Engineering topics

Wang, J

Publications and source records attributed to Wang, J.

At least 37 records · Page 2

DOE OSTI2018

The limiting layer of fish scales: structure and properties

Fish scales serve as a flexible natural armor that have received increasing attention across the materials community. Most efforts in this area have focused on the composite structure of the predominately organic elasmodine, and limited work addresses the highly mineralized external portion known as the Limiting Layer (LL). This coating serves as the first barrier to external threats and plays an important role in resisting puncture. In this investigation the structure, composition and mechanical behavior of the LL were explored for three different fish, including the arapaima (Arapaima gigas), the tarpon (Megalops atlanticus) and the carp (Cyprinus carpio). The scales of these three fish have received the most attention within the materials community. Features of the LL were evaluated with respect to anatomical position to distinguish site-specific functional differences. Results show that there are significant differences in the surface morphology of the LL from posterior and anterior regions in the scales, and between the three fish species. The calcium to phosphorus ratio and the mineral to collagen ratios of the LL are not equivalent among the three fish. Results from nanoindentation showed that the LL of tarpon scales is the hardest, followed by the carp and the arapaima and the differences in hardness are related to the apatite structure, possibly induced by the growth rate and environment of each fish.

Arola, Dwayne D.↗

DOE OSTI2017

Parallel variable selection for effective performance prediction

Large data analysis problems often involve a large number of variables, and the corresponding analysis algorithms may examine all variable combinations to find the optimal solution. For example, to model the time required to complete a scientific workflow, we need to consider the impact of dozens of parameters. To reduce the model building time and reduce the likelihood of overfitting, we look to variable selection methods to identify the critical variables for the performance model. In this work, we create a combination of variable selection and performance prediction methods that is as effective as the exhaustive search approach when the exhaustive search could be completed in a reasonable amount of time. To handle the cases where the exhaustive search is too time consuming, we develop the parallelized variable selection algorithm. Additionally, we develop a parallel grouping mechanism that further reduces the variable selection time by 70%.As a case study, we exercise the variable selection technique with the performance measurement data from the Palomar Transient Factory (PTF) workflow. The application scientists have determined that about 50 variables and parameters are important to the performance of the workflows. Our tests show that the Sequential Backward Selection algorithm is able to approximate the optimal subset relatively quickly. By reducing the number of variables used to build the model from 50 to 4, we are able to maintain the prediction quality while reducing the model building time by a factor of 6. Using the parallelization and grouping techniques we developed in this work, the variable selection process was reduced from over 18 hours to 15 minutes while ending up with the same variable subset.

Wang, J↗

DOE OSTI2016

SU-C-207A-06: On-Line Beam Range Verification with Multiple Scanning Particle Beams: Initial Feasibility Study with Simulations

Purpose: To investigate the feasibility and requirement for intra-fraction on-line multiple scanning particle beam range verifications (BRVs) with in-situ PET imaging, which is beyond the current single-beam BRV with extra factors that will affect the BR measurement accuracy, such as beam diameter, separation between beams, and different image counts at different BRV positions. Methods: We simulated a 110-MeV proton beam with 5-mm diameter irradiating a uniform PMMA phantom by GATE simulation, which generated nuclear interaction-induced positrons. In this preliminary study, we simply duplicated these positrons and placed them next to the initial protons to approximately mimic the two spatially separated positron distributions produced by two beams parallel to each other but with different beam ranges. These positrons were then imaged by a PET (∼2-mm resolution, 10% sensitivity, 320×320×128 mm^3 FOV) with different acquisition times. We calculated the positron activity ranges (ARs) from reconstructed PET images and compared them with the corresponding ARs of original positron distributions. Results: Without further image data processing and correction, the preliminary study show the errors between the measured and original ARs varied from 0.2 mm to 2.3 mm as center-to-center separations and range differences were in the range of 8–12 mm and 2–8 mm respectively, indicating the accuracy of AR measurement strongly depends on the beam separations and range differences. In addition, it is feasible to achieve ≤ 1.0-mm accuracy for both beams with 1-min PET acquisition and 12 mm beam separation. Conclusion: This study shows that the overlap between the positron distributions from multiple scanning beams can significantly impact the accuracy of BRVs of distributed particle beams and need to be further addressed beyond the established method of single-beam BRV, but it also indicates the feasibility to achieve accurate on-line multi-beam BRV with further improved method.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-C-207B-03: A Geometrical Constrained Chan-Vese Based Tumor Segmentation Scheme for PET

