bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐T‐813: What Is the “real” Field‐Size in Photon Dosimetry?
Authors: Gainey M , Kollefrath M , Saum R , Bruggmoser G 
Published: June 2015

Purpose:The definition of field sizes in photon dosimetry and the measurement of profiles are non‐trivial. Current definitions are nominal, geometric, dosimetric (actual) or equivalent field size. In reality most detectors are not water equivalent since they contain air or high density materials. These materials can blur profiles, particularly in small fields. If necessary, detector and field size‐specific volume dependent effects need to be considered.Methods:A TrueBeam‐linac (Varian Medical Systems) was used. All measurements were performed within a water phantom (MP3, PTW‐Freiburg), with filter (WFF) and without filter (FFF), using ionization chambers, shielded and unshielded diodes and diamond detectors. The position of the jaws was verified according to our QA‐system. Field size profiles were taken at a defined depth (SSD =90 cm, SCD=100 cm). The penumbra of the profiles measured with the various detectors was compared to determine the dosimetric field size. For the evaluation of the field sizes the inclination points were also calculated.Results:The field size, both for the WFF and the FFF‐mode, coincided within 1 mm of the nominal field size. Due to the fact that the jaws were adjusted properly, the dosimetric field size coincides with the geometric field size. Exceptions are very small fields, where the dosimetric field size, defined by the inclination points, becomes broader than the geometric field size.Conclusion:Profiles, particularly of small fields, have to be measured very carefully using a suitable detector. For this purpose, a detector with a negligible volume correction factor should be used. The dosimetric field size can be found by evaluating the inclination points for both WFF and FFF beams. For dosimetric purposes it is necessary to find the dosimetric size. Alternatively, if the measurements are basic data for a TPS, both, the geometric and the dosimetric sizes should be recorded.
SU‐E‐T‐814: Whole Breast Irradiation with Two Different Intensity Modulation Radiotherapy Techniques
Authors: Sun T , Yin Y , Lin X , Zhang G 
Published: June 2015

Purpose:Breast cancer now mainly received forward intensity modulation radiotherapy (f‐IMRT) and inverse IMRT (i‐IMRT). The purpose of this study was to observe the differences of two treatment methods.Methods:10 patients after left breast‐conserving surgery were selected to receive radiotherapy. For each patient, two treatment plans (f‐IMRT and i‐IMRT) were designed. For f‐IMRT plans, two tangent beams were designed to the target, and in each tangent orientation two or three segment beams were designed to reduced high dose region in the target and the dose of lung received. For i‐IMRT plans, two tangent beams were designed to the target and the treatment planning system optimize the dose according to the optimization parameters. For each plan 50Gy was prescribed.Results:In f‐IMRT and i‐IMRT plans, the average target conformal index (CI) were (0.67±0.06) and (0.66±0.06), (P>0.05); average homogeneity index (HI) were (28.2±6.0)% and (26.1±6.8)%, (P>0.05); volume of left lung received 20Gy (V20) were (18.7±3.3)% and (17.0±2.8)%, (P<0.05), V30 were (15.5±3.0)% and (14.0±2.6)%, (P<0.05); V30 of heart were (4.1±3.1)% and (3.5±2.5)%, (P>0.05); Monitor Unit (MU) were (262±5)MU and (308±14)MU.Conclusion:Compared with i‐IMRT plan, for breast cancer, the differences of CI and HI were not significant. Because of fewer MU, f‐IMRT plan could reduce the machine abrasion and treatment time, but dose of normal tissue received were higher significantly than i‐IMRT plan.
SU‐F‐BRD‐01: A Novel 4D Robust Optimization Mitigates Interplay Effect in Intensity‐Modulated Proton Therapy for Lung Cancer
Authors: Liu W , Schild S , Chang J , Liao Z , Wen Z , Shen J , Stoker J , Wong W , Sahoo N , Herman M , Mohan R , Bues M 
Published: June 2015

