Triboelectric Nanogenerators: Polymer Nanocomposite Materials for Charge Generation
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Xu, X
Publications and source records attributed to Xu, X.
SU-D-202-04: Validation of Deformable Image Registration Algorithms for Head and Neck Adaptive Radiotherapy in Routine Clinical Setting
Purpose: To evaluate the ROI contours and accumulated dose difference using different deformable image registration (DIR) algorithms for head and neck (H&N) adaptive radiotherapy. Methods: Eight H&N cancer patients were randomly selected from the affiliated hospital. During the treatment, patients were rescanned every week with ROIs well delineated by radiation oncologist on each weekly CT. New weekly treatment plans were also re-designed with consistent dose prescription on the rescanned CT and executed for one week on Siemens CT-on-rails accelerator. At the end, we got six weekly CT scans from CT1 to CT6 including six weekly treatment plans for each patient. The primary CT1 was set as the reference CT for DIR proceeding with the left five weekly CTs using ANACONDA and MORFEUS algorithms separately in RayStation and the external skin ROI was set to be the controlling ROI both. The entire calculated weekly dose were deformed and accumulated on corresponding reference CT1 according to the deformation vector field (DVFs) generated by the two different DIR algorithms respectively. Thus we got both the ANACONDA-based and MORFEUS-based accumulated total dose on CT1 for each patient. At the same time, we mapped the ROIs on CT1 to generate the corresponding ROIs on CT6 using ANACONDA and MORFEUS DIR algorithms. DICE coefficients between the DIR deformed and radiation oncologist delineated ROIs on CT6 were calculated. Results: For DIR accumulated dose, PTV D95 and Left-Eyeball Dmax show significant differences with 67.13 cGy and 109.29 cGy respectively (Table1). For DIR mapped ROIs, PTV, Spinal cord and Left-Optic nerve show difference with −0.025, −0.127 and −0.124 (Table2). Conclusion: Even two excellent DIR algorithms can give divergent results for ROI deformation and dose accumulation. As more and more TPS get DIR module integrated, there is an urgent need to realize the potential risk using DIR in clinical.
60 APPLIED LIFE SCIENCES↗
SU-F-T-347: An Absolute Dose-Volume Constraint Based Deterministic Optimization Framework for Multi-Co60 Source Focused Radiotherapy
Purpose: Treatment plan optimization in multi-Co60 source focused radiotherapy with multiple isocenters is challenging, because dose distribution is normalized to maximum dose during optimization and evaluation. The objective functions are traditionally defined based on relative dosimetric distribution. This study presents an alternative absolute dose-volume constraint (ADC) based deterministic optimization framework (ADC-DOF). Methods: The initial isocenters are placed on the eroded target surface. Collimator size is chosen based on the area of 2D contour on corresponding axial slice. The isocenter spacing is determined by adjacent collimator sizes. The weights are optimized by minimizing the deviation from ADCs using the steepest descent technique. An iterative procedure is developed to reduce the number of isocenters, where the isocenter with lowest weight is removed without affecting plan quality. The ADC-DOF is compared with the genetic algorithm (GA) using the same arbitrary shaped target (254cc), with a 15mm margin ring structure representing normal tissues. Results: For ADC-DOF, the ADCs imposed on target and ring are (D100>10Gy, D50,10, 0<12Gy, 15Gy and 20Gy) and (D40<10Gy). The resulting D100, 50, 10, 0 and D40 are (9.9Gy, 12.0Gy, 14.1Gy and 16.2Gy) and (10.2Gy). The objectives of GA are to maximize 50% isodose target coverage (TC) while minimize the dose delivered to the ring structure, which results in 97% TC and 47.2% average dose in ring structure. For ADC-DOF (GA) techniques, 20 out of 38 (10 out of 12) initial isocenters are used in the final plan, and the computation time is 8.7s (412.2s) on an i5 computer. Conclusion: We have developed a new optimization technique using ADC and deterministic optimization. Compared with GA, ADC-DOF uses more isocenters but is faster and more robust, and achieves a better conformity. For future work, we will focus on developing a more effective mechanism for initial isocenter determination.