Purpose: Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan-Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices. Methods: The proposed scheme performs segmentation in a slice-by-slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directly connected to organs/tissues with similar intensity values, a conventional clustering-based segmentation method under user’s guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan-Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan-Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme. Results: Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively. Conclusion: We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

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

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

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-D-206-04: Iterative CBCT Scatter Shading Correction Without Prior Information

Purpose: To estimate and remove the scatter contamination in the acquired projection of cone-beam CT (CBCT), to suppress the shading artifacts and improve the image quality without prior information. Methods: The uncorrected CBCT images containing shading artifacts are reconstructed by applying the standard FDK algorithm on CBCT raw projections. The uncorrected image is then segmented to generate an initial template image. To estimate scatter signal, the differences are calculated by subtracting the simulated projections of the template image from the raw projections. Since scatter signals are dominantly continuous and low-frequency in the projection domain, they are estimated by low-pass filtering the difference signals and subtracted from the raw CBCT projections to achieve the scatter correction. Finally, the corrected CBCT image is reconstructed from the corrected projection data. Since an accurate template image is not readily segmented from the uncorrected CBCT image, the proposed scheme is iterated until the produced template is not altered. Results: The proposed scheme is evaluated on the Catphan©600 phantom data and CBCT images acquired from a pelvis patient. The result shows that shading artifacts have been effectively suppressed by the proposed method. Using multi-detector CT (MDCT) images as reference, quantitative analysis is operated to measure the quality of corrected images. Compared to images without correction, the method proposed reduces the overall CT number error from over 200 HU to be less than 50 HU and can increase the spatial uniformity. Conclusion: An iterative strategy without relying on the prior information is proposed in this work to remove the shading artifacts due to scatter contamination in the projection domain. The method is evaluated in phantom and patient studies and the result shows that the image quality is remarkably improved. The proposed method is efficient and practical to address the poor image quality issue of CBCT images. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-D-207B-01: Radiomics Feature Reproducibility From Repeat CT Scans of Patients with Rectal Cancer

Purpose: To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer. Methods: 40 rectal cancer patients were enrolled in this study, each of whom underwent two CT scans within average 8.7 days (5 days to 17 days), before any treatment was delivered. The rectal gross tumor volume (GTV) was distinguished and segmented by an experienced oncologist in both CTs. Totally, more than 2000 radiomics features were defined in this study, which were divided into four groups (I: GLCM, II: GLRLM III: Wavelet GLCM and IV: Wavelet GLRLM). For each group, five types of features were extracted (Max slice: features from the largest slice of target images, Max value: features from all slices of target images and choose the maximum value, Min value: minimum value of features for all slices, Average value: average value of features for all slices, Matrix sum: all slices of target images translate into GLCM and GLRLM matrices and superpose all matrices, then extract features from the superposed matrix). Meanwhile a LOG (Laplace of Gauss) filter with different parameters was applied to these images. Concordance correlation coefficients (CCC) and inter-class correlation coefficients (ICC) were calculated to assess the reproducibility. Results: 403 radiomics features were extracted from each type of patients’ medical images. Features of average type are the most reproducible. Different filters have little effect for radiomics features. For the average type features, 253 out of 403 features (62.8%) showed high reproducibility (ICC≥0.8), 133 out of 403 features (33.0%) showed medium reproducibility (0.8≥ICC≥0.5) and 17 out of 403 features (4.2%) showed low reproducibility (ICC≥0.5). Conclusion: The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and prognosis prediction.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidential reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom

Purpose: To investigate the sensitivity of classic texture features to variations of MRI acquisition parameters. Methods: This study was performed on American College of Radiology (ACR) MRI Accreditation Program Phantom. MR imaging was acquired on a GE 750 3T scanner with XRM explain gradient, employing a T1-weighted images (TR/TE=500/20ms) with the following parameters as the reference standard: number of signal average (NEX) = 1, matrix size = 256×256, flip angle = 90°, slice thickness = 5mm. The effect of the acquisition parameters on texture features with and without non-uniformity correction were investigated respectively, while all the other parameters were kept as reference standard. Protocol parameters were set as follows: (a). NEX = 0.5, 2 and 4; (b).Phase encoding steps = 128, 160 and 192; (c). Matrix size = 128×128, 192×192 and 512×512. 32 classic texture features were generated using the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from each image data set. Normalized range ((maximum-minimum)/mean) was calculated to determine variation among the scans with different protocol parameters. Results: For different NEX, 31 out of 32 texture features’ range are within 10%. For different phase encoding steps, 31 out of 32 texture features’ range are within 10%. For different acquisition matrix size without non-uniformity correction, 14 out of 32 texture features’ range are within 10%; for different acquisition matrix size with non-uniformity correction, 16 out of 32 texture features’ range are within 10%. Conclusion: Initial results indicated that those texture features that range within 10% are less sensitive to variations in T1-weighted MRI acquisition parameters. This might suggest that certain texture features might be more reliable to be used as potential biomarkers in MR quantitative image analysis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-R-33: Can CT and CBCT Be Used Simultaneously for Radiomics Analysis

Purpose: To investigate whether CBCT and CT can be used in radiomics analysis simultaneously. To establish a batch correction method for radiomics in two similar image modalities. Methods: Four sites including rectum, bladder, femoral head and lung were considered as region of interest (ROI) in this study. For each site, 10 treatment planning CT images were collected. And 10 CBCT images which came from same site of same patient were acquired at first radiotherapy fraction. 253 radiomics features, which were selected by our test-retest study at rectum cancer CT (ICC>0.8), were calculated for both CBCT and CT images in MATLAB. Simple scaling (z-score) and nonlinear correction methods were applied to the CBCT radiomics features. The Pearson Correlation Coefficient was calculated to analyze the correlation between radiomics features of CT and CBCT images before and after correction. Cluster analysis of mixed data (for each site, 5 CT and 5 CBCT data are randomly selected) was implemented to validate the feasibility to merge radiomics data from CBCT and CT. The consistency of clustering result and site grouping was verified by a chi-square test for different datasets respectively. Results: For simple scaling, 234 of the 253 features have correlation coefficient ρ>0.8 among which 154 features haveρ>0.9 . For radiomics data after nonlinear correction, 240 of the 253 features have ρ>0.8 among which 220 features have ρ>0.9. Cluster analysis of mixed data shows that data of four sites was almost precisely separated for simple scaling(p=1.29 * 10{sup −7}, χ{sup 2} test) and nonlinear correction (p=5.98 * 10{sup −7}, χ{sup 2} test), which is similar to the cluster result of CT data (p=4.52 * 10{sup −8}, χ{sup 2} test). Conclusion: Radiomics data from CBCT can be merged with those from CT by simple scaling or nonlinear correction for radiomics analysis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-R-46: Predicting Distant Failure in Lung SBRT Using Multi-Objective Radiomics Model

Purpose: To predict distant failure in lung stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC) by using a new multi-objective radiomics model. Methods: Currently, most available radiomics models use the overall accuracy as the objective function. However, due to data imbalance, a single object may not reflect the performance of a predictive model. Therefore, we developed a multi-objective radiomics model which considers both sensitivity and specificity as the objective functions simultaneously. The new model is used to predict distant failure in lung SBRT using 52 patients treated at our institute. Quantitative imaging features of PET and CT as well as clinical parameters are utilized to build the predictive model. Image features include intensity features (9), textural features (12) and geometric features (8). Clinical parameters for each patient include demographic parameters (4), tumor characteristics (8), treatment faction schemes (4) and pretreatment medicines (6). The modelling procedure consists of two steps: extracting features from segmented tumors in PET and CT; and selecting features and training model parameters based on multi-objective. Support Vector Machine (SVM) is used as the predictive model, while a nondominated sorting-based multi-objective evolutionary computation algorithm II (NSGA-II) is used for solving the multi-objective optimization. Results: The accuracy for PET, clinical, CT, PET+clinical, PET+CT, CT+clinical, PET+CT+clinical are 71.15%, 84.62%, 84.62%, 85.54%, 82.69%, 84.62%, 86.54%, respectively. The sensitivities for the above seven combinations are 41.76%, 58.33%, 50.00%, 50.00%, 41.67%, 41.67%, 58.33%, while the specificities are 80.00%, 92.50%, 90.00%, 97.50%, 92.50%, 97.50%, 97.50%. Conclusion: A new multi-objective radiomics model for predicting distant failure in NSCLC treated with SBRT was developed. The experimental results show that the best performance can be obtained by combining all features.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-R-56: Early Assessment of Treatment Response During Radiation Therapy Delivery for Esophageal Cancer Using Quantitative CT

