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At least 1,117 records · Page 62
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DOE OSTI2016

TU-AB-BRA-03: Atlas-Based Algorithms with Local Registration-Goodness Weighting for MRI-Driven Electron Density Mapping

Purpose: To develop image-analysis algorithms to synthesize CT with accurate electron densities for MR-only radiotherapy of head & neck (H&N) and pelvis anatomies. Methods: CT and 3T-MRI (Philips, mDixon sequence) scans were randomly selected from a pool of H&N (n=11) and pelvis (n=12) anatomies to form an atlas. All MRIs were pre-processed to eliminate scanner and patient-induced intensity inhomogeneities and standardize their intensity histograms. CT and MRI for each patient were then co-registered to construct CT-MRI atlases. For more accurate CT-MR fusion, bone intensities in CT were suppressed to improve the similarity between CT and MRI. For a new patient, all CT-MRI atlases are deformed onto the new patients’ MRI initially. A newly-developed generalized registration error (GRE) metric was then calculated as a measure of local registration accuracy. The synthetic CT value at each point is a 1/GRE-weighted average of CTs from all CT-MR atlases. For evaluation, the mean absolute error (MAE) between the original and synthetic CT (generated in a leave-one-out scheme) was computed. The planning dose from the original and synthetic CT was also compared. Results: For H&N patients, MAE was 67±9, 114±22, and 116±9 HU over the entire-CT, air and bone regions, respectively. For pelvis anatomy, MAE was 47±5 and 146±14 for the entire and bone regions. In comparison with MIRADA medical, an FDA-approved registration tool, we found that our proposed registration strategy reduces MAE by ∼30% and ∼50% over the entire and bone regions, respectively. GRE-weighted strategy further lowers MAE by ∼15% to ∼40%. Our primary dose calculation also showed highly consistent results between the original and synthetic CT. Conclusion: We’ve developed a novel image-analysis technique to synthesize CT for H&N and pelvis anatomies. Our proposed image fusion strategy and GRE metric help generate more accurate synthetic CT using locally more similar atlases (Support: Philips Healthcare). The research is supported by Philips HealthCare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-D-201-06: HDR Plan Prechecks Using Eclipse Scripting API

Purpose: Automate brachytherapy treatment plan quality check using Eclipse v13.6 scripting API based on pre-configured rules to minimize human error and maximize efficiency. Methods: The HDR Precheck system is developed based on a rules-driven approach using Eclipse scripting API. This system checks for critical plan parameters like channel length, first source position, source step size and channel mapping. The planned treatment time is verified independently based on analytical methods. For interstitial or SAVI APBI treatment plans, a Patterson-Parker system calculation is performed to verify the planned treatment time. For endobronchial treatments, an analytical formula from TG-59 is used. Acceptable tolerances were defined based on clinical experiences in our department. The system was designed to show PASS/FAIL status levels. Additional information, if necessary, is indicated appropriately in a separate comments field in the user interface. Results: The HDR Precheck system has been developed and tested to verify the treatment plan parameters that are routinely checked by the clinical physicist. The report also serves as a reminder or checklist for the planner to perform any additional critical checks such as applicator digitization or scenarios where the channel mapping was intentionally changed. It is expected to reduce the current manual plan check time from 15 minutes to <1 minute. Conclusion: Automating brachytherapy plan prechecks significantly reduces treatment plan precheck time and reduces human errors. When fully developed, this system will be able to perform TG-43 based second check of the treatment planning system’s dose calculation using random points in the target and critical structures. A histogram will be generated along with tabulated mean and standard deviation values for each structure. A knowledge database will also be developed for Brachyvision plans which will then be used for knowledge-based plan quality checks to further reduce treatment planning errors and increase confidence in the planned treatment.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

TU-D-207B-02: Delta-Radiomics: The Prognostic Value of Therapy-Induced Changes in Radiomics Features for Stage III Non-Small Cell Lung Cancer Patients

