimarker position optimization problem. The model is able to overcome the major drawbacks of the sparse optimization approach (SOA) model. Methods: The principle-component-analysis (PCA) method was employed as the framework to build the authors’ statistical prediction model. The method can be divided into two stages. The first stage is to build the surrogate tumor matrix and calculate its eigenvalues and associated eigenvectors. The second stage is to determine the “best represented” columns of the eigenvector matrix obtained from stage one and subsequently acquire the optimal marker positions as well as numbers. Using 4-dimensional CT (4DCT) and breath hold CT imaging data, the PCA method was compared to the SOA method with respect to calculation time, average prediction accuracy, prediction stability, noise resistance, marker position consistency, and marker distribution. Results: The PCA and SOA methods which were both tested were on all 11 patients for a total of 130 cases including 4DCT and breath-hold CT scenarios. The maximum calculation time for the PCA method was less than 1 s with 64 752 surface points, whereas the average calculation time for the SOA method was over 12 min with 400 surface points. Overall, the tumor center position prediction errors were comparable between the two methods, and all were less than 1.5 mm. However, for the extreme scenarios (breath hold), the prediction errors for the PCA method were not only smaller, but were also more stable than for the SOA method. Results obtained by imposing a series of random noises to the surrogates indicated that the PCA method was much more noise resistant than the SOA method. The marker position consistency tests using various combinations of 4DCT phases to construct the surrogates suggested that the marker position predictions of the PCA method were more consistent than those of the SOA method, in spite of surrogate construction. Marker distribution tests indicated that greater than 80% of the calculated marker positions fell into the high cross correlation and high motion magnitude regions for both of the algorithms. Conclusions: The PCA model is an accurate, efficient, robust, and practical model for solving the multimarker position optimization problem to predict lung tumor motion during SBRT treatments. Due to its generality, PCA model can also be applied to other imaging guidance system whichever using surface motion as the surrogates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Robust electromagnetically guided endoscopic procedure using enhanced particle swarm optimization for multimodal information fusion

Purpose: Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. Methods: The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) as a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the authors introduce the current (endoscopic camera and electromagnetic sensor’s) observation to boost the particle swarm optimization and also adaptively update evolutionary parameters in accordance with spatial constraints and the current observation, resulting in advantageous performance in the enhanced algorithm. Results: The experimental results demonstrate that the authors’ proposed method provides a more accurate and robust endoscopic guidance framework than state-of-the-art methods. The average guidance accuracy of the authors’ framework was about 3.0 mm and 5.6° while the previous methods show at least 3.9 mm and 7.0°. The average position and orientation smoothness of their method was 1.0 mm and 1.6°, which is significantly better than the other methods at least with (2.0 mm and 2.6°). Additionally, the average visual quality of the endoscopic guidance was improved to 0.29. Conclusions: A robust electromagnetically guided endoscopy framework was proposed on the basis of an enhanced particle swarm optimization method with using the current observation information and adaptive evolutionary factors. The authors proposed framework greatly reduced the guidance errors from (4.3, 7.8) to (3.0 mm, 5.6°), compared to state-of-the-art methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Determination of the optimal tolerance for MLC positioning in sliding window and VMAT techniques

Purpose: Several authors have recommended a 2 mm tolerance for multileaf collimator (MLC) positioning in sliding window treatments. In volumetric modulated arc therapy (VMAT) treatments, however, the optimal tolerance for MLC positioning remains unknown. In this paper, the authors present the results of a multicenter study to determine the optimal tolerance for both techniques. Methods: The procedure used is based on dynalog file analysis. The study was carried out using seven Varian linear accelerators from five different centers. Dynalogs were collected from over 100 000 clinical treatments and in-house software was used to compute the number of tolerance faults as a function of the user-defined tolerance. Thus, the optimal value for this tolerance, defined as the lowest achievable value, was investigated. Results: Dynalog files accurately predict the number of tolerance faults as a function of the tolerance value, especially for low fault incidences. All MLCs behaved similarly and the Millennium120 and the HD120 models yielded comparable results. In sliding window techniques, the number of beams with an incidence of hold-offs >1% rapidly decreases for a tolerance of 1.5 mm. In VMAT techniques, the number of tolerance faults sharply drops for tolerances around 2 mm. For a tolerance of 2.5 mm, less than 0.1% of the VMAT arcs presented tolerance faults. Conclusions: Dynalog analysis provides a feasible method for investigating the optimal tolerance for MLC positioning in dynamic fields. In sliding window treatments, the tolerance of 2 mm was found to be adequate, although it can be reduced to 1.5 mm. In VMAT treatments, the typically used 5 mm tolerance is excessively high. Instead, a tolerance of 2.5 mm is recommended.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