Purpose: To investigate the feasibility of assessing treatment response using CTs during delivery of radiation therapy (RT) for esophageal cancer. Methods: Daily CTs acquired using a CT-on-Rails during the routine CT-guided RT for 20 patients with stage II to IV esophageal cancers were analyzed. All patients were treated with combined chemotherapy and IMRT of 45–50 Gy in 25 fractions, and were followed up for two years. Contours of GTV, spinal cord, and non-specified tissue (NST) irradiated with low dose were generated on each daily CT. A series of CT-texture metrics including Hounsfield Unit (HU) histogram, mean HU, standard derivation (STD), entropy, and energy were obtained in these contours on each daily CT. The changes of these metrics and GTV volume during RT delivery were calculated and correlated with treatment outcome. Results: Changes in CT texture (e.g., HU histogram) in GTV and spinal cord (but not in NST) were observed during RT delivery and were consistently increased with radiation dose. For the 20 cases studied, the mean HU in GTV was reduced on average by 4.0HU from the first to the last fractions, while 8 patients (responders) had larger reductions in GTV mean HU (average 7.8 HU) with an average GTV reduction of 51% and had increased consistently in GTV STD and entropy with radiation dose. The rest of 12 patients (non-responders) had lower reductions in GTV mean HU (average 1.5HU) and almost no change in STD and entropy. For the 8 responders, 2 experienced complete response, 7 (88%) survived and 1 died. In contrast, for the 12 non-responders, 4 (33%) survived and 8 died. Conclusion: Radiation can induce changes in CT texture in tumor (e.g., mean HU) during the delivery of RT for esophageal cancer. If validated with more data, such changes may be used for early prediction of RT response for esophageal cancer.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-143: Initial Assessment of Image Quality of An Integrated MR-Linac System with ACR Phantom

Purpose/Objective(s): To assess the image quality of an integrated MR-Linac system and compare with other MRI systems that are primarily used for diagnostic purposes. Materials/Methods: An ACR MRI quality control (QC) phantom was used to evaluate the image quality of a fully integrated 1.5T MRI-Linac system recently installed at our institution. This system has a new split magnet design which gives the magnetic field strength of 1.5T. All images were acquired with a set of phased-array surface coils which are designed to have minimal attention of radiation beam. The anterior coil rests on a coil holder which keeps the anterior coil’s position consistent for QA purposes. The posterior coil is imbedded in the patient couch. Multiple sets of T1, T2/PD images were acquired using the protocols as prescribed by the ACR on three different dates, ranging 3 months apart. Results: The geometric distortion are within 0.5 mm in the axial scans and within 1mm in the saggital (z-direction) scans. Slice thickness accuracy, image uniformity, ghosting ratio, high contrast detectability are comparable to other 1.5T diagnostic MRI scanners. The low-contrast object detectability are lower comparatively, which is a result of using the body array coil. Additionally, the beam’s-eye-view images (oblique coronal and saggital images) have minimal geometric distortion at all linac gantry angles tested. No observable changes or drift in image quality is found from images acquired 3 month apart. Conclusion: Despite the use of a body array surface coil, the image quality is comparable to that of an 1.5T MRI scanner and is of sufficient quality to pass the ACR MRI accreditation program. The geometric distortion of the MRI system of the integrated MR-Linac is within 1mm for an object size similar to the ACR phantom, sufficient for radiation therapy treatment purpose. The authors received corporate sponsored research grants from Elekta which is the vendor for the MR-Linac evaluated in this study.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-144: Scatter and Leakage Survey of An Integrated MR-Linac System