Purpose: To determine how radiomics features change during radiation therapy and whether those changes (delta-radiomics features) can improve prognostic models built with clinical factors. Methods: 62 radiomics features, including histogram, co-occurrence, run-length, gray-tone difference, and shape features, were calculated from pretreatment and weekly intra-treatment CTs for 107 stage III NSCLC patients (5–9 images per patient). Image preprocessing for each feature was determined using the set of pretreatment images: bit-depth resample and/or a smoothing filter were tested for their impact on volume-correlation and significance of each feature in univariate cox regression models to maximize their information content. Next, the optimized features were calculated from the intratreatment images and tested in linear mixed-effects models to determine which features changed significantly with dose-fraction. The slopes in these significant features were defined as delta-radiomics features. To test their prognostic potential multivariate cox regression models were fitted, first using only clinical features and then clinical+delta-radiomics features for overall-survival, local-recurrence, and distant-metastases. Leave-one-out cross validation was used for model-fitting and patient predictions. Concordance indices(c-index) and p-values for the log-rank test with patients stratified at the median were calculated. Results: Approximately one-half of the 62 optimized features required no preprocessing, one-fourth required smoothing, and one-fourth required smoothing and resampling. From these, 54 changed significantly during treatment. For overall-survival, the c-index improved from 0.52 for clinical factors alone to 0.62 for clinical+delta-radiomics features. For distant-metastases, the c-index improved from 0.53 to 0.58, while for local-recurrence it did not improve. Patient stratification significantly improved (p-value<0.05) for overallsurvival and distant-metastases when delta-radiomics features were included. The delta-radiomics versions of autocorrelation, kurtosis, and compactness were selected most frequently in leave-one-out iterations. Conclusion: Weekly changes in radiomics features can potentially be used to evaluate treatment response and predict patient outcomes. High-risk patients could be recommended for dose escalation or consolidation chemotherapy. This project was funded in part by grants from the National Cancer Institute (NCI) and the Cancer Prevention Research Institute of Texas (CPRIT).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-H-CAMPUS-JeP2-05: Can Automatic Delineation of Cardiac Substructures On Noncontrast CT Be Used for Cardiac Toxicity Analysis?

Purpose: To evaluate the feasibility of using an automatic segmentation tool to delineate cardiac substructures from computed tomography (CT) images for cardiac toxicity analysis for non-small cell lung cancer (NSCLC) patients after radiotherapy. Methods: A multi-atlas segmentation tool developed in-house was used to delineate eleven cardiac substructures including the whole heart, four heart chambers, and six greater vessels automatically from the averaged 4DCT planning images for 49 NSCLC patients. The automatic segmented contours were edited appropriately by two experienced radiation oncologists. The modified contours were compared with the auto-segmented contours using Dice similarity coefficient (DSC) and mean surface distance (MSD) to evaluate how much modification was needed. In addition, the dose volume histogram (DVH) of the modified contours were compared with that of the auto-segmented contours to evaluate the dosimetric difference between modified and auto-segmented contours. Results: Of the eleven structures, the averaged DSC values ranged from 0.73 ± 0.08 to 0.95 ± 0.04 and the averaged MSD values ranged from 1.3 ± 0.6 mm to 2.9 ± 5.1mm for the 49 patients. Overall, the modification is small. The pulmonary vein (PV) and the inferior vena cava required the most modifications. The V30 (volume receiving 30 Gy or above) for the whole heart and the mean dose to the whole heart and four heart chambers did not show statistically significant difference between modified and auto-segmented contours. The maximum dose to the greater vessels did not show statistically significant difference except for the PV. Conclusion: The automatic segmentation of the cardiac substructures did not require substantial modification. The dosimetric evaluation showed no statistically significant difference between auto-segmented and modified contours except for the PV, which suggests that auto-segmented contours for the cardiac dose response study are feasible in the clinical practice with a minor modification to the PV vessel.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-BRA-05: PET-Guided Delivery Quality Evaluation of Yttrium-90 Microsphere Radioembolizaton for Hepatocellular Carcinoma Patients: The Optimal Sequence of Radioembolizaton and Chemoembolization Treatments