SU-D-BRB-06: Treating Glioblastoma Multiforme (GBM) as a Chronic Disease: Implication of Temporal-Spatial Dose Fractionation Optimization Including Cancer Stem Cell Dynamics

Purpose: To explore the feasibility of improving GBM treatment outcome with temporal-spatial dose optimization of an ordinary differential equation (ODE) that models the differentiation and distinct radiosensitivity between cancer stem cells (CSC) and differentiated cancer cells (DCC). Methods: The ODE was formulated into a non-convex optimization problem with the objective to minimize remaining total cancer cells 500 days from the onset of radiotherapy when the total cancer cell number was 3.5×10{sup 7}, while maintaining normal tissue biological effective dose (BED) of 100Gy resulted from standard prescription of 2Gyx30. Assuming spatially separated CSC and DCC, optimization was also performed to explore the potential benefit from dose-painting the two compartments. Dose escalation to a sub-cell-population in the GTV was also examined assuming that a 2 cm margin around the GTV allows sufficient dose drop-off to 100Gy BED. The recurrence time was determined as the time at which the total cancer cell number regrows to 10{sup 9} cells. Results: The recurrence time with variable fractional doses administered once per week, bi-week and month for one year were found to be 615, 593 and 570 days, superior to the standard-prescription recurrence time of 418 days. The optimal dose-fraction size progression for both uniform and dose-painting to the tumor is low and relatively constant in the beginning and gradually increases to more aggressive fractions at end of the treatment course. Dose escalation to BED of 200Gy to the whole tumor alongside with protracted weekly treatment was found to further delay recurrence to 733 days. Dose-painting of 200 and 500Gy BED to CSC on a year-long weekly schedule further extended recurrence to 736 and 1076 days, respectively. Conclusion: GBM treatment outcome can possibly be improved with a chronic treatment approach. Further dose escalation to the entire tumor or CSC targeted killing is needed to achieve total tumor control. This work is supported by the NSF Graduate Research Fellowship (DGE-1144087)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-42: A Method to Determine the Optimal Proton Scanned Beam Angle to Ensure Robust Treatment Planning

Purpose: The ability of pencil beam scanning (PBS) to deliver highly conformal dose distributions may be affected by patient- and physics-related uncertainties. In clinical practice, selection of proton beam angles is determined qualitatively. This study investigates whether an optimal proton PBS beam angle could be quantitatively determined to ensure robust planning for pelvic targets. Methods: PBS beam angles were optimized based on two independent criteria; shortest and most homogeneous path from the patient surface to the distal edge of the target. The beam angle optimization criteria for gantry angles between 90°-270° were quantified in 10° increments for each ray, calculated as the straight line distance from the surface of the skin to the CTV’s distal edge. The goal was to minimize the path length of a proton PBS beam from the patient surface to the distal edge of the CTV, relative to the entry point, while minimizing HU inhomogeneity along the ray. HU homogeneity (i.e. HU variation) was quantitatively defined as the standard deviation of the average intra-ray HU intensity distribution of the rays comprising a single beam. This method was validated relative to inter-fraction changes on ten consecutive, locally advanced, rectal cancer patients, who underwent an average 4 verification CTs. The displacement of the 95–98% isodose lines was determined from forward calculated dose distributions on verification CTs. Results: The posterior beam (180°) had the average shortest path length, 132.7±17.2mm, and the most homogenous path, 31.9±4.3HU. The 95–98% isodose lines from all plans verified our path length to within 2.3±1.2% and HU homogeneity to within 1.2±0.5%. Conclusion: The proposed optimization algorithm determined the posterior beam dose distribution as the most robust relative to inter-fraction variation for large pelvic targets treated with PBS and was validated via verification CT for our patient cohort. Future work will focus on further algorithm development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-446: Group-Sparsity Based Angle Generation Method for Beam Angle Optimization