60 APPLIED LIFE SCIENCES↗
SU-F-T-620: Development of a Convolution/Superposition Dose Engine for CyberKnife System
Purpose: Current CyberKnife treatment planning system (TPS) provided two dose calculation algorithms: Ray-tracing and Monte Carlo. Ray-tracing algorithm is fast, but less accurate, and also can’t handle irregular fields since a multi-leaf collimator system was recently introduced to CyberKnife M6 system. Monte Carlo method has well-known accuracy, but the current version still takes a long time to finish dose calculations. The purpose of this paper is to develop a GPU-based fast C/S dose engine for CyberKnife system to achieve both accuracy and efficiency. Methods: The TERMA distribution from a poly-energetic source was calculated based on beam’s eye view coordinate system, which is GPU friendly and has linear complexity. The dose distribution was then computed by inversely collecting the energy depositions from all TERMA points along 192 collapsed-cone directions. EGSnrc user code was used to pre-calculate energy deposition kernels (EDKs) for a series of mono-energy photons The energy spectrum was reconstructed based on measured tissue maximum ratio (TMR) curve, the TERMA averaged cumulative kernels was then calculated. Beam hardening parameters and intensity profiles were optimized based on measurement data from CyberKnife system. Results: The difference between measured and calculated TMR are less than 1% for all collimators except in the build-up regions. The calculated profiles also showed good agreements with the measured doses within 1% except in the penumbra regions. The developed C/S dose engine was also used to evaluate four clinical CyberKnife treatment plans, the results showed a better dose calculation accuracy than Ray-tracing algorithm compared with Monte Carlo method for heterogeneous cases. For the dose calculation time, it takes about several seconds for one beam depends on collimator size and dose calculation grids. Conclusion: A GPU-based C/S dose engine has been developed for CyberKnife system, which was proven to be efficient and accurate for clinical purpose, and can be easily implemented in TPS.
60 APPLIED LIFE SCIENCES↗
SU-G-BRC-13: Model Based Classification for Optimal Position Selection for Left-Sided Breast Radiotherapy: Free Breathing, DIBH, Or Prone
Purpose: There are clinical decision challenges to select optimal treatment positions for left-sided breast cancer patients—supine free breathing (FB), supine Deep Inspiration Breath Hold (DIBH) and prone free breathing (prone). Physicians often make the decision based on experiences and trials, which might not always result optimal OAR doses. We herein propose a mathematical model to predict the lowest OAR doses among these three positions, providing a quantitative tool for corresponding clinical decision. Methods: Patients were scanned in FB, DIBH, and prone positions under an IRB approved protocol. Tangential beam plans were generated for each position, and OAR doses were calculated. The position with least OAR doses is defined as the optimal position. The following features were extracted from each scan to build the model: heart, ipsilateral lung, breast volume, in-field heart, ipsilateral lung volume, distance between heart and target, laterality of heart, and dose to heart and ipsilateral lung. Principal Components Analysis (PCA) was applied to remove the co-linearity of the input data and also to lower the data dimensionality. Feature selection, another method to reduce dimensionality, was applied as a comparison. Support Vector Machine (SVM) was then used for classification. Thirtyseven patient data were acquired; up to now, five patient plans were available. K-fold cross validation was used to validate the accuracy of the classifier model with small training size. Results: The classification results and K-fold cross validation demonstrated the model is capable of predicting the optimal position for patients. The accuracy of K-fold cross validations has reached 80%. Compared to PCA, feature selection allows causal features of dose to be determined. This provides more clinical insights. Conclusion: The proposed classification system appeared to be feasible. We are generating plans for the rest of the 37 patient images, and more statistically significant results are to be presented.