Purpose:To compare the impact of interplay effect on 3D and 4D robustly optimized intensity‐modulated proton therapy (IMPT) plans to treat lung cancer.Methods:Two IMPT plans were created for 11 non‐small‐cell‐lung‐cancer cases with 6–14 mm spots. 3D robust optimization generated plans on average CTs with the internal gross tumor volume density overridden to deliver 66 CGyE in 33 fractions to the internal target volume (ITV). 4D robust optimization generated plans on 4D CTs with the delivery of prescribed dose to the clinical target volume (CTV). In 4D optimization, the CTV of individual 4D CT phases received non‐uniform doses to achieve a uniform cumulative dose. Dose evaluation software was developed to model time‐dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Patient anatomy voxels were mapped from phase to phase via deformable image registration to score doses. Indices from dose‐volume histograms were used to compare target coverage, dose homogeneity, and normal‐tissue sparing. DVH indices were compared using Wilcoxon test.Results:Given the presence of interplay effect, 4D robust optimization produced IMPT plans with better target coverage and homogeneity, but slightly worse normal tissue sparing compared to 3D robust optimization (unit: Gy) [D95% ITV: 63.5 vs 62.0 (p=0.014), D5% ‐ D95% ITV: 6.2 vs 7.3 (p=0.37), D1% spinal cord: 29.0 vs 29.5 (p=0.52), Dmean total lung: 14.8 vs 14.5 (p=0.12), D33% esophagus: 33.6 vs 33.1 (p=0.28)]. The improvement of target coverage (D95%,4D – D95%,3D) was related to the ratio RMA3/(TVx10−4), with RMA and TV being respiratory motion amplitude (RMA) and tumor volume (TV), respectively. Peak benefit was observed at ratios between 2 and 10. This corresponds to 125 – 625 cm3 TV with 0.5‐cm RMA.Conclusion:4D optimization produced more interplay‐effect‐resistant plans compared to 3D optimization. It is most effective when respiratory motion is modest compared to TV.NIH/NCI K25CA168984; Eagles Cancer Research Career Development; The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research; Mayo ASU Seed Grant; The Kemper Marley Foundation
SU‐F‐BRD‐02: Incorporating Uncertainty Analysis in Plan Comparison of VMAT, Double Scattering Proton Plan and IMPT for Lung Irradiation
Authors: Cheng C , Wessels B , Mansur D , Machtay M 
Published: June 2015

Purpose:We investigate the effect of residual setup and motion errors in lung irradiation for VMAT, double scattering (DS) proton beams and spot scanning (IMPT) in a case study.Methods:The CT image and contour sets of a lung patient treated with 6 MV VMAT is re‐planned with DS as well as IMPT subject to the same constraints; V20(lung), V10(lung) and V5(lung)< 15%, 20% and 25% respectively, V20(heart)<25% and V100%(PTV)≥95%. In addition, uncertainty analysis in the form of isocenter shifts (±1–3mm) was incorporated in the DVH calculations to assess the plan robustness.Results:Only the IMPT plan satisfies all the specified constraints. The 3D‐conformal DS proton plan is able to achieve better sparing of the lung and heart dose compared to VMAT. For the lung, V20, V10 and V5 are 13%, 19% and 25% respectively for IMPT, 18%, 23% and 30% respectively for DS, and 20%, 30% and 42% respectively for VMAT. For heart: 0.6% for IMPT, 2.4% for DS and 30% for VMAT. When incorporating isocenter shifts in DVH calculations, the maximum changes in V20, V10 and V5 for lung are 14%, 21% and 28% respectively for IMPT. The corresponding max changes are19%, 24% and 32% respectively for DS, and 22%, 32% and 44% respectively for VMAT. The largest change occurs in the PTV coverage. For IMPT, V100%(PTV) varies between 88–96%, while V100%(PTV) for VMAT suffers a larger change compared to DS (Δ=5.5% vs 3.3%).Conclusion:While only IMPT satisfies the stringent dose‐volume constraints for the lung irradiation, it is not as robust as the 3D conformal DS plan. DS also has better sparing in lung and heart compared to VMAT and similar PTV coverage. By including isocenter shifts in dose‐volume calculations in treatment planning of lung, DS appears to be more robust than VMAT.
SU‐F‐BRD‐03: Evaluation of Head‐Neck IMPT Plans Quality Using a Knowledge Based Model
Authors: Jingqian W , Yuan L , Li Y , Li H , Frank S , Wu Q , Zhang X 
Published: June 2015