Purpose: This work is to develop the effective algorithm for beam angle optimization (BAO), with the emphasis on enabling further improvement from existing treatment-dependent templates based on clinical knowledge and experience. Methods: The proposed BAO algorithm utilizes a priori beam angle templates as the initial guess, and iteratively generates angular updates for this initial set, namely angle generation method, with improved dose conformality that is quantitatively measured by the objective function. That is, during each iteration, we select “the test angle” in the initial set, and use group-sparsity based fluence map optimization to identify “the candidate angle” for updating “the test angle”, for which all the angles in the initial set except “the test angle”, namely “the fixed set”, are set free, i.e., with no group-sparsity penalty, and the rest of angles including “the test angle” during this iteration are in “the working set”. And then “the candidate angle” is selected with the smallest objective function value from the angles in “the working set” with locally maximal group sparsity, and replaces “the test angle” if “the fixed set” with “the candidate angle” has a smaller objective function value by solving the standard fluence map optimization (with no group-sparsity regularization). Similarly other angles in the initial set are in turn selected as “the test angle” for angular updates and this chain of updates is iterated until no further new angular update is identified for a full loop. Results: The tests using the MGH public prostate dataset demonstrated the effectiveness of the proposed BAO algorithm. For example, the optimized angular set from the proposed BAO algorithm was better the MGH template. Conclusion: A new BAO algorithm is proposed based on the angle generation method via group sparsity, with improved dose conformality from the given template. Hao Gao was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-527: Is CTV-Based Robust Optimized IMPT in Non-Small-Cell Lung Cancer Robust Against Respiratory Motion?

Purpose: To determine which proton planning technique on average-CT is more vulnerable to respiratory motion induced density changes and interplay effect among (a) IMPT of CTV-based minimax robust optimization with 5mm set-up error considered, (b, c) IMPT/SFUD of 5mm-expanded PTV optimization. Methods: Three planning techniques were optimized in Raystation with a prescription of 60/25 (Gy/fractions) and almost the same OAR constraints/objectives for each of 10 NSCLC patients. 4D dose without/with interplay effect was recalculated on eight 4D-CT phases and accumulated after deforming the dose of each phase to a reference (exhalation phase). The change of D98% of each CTV caused by density changes and interplay was determined. In addition, evaluation of the DVH information vector (D99%, D98%, D95%, Dave, D50%, D2%, D1%) which compares the whole DVH by η score = (cosine similarity × Pearson correlation coefficient − 0.9) × 1000 quantified the degree of DVH change: score below 100 indicates changed DVH. Results: Three 3D plans of each technique satisfied our clinical goals. D98% shift mean±SD (Gy) due to density changes was largest in (c): −0.78±1.1 while (a): −0.11±0.65 and (b): − 0.59±0.93. Also the shift due to interplay effect most was (c): −.54±0.70 whereas (a): −0.25±0.93 and (b): −0.12±0.13. Moreover lowest η score caused by density change was also (c): 69, while (a) and (b) kept around 90. η score also indicated less effect of interplay than density changes. Note that generally the changed DVH were still acceptable clinically. Paired T-tests showed a significantly smaller density change effect in (a) (p<0.05) than in (b) or (c) and no significant difference in interplay effect. Conclusion: CTV-based robust optimized IMPT was more robust against respiratory motion induced density changes than PTV-based IMPT and SFUD. The interplay effect was smaller than the effect of density changes and similar among the three techniques. The JSPS Core-to-Core Program (No. 23003), Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research (No. 23390300), Grant-in-Aid for Young Scientists (B) (No. 21791194) and Grant-in-Aid for Cancer Research (H22-3rd Term Cancer Control-General-043)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-587: Optimal Volumetric Modulated Arc Radiotherapy Treatment Planning Technique for Multiple Brain Metastases with Increasing Number of Arcs