60 APPLIED LIFE SCIENCES↗
SU-G-TeP1-08: LINAC Head Geometry Modeling for Cyber Knife System
Purpose: Knowledge of the LINAC head information is critical for model based dose calculation algorithms. However, the geometries are difficult to measure precisely. The purpose of this study is to develop linac head models for Cyber Knife system (CKS). Methods: For CKS, the commissioning data were measured in water at 800mm SAD. The measured full width at half maximum (FWHM) for each cone was found greater than the nominal value, this was further confirmed by additional film measurement in air. Diameter correction, cone shift and source shift models (DCM, CSM and SSM) are proposed to account for the differences. In DCM, a cone-specific correction is applied. For CSM and SSM, a single shift is applied to the cone or source physical position. All three models were validated with an in-house developed pencil beam dose calculation algorithm, and further evaluated by the collimator scatter factor (Sc) correction. Results: The mean square error (MSE) between nominal diameter and the FWHM derived from commissioning data and in-air measurement are 0.54mm and 0.44mm, with the discrepancy increasing with cone size. Optimal shift for CSM and SSM is found to be 9mm upward and 18mm downward, respectively. The MSE in FWHM is reduced to 0.04mm and 0.14mm for DCM and CSM (SSM). Both DCM and CSM result in the same set of Sc values. Combining all cones at SAD 600–1000mm, the average deviation from 1 in Sc of DCM (CSM) and SSM is 2.6% and 2.2%, and reduced to 0.9% and 0.7% for the cones with diameter greater than 15mm. Conclusion: We developed three geometrical models for CKS. All models can handle the discrepancy between vendor specifications and commissioning data. And SSM has the best performance for Sc correction. The study also validated that a point source can be used in CKS dose calculation algorithms.
60 APPLIED LIFE SCIENCES↗
TU-AB-BRC-10: Modeling of Radiotherapy Linac Source Terms Using ARCHER Monte Carlo Code: Performance Comparison of GPU and MIC Computing Accelerators
Purpose: (1) To perform phase space (PS) based source modeling for Tomotherapy and Varian TrueBeam 6 MV Linacs, (2) to examine the accuracy and performance of the ARCHER Monte Carlo code on a heterogeneous computing platform with Many Integrated Core coprocessors (MIC, aka Xeon Phi) and GPUs, and (3) to explore the software micro-optimization methods. Methods: The patient-specific source of Tomotherapy and Varian TrueBeam Linacs was modeled using the PS approach. For the helical Tomotherapy case, the PS data were calculated in our previous study (Su et al. 2014 41(7) Medical Physics). For the single-view Varian TrueBeam case, we analytically derived them from the raw patient-independent PS data in IAEA’s database, partial geometry information of the jaw and MLC as well as the fluence map. The phantom was generated from DICOM images. The Monte Carlo simulation was performed by ARCHER-MIC and GPU codes, which were benchmarked against a modified parallel DPM code. Software micro-optimization was systematically conducted, and was focused on SIMD vectorization of tight for-loops and data prefetch, with the ultimate goal of increasing 512-bit register utilization and reducing memory access latency. Results: Dose calculation was performed for two clinical cases, a Tomotherapy-based prostate cancer treatment and a TrueBeam-based left breast treatment. ARCHER was verified against the DPM code. The statistical uncertainty of the dose to the PTV was less than 1%. Using double-precision, the total wall time of the multithreaded CPU code on a X5650 CPU was 339 seconds for the Tomotherapy case and 131 seconds for the TrueBeam, while on 3 5110P MICs it was reduced to 79 and 59 seconds, respectively. The single-precision GPU code on a K40 GPU took 45 seconds for the Tomotherapy dose calculation. Conclusion: We have extended ARCHER, the MIC and GPU-based Monte Carlo dose engine to Tomotherapy and Truebeam dose calculations.
60 APPLIED LIFE SCIENCES↗
TU-D-209-07: Monte Carlo Assessment of Dose to the Lens of the Eye of Radiologist Using Realistic Phantoms and Eyeglass Models
Purpose: To study how eyeglass design features and postures of the interventional radiologist affect the radiation dose to the lens of the eye. Methods: A mesh-based deformable phantom, consisting of an ultra-fine eye model, was used to simulate postures of a radiologist in fluoroscopically guided interventional procedure (facing the patient, 45 degree to the left, and 45 degree to the right). Various eyewear design features were studied, including the shape, lead-equivalent thickness, and separation from the face. The MCNPX Monte Carlo code was used to simulate the X-ray source used for the transcatheter arterial chemoembolization procedure (The X-ray tube is located 35 cm from the ground, emitting X-rays toward to the ceiling; Field size is 40cm X 40cm; X-ray tube voltage is 90 kVp). Experiments were also performed using dosimeter placed on a physical phantom behind eyeglasses. Results: Without protective eyewear, the radiologist’s eye lens can receive an annual dose equivalent of about 80 mSv. When wearing a pair of lead eyeglasses with lead-equivalent of 0.5-mm Pb, the annual dose equivalent of the eye lens is reduced to 31.47 mSv, but both exceed the new ICRP limit of 20 mSv. A face shield with a lead-equivalent of 0.125-mm Pb in the shape of a semi-cylinder (13cm in radius and 20-cm in height) would further reduce the exposure to the lens of the eye. Examination of postures and eyeglass features reveal surprising information, including that the glass-to-eye separation also plays an important role in the dose to the eye lens from scattered X-ray from underneath and the side. Results are in general agreement with measurements. Conclusion: There is an urgent need to further understand the relationship between the radiation environment and the radiologist’s eyewear and posture in order to provide necessary protection to the interventional radiologists under newly reduced dose limits.