Purpose: Selective-internal-radiation-therapy (SIRT) and transarterial-chemoembolization (TACE) are commonly used for treatment of liver tumors. The use of TACE, which is macroembolic, prior to SIRT may cause hemodynamic changes in tumor vasculature that impair yttrium-90 (90Y) microsphere delivery to the targeted lesions. This work aims to quantify dosimetric tumor coverage using 90Y positron emission tomography (PET) dosimetry after SIRT alone compared to TACE followed by SIRT. Methods: A total of 40 consecutive hepatocellular carcinoma (HCC) SIRT patients who had a post-SIRT 90Y PET/CT scan were evaluated. The patient-specific-3D-dose was reconstructed from the PET images. Patients were categorized into two groups: patients received TACE prior SIRT procedure (n=18) and patient received SIRT alone (n=22). The lesions and liver were delineated by a senior radiologist. We evaluated both the lesion-specific dose-volume-histogram (DVH) and the selectivity index (SI) defined as the ratio of the average dose inside the total lesion(s) and the average dose of the normal liver. The SI values of patients were compared based on whether TACE was previously used. Results: A wide spectrum was observed in the lesion-specific DVH-evaluation and SI appeared to be suitable of evaluating the quality of each SIRT infusion. The average SI of the entire patient group was 3.0, i.e. targeted lesion receiving three times higher dose than normal liver. The average SI was 1.8 for patients who had prior TACE and 3.9 for patients who did not have prior TACE (p=0.008). 85% of the patients with prior TACE demonstrated poor 90Y-microsphere delivery (SI <2) while none demonstrated excellent delivery (SI >4). On the other hand, the incidence SI >4 among patients with no prior TACE was 37%. Conclusion: 3D dose evaluation using post-SIRT PET suggests that 90Y microsphere delivery to liver tumors is impaired among patients who received prior TACE compared to those who receive SIRT alone.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-202-03: Quantifying Ventilation Change Due to Radiation Therapy Using 4DCT Jacobian Calculations

Purpose: Four-dimensional computed tomography (4DCT) and image registration can be used to determine regional lung ventilation changes after radiation therapy (RT). This study aimed to determine if lung ventilation change following radiation therapy was affected by the pre-RT ventilation of the lung. Methods: 13 subjects had three 4DCT scans: two repeat scans acquired before RT and one three months after RT. Regional ventilation was computed using Jacobian determinant calculations on the registered 4DCT images. The post-RT ventilation map was divided by the pre-RT ventilation map to get a voxel-by-voxel Jacobian ratio map depicting ventilation change over the course of RT. Jacobian ratio change was compared over the range of delivered doses. The first pre-RT ventilation image was divided by the second to establish a control for Jacobian ratio change without radiation delivered. The functional change between scans was assessed using histograms of the Jacobian ratios. Results: There were significantly (p < 0.05) more voxels that had a large decrease in Jacobian ratio in the post-RT divided by pre-RT map (15.6%) than the control (13.2%). There were also significantly (p < .01) more voxels that had a large increase in Jacobian ratio (16.2%) when compared to control (13.3%). Lung regions with low function (<10% expansion by Jacobian) showed a slight linear reduction in expansion (0.2%/10 Gy delivered), while high function regions (>10% expansion) showed a greater response (1.2% reduction/10 Gy). Contiguous high function regions > 1 liter occurred in 11 of 13 subjects. Conclusion: There is a significant change in regional ventilation following a course of radiation therapy. The change in Jacobian following RT is dependent both on the delivered dose and the initial ventilation of the lung tissue: high functioning lung has greater ventilation loss for equivalent radiation doses. Substantial regions of high function lung tissue are prevalent. Research support from NIH grants CA166119 and CA166703, a gift from Roger Koch, and a Pilot Grant from University of Iowa Carver College of Medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-207B-01: Dose Tolerance for SBRT/SABR

Purpose: Stereotactic body radiation therapy (SBRT) / stereotactic ablative body radiotherapy (SABR) is gaining popularity, but quantitative dose tolerance has still been lacking. To improve this, the April 2016 issue of Seminars in Radiation Oncology will have normal tissue complication probability (NTCP) models for 10 critical structures: optic pathway, cochlea, oral mucosa, esophagus, chestwall, aorta, bronchi, duodenum, small bowel, and spinal cord. Methods: The project included more than 1500 treatments in 1–5 fractions using CyberKnife, Gamma Knife, or LINAC, with 60 authors from 15 institutions. NTCP models were constructed from the 97 grade 2–3 complications, predominantly scored using the common terminology criteria for adverse events (CTCAEv4). Dose volume histogram (DVH) data from each institutional dataset was loaded into the DVH Evaluator software (DiversiLabs, LLC, Huntingdon Valley, Pa) for modeling. The current state of the literature for the critical structures was depicted using DVH Risk Maps: comparative graphs of dose tolerance limits that can include estimated risk levels, reported complications, DVH data for study patients, as well as high- and low-risk dose tolerance limits. Results: For relatively acceptable toxicity like grade 1–3 rib fractures and chestwall pain, the high-risk limits have 50% risk and the low-risk limits have 5% risk. Emami et al (IJROBP 1991 May 15;21(1):109–22) used 50% and 5% risk levels for all structures, whereas this effort used clinically acceptable ranges for each: in structures like aorta or spinal cord where complications must be avoided, the high- and low-risk limits have about 3% and 1% risk, respectively, in this issue of Seminars. These statistically based guidelines can help ensure plan quality for each patient. Conclusion: NTCP for SBRT is now becoming available. Hypofractionated dose tolerance can be dramatically different than extrapolations of conventional fractionation so NTCP analysis of the SBRT/SBRT data is important to ensure safe clinical practice. Dr. Grimm, designed and holds intellectual property rights to the DVH Evaluator software tool which is an FDA-cleared product in commercial use, and was used to analyze the data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-207B-06: Dose and Biological Uncertainties in Sarcoma