Purpose: To show improvements in dose conformity and normal brain tissue sparing using an optimal planning technique (OPT) against clinically acceptable planning technique (CAP) in the treatment of multiple brain metastases. Methods: A standardized international benchmark case with12 intracranial tumors was planned using two different VMAT optimization methods. Plans were split into four groups with 3, 6, 9, and 12 targets each planned with 3, 5, and 7 arcs using Eclipse TPS. The beam geometries were 1 full coplanar and half non-coplanar arcs. A prescription dose of 20Gy was used for all targets. The following optimization criteria was used (OPT vs. CAP): (No upper limit vs.108% upper limit for target volume), (priority 140–150 vs. 75–85 for normal-brain-tissue), and (selection of automatic sparing Normal-Tissue-Objective (NTO) vs. Manual NTO). Both had priority 50 to critical structures such as brainstem and optic-chiasm, and both had an NTO priority 150. Normal-brain-tissue doses along with Paddick Conformity Index (PCI) were evaluated. Results: In all cases PCI was higher for OPT plans. The average PCI (OPT,CAP) for all targets was (0.81,0.64), (0.81,0.63), (0.79,0.57), and (0.72,0.55) for 3, 6, 9, and 12 target plans respectively. The percent decrease in normal brain tissue volume (OPT/CAP*100) achieved by OPT plans was (reported as follows: V4, V8, V12, V16, V20) (184, 343, 350, 294, 371%), (192, 417, 380, 299, 360%), and (235, 390, 299, 281, 502%) for the 3, 5, 7 arc 12 target plans, respectively. The maximum brainstem dose decreased for the OPT plan by 4.93, 4.89, and 5.30 Gy for 3, 5, 7 arc 12 target plans, respectively. Conclusion: Substantial increases in PCI, critical structure sparing, and decreases in normal brain tissue dose were achieved by eliminating upper limits from optimization, using automatic sparing of normal tissue function with high priority, and a high priority to normal brain tissue.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

MO-AB-BRA-08: Rapid Treatment Field Uniformity Optimization for Total Skin Electron Beam Therapy Using Cherenkov Imaging

Purpose: To evaluate treatment field heterogeneity resulting from gantry angle choice in total skin electron beam therapy (TSEBT) following a modified Stanford dual-field technique, and determine a relationship between source to surface distance (SSD) and optimized gantry angle spread. Methods: Cherenkov imaging was used to image 62 treatment fields on a sheet of 1.2m x 2.2m x 1.2cm polyethylene following standard TSEBT setup at our institution (6 MeV, 888 MU/min, no spoiler, SSD=441cm), where gantry angles spanned from 239.5° to 300.5° at 1° increments. Average Cherenkov intensity and coefficient of variation in the region of interest were compared for the set of composite Cherenkov images created by summing all unique combinations of angle pairs to simulate dual-field treatment. The angle pair which produced the lowest coefficient of variation was further studied using an ionization chamber. The experiment was repeated at SSD=300cm, and SSD=370.5cm. Cherenkov imaging was also implemented during TSEBT of three patients. Results: The most uniform treatment region from a symmetric angle spread was achieved using gantry angles +/−17.5° about the horizontal axis at SSD=441cm, +/−18.5° at SSD=370.5cm, and +/−19.5° at SSD=300cm. Ionization chamber measurements comparing the original treatment spread (+/−14.5°) and the optimized angle pair (+/−17.5°) at SSD=441cm showed no significant deviation (r=0.999) in percent depth dose curves, and chamber measurements from nine locations within the field showed an improvement in dose uniformity from 24.41% to 9.75%. Ionization chamber measurements correlated strongly (r=0.981) with Cherenkov intensity measured concurrently on the flat Plastic Water phantom. Patient images and TLD results also showed modest uniformity improvements. Conclusion: A decreasing linear relationship between optimal angle spread and SSD was observed. Cherenkov imaging offers a new method of rapidly analyzing and optimizing TSEBT setup geometry by providing a 2D image of the treatment plane as a sum of the two fields. This study has been funded by NIH grants R21EB17559 and R01CA109558 as well as Norris Cotton Cancer Center Pilot funding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SIFT-based dense pixel tracking on 0.35 T cine-MR images acquired during image-guided radiation therapy with application to gating optimization