60 APPLIED LIFE SCIENCES↗
TH-AB-207A-07: Radiation Dose Simulation for a Newly Proposed Dynamic Bowtie Filters for CT Using Fast Monte Carlo Methods
Purpose: Dynamic bowtie filter is an innovative design capable of modulating the X-ray and balancing the flux in the detectors, and it introduces a new way of patient-specific CT scan optimizations. This study demonstrates the feasibility of performing fast Monte Carlo dose calculation for a type of dynamic bowtie filter for cone-beam CT (Liu et al. 2014 9(7) PloS one) using MIC coprocessors. Methods: The dynamic bowtie filter in question consists of a highly attenuating bowtie component (HB) and a weakly attenuating bowtie (WB). The HB is filled with CeCl3 solution and its surface is defined by a transcendental equation. The WB is an elliptical cylinder filled with air and immersed in the HB. As the scanner rotates, the orientation of WB remains the same with the static patient. In our Monte Carlo simulation, the HB was approximated by 576 boxes. The phantom was a voxelized elliptical cylinder composed of PMMA and surrounded by air (44cm×44cm×40cm, 1000×1000×1 voxels). The dose to the PMMA phantom was tallied with 0.15% statistical uncertainty under 100 kVp source. Two Monte Carlo codes ARCHER and MCNP-6.1 were compared. Both used double-precision. Compiler flags that may trade accuracy for speed were avoided. Results: The wall time of the simulation was 25.4 seconds by ARCHER on a 5110P MIC, 40 seconds on a X5650 CPU, and 523 seconds by the multithreaded MCNP on the same CPU. The high performance of ARCHER is attributed to the parameterized geometry and vectorization of the program hotspots. Conclusion: The dynamic bowtie filter modeled in this study is able to effectively reduce the dynamic range of the detected signals for the photon-counting detectors. With appropriate software optimization methods, the accelerator-based (MIC and GPU) Monte Carlo dose engines have shown good performance and can contribute to patient-specific CT scan optimizations.
60 APPLIED LIFE SCIENCES↗
SU-E-I-37: Eye Lens Dose Reduction From CT Scan Using Organ Based Tube Current Modulation
Purpose: To investigate the eye lens dose reduction by CT scan with organ based tube current modulation (OBTCM) using GPU Monte Carlo code ARCHER-CT. Methods: 36 X-ray sources and bowtie filters were placed around the patient head with the projection angle interval of 10° for one rotation of CT scan, each projection was simulated respectively. The voxel eye models with high resolution(0.1mm*0.1mm*0.1mm) were used in the simulation and different tube voltage including 80kVp, 100kVp, 120kVp and 140kVp were taken into consideration. Results: The radiation doses to the eye lens increased with the tube voltage raised from 80kVp to 140kVp, and the dose results from 0° (AP) direction are much higher than those from 180° (PA) direction for all the 4 different tube voltage investigated. This 360° projection dose characteristic enables organ based TCM, which can reduce the eye lens dose by more than 55%. Conclusion: As the eye lens belongs to superficial tissues, its radiation dose to external exposure like CT is direction sensitive, and this characteristic feature makes organ based TCM to be an effective way to reduce the eye lens dose, so more clinical use of this technique were recommended. National Nature Science Foundation of China(No.11475047)
60 APPLIED LIFE SCIENCES↗
SU-F-BRB-02: Towards Quantitative Clinical Decision On Deep Inspiration Breath Hold (DIBH) Or Prone for Left-Sided Breast Irradiation
Purpose: To develop quantitative clinical guidelines between supine Deep Inspiratory Breath Hold (DIBH) and prone free breathing treatments for breast patients, we applied 3D deformable phantoms to perform Monte Carlo simulation to predict corresponding Dose to the Organs at Risk (OARs). Methods: The RPI-adult female phantom (two selected cup sizes: A and D) was used to represent the female patient, and it was simulated using the MCNP6 Monte Carlo code. Doses to OARs were investigated for supine DIBH and prone treatments, considering two breast sizes. The fluence maps of the 6-MV opposed tangential fields were exported. In the Monte Carlo simulation, the fluence maps allow each simulated photon particle to be weighed in the final dose calculation. The relative error of all dose calculations was kept below 5% by simulating 3*10{sup 7} photons for each projection. Results: In terms of dosimetric accuracy, the RPI Adult Female phantom with cup size D in DIBH positioning matched with a DIBH treatment plan of the patient. Based on the simulation