Purpose: To understand the clinical impact of key uncertainties in proton therapy potentially affecting the analysis of clinical trials, namely the assumption of using a constant relative biological effectiveness (RBE) of 1.1 compared to variable RBE for proton therapy and the use of analytical dose calculation (ADC) methods. Methods: Proton dose distributions were compared for analytical and Monte Carlo (TOPAS) dose calculations. In addition, differences between using a constant RBE of 1.1 (RBE-constant) were compared with four different RBE models (to assess model variations). 10 patients were selected from an ongoing clinical trial on IMRT versus scanned protons for sarcoma. Comparisons were performed using dosimetric indices based on dose-volume histogram analyses and γ-index analyses. Results: For three of the RBE-models the mean dose, D95, D50 and D02 (dose values covering 95%, 50% and 2% of the target volume, respectively) were up to 5% lower than for RBE-constant. The dosimetric indices for one of the RBE-models were around 9% lower than for the RBE-constant model. The differences for V90 (the percentage of the target volume covered by 90% of the prescription dose) were up to 40% for three RBE-models, whereas for one the difference was around 95%. All ADC dosimetric indices were up to 5% larger than for RBE-constant. The γ-index passing rate for the target volume with a 3%/3mm criterion was above 97% for all models except for one, which was below 24%. Conclusion: Interpretation of clinical trials on sarcoma may depend on dose calculation uncertainties (as assessed by Monte Carlo). In addition, the biological dose distribution depends notably on which RBE model is utilized. The current practice of using a constant RBE of 1.1 may overestimate the target dose by as much as 5% for biological dose calculations. Performing an RBE uncertainty analysis is recommended for trial analysis. U19 projects - U19 CA 021239. PI: Delaney.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-201-01: BEST IN PHYSICS (THERAPY): A Fast Multi-Target Inverse Treatment Planning Strategy Optimizing Dosimetric Measures for High-Dose-Rate (HDR) Brachytherapy

Purpose: Inverse treatment planning (ITP) for interstitial HDR brachytherapy of gynecologic cancers seeks to maximize coverage of the clinical target volumes (tumor and vagina) while respecting dose-volume-histogram related dosimetric measures (DMs) for organs at risk (OARs). Commercially available ITP tools do not support DM-based planning because it is computationally too expensive to solve. In this study we present a novel approach that allows fast ITP for gynecologic cancers based on DMs for the first time. Methods: This novel strategy is an optimization model based on a smooth DM-based objective function. The smooth approximation is achieved by utilizing a logistic function for the evaluation of DMs. The resulting nonconvex and constrained optimization problem is then optimized with a BFGS algorithm. The model was evaluated using the implant geometry extracted from 20 patient treatment plans under an IRB-approved retrospective study. For each plan, the final DMs were evaluated and compared to the original clinical plans. The CTVs were the contoured tumor volume and the contoured surface of the vagina. Statistical significance was evaluated with a one-sided paired Wilcoxon signed-rank test. Results: As did the clinical plans, all generated plans fulfilled the defined DMs for OARs. The proposed strategy showed a statistically significant improvement (p<0.001) in coverage of the tumor and vagina, with absolute improvements of related DMs of (6.9 +/− 7.9)% and (28.2 +/− 12.0)%, respectively. This was achieved with a statistically significant (p<0.01) decrease of the high-dose-related DM for the tumor. The runtime of the optimization was (2.3 +/− 2.0) seconds. Conclusion: We demonstrated using clinical data that our novel approach allows rapid DM-based optimization with improved coverage of CTVs with fewer hot spots. Being up to three orders of magnitude faster than the current clinical practice, the method dramatically shortens planning time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-FG-207B-03: Multi-Energy CT Reconstruction with Spatial Spectral Nonlocal Means Regularization