Purpose:To develop and evaluate a model that predicts the dose volume histogram (DVH) of head and neck IMPT plans based on knowledge of prior plans.Methods:Total of forty Head‐Neck cancer patients underwent IMPT were used in the study. Using thirty patient CT, contours, IMPT treatment plans and calculated dose as input, significant factors that predicts the dose volume histogram (DVH) for organs at risks (OARs) including right/left parotid, oral cavity, esophagus, brain stem, larynx, and spinal cord were identified using principle component analysis (PCA) method. The model was then evaluated by comparing model predicted DVH for with planned DVH for ten additional IMPT plans.Results:Combined distance‐to‐target Histogram (DTH) Principal Components (PCs) were found to be the most important in the first principal component of parotids, oral cavity, and esophagus. The quality of the model prediction is correlated to the knowledge or quantities of the plans that model learned. For patients with tumor and OARs geometry deviates from the training data set, the predicted DVH may be inferior to the actual treatment plans. For patients with tumor and OARs geometry similar to the training data set, the model was able to predict the performance of the actual treatment plan.Conclusion:The quality of DVH prediction knowledge base model was investigated using head‐neck plans. The results indicated that the performance of the model is dependent on the quality and quantity of the training data set. The prediction model may provide real time evaluations for plan optimization in complex patient geometries such as head and neck cancer with multiple dose levels.Supported by Research agreement with Varian Medical Systems.
SU‐F‐BRD‐04: Robustness Analysis of Proton Breast Treatments Using An Alpha‐Stable Distribution Parameterization
Authors: Van den Heuvel F , Hackett S , Fiorini F , Taylor C , Darby S , Vallis K 
Published: June 2015

Purpose:Currently, planning systems allow robustness calculations to be performed, but a generalized assessment methodology is not yet available. We introduce and evaluate a methodology to quantify the robustness of a plan on an individual patient basis.Methods:We introduce the notion of characterizing a treatment instance (i.e. one single fraction delivery) by describing the dose distribution within an organ as an alpha‐stable distribution. The parameters of the distribution (shape(α), scale(γ), position(δ), and symmetry(β)), will vary continuously (in a mathematical sense) as the distributions change with the different positions. The rate of change of the parameters provides a measure of the robustness of the treatment. The methodology is tested in a planning study of 25 patients with known residual errors at each fraction. Each patient was planned using Eclipse with an IBA‐proton beam model. The residual error space for every patient was sampled 30 times, yielding 31 treatment plans for each patient and dose distributions in 5 organs. The parameters’ change rate as a function of Euclidean distance from the original plan was analyzed.Results:More than 1,000 dose distributions were analyzed. For 4 of the 25 patients the change in scale rate (γ) was considerably higher than the lowest change rate, indicating a lack of robustness. The sign of the shape change rate (α) also seemed indicative but the experiment lacked the power to prove significance.Conclusion:There are indications that this robustness measure is a valuable tool to allow a more patient individualized approach to the determination of margins. In a further study we will also evaluate this robustness measure using photon treatments, and evaluate the impact of using breath hold techniques, and the a Monte Carlo based dose deposition calculation. A principle component analysis is also planned.
SU‐F‐BRD‐10: Improving Plan Delivery Efficiency of Intensity Modulated Proton Plans with Prioritized Optimization
Authors: Müller BS , Wilkens JJ 
Published: June 2015

