bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐T‐24: A Simple Correction‐Based Method for Independent Monitor Unit (MU) Verification in Monte Carlo (MC) Lung SBRT Plans
Authors: Pokhrel D , Badkul R , Jiang H , Estes C , Kumar P , Wang F 
Published: July 2014

Purpose:Lung‐SBRT uses hypo‐fractionated dose in small non‐IMRT fields with tissue‐heterogeneity corrected plans. An independent MU verification is mandatory for safe and effective delivery of the treatment plan. This report compares planned MU obtained from iPlan‐XVM‐Calgorithm against spreadsheet‐based hand‐calculation using most commonly used simple TMR‐based method.Methods:Treatment plans of 15 patients who underwent for MC‐based lung‐SBRT to 50Gy in 5 fractions for PTV V100%=95% were studied. ITV was delineated on MIP images based on 4D‐CT scans. PTVs(ITV+5mm margins) ranged from 10.1‐ 106.5cc(average=48.6cc). MC‐SBRT plans were generated using a combination of non‐coplanar conformal arcs/beams using iPlan XVM‐Calgorithm (BrainLAB iPlan ver.4.1.2) for Novalis‐TX consisting of micro‐MLCs and 6MV‐SRS (1000MU/min) beam. These plans were re‐computed using heterogeneity‐corrected Pencil‐Beam (PB‐hete) algorithm without changing any beam parameters, such as MLCs/MUs. Dose‐ratio: PB‐hete/MC gave beam‐by‐beam inhomogeneity‐correction‐factors (ICFs):Individual Correction. For independent‐2nd‐check, MC‐MUs were verified using TMR‐based hand‐calculation and obtained an average ICF:Average Correction, whereas TMR‐based hand‐calculation systematically underestimated MC‐MUs by ∼5%. Also, first 10 MC‐plans were verified with an ion‐chamber measurement using homogenous phantom.Results:For both beams/arcs, mean PB‐hete dose was systematically overestimated by 5.5±2.6% and mean hand‐calculated MU systematic underestimated by 5.5±2.5% compared to XVMC. With individual correction, mean hand‐calculated MUs matched with XVMC by – 0.3±1.4%/0.4±1.4 for beams/arcs, respectively. After average 5% correction, hand‐calculated MUs matched with XVMC by 0.5±2.5%/0.6±2.0% for beams/arcs, respectively. Smaller dependence on tumor volume(TV)/field size(FS) was also observed. Ion‐chamber measurement was within ±3.0%.Conclusion:PB‐hete overestimates dose to lung tumor relative to XVMC. XVMC‐algorithm is much more‐complex and accurate with tissues‐heterogeneities. Measurement at machine is time consuming and need extra resources; also direct measurement of dose for heterogeneous treatment plans is not clinically practiced, yet. This simple correction‐based method was very helpful for independent‐2nd‐check of MC‐lung‐SBRT plans and routinely used in our clinic. A look‐up table can be generated to include TV/FS dependence in ICFs.
SU‐E‐T‐27: A Tool for Routine Quality Assurance of Radiotherapy Dose Calculation Software
Authors: Popple R , Cardan R , Duan J , Wu X , Shen S , Brezovich I 
Published: July 2014

Purpose:Dose calculation software is thoroughly evaluated when it is commissioned; however, evaluation of periodic software updates is typically limited in scope due to staffing constraints and the need to quickly return the treatment planning system to clinical service. We developed a tool for quickly and comprehensively testing and documenting dose calculation software against measured data.Methods:A tool was developed using MatLab (The MathWorks, Natick, MA) for evaluation of dose calculation algorithms against measured data. Inputs to the tool are measured data, reference DICOM RT PLAN files describing the measurements, and dose calculations in DICOM format. The tool consists of a collection of extensible modules that can perform analysis of point dose, depth dose curves, and profiles using dose difference, distance‐to‐agreement, and the gamma‐index. Each module generates a report subsection that is incorporated into a master template, which is converted to final form in portable document format (PDF).Results:After each change to the treatment planning system, a report can be generated in approximately 90 minutes. The tool has been in use for more than 5 years, spanning 5 versions of the eMC and 4 versions of the AAA. We have detected changes to the algorithms that affected clinical practice once during this period.Conclusion:Our tool provides an efficient method for quality assurance of dose calculation software, providing a complete set of tests for an update. Future work includes the addition of plan level tests, allowing incorporation of, for example, the TG‐119 test suite for IMRT, and integration with the treatment planning system via an application programming interface. Integration with the planning system will permit fully‐automated testing and reporting at scheduled intervals.
SU‐E‐T‐30: Absorbed Doses Determined by Texture Analysis of Gafchromic EBT3 Films Using Scanning Electron Microscopy: A Feasibility Study
Authors: Park S , Kim H , Ye S 
Published: July 2014