Purpose: Multi-energy computed tomography (MECT) is an emerging application in medical imaging due to its ability of material differentiation and potential for molecular imaging. In MECT, image correlations at different spatial and channels exist. It is desirable to incorporate these correlations in reconstruction to improve image quality. For this purpose, this study proposes a MECT reconstruction technique that employes spatial spectral non-local means (ssNLM) regularization. Methods: We consider a kVp-switching scanning method in which source energy is rapidly switched during data acquisition. For each energy channel, this yields projection data acquired at a number of angles, whereas projection angles among channels are different. We formulate the reconstruction task as an optimziation problem. A least square term enfores data fidelity. A ssNLM term is used as regularization to encourage similarities among image patches at different spatial locations and channels. When comparing image patches at different channels, intensity difference were corrected by a transformation estimated via histogram equalization during the reconstruction process. Results: We tested our method in a simulation study with a NCAT phantom and an experimental study with a Gammex phantom. For comparison purpose, we also performed reconstructions using conjugate-gradient least square (CGLS) method and conventional NLM method that only considers spatial correlation in an image. ssNLM is able to better suppress streak artifacts. The streaks are along different projection directions in images at different channels. ssNLM discourages this dissimilarity and hence removes them. True image structures are preserved in this process. Measurements in regions of interests yield 1.1 to 3.2 and 1.5 to 1.8 times higher contrast to noise ratio than the NLM approach. Improvements over CGLS is even more profound due to lack of regularization in the CGLS method and hence amplified noise. Conclusion: The proposed ssNLM method for kVp-switching MECT reconstruction can achieve high quality MECT images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-AB-201-11: Small-Field Beam Quality Corrections and Their Clinical Impact for Flattened and Unflattened Fields of the TrueBeam

Purpose: To determine small-field beam quality correction factors for several detectors used with flattened and unflattened beams of the Varian TrueBeam accelerator, and to quantify the clinical impact of these corrections through a treatment planning study. Methods: Small-field beam quality correction factors were measured and simulated in EGSnrc for several microchambers and diodes. The Exradin W1 plastic scintillation detector was used as a reference for the measured results, and its response was validated using alanine measurements traceable to a primary standard. Symmetric, jaw-defined field sizes ranging from 6 mm to 10 cm were used. Twelve hypofractionated clinical cases were then recalculated and/or reoptimized using beam models that were modified based on the resulting output factors. Three-dimensional dose distributions and cumulative dose-volume-histogram plots were compared between the models. The impact of these measurements on the flattening-filter-scatter-source (FFSS) model, and its subsequent effect on treatment plans, was also investigated. Results: The diodes exhibited over-response in small fields, whereas the microchambers tended to under-respond as field size decreased. Field-size-dependent effects were less significant for the flattening-filter-free beams (i.e., corrections were closer to unity) than for flattened fields of the same size. Recalculated and reoptimized plans displayed varying levels of deviation from the original dose distributions, with larger discrepancies at effective jaw settings of 3×3 cm{sup 2} or smaller. Dose distributions calculated using uncorrected microchamber output factors and/or modified FFSS showed large discrepancies in the low-dose regions, which manifested as DVH changes for the organs at risk (OAR). Conclusion: Field-size-dependent beam quality corrections were measured and simulated for ionization chambers and diodes typically used in small fields. Plans calculated with models based on these measured data showed dosimetric deviations mainly out of field, which affected OAR dose metrics. Accordingly, these beam quality corrections should be accounted for during commissioning to ensure greater treatment planning accuracy.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

TH-AB-BRA-03: Backscatter Dose Factors Re-Evaluated for Inhomogeneities in the Presence of a 1.5 T Magnetic Field Using the GPUMCD Monte Carlo Algorithm

