Water Tank Data Research Articles

A novel denoising method for low SNR NMR logging echo signal based on deep learning

The T 2 spectrum obtained by inversion of the nuclear magnetic resonance logging echo signal can provide various petrophysical parameters to help technicians effectively identify the type of fluid. However, raw logging data with a low signal-to-noise ratio can cause inversion results to deviate from the truth. Therefore, a deep learning denoising method is proposed to eliminate the limitations of traditional mathematical transform methods. A one-dimensional deep convolutional generative adversarial networks model is designed to fit the noise distribution of actual logging data, then generate simulation data. A multi-scale echo denoising network (MsEDNet) is designed to adaptively learn the multi-exponential decay characteristics of the signal and the optimal transform space. The denoising dataset consists of simulation data and logging data, which is applied to train MsEDNet and improve the generalization performance. With effectiveness analysis and various denoising experiments, it is validated that the proposed method has excellent denoising performance on simulation data, logging data, and water tank data.

Contact Adapting Electrode Model for Electrical Impedance Tomography

Electrical impedance tomography is an imaging modality for extracting information on the interior structure of a physical body from boundary measurements of current and voltage. This work studies a new robust way of modeling the contact electrodes used for driving current patterns into the examined object and measuring the resulting voltages. The idea is to not define the electrodes as strict geometric objects on the measurement boundary, but only to assume approximate knowledge about their whereabouts and let a boundary admittivity function determine the actual locations of the current inputs. Such an approach enables reconstructing the boundary admittivity, i.e. the locations and strengths of the contacts, at the same time and with analogous methods as the interior admittivity. The functionality of the new model is verified by two-dimensional numerical experiments based on water tank data.

Out-of-field dose and its constituent components for a 1.5 T MR-Linac

This study aims to quantify the relative contributions of phantom scatter, collimator scatter and head leakage to the out-of-field doses (OFDs) of both static fields and clinical intensity-modulated radiation therapy (IMRT) treatments in a 1.5 T MR-Linac. The OFDs of static fields were measured at increasing distances from the field edge in an MR-conditional water phantom. Inline scans at depths of dmax (14 mm), 50 and 100 mm were performed for static fields of 5 × 5, 10 × 10 and 15 × 15 cm2 under three different conditions: full scatter, with phantom scatter prevented, and head leakage only. Crossline scans at isocenter and offset positions were performed in full scatter condition. EBT3 radiochromic films were placed at 100 mm depth of solid water phantom to measure the OFD of clinical IMRT plans. All water tank data were normalized to Dmax of a 10 × 10 cm2 field and the film results were presented as a fraction of the target mean dose. The OFD in the inline direction varied from 3.5% (15 × 15 cm2, 100 mm depth, 50 mm distance) to 0.014% (5 × 5 cm2, dmax, 400 mm distance). For all static fields, the collimator scatter was higher than the phantom scatter and head leakage at a distance of 100–400 mm. Head leakage remained the smallest among the three components, except at long distances (>375 mm) with small field size. Compared to the inline scans, the crossline scans at the isocenter showed higher doses at distances longer than 80 mm. All crossline profiles at longitudinal offset positions showed a cone shape with laterally shifted maxima. The OFD of IMRT deliveries varied with different target size. For prostate stereotactic body radiation therapy (SBRT) treatment, the OFD decreased from 2% to 0.03% at a distance of 50–500 mm. The OFDs have been measured for a 1.5 T MR-Linac. The presented dosimetric data are valuable for radiation safety assessments on patients treated with the MR-Linac, such as evaluating carcinogenic risk and radiation exposure to cardiac implantable electronic devices.

