bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐J‐136: Investigation Into Robustness of Stopping Power Calculated by DECT and SECT for Proton Therapy Treatment Planning
Authors: Zhu J , Penfold S 
Published: June 2015

Purpose:To investigate the robustness of dual energy CT (DECT) and single energy CT (SECT) proton stopping power calibration techniques and quantify the associated errors when imaging a phantom differing in chemical composition to that used during stopping power calibration.Methods:The CIRS tissue substitute phantom was scanned in a CT‐simulator at 90kV and 140kV. This image set was used to generate a DECT proton SPR calibration based on a relationship between effective atomic number and mean excitation energy. A SECT proton SPR calibration based only on Hounsfield units (HUs) was also generated. DECT and SECT scans of a second phantom of known density and chemical composition were performed. The SPR of the second phantom was calculated with the DECT approach (SPR_DECT),the SECT approach (SPR_SECT) and finally the known density and chemical composition of the phantom (SPR_ref). The DECT and SECT image sets were imported into the Pinnacle3 research release of proton therapy treatment planning. The difference in dose when exposed to a common pencil beam distribution was investigated.Results:SPR_DECT was found to be in better agreement with SPR_ref than SPR_ SECT. The mean difference in SPR for all materials was 0.51% for DECT and 6.89% for SECT. With the exception of Teflon, SPR_DECT was found to agree with SPR_ref to within 1%. Significant differences in calculated dose were found when using the DECT image set or the SECT image set.Conclusion:The DECT calibration technique was found to be more robust to situations in which the physical properties of the test materials differed from the materials used during SPR calibration. Furthermore, it was demonstrated that the DECT and SECT SPR calibration techniques can Result in significantly different calculated dose distributions.
SU‐E‐J‐141: Activity‐Equivalent Path Length Approach for the 3D PET‐Based Dose Reconstruction in Proton Therapy
Authors: Attili A , Kraan A , Dalmasso F , Vignati A , Giordanengo S , Battistoni G 
Published: June 2015

Purpose:Ion beam therapy is sensitive to uncertainties from treatment planning and dose delivery. PET imaging of induced positron emitter distributions is a practical approach for in vivo, in situ verification of ion beam treatments. Treatment verification is usually done by comparing measured activity distributions with reference distributions, evaluated in nominal conditions. Although such comparisons give valuable information on treatment quality, a proper clinical evaluation of the treatment ultimately relies on the knowledge of the actual delivered dose. Analytical deconvolution methods relating activity and dose have been studied in this context, but were not clinically applied. In this work we present a feasibility study of an alternative approach for dose reconstruction from activity data, which is based on relating variations in accumulated activity to tissue density variations.Methods:First, reference distributions of dose and activity were calculated from the treatment plan and CT data. Then, the actual measured activity data were cumulatively matched with the reference activity distributions to obtain a set of activity‐equivalent path lengths (AEPLs) along the rays of the pencil beams. Finally, these AEPLs were used to deform the original dose distribution, yielding the actual delivered dose. The method was tested by simulating a proton therapy treatment plan delivering 2 Gy on a homogeneous water phantom (the reference), which was compared with the same plan delivered on a phantom containing inhomogeneities. Activity and dose distributions were were calculated by means of the FLUKA Monte Carlo toolkit.Results:The main features of the observed dose distribution in the inhomogeneous situation were reproduced using the AEPL approach. Variations in particle range were reproduced and the positions, where these deviations originated, were properly identified.Conclusions:For a simple inhomogeneous phantom the 3D dose reconstruction from PET‐activity induced by proton beams was shown to be feasible.
SU‐E‐J‐145: Validation of An Analytical Model for in Vivo Range Verification Using GATE Monte Carlo Simulation in Proton Therapy
Authors: Lee C , Lin H , Chao T , Hsiao I , Chuang K 
Published: June 2015