Purpose:To integrate treatment delivery time into plan optimization in spot scanning intensity modulated proton therapy. Utilizing a dedicated research treatment planning system we present an optimization approach to explore the trade‐off between the correlated parameters treatment time and plan quality on an astrocytoma patient case.Methods:The planning system is based on prioritized optimization, a stepwise approach of implementing clinical goals. After each optimization step, dosimetric achievements are turned into hard constraints to maintain the achieved plan quality. Prior achievements can be violated by a so‐called slip‐factor which allows to study possible trade‐offs of conflicting goals. Plan quality is obtained in the first two steps, while the third step optimizes delivery efficiency by working on the spot weight distribution via four alternativeMethods:elimination of low weighted spots (1), elimination of spots hardly contributing to PTV dose, followed by reoptimization of the resulting smaller optimization problem (2), reduction of spot weights variance within each energy layer (3), and reduction of the overall spot weight sum (4). Treatment times were calculated assuming either constant or variable beam current depending on the lowest spot weight.Results:Delivery efficiency can be improved remarkably without influencing the plan quality. Absolute time savings depend on the utilized method and facility properties. By varying slip‐factor and spot reduction limits, a border of worsening quality is detectable for all methods.Deleting low weighted spots by 10% results in a noticeable decrease in minimum target dose. Further reduction results in more heterogeneous dose distributions and insufficient coverage. Option 2 showed constant plan quality for spot reductions of more than 10%.Conclusion:Including treatment time optimization as a final step into prioritized optimization allows for more efficient treatment plans by redistributing the spot patterns without compromising plan quality, which has to remain the main intent of radiotherapy treatment.The authors report grants from German Research Foundation (DFG) during the conduct of the study.
SU‐F‐BRD‐15: Quality Correction Factors in Scanned Or Broad Proton Therapy Beams Are Indistinguishable
Authors: Sorriaux J , Testa M , Paganetti H , Bertrand D , de Xivry J Orban , Lee J , Palmans H , Vynckier S , Sterpin E 
Published: June 2015

Purpose:The IAEA TRS‐398 code of practice details the reference conditions for reference dosimetry of proton beams using ionization chambers and the required beam quality correction factors (kQ). Pencil beam scanning (PBS) requires multiple spots to reproduce the reference conditions. The objective is to demonstrate, using Monte Carlo (MC) calculations, that kQ factors for broad beams can be used for scanned beams under the same reference conditions with no significant additional uncertainty. We consider hereafter the general Alfonso formalism (Alfonso et al, 2008) for non‐standard beam.Methods:To approach the reference conditions and the associated dose distributions, PBS must combine many pencil beams with range modulation and shaping techniques different than those used in passive systems (broad beams). This might lead to a different energy spectrum at the measurement point. In order to evaluate the impact of these differences on kQ factors, ion chamber responses are computed with MC (Geant4 9.6) in a dedicated scanned pencil beam (Q_pcsr) producing a 10×10cm2 composite field with a flat dose distribution from 10 to 16 cm depth. Ion chamber responses are also computed by MC in a broad beam with quality Q_ds (double scattering). The dose distribution of Q _pcsr matches the dose distribution of Q_ds. k_(Q_pcsr,Q_ds) is computed for a 2×2×0.2cm3 idealized air cavity and a realistic plane‐parallel ion chamber (IC).Results:Under reference conditions, quality correction factors for a scanned composite field versus a broad beam are the same for air cavity dose response, k_(Q_pcsr,Q_ds) =1.001±0.001 and for a Roos IC, k_(Q_pcsr,Q_ds) =0.999±0.005.Conclusion:Quality correction factors for ion chamber response in scanned and broad proton therapy beams are identical under reference conditions within the calculation uncertainties. The results indicate that quality correction factors published in IAEA TRS‐398 can be used for scanned beams in the SOBP of a high‐energy proton beam.Jefferson Sorriaux is financed by the Walloon Region under the convention 1217662. Jefferson Sorriaux is sponsored by a public‐private partnership IBA ‐ Walloon Region
SU‐F‐BRB‐04: Comparison of Coplanar VMAT, Non‐Coplanar VMAT, and 4π Treatment Plans
Authors: Woods K , Nguyen D , Tran A , Yu V , Cao M , Sheng K 
Published: June 2015