Purpose: To assess the scatter and leakage radiation of an integrated 1.5T MRI-Linac system. Methods: A 150cc chamber (model 96020C, Inovision) was used in all the scatter and leakage measurements, after being recalibrated for MV energy by the Accredited Dosimetry Calibration Laboratory at MD Anderson. The scatter radiation was measured by placing a 25 cm stack of solid-water materials at iso-center on the patient couch to simulate patient scatter. Gantry angles were positioned at 0 degree (beam pointing downward) and 270 (beam pointing laterally). Scatter radiation was measured at selective locations inside the RF room. Beam stopper leakage was measured at the exterior panel of the gantry. The head leakage was measured at 1 meter away from the Linac head in the direction which was determined to be the area of maximum leakage by wrapped films test. All measurements were repeated with the 1.5T magnetic field turned off to study the effect of magnetic field. Results: When the magnet was on (B=1.5T), the maximum head leakage at 1 meter was 191.6mR/1000MU. The scatter radiation at 1 meter from the iso-center was 1.091R/1000MU when the radiation beam was pointing downward, 1.296R/1000MU when the beam pointed laterally. The beam stopper leakage was measured as 299.4 mR/1000MU at the exterior panel of the gantry. When magnet was off (B=0), the head leakage was measured as 198.6mR/1000MU. The scatter radiation at 1 meter was 1.153R/1000MU when beam pointed downward, 1.287R/1000MU when beam pointed laterally. The beam stopper leakage was measured as 309.4 mR/1000MU at the exterior panel of the gantry. Conclusion: The measurements indicate that the scatter and leakage radiation from the integrated MR-Linac system are in-line with the expected values. The beam stopper leakage is approximately 300 mR/1000MU. The leakage and scatter difference with the magnetic field ON and OFF was within 5%. The authors received a corporate sponsored grant from Elekta which is the vendor of the MR-Linac system studied in this work.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-192: Study of Robustness Analysis Method of Multiple Field Optimized IMPT Plans for Head & Neck Patients

Purpose: Proton therapy is more sensitive to uncertainties than photon treatments due to protons’ finite range depending on the tissue density. Worst case scenario (WCS) method originally proposed by Lomax has been adopted in our institute for robustness analysis of IMPT plans. This work demonstrates that WCS method is sufficient enough to take into account of the uncertainties which could be encountered during daily clinical treatment. Methods: A fast and approximate dose calculation method is developed to calculate the dose for the IMPT plan under different setup and range uncertainties. Effects of two factors, inversed square factor and range uncertainty, are explored. WCS robustness analysis method was evaluated using this fast dose calculation method. The worst-case dose distribution was generated by shifting isocenter by 3 mm along x,y and z directions and modifying stopping power ratios by ±3.5%. 1000 randomly perturbed cases in proton range and x, yz directions were created and the corresponding dose distributions were calculated using this approximated method. DVH and dosimetric indexes of all 1000 perturbed cases were calculated and compared with the result using worst case scenario method. Results: The distributions of dosimetric indexes of 1000 perturbed cases were generated and compared with the results using worst case scenario. For D95 of CTVs, at least 97% of 1000 perturbed cases show higher values than the one of worst case scenario. For D5 of CTVs, at least 98% of perturbed cases have lower values than worst case scenario. Conclusion: By extensively calculating the dose distributions under random uncertainties, WCS method was verified to be reliable in evaluating the robustness level of MFO IMPT plans of H&N patients. The extensively sampling approach using fast approximated method could be used in evaluating the effects of different factors on the robustness level of IMPT plans in the future.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-199: A New Strategy for Integrating Photon with Proton and Carbon Ion in the Treatment Planning