Purpose: To quantify the backscatter dose factors near the interfaces for clinically relevant high atomic number materials using GPUMCD for the Elekta MRI Linac. Methods: Backscatter dose factors (BSDF) were calculated as the ratio of the dose with and without the presence of the heterogeneity. The BSDF’s were calculated either in the absence or presence of an orthogonal 1.5 T magnetic field. Doses were scored in small voxels of side 1 mm in a water phantom with dimensions of 20×20×20 cm using GPUMCD (Elekta). The minimum uncertainty in dose calculations was kept to 0.5%. A slab of thickness 2 cm, representing the inhomogeneity, was placed inside the phantom with variable position from the surface of the phantom. The slab was filled with either bone, aluminum, titanium, stainless steel, or dental amalgam. The phantom was irradiated using particles sampled from a histogram which represented the true MRI Linac spectrum. Results: With the application of the 1.5 T magnetic field (B-On), all of the BSDF’s were reduced by at least 8% compared to the no magnetic field (B-Off) cases. For the B-Off case, the BSDF decreases exponentially with the upstream distance away from the interface. With B-On, the BSDF decreases exponentially for titanium, SS, and amalgam. However, it remains constant for Aluminum. In the case of bone, the BSDF increases up to a distance of 4 mm away from the interface in the presence of the magnetic field. Conclusion: The BSDF does not depend upon the thickness of the homogeneous material above the inhomogeneity for either the B-Off or B-On cases. For all the materials investigated, the BSDF is lower at the interface for the B-On case. The exponential fall-off of the BSDF away from the interface is not valid for all the materials when the magnetic field is turned ON. Funding support for this research was provided by Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-AB-BRA-10: The Physics of Interface Effects for Radiation Treatments in a MRI-Linac: A Monte Carlo Study

Purpose: To investigate and explain the interface effects for clinically relevant materials being irradiated in the presence of a 1.5 T transverse magnetic field. Methods: Interface effects were investigated using Geant4.10.1 both with (B-On) and without (B-Off) a magnetic field for an Elekta MRI-Linac. A slab of thickness 8 cm, representing inhomogeneity, was placed at a depth of 4 cm in a 20×20×20 cm water phantom. Backscattered electron fluence was calculated through a 20×20 cm plane aligned with the surface of the inhomogeneity. Inhomogeneities investigated were lung, bone, aluminum, titanium, stainless steel, and dental filling. A photon beam with field size of 2×2 cm at the isocenter and SAD of 143.5 cm was generated from a point source with energy distribution sampled from a histogram representing the true Elekta MRI-Linac photon spectrum. Results: In the B-On case, if the heterogeneity is a low Z{sub eff} material, such as lung, the backscattered electron fluence is increased considerably, i.e. by 54 %, and the corresponding dose is expected to be higher near the interface compared to the B-Off case. On the contrary, if the heterogeneity is a high Z{sub eff} material then the backscattered electron fluence is reduced in the B-On electron fluence is reduced in the B-On case. This reduction leads to a lower dose deposition at the interface compared to the B-Off case. Conclusion: The reduction in dose at the interface, in the B-On case, is directly related to the reduction in backscattered electron fluence. The reduction in backscattered electron fluence occurs due to two different reasons. First, the electron energy spectrum hitting the interface is changed for the B-On case which changes the electron scattering probability. Second, some electrons that are looping under the influence of the magnetic field are captured by the higher density side of the interface and no longer contribute to the backscattered electron stream. Funding support for this study was provided by ElektaTM.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-201-07: Experimentally Investigating Proton Energy Deposition On the Microscopic Scale Using Fluorescence Nuclear Track Detectors

Purpose: In order to further understand the interplay between proton physics and radiobiology it is necessary to consider proton energy deposition on the microscopic scale. In this work we used Fluorescent Nuclear Track Detectors (FNTDs) to experimentally investigate proton energy deposition, track-by-track. Methods: We irradiated 8×4×0.5mm{sup 3} FNTD chips (Landauer Inc) at seven water depths along a pristine proton Bragg peak with range=12cm. After irradiation, the FNTDs were scanned using a confocal microscope (FV1200, Olympus) with a high-power red laser and an oil-immersion objective lens (UPLSAPO60XO, NA=1.35). 10 slice image stacks were acquired with a slice-thickness of 2µm at multiple positions across each FNTD. Image-based analyses of track radius and track “mass” (integrated signal intensity) were performed using trackpy. For comparison, Monte Carlo simulated data were obtained using TOPAS and TOPAS-nBio. Results: Excellent correlation was observed between median track mass and TOPAS dose-averaged linear energy transfer. The resolution of the imaging system was determined insufficient to detect a relationship between track radius and exposure depth. Histograms of track mass (i) displayed strong repeatability across positions within an FNTD and (ii) varied in peak position and shape as a function of depth. TOPAS-nBio simulations implemented on the nanometer scale using physics lists from GEANT4-DNA yielded energy deposition distributions for individual protons and electrons scored within a virtual FNTD. Good agreement was found between these simulated datasets and the FNTD track mass distributions. Conclusion: Robust experimental measurements of the integral energy deposited by individual proton tracks can be performed using FNTDs. Monte Carlo simulations offer an exceedingly powerful approach to the quantification of proton energy deposition on the microscopic scale, but whilst they have been well validated at the macroscopic level, their microscopic validation is far from complete. Our results demonstrate that FNTD-based study can play an important role in addressing this deficit. Tracy Underwood gratefully acknowledges the support of the European Commission under an FP7 Marie Curie International Outgoing Fellowship for Career Development (#630064).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-202-08: Feasibility Study of Planning Phase Optimization Using Patient Geometry-Driven Information for Better Dose Sparing of Organ at Risks