Purpose:The 4π non‐coplanar radiotherapy delivery technique has demonstrated significantly better normal tissue sparing and dose conformality than the clinically used volumetric modulated arc therapy (VMAT). It is unclear whether this is a fundamental limitation of VMAT delivery or the coplanar nature of its typical clinical plans. The non‐coplanar basis of 4π is incorporated into VMAT treatment planning to compare its effect on plan quality.Methods:Clinical stereotactic body radiation therapy plans for 9 liver patients treated with 30–60 Gy using coplanar VMAT (cVMAT) were re‐planned using non‐coplanar VMAT (nVMAT) with 3 arcs and 4 π with 20 intensity‐modulated non‐coplanar fields. All plans were optimized to deliver 100% of the prescribed dose to 95% of the planning target volume (PTV), and nVMAT and 4π plans were tailored to match the maximum and mean PTV dose from the clinical plan. The conformality index (CI), 50% dose spillage volume (R50), normal liver volume receiving >15 Gy (VL>15), and doses to organs at risk (OARs) were compared for all three treatment plans.Results:Compared to cVMAT, the nVMAT and 4π plans reduced VL>15 by an average of 30.6 cm3 and 96.3 cm3, respectively. The average CI was also reduced from 1.22 (cVMAT) to 1.17 (nVMAT) and 1.14 (4π), indicating higher conformality in the same order. Similarly, R50 was reduced from 3.87 (cVMAT) to 3.58 (nVMAT) and 2.74 (4π). With the exception of the mean right kidney dose, which increased by an average of only 0.6 Gy for nVMAT, the dose differences to OARs were not statistically significant between the two VMAT plans. 4π plans either significantly decreased or maintained OAR doses.Conclusion:While the manual selection of intuitive non‐coplanar arcs does show some improvement over coplanar VMAT, the automated beam selection for 4π still results in superior plan quality.This project is supported in part by Varian Medical Systems and NIH R43 CA183390.
SU‐F‐BRB‐05: Collision Avoidance Mapping Using Consumer 3D Camera
Authors: Cardan R , Popple R 
Published: June 2015

Purpose:To develop a fast and economical method of scanning a patient's full body contour for use in collision avoidance mapping without the use of ionizing radiation.Methods:Two consumer level 3D cameras used in electronic gaming were placed in a CT simulator room to scan a phantom patient set up in a high collision probability position. A registration pattern and computer vision algorithms were used to transform the scan into the appropriate coordinate systems. The cameras were then used to scan the surface of a gantry in the treatment vault. Each scan was converted into a polygon mesh for collision testing in a general purpose polygon interference algorithm. All clinically relevant transforms were applied to the gantry and patient support to create a map of all possible collisions. The map was then tested for accuracy by physically testing the collisions with the phantom in the vault.Results:The scanning fidelity of both the gantry and patient was sufficient to produce a collision prediction accuracy of 97.1% with 64620 geometry states tested in 11.5 s. The total scanning time including computation, transformation, and generation was 22.3 seconds.Conclusion:Our results demonstrate an economical system to generate collision avoidance maps. Future work includes testing the speed of the framework in real‐time collision avoidance scenarios.Research partially supported by a grant from Varian Medical Systems
SU‐F‐BRB‐06: Validation of Dose Calculation for Helical Tomotherapy with a Rigidly Moving Object
Authors: Chao E , Lucas D , Beneke M , Casey D , Henderson D , Homp J , Kammeyer T , Lai S , Mauer C , O'Connell R , Schnarr E 
Published: June 2015

Purpose:To validate dose calculations in a rigidly moving object.Methods:An off‐line version of the TomoTherapy™ dose calculation software was extended to allow dose calculation for rigidly moving objects. The interface allows users to extract the necessary data from TomoTherapy patient archives to perform an off‐line dose calculation, and to specify arbitrary translational motion by creating a text file with a column for time, and columns for x, y, and z translations. Film measurements were performed using a phantom that was rigidly moved with the same motion profile as used in the calculation. A variety of motion profiles were studied and the motion profiles were applied to delivery plans with varying field sizes (1, 2.5, and 5 cm) and with dynamic jaws and static jaws.Results:Calculations matched measurements to within 2% or 1 mm for the variety of motion profiles studied. A 4‐mm step motion in the longitudinal (IEC‐Y) direction timed to occur halfway through a 1 cm field‐width delivery resulted in a 29% decrease in both the calculated dose and measured dose in a central region of the dose profile. For a 5 cm field‐width dynamic jaw delivery, the 4 mm step motion resulted in a more broadly distributed reduction in dose of 8%. A 6 mm sinusoidal motion in the longitudinal direction with a 6 second period had a negligible impact on delivered dose for one particular delivery plan. Similarly, a step motion in the transverse direction (IEC‐X) had a negligible impact on delivered dose other than to shift the dose volume.Conclusion:A research version of the TomoTherapy™ dose calculator can accurately calculate dose for a rigidly moving object. Further studies with more clinical motion traces and with clinical treatment delivery plans will yield valuable insight into the impact of motion on the delivered dose.