Purpose:Predicted PET images on the basis of analytical filtering approach for proton range verification has been successful developed and validated using FLUKA Monte Carlo (MC) codes and phantom measurements. The purpose of the study is to validate the effectiveness of analytical filtering model for proton range verification on GATE/GEANT4 Monte Carlo simulation codes.Methods:In this study, we performed two experiments for validation of predicted β+‐isotope by the analytical model with GATE/GEANT4 simulations. The first experiments to evaluate the accuracy of predicting β+‐yields as a function of irradiated proton energies. In second experiment, we simulate homogeneous phantoms of different materials irradiated by a mono‐energetic pencil‐like proton beam. The results of filtered β+‐yields distributions by the analytical model is compared with those of MC simulated β+‐yields in proximal and distal fall‐off ranges.Results:The results investigate the distribution between filtered β+‐yields and MC simulated β+‐yields distribution in different conditions. First, we found that the analytical filtering can be applied over the whole range of the therapeutic energies. Second, the range difference between filtered β+‐yields and MC simulated β+‐yields at the distal fall‐off region are within 1.5mm for all materials used. The findings validated the usefulness of analytical filtering model on range verification of proton therapy on GATE Monte Carlo simulations. In addition, there is a larger discrepancy between filtered prediction and MC simulated β+‐yields using GATE code, especially in proximal region. This discrepancy might Result from the absence of wellestablished theoretical models for predicting the nuclear interactions.Conclusion:Despite the fact that large discrepancies of the distributions between MC‐simulated and predicted β+‐yields were observed, the study prove the effectiveness of analytical filtering model for proton range verification using GATE Monte Carlo simulation.
SU‐E‐J‐148: Tools for Development of 4D Proton CT
Authors: Dou T , Ramos‐Mendez J , Piersimoni P , Giacometti V , Penfold S , Censor Y , Faddegon B , Low D , Schulte R 
Published: June 2015

Purpose:To develop tools for performing 4D proton computed tomography (CT).Methods:A suitable patient with a tumor in the right lower lobe was selected from a set of 4D CT scans. The volumetric CT images formed the basis for calculating the parameters of a breathing model that allows reconstruction of a static reference CT and CT images in each breathing phase. The images were imported into the TOPAS Monte Carlo simulation platform for simulating an experimental proton CT scan with 45 projections spaced by 4 degree intervals. Each projection acquired data for 2 seconds followed by a gantry rotation for 2 seconds without acquisition. The scan covered 180 degrees with individual protons passing through a 9‐cm slab of the patient's lung covering the moving tumor. An initial proton energy sufficient for penetrating the patient from all directions was determined. Performing the proton CT simulation, TOPAS provided output of the proton energy and coordinates registered in two planes before and after the patient, respectively. The set of projection data was then used with an iterative reconstruction algorithm to generate a volumetric proton CT image set of the static reference image and the image obtained under breathing motion, respectively.Results:An initial proton energy of 230 MeV was found to be sufficient, while for an initial energy of 200 MeV a substantial number of protons did not penetrate the patient. The reconstruction of the static reference image set provided sufficient detail for treatment planning.Conclusion:We have developed tools to perform studies of proton CT in the presence of lung motion based on the TOPAS simulation toolkit. This will allow to optimize 4D reconstruction algorithms by synchronizing the acquired proton CT data with a breathing signal and utilizing a breathing model obtained prior to the proton CT scan.This research has been supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R01EB013118.
SU‐E‐J‐149: Secondary Emission Detection for Improved Proton Relative Stopping Power Identification
Authors: Saunders J , Musall B , Erickson A 
Published: June 2015

Purpose:This research investigates application of secondary prompt gamma (PG) emission spectra, resulting from nuclear reactions induced by protons, to characterize tissue composition along the particle path. The objective of utilizing the intensity of discrete high‐energy peaks of PG is to improve the accuracy of relative stopping power (RSP) values available for proton therapy treatment planning on a patient specific basis and to reduce uncertainty in dose depth calculations.Methods:In this research, MCNP6 was used to simulate PG emission spectra generated from proton induced nuclear reactions in medium of varying composition of carbon, oxygen, calcium and nitrogen, the predominant elements found in human tissue. The relative peak intensities at discrete energies predicted by MCNP6 were compared to the corresponding atomic composition of the medium.Results:The results have shown a good general agreement with experimentally measured values reported by other investigators. Unexpected divergence from experimental spectra was noted in the peak intensities for some cases depending on the source of the cross‐section data when using compiled proton table libraries vs. physics models built into MCNP6. While the use of proton cross‐section libraries is generally recommended when available, these libraries lack data for several less abundant isotopes. This limits the range of their applicability and forces the simulations to rely on physics models for reactions with natural atomic compositions.Conclusion:Current end‐of‐range proton imaging provides an average RSP for the total estimated track length. The accurate identification of tissue composition along the incident particle path using PG detection and characterization allows for improved determination of the tissue RSP on the local level. While this would allow for more accurate depth calculations resulting in tighter treatment margins, precise understanding of proton beam behavior in tissue of various compositions is necessary requiring detailed simulations with a high degree of accuracy.
SU‐E‐J‐151: Day‐To‐Day Variations in Fraction‐Specific Motion Modeling Using Patient 4DCBCT Images
Authors: Dhou S , Cai W , Hurwitz M , Williams C , Cifter F , Myronakis M , Ionascu D , Lewis J 
Published: June 2015