Purpose: To propose a simple and effective cost value function to search optimal planning phase (gating window) and demonstrated its feasibility for respiratory correlated radiation therapy. Methods: We acquired 4DCT of 10 phases for 10 lung patients who have tumor located near OARs such as esophagus, heart, and spinal cord (i.e., central lung cancer patients). A simplified mathematical optimization function was established by using overlap volume histogram (OVH) between the target and organ at risk (OAR) at each phase and the tolerance dose of selected OARs to achieve surrounding OARs dose-sparing. For all patients and all phases, delineation of the target volume and selected OARs (esophagus, heart, and spinal cord) was performed (by one observer to avoid inter-observer variation), then cost values were calculated for all phases. After the breathing phases were ranked according to cost value function, the relationship between score and dose distribution at highest and lowest cost value phases were evaluated by comparing the mean/max dose. Results: A simplified mathematical cost value function showed noticeable difference from phase to phase, implying it is possible to find optimal phases for gating window. The lowest cost value which may result in lower mean/max dose to OARs was distributed at various phases for all patients. The mean doses of the OARs significantly decreased about 10% with statistical significance for all 3 OARs at the phase with the lowest cost value. Also, the max doses of the OARs were decreased about 2∼5% at the phase with the lowest cost value compared to the phase with the highest cost value. Conclusion: It is demonstrated that optimal phases (in dose distribution perspective) for gating window could exist differently through each patient and the proposed cost value function can be a useful tool for determining such phases without performing dose optimization calculations. This research was supported by the Mid-career Researcher Program through NRF funded by the Ministry of Science, ICT & Future Planning of Korea (NRF-2014R1A2A1A10050270) and by the Radiation Technology R&D program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (No. 2013M2A2A7038291)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-209-04: Fuzzy Robust Optimization in Intensity-Modulated Proton Therapy Planning to Account for Range and Patient Setup Uncertainties

Purpose: We propose to apply a robust optimization model based on fuzzy-logic constraints in the intensity-modulated proton therapy (IMPT) planning subject to range and patient setup uncertainties. The purpose is to ensure the plan robustness under uncertainty and obtain the best trade-off between tumor dose coverage and organ-at-risk(OAR) sparing. Methods: Two IMPT plans were generated for 3 head-and-neck cancer patients: one used the planning target volume(PTV) method; the other used the fuzzy robust optimization method. In the latter method, nine dose distributions were computed - the nominal one and one each for ±3mm setup uncertainties along three cardinal axes and for ±3.5% range uncertainty. For tumors, these nine dose distributions were explicitly controlled by adding hard constraints with adjustable parameters. For OARs, fuzzy constraints that allow the dose to vary within a certain range were used so that the tumor dose distribution was guaranteed by minimum compromise of that of OARs. We rendered this model tractable by converting the fuzzy constraints to linear constraints. The plan quality was evaluated using dose-volume histogram(DVH) indices such as tumor dose coverage(D95%), homogeneity(D5%-D95%), plan robustness(DVH band at D95%), and OAR sparing like D1% of brain and D1% of brainstem. Results: Our model could yield clinically acceptable plans. The fuzzy-logic robust optimization method produced IMPT plans with comparable target dose coverage and homogeneity compared to the PTV method(unit: Gy[RBE]; average[min, max])(CTV D95%: 59 [52.7, 63.5] vs 53.5[46.4, 60.1], CTV D5% - D95%: 11.1[5.3, 18.6] vs 14.4[9.2, 21.5]). It also generated more robust plans(CTV DVH band at D95%: 3.8[1.2, 5.6] vs 11.5[6.2, 16.7]). The parameters of tumor constraints could be adjusted to control the tradeoff between tumor coverage and OAR sparing. Conclusion: The fuzzy-logic robust optimization generates superior IMPT with minimum compromise of OAR sparing. This research was supported by the National Cancer Institute Career Developmental Award K25CA168984, by the Fraternal Order of Eagles Cancer Research Fund Career Development Award, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, by Mayo Arizona State University Seed Grant, and by The Kemper Marley Foundation. eRA Person ID(s) for the Principal Investigator: 11017970 (Research Supported by National Institutes of Health)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-209-10: Scanning Proton Arc Therapy (SPArc) - The First Robust and Delivery-Efficient Spot Scanning Proton Arc Therapy