Purpose: To first demonstrate the viability of applying an image processing technique for tracking regions on low-contrast cine-MR images acquired during image-guided radiation therapy, and then outline a scheme that uses tracking data for optimizing gating results in a patient-specific manner. Methods: A first-generation MR-IGRT system—treating patients since January 2014—integrates a 0.35 T MR scanner into an annular gantry consisting of three independent Co-60 sources. Obtaining adequate frame rates for capturing relevant patient motion across large fields-of-view currently requires coarse in-plane spatial resolution. This study initially (1) investigate the feasibility of rapidly tracking dense pixel correspondences across single, sagittal plane images (with both moderate signal-to-noise and spatial resolution) using a matching objective for highly descriptive vectors called scale-invariant feature transform (SIFT) descriptors associated to all pixels that describe intensity gradients in local regions around each pixel. To more accurately track features, (2) harmonic analysis was then applied to all pixel trajectories within a region-of-interest across a short training period. In particular, the procedure adjusts the motion of outlying trajectories whose relative spectral power within a frequency bandwidth consistent with respiration (or another form of periodic motion) does not exceed a threshold value that is manually specified following the training period. To evaluate the tracking reliability after applying this correction, conventional metrics—including Dice similarity coefficients (DSCs), mean tracking errors (MTEs), and Hausdorff distances (HD)—were used to compare target segmentations obtained via tracking to manually delineated segmentations. Upon confirming the viability of this descriptor-based procedure for reliably tracking features, the study (3) outlines a scheme for optimizing gating parameters—including relative target position and a tolerable margin about this position—derived from a probability density function that is constructed using tracking results obtained just prior to treatment. Results: The feasibility of applying the matching objective for SIFT descriptors toward pixel-by-pixel tracking on cine-MR acquisitions was first retrospectively demonstrated for 19 treatments (spanning various sites). Both with and without motion correction based on harmonic analysis, sub-pixel MTEs were obtained. A mean DSC value spanning all patients of 0.916 ± 0.001 was obtained without motion correction, with DSC values exceeding 0.85 for all patients considered. While most patients show accurate tracking without motion correction, harmonic analysis does yield substantial gain in accuracy (defined using HDs) for three particularly challenging subjects. An application of tracking toward a gating optimization procedure was then demonstrated that should allow a physician to balance beam-on time and tissue sparing in a patient-specific manner by tuning several intuitive parameters. Conclusions: Tracking results show high fidelity in assessing intrafractional motion observed on cine-MR acquisitions. Incorporating harmonic analysis during a training period improves the robustness of the tracking for challenging targets. The concomitant gating optimization procedure should allow for physicians to quantitatively assess gating effectiveness quickly just prior to treatment in a patient-specific manner.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

An online replanning method using warm start optimization and aperture morphing for flattening-filter-free beams

Purpose: In a situation where a couch shift for patient positioning is not preferred or prohibited (e.g., MR-linac), segment aperture morphing (SAM) can address target dislocation and deformation. For IMRT/VMAT with flattening-filter-free (FFF) beams, however, SAM method would lead to an adverse translational dose effect due to the beam unflattening. Here the authors propose a new two-step process to address both the translational effect of FFF beams and the target deformation. Methods: The replanning method consists of an offline and an online step. The offline step is to create a series of preshifted-plans (PSPs) obtained by a so-called “warm start” optimization (starting optimization from the original plan, rather than from scratch) at a series of isocenter shifts. The PSPs all have the same number of segments with very similar shapes, since the warm start optimization only adjusts the MLC positions instead of regenerating them. In the online step, a new plan is obtained by picking the closest PSP or linearly interpolating the MLC positions and the monitor units of the closest PSPs for the shift determined from the image of the day. This two-step process is completely automated and almost instantaneous (no optimization or dose calculation needed). The previously developed SAM algorithm is then applied for daily deformation. The authors tested the method on sample prostate and pancreas cases. Results: The two-step interpolation method can account for the adverse dose effects from FFF beams, while SAM corrects for the target deformation. Plan interpolation method is effective in diminishing the unflat beam effect and may allow reducing the required number of PSPs. The whole process takes the same time as the previously reported SAM process (5–10 min). Conclusions: The new two-step method plus SAM can address both the translation effects of FFF beams and target deformation, and can be executed in full automation except the delineation of target contour required by the SAM process.