Purpose:The texture analysis method is useful to estimate structural features of images as color, size, and shape. The study aims to determine a dose‐response curve by texture analysis of Gafchromic EBT3 film images using scanning electron microscopy (SEM).Methods:The uncoated Gafchromic EBT3 films were prepared to directly scan over the active surface layer of EBT3 film using SEM. The EBT3 films were exposed at a dose range of 0 to 10 Gy using a 6 MV photon beam. The exposed film samples were SEM‐scanned at 100X, 1000X, and 3000X magnifications. The four texture features (Homogeneity, Correlation, Contrast, and Energy) were calculated based on the gray level co‐occurrence matrix (GLCM) derived from the SEM images at each dose. To validate a correlation between delivered doses and texture features, an R‐squared value in linear regression was tested.Results:The results showed that the Correlation index was more suitable as dose indices than the other three texture features due to higher linearity and sensitivity of the dose response curves. Further the Correlation index of 3000X magnified SEM images with 9 pixel offsets had an R‐squared value of 0.964. The differences between the delivered doses and the doses measured by this method were 0.9, 1.2, 0.2, and 0.2 Gy at 5, 10, 15, and 20 Gy, respectively.Conclusion:It seems to be feasible to convert micro‐scale structural features of χtχχχhe EBT3 films to absorbed doses using the texture analysis method.
SU‐E‐T‐38: An Overlap‐Wall‐Histogram Plan Quality Classifier for Automatic Prostate Cancer IMRT Treatment Plan Quality Control
Authors: Song T , Tian Z , Jia X , Zhou L , Jiang S , Gu X 
Published: July 2014

Purpose:A new patient geometry descriptor, PTV and a hollow organ overlapping wall histogram (OWH), is proposed to combine with dose to wall histogram (DWH) to develop a plan quality classification model for automatic prostate IMRT plan quality assessment and improvement.Methods:In this study, we define a geometric metric named COP (closeness of an OAR to PTV) to quantify the difficulty of patient geometry for planning and a dosimetric metric named DSO (dose spillage over an OAR) to evaluate treatment plan quality in terms of OAR dose sparing. COP and DSO are defined as the weighted sum of OWH and DWH respectively. Fifteen clinically acceptable prostate treatment plans were selected to study the correlation between COP and DSO. After plotting COP as X axis and DSO as Y axis, a linear correlation was established and the entire space is classified into high and poor plan quality regions by a linear fitting with these COP‐DSO pairs. This proposed classifier is evaluated with other 25 prostate plans. Any evaluation plan falling into the poor plan quality region will be re‐planned, and the re‐planning can be guided by a selected reference plan having similar COP but lower DSO values. Re‐planned high‐quality plans will be added to database, affording more options during reference plan selection.Results:Using our classification model, 8 out of 25 plans are identified as poor quality plans. After re‐planning, the dose volume for bladder wall W7 5(wall receiving more than 75Gy),W7 0,W6 5 and W6 0 can be reduced by 3.34%, 3%, 6.99%, 6.54% for the worst quality plan and 1.11%, 0.95%, 1.45% and 1.81% averaged over 8 plans, without sacrificing PTV coverage and rectum dose sparing.Conclusion:Our proposed model is capable to identify poor quality plans and find a specific reference plan to guide re‐planning, thus improve plan quality.
SU‐E‐T‐40: Analysis of Composite MVCT Planning Dosimetry with SBRT of Upper Peripheral Lung Cancer
Authors: Yang C , Doxsee K , Chen Y 
Published: July 2014