Supershape Recovery From Electrical Impedance Tomography Data

The idea of accounting for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> shape information is gaining increasing levels of interest and traction in the electrical impedance tomography (EIT) reconstruction. A supershape-based reconstruction approach is proposed for EIT. We begin by assuming that the conductivity profile to be reconstructed in the measured domain is piecewise constant distributed. Using this formulation, the image reconstruction problem is transformed into a shape reconstruction problem. The inclusion boundary (e.g., interface between the inclusion and the background) to be estimated is treated as a supershape and expressed through a single equation—the so-called super formula. We illustrate the performance of the proposed approach using synthetic and experimental water tank data. In addition, robustness studies considering different regularization types ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{1}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{2}$ </tex-math></inline-formula> norms), varying noise levels and different initial settings are tested of the proposed approach. Four evaluation matrices relative size coverage ratio (RCR), structural similarity index (SSIM), relative contrast (RCo), and correlation coefficient (CC) are used to quantitatively evaluate the performance of the proposed method. Both the simulation and experimental results show that the supershape-based method leads to reliable and robust reconstructions and improves the ability to simultaneously reconstruct objects with smooth boundaries and/or sharp features. The proposed approach provides an excellent opportunity for the shape reconstruction framework to express a wide variety of shapes, including geometric primitives. Supershapes can simply represent regular polygons and natural shapes with various symmetries while maintaining a parametric representation.

B-Spline Level Set Method for Shape Reconstruction in Electrical Impedance Tomography.

A B-spline level set (BLS) based method is proposed for shape reconstruction in electrical impedance tomography (EIT). We assume that the conductivity distribution to be reconstructed is piecewise constant, transforming the image reconstruction problem into a shape reconstruction problem. The shape/interface of inclusions is implicitly represented by a level set function (LSF), which is modeled as a continuous parametric function expressed using B-spline functions. Starting from modeling the conductivity distribution with the B-spline based LSF, we show that the shape modeling allows us to compute the solution by restricting the minimization problem to the space spanned by the B-splines. As a consequence, the solution to the minimization problem is obtained in terms of the B-spline coefficients. We illustrate the behavior of this method using simulated as well as water tank data. In addition, robustness studies considering varying initial guesses, differing numbers of control points, and modeling errors caused by inhomogeneity are performed. Both simulation and experimental results show that the BLS-based approach offers clear improvements in preserving the sharp features of the inclusions in comparison to the recently published parametric level set method.

Multivariate Bernoulli Logit-Normal Model for Failure Prediction

&#x0D; &#x0D; &#x0D; The failures among connected devices that are geographically close may have correlations and even propagate from one to another. However, there is little research to model this prob- lem due to the lacking of insights of the correlations in such devices. Most existing methods build one model for one de- vice independently so that they are not capable of captur- ing the underlying correlations, which can be important in- formation to leverage for failure prediction. To address this problem, we propose a multivariate Bernoulli Logit-Normal model (MBLN) to explicitly model the correlations of devices and predict failure probabilities of multiple devices simulta- neously. The proposed method is applied to a water tank data set where tanks are connected in a local area. The results indicate that our proposed method outperforms baseline ap- proaches in terms of the prediction performance such as ROC.&#x0D; &#x0D; &#x0D;

Improved Monte Carlo clinical electron beam modelling

PurposeAn EGSnrc based electron model was developed and validated for an Elekta Synergy® 160-leaf Agility™ linear accelerator. It was able to reproduce measured central axis (CAX) percentage depth dose (PDD) curves and off-axis profiles (OAPs) within 2%/2 mm, and relative output factors (ROFs) within 3%. MethodsBEAMnrc component modules were used to model the accelerator accurately according to vendor supplied specifications. The electron beam focal spot size and input energy spectrum were determined through their effects on electron CAX PDDs and OAPs as benchmarked against water tank data. Phase space files were used as source input in DOSXYZnrc water phantom simulations. Dose distributions were calculated for six electron nominal energies, 11 field sizes and two source-to-surface distances. ResultsThe full width at half maximum of the focal spot (assuming a Gaussian intensity distribution) was determined to be 1.50 mm. An asymmetrical input electron energy spectrum with a low-energy tail produced good agreement with measured data and solved the match in the build-up (BU) region for all electron energies used in this study. ConclusionsThe improved input electron spectra for the electron model could predict dose distributions within 2%/2 mm of measured data. The model’s success is embedded in the asymmetrical energy spectrum which provided a valuable free parameter which, by fine adjustment, improved the match in the BU region of dose distributions. Furthermore, focal spot parameters could be determined by means of iterative simulations.