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-T-89: Investigation of Simultaneous Optimization of Photon and Electron Apertures for Mixed Beam Radiotherapy Based On An Academic Case

Purpose: To estimate the dosimetric potential of mixed beam radiotherapy (MBRT) by using a single process optimizing the shape and weight of photon and electron apertures simultaneously based on Monte Carlo beamlet dose distributions. Methods: A simulated annealing based direct aperture optimization capable to perform simultaneous optimization was developed to generate treatment plans for MERT, photon-IMRT and MBRT. Both photon and electron apertures are collimated with the photon-MLC and are delivered in a segmented manner. For dosimetric comparison and for investigating the dependency on the number of apertures, photon-IMRT, MERT and MBRT plans were generated for an academic case consisting of a water phantom containing two shallow PTVs differing in the maximal depth of 5 and 7 cm, respectively and two OARs in distal and lateral direction to the PTVs. Results: For the superficial PTV, the dose homogeneity (V95%–V107%) and the mean dose (in percent of the prescribed dose) to the distal and the lateral OARs of the MBRT plan (94.9%, 16.9%, 17.8%) are superior or comparable to those for the MERT (74%, 18.4%, 15.4%) and the photon-IMRT plan (89.4%, 20.8%, 24.7%). For the enlarged PTV, the dosimetric superiority of MBRT compared to MERT and photon-IMRT is even more pronounced. Furthermore, an MBRT plan with 12 electron and 10 photon apertures lead to an objective function value 38% lower than that of a photon-IMRT plan with 40 apertures. Conclusion: The results of simultaneous optimization for MBRT are promising with regards to further OAR sparing and improved dose coverage to the PTV compared to photon-IMRT and MERT. Especially superficial targets with deeper subparts (>5 cm) could substantially benefit. Moreover, MBRT seems to be a possible solution of two downsides of photon-IMRT, namely the extended low dose bath and the requirement of numerous apertures. This work was supported by Varian Medical Systems. This work was supported by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-195: Systematic Constraining of Contralateral Parotid Gland Led to Improved Dosimetric Outcomes for Multi-Field Optimization with Scanning Beam Proton Therapy: Promising Results From a Pilot Study in Patients with Base of Tongue Carcinoma

Purpose: Treatment planning for Intensity Modulated Proton Therapy (IMPT) for head and neck cancer is time-consuming due to the large number of organs-at-risk (OAR) to be considered. As there are many competing objectives and also wide range of acceptable OAR constraints, the final approved plan may not be most optimal for the given structures. We evaluated the dose reduction to the contralateral parotid by implementing standardized constraints during optimization for scanning beam proton therapy planning. Methods: Twenty-four (24) consecutive patients previously treated for base of tongue carcinoma were retrospectively selected. The doses were 70Gy, 63Gy and 57Gy (SIB in 33 fractions) for high-, intermediate-, and standard-risk clinical target volumes (CTV), respectively; the treatment included bilateral neck. Scanning beams using MFO with standardized bilateral anterior oblique and PA fields were applied. New plans where then developed and optimized by employing additional contralateral parotid constraints at multiple defined dose levels. Using a step-wise iterative process, the volume-based constraints at each level were then further reduced until known target coverages were compromised. The newly developed plans were then compared to the original clinically approved plans using paired student t-testing. Results: All 24 newly optimized treatment plans maintained initial plan quality as compared to the approved plans, and the 98% prescription dose coverage to the CTV’s were not compromised. Representative DVH comparison is shown in FIGURE 1. The contralateral parotid doses were reduced at all levels of interest when systematic constraints were applied to V10, V20, V30 and V40Gy (All P<0.0001; TABLE 1). Overall, the mean contralateral parotid doses were reduced by 2.26 Gy on average, a ∼13% relative improvement. Conclusion: Applying systematic and volume-based contralateral parotid constraints for IMPT planning significantly reduced the dose at all dosimetric levels for patients with base of tongue cancer.

60 APPLIED LIFE SCIENCES↗