Purpose:Quantitatively evaluate and compare the final adaptive planning doses of upper peripherally located lung SBRT treated with Tomotherapy using 3rd party software tool.Methods:With tumor located in the upper quadrant of lung, a 3rd party software tool was implemented to evaluate the Tomotherapy composite dosimetry created by adaptive fan beam MVCT images described by RTOG 0915 dose criteria (48 Gy / 4 fractions). The composite doses was then summarized with deformable registration in this package with corresponding target and critical structures. The final dosimetry variation, both for target and critical structures, were evaluated in a tabular format and isodose distribution comparisons.Results:Composite SBRT treatment doses were evaluated with adaptive planning. The PTV and several critical structures were mapped/deformed into the package via DICOM from Tomotherapy after the final composite doses were created. Initial plan versus the final composite plan calculated from verification images were compared. The ITV defined by 4D CT and contoured on MVCT images were correlated in patient repositioning. Final composite dose calculated for PTV coverage has shown 0.1–0.17 cGy coverage (0.2–0.4% of prescription dose) variation. Total lung and cord were both less than 0.17 Gy which represented <0.4% difference. All other critical structure were within statistical significance. The adaptive plans justified/included the breathing and motion during the treatment process. Final 95% isotope line coverage from prescription has been met without issues.Conclusions:With lung tumor location in the upper peripheral area, breathing control was not necessary required during SBRT treatment using Tomotherapy technique. Slow fan beam CT provides definitive ITV information and the adaptive composite plan for all fractions were suitable for final dose delivery. The final composite dose calculated with Tomotherapy adaptive tool indicated that the composite dosimetry justified the target location with SBRT delivery, safe with minimum margin of errors.
SU‐E‐T‐51: Bayesian Network Models for Radiotherapy Error Detection
Authors: Kalet A , Phillips M , Gennari J 
Published: July 2014

Purpose:To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery.Methods:Semi‐structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant radiotherapy concepts and their associated interdependencies. Concepts in the final network were limited to those whose parameters are represented in the institutional database at a level significant enough to develop mathematical distributions. The concept‐relation knowledge base was constructed using the Web Ontology Language (OWL) and translated into Hugin Expert Bayes Network files via the the RHugin package in the R statistical programming language. A subset of de‐identified data derived from a Mosaiq relational database representing 1937 unique prescription cases was processed and pre‐screened for errors and then used by the Hugin implementation of the Estimation‐Maximization (EM) algorithm for machine learning all parameter distributions. Individual networks were generated for each of several commonly treated anatomic regions identified by ICD‐9 neoplasm categories including lung, brain, lymphoma, and female breast.Results:The resulting Bayesian networks represent a large part of the probabilistic knowledge inherent in treatment planning. By populating the networks entirely with data captured from a clinical oncology information management system over the course of several years of normal practice, we were able to create accurate probability tables with no additional time spent by experts or clinicians. These probabilistic descriptions of the treatment planning allow one to check if a treatment plan is within the normal scope of practice, given some initial set of clinical evidence and thereby detect for potential outliers to be flagged for further investigation.Conclusion:The networks developed here support the use of probabilistic models into clinical chart checking for improved detection of potential errors in RT plans.
SU‐E‐T‐54: Benefits of Biological Cost Functions
Authors: Demirag N 
Published: July 2014