Purpose:The goal of this study is to quantify the interfraction reproducibility of patient‐specific motion models derived from 4DCBCT acquired on the day of treatment of lung cancer stereotactic body radiotherapy (SBRT) patients.Methods:Motion models are derived from patient 4DCBCT images acquired daily over 3–5 fractions of treatment by 1) applying deformable image registration between each 4DCBCT image and a reference phase from that day, resulting in a set of displacement vector fields (DVFs), and 2) performing principal component analysis (PCA) on the DVFs to derive a motion model. The motion model from the first day of treatment is compared to motion models from each successive day of treatment to quantify variability in motion models generated from different days. Four SBRT patient datasets have been acquired thus far in this IRB approved study.Results:Fraction‐specific motion models for each fraction and patient were derived and PCA eigenvectors and their associated eigenvalues are compared for each fraction. For the first patient dataset, the average root mean square error between the first two eigenvectors associated with the highest two eigenvalues, in four fractions was 0.1, while it was 0.25 between the last three PCA eigenvectors associated with the lowest three eigenvalues. It was found that the eigenvectors and eigenvalues of PCA motion models for each treatment fraction have variations and the first few eigenvectors are shown to be more stable across treatment fractions than others.Conclusion:Analysis of this dataset showed that the first two eigenvectors of the PCA patient‐specific motion models derived from 4DCBCT were stable over the course of several treatment fractions. The third, fourth, and fifth eigenvectors had larger variations.
SU‐E‐J‐154: Image Quality Assessment of Contrast‐Enhanced 4D‐CT for Pancreatic Adenocarcinoma in Radiotherapy Simulation
Authors: Choi W , Xue M , Kang M , Patel K , Regine W , Klahr P , Wang J , D'souza W , Lu W 
Published: June 2015

Purpose:This study presents quantitative and qualitative assessment of the image qualities in contrast‐enhanced (CE) 3D‐CT, 4D‐CT and CE 4D‐CT to identify feasibility for replacing the clinical standard simulation with a single CE 4D‐CT for pancreatic adenocarcinoma (PDA) in radiotherapy simulation.Methods:Ten PDA patients were enrolled and underwent three CT scans: a clinical standard pair of CE 3D‐CT immediately followed by a 4D‐CT, and a CE 4D‐CT one week later. Physicians qualitatively evaluated the general image quality and regional vessel definitions and gave a score from 1 to 5. Next, physicians delineated the contours of the tumor (T) and the normal pancreatic parenchyma (P) on the three CTs (CE 3D‐CT, 50% phase for 4D‐CT and CE 4D‐CT), then high density areas were automatically removed by thresholding at 500 HU and morphological operations. The pancreatic tumor contrast‐to‐noise ratio (CNR), signal‐tonoise ratio (SNR) and conspicuity (C, absolute difference of mean enhancement levels in P and T) were computed to quantitatively assess image quality. The Wilcoxon rank sum test was used to compare these quantities.Results:In qualitative evaluations, CE 3D‐CT and CE 4D‐CT scored equivalently (4.4±0.4 and 4.3±0.4) and both were significantly better than 4D‐CT (3.1±0.6). In quantitative evaluations, the C values were higher in CE 4D‐CT (28±19 HU, p=0.19 and 0.17) than the clinical standard pair of CE 3D‐CT and 4D‐CT (17±12 and 16±17 HU, p=0.65). In CE 3D‐CT and CE 4D‐CT, mean CNR (1.8±1.4 and 1.8±1.7, p=0.94) and mean SNR (5.8±2.6 and 5.5±3.2, p=0.71) both were higher than 4D‐CT (CNR: 1.1±1.3, p<0.3; SNR: 3.3±2.1, p<0.1). The absolute enhancement levels for T and P were higher in CE 4D‐CT (87, 82 HU) than in CE 3D‐CT (60, 56) and 4DCT (53, 70).Conclusions:The individually optimized CE 4D‐CT is feasible and achieved comparable image qualities to the clinical standard simulation. This study was supported in part by Philips Healthcare.
SU‐E‐J‐162: Systematic Feasibility Analysis of a Quantitative Elasticity Estimation for Breast Anatomy Using Supine/prone Model Postures
Authors: Hasse K , Neylon J , Santhanam A 
Published: June 2015