results, for cup size D phantom, prone positioning reduced the cardiac dose and the dose to other OARs, while cup size A phantom benefits more from DIBH positioning. Comparing simulation results for cup size A and D phantom, dose to OARs was generally higher for the large breast size due to increased scattering arising from a larger portion of the body in the primary beam. The lower dose that was registered for the heart in the large breast phantom in prone positioning was due to the increase of the distance between the heart and the primary beam when the breast was pendulous. Conclusion: Our 3D deformable phantom appears an excellent tool to predict dose to the OARs for the supine DIBH and prone positions, which might help quantitative clinical decisions. Further investigation will be conducted. National Institutes of Health R01EB015478.
60 APPLIED LIFE SCIENCES↗
SU-F-207-03: Dosimetric Effect of the Position of Arms in Torso CT Scan with Tube Current Modulation
Purpose: To evaluate the patient organ dose differences between the arms-raised and arms-lowered postures in Torso multidetector computed tomography (MDCT) scan protocols with tube current modulation (TCM). Methods: Patient CT organ doses were simulated using the Monte Carlo method with human phantoms and a validated CT scanner model. A set of adult human phantoms with arms raised and arms lowered postures were developed using advanced BREP-based mesh surface geometries. Organ doses from routine Torso scan protocols such as chest, abdomen-pelvis, and CAP scans were simulated. The organ doses differences caused by two different posutres were investigated when tube current modulation (TCM) were applied during the CT scan. Results: With TCM applied, organ doses of all the listed organs of arms-lowered posture phantom are larger than those of arms raised phantom. The dose difference for most of the organs or tissues are larger than 50%, and the skin doses difference for abdomen-pelvis scan even reaches 112.03%. This is due to the fact that the tube current for patient with arms-lowered is much higher than for the arms raised posture. Conclusion: Considering CT scan with TCM, which is commonly applied clinically, patients who could not raise their arms will receive higher radiation dose than the arms raised patient, with dose differences for some tissues such as the skin being larger than 100%. This is due to the additional tube current necessary to penetrate the arms while maintaining consistent image quality. National Nature Science Foundation of China(No.11475047)
60 APPLIED LIFE SCIENCES↗
TU-EF-204-09: A Preliminary Method of Risk-Informed Optimization of Tube Current Modulation for Dose Reduction in CT
Purpose: X-rays from CT scans can increase cancer risk to patients. Lifetime Attributable Risk of Cancer Incidence for adult patients has been investigated and shown to decrease as patient age. However, a new risk model shows an increasing risk trend for several radiosensitive organs for middle age patients. This study investigates the feasibility of a general method for optimizing tube current modulation (TCM) functions to minimize risk by reducing radiation dose to radiosensitive organs of patients. Methods: Organ-based TCM has been investigated in literature for eye lens dose and breast dose. Adopting the concept in organ-based TCM, this study seeks to find an optimized tube current for minimal total risk to breasts and lungs by reducing dose to these organs. The contributions of each CT view to organ dose are determined through simulations of CT scan view-by-view using a GPU-based fast Monte Carlo code, ARCHER. A Linear Programming problem is established for tube current optimization, with Monte Carlo results as weighting factors at each view. A pre-determined dose is used as upper dose boundary, and tube current of each view is optimized to minimize the total risk. Results: An optimized tube current is found to minimize the total risk of lungs and breasts: compared to fixed current, the risk is reduced by 13%, with breast dose reduced by 38% and lung dose reduced by 7%. The average tube current is maintained during optimization to maintain image quality. In addition, dose to other organs in chest region is slightly affected, with relative change in dose smaller than 10%. Conclusion: Optimized tube current plans can be generated to minimize cancer risk to lungs and breasts while maintaining image quality. In the future, various risk models and greater number of projections per rotation will be simulated on phantoms of different gender and age. National Institutes of Health R01EB015478.