Purpose: To develop a delivery-efficient proton spot-scanning arc therapy technique with robust plan quality. Methods: We developed a Scanning Proton Arc(SPArc) optimization algorithm integrated with (1)Control point re-sampling by splitting control point into adjacent sub-control points; (2)Energy layer re-distribution by assigning the original energy layers to the new sub-control points; (3)Energy layer filtration by deleting low MU weighting energy layers; (4)Energy layer re-sampling by sampling additional layers to ensure the optimal solution. A bilateral head and neck oropharynx case and a non-mobile lung target case were tested. Plan quality and total estimated delivery time were compared to original robust optimized multi-field step-and-shoot arc plan without SPArc optimization (Arcmulti-field) and standard robust optimized Intensity Modulated Proton Therapy(IMPT) plans. Dose-Volume-Histograms (DVH) of target and Organ-at-Risks (OARs) were analyzed along with all worst case scenarios. Total delivery time was calculated based on the assumption of a 360 degree gantry room with 1 RPM rotation speed, 2ms spot switching time, beam current 1nA, minimum spot weighting 0.01 MU, energy-layer-switching-time (ELST) from 0.5 to 4s. Results: Compared to IMPT, SPArc delivered less integral dose(−14% lung and −8% oropharynx). For lung case, SPArc reduced 60% of skin max dose, 35% of rib max dose and 15% of lung mean dose. Conformity Index is improved from 7.6(IMPT) to 4.0(SPArc). Compared to Arcmulti-field, SPArc reduced number of energy layers by 61%(276 layers in lung) and 80%(1008 layers in oropharynx) while kept the same robust plan quality. With ELST from 0.5s to 4s, it reduced 55%–60% of Arcmulti-field delivery time for the lung case and 56%–67% for the oropharynx case. Conclusion: SPArc is the first robust and delivery-efficient proton spot-scanning arc therapy technique which could be implemented in routine clinic. For modern proton machine with ELST close to 0.5s, SPArc would be a popular treatment option for both single and multi-room center.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-207B-07: Noise Modeling of Single Photon Avalanche Diode (SPAD) for Photon Counting CT Applications

Purpose: Silicon photomultiplier (SiPM) has recently emerged as a promising photodetector for biomedical imaging applications. Due to its high multiplication gain (comparable to PMT), fast timing, low cost and compactness, it is considered a good candidate for photon counting CT. Dark noise is a limiting factor which impacts both energy resolution and detection dynamic range. Our goal is to develop a comprehensive model for noise sources for SiPM sensors. Methods: The physical parameters used in this work were based upon a test SPAD fabricated in 130nm CMOS process. The SPAD uses an n+/p-well junction, which is isolated from the p-substrate by a deep n-well junction. Inter-avalanche time measurement was used to record the time interval between two adjacent avalanche pulses. After collecting 1×106 counts, the histogram was obtained and multiple exponential fitting process was used to extract the lifetime associated with the traps within the bandgap. Results: At room temperature, the breakdown voltage of the SPAD is ∼11.4V and shows a temperature coefficient of 7.7mV/°C. The dark noise of SPAD increases with both the excess biasing voltage and temperature. The primary dark counts from the model were validated against the measurement results. A maximum relative error of 8.7% is observed at 20 °C with an excess voltage of 0.5V. The probabilities of after-pulsing are found to be dependent of both temperature and excess voltage. With 0.5V excess voltage, the after-pulsing probability is 63.5% at - 30 °C and drops to ∼6.6% at 40 °C. Conclusion: A comprehensive noise model for SPAD sensor was proposed. The model takes into account of static, dynamic and statistical behavior of SPADs. We believe that this is the first SPAD circuit simulation model that includes the band-to-band tunneling dark noise contribution and temporal dependence of the after-pulsing probability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