Purpose: The aim of this study was to develop a viable strategy to integrate photon plan and proton/carbon ion plan based on deformable registration. Methods: Two prostate cancer patients were enrolled in this study. Each patient has 2 CTs, which were input in the Raystation radiotherapy treatment planning system (TPS). CT1 was deformed to the second CT2 using the Hybrid deformation method. The dice similarity coefficient (DSC) parameter was used to evaluate the difference between the actual structures (bladder, rectum and CTV) and the corresponding deformed structures on CT2. The prescription dose was 63.02GyE to CTV, which included 49.32GyE for CTV1 with carbon and boost 13.7Gy for CTV2 with photon. The carbon plan was made first in Syngo TPS (Syngo PT Planning system, version VB10. Siemens, Germany) on CT1 and transferred to Raystation TPS. Selected Isodoses (23.5Gy, 36.8Gy, 39.1Gy, 47.0Gy and 49.3Gy) of carbon plan were converted to contours and then deformed to CT2, which was used as normal tissues for photon plan optimization on CT2. The final plan was the combination of photon plan and the carbon deformation plan on the CT2. The plan from this strategy was compared with direct optimization of the photon plan on CT2 added some clinical endpoints from carbon plan on CT1. Results: The new strategy with deformable registration is tested and combined plans were successfully obtained for the 2 patients. This strategy obtained both integrated DVH and dose distribution information. For patient 1, the rectum V30, V60 and bladder V63 were 45.8, 10.3 and 9.7 for the combined plan with deformation and 48.1, 11.0 and 12.0 for the direct photon plan. Conclusion: The new strategy for combining photon and carbon/proton is feasible. However, the clinical accuracy is still need more evaluation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-229: A Novel Method for EPID-Based In-Vivo Exit Dose Verification for Intensity Modulated Radiotherapy

Purpose: Electronic portal imaging device (EPID) can be used to acquire a two-dimensional exit dose distribution during treatment delivery, thus allowing the in-vivo verification of the dose delivery through a comparison of measured portal images to predicted portal dose images (PDI). The aim of this study was to present a novel method to easily and accurately predict PDI, and to establish an EPID-based in-vivo dose verification method during IMRT treatments. Methods: We developed a model to determine the predicted portal dose at the same plane of the EPID detector location. The Varian EPID (aS1000) positions at 150cm source-to-detector-distance (SDD), and can be used to acquire in-vivo exit dose using Portal Dosimetry (PD) function. Our model was generated to make an equivalent water thickness represent the buildup plate of EPID. The exit dose at extend SDD plane with patient CT data in the beam can be calculated as the predicted PDI in the treatment planning system (TPS). After that, the PDI was converted to the fluence at SDD of 150cm using the inverse square law coded in MATLAB. Five head-and-neck and prostate IMRT patient plans contain 32 fields were investigated to evaluate the feasibility of this new method. The measured EPID image was compared with PDI using the gamma analysis. Results: The average results for cumulative dose comparison were 81.9% and 91.6% for 3%, 3mm and 4%, 4mm gamma criteria, respectively. Results indicate that the patient transit dosimetry predicted algorithm compares well with EPID measured PD doses for test situations. Conclusion: Our new method can be used as an easy and feasible tool for online EPID-based in-vivo dose delivery verification for IMRT treatments. It can be implemented for fast detecting those obvious treatment delivery errors for individual field and patient quality assurance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-245: The Investigation of Failure Mode and Effects Analysis and PDCA for the Radiotherapy Risk Reduction

Purpose: To optimize the clinical processes of radiotherapy and to reduce the radiotherapy risks by implementing the powerful risk management tools of failure mode and effects analysis(FMEA) and PDCA(plan-do-check-act). Methods: A multidiciplinary QA(Quality Assurance) team from our department consisting of oncologists, physicists, dosimetrists, therapists and administrator was established and an entire workflow QA process management using FMEA and PDCA tools was implemented for the whole treatment process. After the primary process tree was created, the failure modes and Risk priority numbers(RPNs) were determined by each member, and then the RPNs were averaged after team discussion. Results: 3 of 9 failure modes with RPN above 100 in the practice were identified in the first PDCA cycle, which were further analyzed to investigate the RPNs: including of patient registration error, prescription error and treating wrong patient. New process controls reduced the occurrence, or detectability scores from the top 3 failure modes. Two important corrective actions reduced the highest RPNs from 300 to 50, and the error rate of radiotherapy decreased remarkably. Conclusion: FMEA and PDCA are helpful in identifying potential problems in the radiotherapy process, which was proven to improve the safety, quality and efficiency of radiation therapy in our department. The implementation of the FMEA approach may improve the understanding of the overall process of radiotherapy while may identify potential flaws in the whole process. Further more, repeating the PDCA cycle can bring us closer to the goal: higher safety and accuracy radiotherapy.

60 APPLIED LIFE SCIENCES↗