Purpose:To verify the benefits of the biological cost functions.Methods:TG166 patients were used for the test case scenarios. Patients were planned using Monaco V5.0 (CMS/Elekta, St.Louis, MO) Monaco has 3 biological and 8 physical CFs. In this study the plans were optimized using 3 different scenarios. 1‐ Biological CFs only 2‐Physical CFs only 3‐ Combination of Physical&Biological CFsMonaco has 3 biological CFs. Target EUD used for the targets, derived from the poisson cell kill model, has an α value that controls the cold spots inside the target. α values used in the optimization were 0.5 and 0.8. if cold spots needs to be penalized α value increased. Serial CF: it's called serial to mimic the behaviour of the serial organs, if a high k value like 12 or 14 is used it controls the maximum dose. Serial CF has a k parameter that is used to shape the whole dvh curve. K value ranges between 1–20. k:1 is used to control the mean dose, lower k value controls the mean dose, higher k value controls the higher dose, using 2 serial CFs with different k values controls the whole DVH. Paralel CF controls the percentage of the volume that tolerates higher doses than the reference dose to mimic the behaviour of the paralel organs.Results:It was possible to achive clinically accepted plans in all 3 scenarios. The benefit of the biological cost functions were to control the mean dose for target and OAR, to shape the DVH curve using one EUD value and one k value simplifies the optimization process. Using the biological CFs alone, it was hard to control the dose at a point.Conclusion:Biological CFs in Monaco doesn' t require the ntcp/tcp values from the labs and useful to shape the whole dvh curve.I work as an applications support specialist for Elekta and I am a Ph.D. Student in Istanbul University for radiation therapy physics.
SU‐E‐T‐241: Monte Carlo Simulation Study About the Prediction of Proton‐Induced DNA Strand Breakage On the Double Helix Structure
Authors: Shin J , Park S , Jeong J , Jeong C , Lim Y , SHIN D , Incerti S , Lee S 
Published: July 2014

Purpose:In particle therapy and radiobiology, the investigation of mechanisms leading to the death of target cancer cells induced by ionising radiation is an active field of research. Recently, several studies based on Monte Carlo simulation codes have been initiated in order to simulate physical interactions of ionising particles at cellular scale and in DNA. Geant4‐DNA is the one of them; it is an extension of the general purpose Geant4 Monte Carlo simulation toolkit for the simulation of physical interactions at sub‐micrometre scale. In this study, we present Geant4‐DNA Monte Carlo simulations for the prediction of DNA strand breakage using a geometrical modelling of DNA structure.Methods:For the simulation of DNA strand breakage, we developed a specific DNA geometrical structure. This structure consists of DNA components, such as the deoxynucleotide pairs, the DNA double helix, the nucleosomes and the chromatin fibre. Each component is made of water because the cross sections models currently available in Geant4‐DNA for protons apply to liquid water only. Also, at the macroscopic‐scale, protons were generated with various energies available for proton therapy at the National Cancer Center, obtained using validated proton beam simulations developed in previous studies. These multi‐scale simulations were combined for the validation of Geant4‐DNA in radiobiology.Results:In the double helix structure, the deposited energy in a strand allowed to determine direct DNA damage from physical interaction. In other words, the amount of dose and frequency of damage in microscopic geometries was related to direct radiobiological effect.Conclusion:In this report, we calculated the frequency of DNA strand breakage using Geant4‐ DNA physics processes for liquid water. This study is now on‐going in order to develop geometries which use realistic DNA material, instead of liquid water. This will be tested as soon as cross sections for DNA material become available in Geant4‐DNA.
SU‐E‐T‐244: Motion Control Challenges in High Dose Rate Brachytherapy
Authors: Hyvarinen M , Leventouri T , Pella S , Dumitru N 
Published: July 2014

Purpose:High dose rate (HDR) brachytherapy dose distribution is highly localized and has a very sharp fall‐off. Thus the one of the most important part of the treatment is the localization and immobilization of the applicator from the implantation to the setup verification to the treatment delivery. The smallest motions of the patient can induce a small rotation, tilt, or translational movement of the applicator that can convert into miss of a significant part of the tumor or to over irradiating a nearby critical organ. The purpose of this study is to revise most of the HDR types of treatments with their applicators and their localization challenges. Since every millimeter of misplacement counts the study will look into the necessity of increasing the immobilization for several types of applicators.Methods:The study took over 136 plans generated by the treatment planning system (TPS) looking into the applicator placement in regard to the organs at risk (OR) and simulated the three possible displacements at the hottest dose point on the critical organ for several accessories to evaluate the variation of the delivered dose at the point due to the displacement.Results:Many of the present immobilization devices produced for external radiotherapy can be used to improve the localization of HDR applicators during transportation of the patient and during treatment.Conclusion:This study data indicates that an improvement of the immobilization devices for HDR is absolutely necessary. Better applicator fixation devices are required too. Developing new immobilization devices for all the applicators is recommended.
SU‐E‐T‐249: Neutron Model Upgrade for Radiotherapy Patients Monitoring Using a New Online Detector
Authors: Irazola L , Lorenzoli M , Terron J.A. , Bedogni R. , Pola A. , Sanchez Nieto B. , Romero‐Exposito M. , Sanchez Doblado F. 
Published: July 2014