60 APPLIED LIFE SCIENCES↗
TU-F-CAMPUS-T-02: Risk Assessment of Scattered Neutrons for a Fetus From Proton Therapy of a Brain Tumor During Pregnancy
Purpose: To determine the scattered neutron dose and the resulting risk for a fetus from proton therapy for brain tumors during pregnancy. Methods: Using the Monte Carlo platform TOPAS, the ICRP reference parameters based anthropomorphic pregnancy phantoms for three stages (3-, 6-, 9-month) were applied to evaluate the scattered neutron dose and dose equivalent. To calculate the dose equivalent, organ specific linear energy transfer (LET) based quality factor was used. Treatment plans from both passive scattering (PS) and pencil beam scanning (PBS) methods were considered in this study. Results: For pencil beam scanning, the neutron dose equivalent in the soft tissue of the fetus increases from 1.53x10−{sup 3} to 2.84x10−{sup 3} mSv per treatment Gy with increasing stage of gestation. This is due to scattered neutrons from the patient as the main contaminant source in PBS and a decrease in distance between the soft tissue of the fetus and GTV with increasing stage of gestation. For passive scattering, neutron dose equivalent to the soft tissue of the fetus shows a decrease from 0.17 to 0.13 mSv per treatment Gy in different stages, while the dose to the brain shows little difference around 0.18 mSv per treatment Gy because scattered neutrons from the treatment head contribute predominantly in passive scattering. Conclusion: The results show that the neutron dose to the fetus assuming a prescribed dose of 52.2 Gy is negligible for PBS, and is comparable to the scattered dose (0–10 mSv) from a head and neck CT scan for PS. It can be concluded that the dose to fetus is far lower than the thresholds of malformation, SMR and lethal death. The excess relative risk of childhood cancer induction would be increased by 0.48 and 0.103 using the Oxford Survey of Childhood Cancers and Japanese atomic model, respectively. Changran Geng is supported by the Chinese Scholarship Council (CSC) and the National Natural Science Foundation of China (Grant No. 11475087)
60 APPLIED LIFE SCIENCES↗
WE-AB-204-11: Development of a Nuclear Medicine Dosimetry Module for the GPU-Based Monte Carlo Code ARCHER
Purpose: To develop a nuclear medicine dosimetry module for the GPU-based Monte Carlo code ARCHER. Methods: We have developed a nuclear medicine dosimetry module for the fast Monte Carlo code ARCHER. The coupled electron-photon Monte Carlo transport kernel included in ARCHER is built upon the Dose Planning Method code (DPM). The developed module manages the radioactive decay simulation by consecutively tracking several types of radiation on a per disintegration basis using the statistical sampling method. Optimization techniques such as persistent threads and prefetching are studied and implemented. The developed module is verified against the VIDA code, which is based on Geant4 toolkit and has previously been verified against OLINDA/EXM. A voxelized geometry is used in the preliminary test: a sphere made of ICRP soft tissue is surrounded by a box filled with water. Uniform activity distribution of I-131 is assumed in the sphere. Results: The self-absorption dose factors (mGy/MBqs) of the sphere with varying diameters are calculated by ARCHER and VIDA respectively. ARCHER’s result is in agreement with VIDA’s that are obtained from a previous publication. VIDA takes hours of CPU time to finish the computation, while it takes ARCHER 4.31 seconds for the 12.4-cm uniform activity sphere case. For a fairer CPU-GPU comparison, more effort will be made to eliminate the algorithmic differences. Conclusion: The coupled electron-photon Monte Carlo code ARCHER has been extended to radioactive decay simulation for nuclear medicine dosimetry. The developed code exhibits good performance in our preliminary test. The GPU-based Monte Carlo code is developed with grant support from the National Institute of Biomedical Imaging and Bioengineering through an R01 grant (R01EB015478)
60 APPLIED LIFE SCIENCES↗