Purpose:The purpose of this project is to estimate an elasticity distribution of breast tissue using supine/prone patient postures. Using biomechanical high‐resolution breast models, a systematic assessment was performed in order to determine the feasibility of using patient standard clinical CT data.Methods:A GPU‐based framework was used to generate a mass‐spring model with a hemispherical geometry to represent a breast in the prone position. The model was anchored to the base of the hemisphere mimicking the chest‐wall/breast tissue interface. The model then was deformed with several ground‐truth elasticity distributions. Both isotropic and anisotropic elasticity distributions were used to demonstrate a tumor's presence in the breast tissue. Solving the inverse elasticity problem was accomplished with a forward iterative approach by resetting the model to a non‐deformed position and iteratively deforming it. A gradient‐based iterative optimization scheme was used to update elasticity distribution in order to minimize the discrepancy between ground‐truth and computed mechanical responses (displacement) for each voxel. For the purpose of our feasibility study, convergence was obtained when each voxel of tissue was within 1 mm of the ground‐truth deformation. The model resolution was systematically varied to verify convergence at different volume representations.Results:For a simulated hemisphere running at 200 deformations per second (dps) with about 100,000 mass elements and 26 mass‐spring connections, convergence occurred within minutes for each elastic distribution. Using apriori information about the underlying anatomy, these elasticity distribution were estimated in half the computation time with the accuracy improving from 89% to 93%. Though the effective elasticity estimation varied slightly from the ground‐truth, displacement magnitude difference was well within 0.1 mm.Conclusion:By utilizing a forward iterative approach to solve the inverse elasticity problem, this work indicates the feasibility and potential of the fast reconstruction of breast tissue elasticity distribution using supine/prone postures.
SU‐E‐J‐169: The Dosimetric and Temporal Effects of Respiratory‐Gated Radiation Therapy in Lung Cancer Patients
Authors: Rouabhi O , Gross B , Bayouth J , Xia J 
Published: June 2015

Purpose:To evaluate the dosimetric and temporal effects of high dose rate treatment mode for respiratory‐gated radiation therapy in lung cancer patients.Methods:Treatment plans from five lung cancer patients (3 nongated (Group 1), 2 gated at 80EX‐80IN (Group 2)) were retrospectively evaluated. The maximum tumor motions range from 6–12 mm. Using the same planning criteria, four new treatment plans, corresponding to four gating windows (20EX–20IN, 40EX–40IN, 60EX–60IN, and 80EX–80IN), were generated for each patient. Mean tumor dose (MTD), mean lung dose (MLD), and lung V20 were used to assess the dosimetric effects. A MATLAB algorithm was developed to compute treatment time by considering gantry rotation time, time to position collimator leaves, dose delivery time (scaled relative to the gating window), and communication overhead. Treatment delivery time for each plan was estimated using a 500 MU/min dose rate for the original plans and a 1500 MU/min dose rate for the gated plans.Results:Differences in MTD were less than 1Gy across plans for all five patients. MLD and lung V20 were on average reduced between −16.1% to −6.0% and −20.0% to −7.2%, respectively for non‐gated plans when compared with the corresponding gated plans, and between − 5.8% to −4.2% and −7.0% to −5.4%, respectively for plans originally gated at 80EX–80IN when compared with the corresponding 20EX‐20IN to 60EX– 60IN gated plans. Treatment delivery times of gated plans using high dose rate were reduced on average between −19.7% (−1.9min) to −27.2% (−2.7min) for originally non‐gated plans and −15.6% (−0.9min) to −20.3% (−1.2min) for originally 80EX‐80IN gated plans.Conclusion:Respiratory‐gated radiation therapy in lung cancer patients can reduce lung toxicity, while maintaining tumor dose. Using a gated high‐dose‐rate treatment, delivery time comparable to non‐gated normal‐dose‐rate treatment can be achieved.This research is supported by Siemens Medical Solutions USA, Inc
SU‐E‐J‐173: Dosimetric Effect of Patient Positioning Uncertainties for IMRT and SBRT
Authors: Luo W , Sandu A 
Published: June 2015