Purpose:The purpose of this work is to improve the existing methodology to estimate neutron equivalent dose in organs during radiotherapy treatments, based on a Static Random Access Memory neutron detector (SRAMnd) [1]. This is possible thanks to the introduction of a new digital detector with improved characteristics, which is able to measure online the neutron fluence rate in the presence of an intense photon background [2]. Its reduced size, allows the direct estimation of doses in specific points inside an anthropomorphic phantom (NORMA) without using passive detectors as TLD or CR‐39. This versatility will allow not only to improve the existing models (generic abdomen and H&N [1]) but to generate more specific ones for any technique.Methods:The new Thermal Neutron Rate Detector (TNRD), based on a diode device sensitized to thermal neutrons, have been inserted in 16 points of the phantom. These points are distributed to infer doses to specific organs. Simultaneous measurements of these devices and a reference one, located in front of the gantry, have been performed for the mentioned generic treatments, in order to improve the existing model.Results:These new devices have shown more precise since they agree better with Monte Carlo simulations. The comparison of the thermal neutron fluence, measured with TNRD, and the existing models, converted from events to fluence, shows an average improvement of (3.90±3.37) % for H&N and (12.61±9.43) % for abdomen, normalized to the maximum value.Conclusion:This work indicates the potential of these new devices for more precise neutron equivalent dose estimation in organs, as a consequence of radiotherapy treatments. The simplicity of the process makes possible to establish more specific models that will provide a better dose estimation. References[1] Phys Med Biol 2012; 57:6167–6191.[2] A new active thermal neutron detector. Radiat. Prot. Dosim. (in press).
SU‐E‐T‐254: Optimization of GATE and PHITS Monte Carlo Code Parameters for Uniform Scanning Proton Beam Based On Simulation with FLUKA General‐Purpose Code
Authors: Kurosu K , Takashina M , Koizumi M , Das I , Moskvin V 
Published: July 2014

Purpose:Monte Carlo codes are becoming important tools for proton beam dosimetry. However, the relationships between the customizing parameters and percentage depth dose (PDD) of GATE and PHITS codes have not been reported which are studied for PDD and proton range compared to the FLUKA code and the experimental data.Methods:The beam delivery system of the Indiana University Health Proton Therapy Center was modeled for the uniform scanning beam in FLUKA and transferred identically into GATE and PHITS. This computational model was built from the blue print and validated with the commissioning data. Three parameters evaluated are the maximum step size, cut off energy and physical and transport model. The dependence of the PDDs on the customizing parameters was compared with the published results of previous studies.Results:The optimal parameters for the simulation of the whole beam delivery system were defined by referring to the calculation results obtained with each parameter. Although the PDDs from FLUKA and the experimental data show a good agreement, those of GATE and PHITS obtained with our optimal parameters show a minor discrepancy. The measured proton range R90 was 269.37 mm, compared to the calculated range of 269.63 mm, 268.96 mm, and 270.85 mm with FLUKA, GATE and PHITS, respectively.Conclusion:We evaluated the dependence of the results for PDDs obtained with GATE and PHITS Monte Carlo generalpurpose codes on the customizing parameters by using the whole computational model of the treatment nozzle. The optimal parameters for the simulation were then defined by referring to the calculation results. The physical model, particle transport mechanics and the different geometrybased descriptions need accurate customization in three simulation codes to agree with experimental data for artifact‐free Monte Carlo simulation.This study was supported by Grants‐in Aid for Cancer Research (H22‐3rd Term Cancer Control‐General‐043) from the Ministry of Health, Labor and Welfare of Japan, Grants‐in‐Aid for Scientific Research (No. 23791419), and JSPS Core‐to‐Core program (No. 23003). The authors have no conflict of interest.