Purpose:To quantify the dosimetric effects of patient positioning uncertainties on PTV coverage and normal tissue sparing and find the tolerance for IMRT and SBRT positioning errors.Method and Materials: Patient positioning uncertainties were represented by isocenter shifts. Three head and neck IMRT, three prostate IMRT, and two lung SBRT plans were included in this study. The potential positioning uncertainties were introduced by shifting the isocenters by 0.1 cm, 0.3 cm, 0.5 cm, .0 cm, and 1.5 cm in Eclipse. Actual isocenter shifts (clinical shift) based on OBI/CBCT were also applied to the plans. The plans with isocenter shifts were recalculated in Eclipse and the results were compared with the original plans.Results:The dose errors increased with isocenter shifts. For head and neck patients, the PTV D95 dropped by 3.3% and the cord dose increased by 3.0% for 3‐mm shift, but D95 dropped 6.8 % with 5 mm shift, and spinal cord dose increased by 6.9%. For prostate, 3‐mm shift reduced 3.4% in D95 and increased 1.2% rectum dose and 2.7% bladder dose, while 5 mm shift caused 9.8% of reduction in D95 and 14.2% increase in bladder dose, but 7.1% decrease in rectum mean dose. For lung SBRT, 1‐mm shift caused 2.2% decrease in D95 and 0.7% decrease in spinal cord, but 3 mm shifts led to 14.9% of decrease in D95, while spinal cord dose also decreased by 1.5%.ConclusionThe patient positioning uncertainties reduced the PTV coverage and changed the dose to the normal tissues. However, the significance of dosimetric effect of patient positioning uncertainties varied with different tumor sites. This study suggested that the positioning uncertainty should be within 3 mm for regular IMRT treatment, and 1 mm for SBRT to avoid significant dose errors.
SU‐E‐J‐186: Using 4DCT‐Based Motion Modeling to Predict Motion and Duty Cycle On Successive Days of Gated Radiotherapy
Authors: Myronakis M , Cai W , Dhou S , Cifter F , Lewis J 
Published: June 2015

Purpose:To determine if 4DCT‐based motion modeling and external surrogate motion measured during treatment simulation can enhance prediction of residual tumor motion and duty cycle during treatment delivery.Methods:This experiment was conducted using simultaneously recorded tumor and external surrogate motion acquired over multiple fractions of lung cancer radiotherapy. These breathing traces were combined with the XCAT phantom to simulate CT images. Data from the first day was used to estimate the residual tumor motion and duty cycle both directly from the 4DCT (the current clinical standard), and from external‐surrogate based motion modeling. The accuracy of these estimated residual tumor motions and duty cycles are evaluated by comparing to the measured internal/external motions from other treatment days.Results:All calculations were done for 25% and 50% duty cycles. The results indicated that duty cycle derived from 4DCT information alone is not enough to accurately predict duty cycles during treatment. Residual tumor motion was determined from the recorded data and compared with the estimated residual tumor motion from 4DCT. Relative differences in residual tumor motion varied from −30% to 55%, suggesting that more information is required to properly predict residual tumor motion. Compared to estimations made from 4DCT, in three out of four patients examined, the 30 seconds of motion modeling data was able to predict the duty cycle with better accuracy than 4DCT. No improvement was observed in prediction of residual tumor motion for this dataset.Conclusion:Motion modeling during simulation has the potential to enhance 4DCT and provide more information about target motion, duty cycles, and delivered dose. Based on these four patients, 30 seconds of motion modeling data produced improve duty cycle estimations but showed no measurable improvement in residual tumor motion prediction. More patient data is needed to verify this Result.I would like to acknowledge funding from MRA, VARIAN Medical Systems, Inc.