B-Spline-Based Sharp Feature Preserving Shape Reconstruction Approach for Electrical Impedance Tomography.

This paper presents a B-spline-based shape reconstruction approach for electrical impedance tomography (EIT). In the proposed approach, the conductivity distribution to be reconstructed is assumed to be piecewise constant. The geometry of the inclusions is parameterized using B-spline curves, and the EIT forward solver is modified as a set of control points representing the inclusions' boundary to the data on the domain boundary. The low-order representation decreases the computational demand and reduces the ill-posedness of the EIT reconstruction problem. The performance of the proposed B-spline-based approach is tested with simulations that demonstrate the most popular biomedical application of EIT: lung imaging. The approach is experimentally validated using water tank data. In addition, robustness studies of the proposed approach considering varying initial guesses, inaccurately known contact impedances, differing numbers of control points, and degree of B-spline are performed. The simulation and experimental results show that the B-spline-based approach offers improvements in image quality in comparison to the traditional Fourier series-based reconstruction approach, as measured by quantitative metrics such as relative size coverage ratio and relative contrast. Inasmuch, the proposed approach is demonstrated to offer clear improvement in the ability to preserve the sharp properties of the inclusions to be imaged.

Technical Note: Use of commercial multilayer Faraday cup for offline daily beam range verification at the McLaren Proton Therapy Center.

Daily verification of the proton beam range in proton radiation therapy is a vital part of the quality assurance (QA) program. The objective of this work is to study the use of a multilayer Faraday cup (MLFC) to perform a quick and precise daily range verification of proton beams produced by a synchrotron. Proton beam depth dose measurements were performed at room iso-center in water using PTW water tank and Bragg Peak ion chamber. The IBA Giraffe, calibrated against the water tank data, was used to measure the water equivalent thickness (WET) of the sample copper plates. The WET measurements provided the range calibration factors for the MLFC. To establish a baseline for in room measurements, range measurements for energies from 70 to 250MeV in steps of 10MeV were performed using the Pyramid MLFC at room iso-center. For the daily range verification measurements, the MLFC is permanently placed at the end of the beam line, inside the accelerator vault.The daily range constancy is performed for five representative beam energies; namely 70, 100, 150, 200, and 250MeV. Data collected over a period of more than 100days are analyzed and presented. The measured WET values of the copper plates increased with increasing energy. The centroid channel number in the MLFC where the protons stop, was converted to depth in water and compared to the depth of the distal 80% (d80) obtained from the water tank measurements. The depths agreed to within 2mm, with the maximum deviation of 1.97mm observed for 250MeV beam. The daily variation in the ranges measured by the MLFC was within ±0.5mm. The total time to verify five proton beam ranges varies between 4 and 5min. Based on the result of our measurements, the MLFC can be used for a daily range constancy check with submillimeter accuracy. It is a quick and simple method to perform range constancy verification on a daily basis.

Remote dosimetric auditing of clinical trials: The need for vendor specific models to convert images to dose.

IntroductionA previous pilot study has demonstrated the feasibility of a novel image‐based approach for remote dosimetric auditing of clinical trials. The approach uses a model to convert in‐air acquired intensity modulated radiotherapy (IMRT) images to delivered dose inside a virtual phantom. The model was developed using images from an electronic portal imaging device (EPID) on a Varian linear accelerator. It was tuned using beam profiles and field size factors (FSFs) of a series of square fields measured in water tank. This work investigates the need for vendor specific conversion models for image‐based auditing. The EPID measured profile and FSF data for Varian (vendor 1) and Elekta (vendor 2) systems are compared along with the performance of the existing Varian model (VM) and a new Elekta model (EM) for a series of audit IMRT fields measured on vendor 2 systems.Materials and methodsThe EPID measured beam profile and FSF data were studied for the two vendors to quantify and understand their relevant dosimetric differences. Then, an EM was developed converting EPID to dose in the virtual water phantom using a vendor 2 water tank data and images from corresponding EPID. The VM and EM were compared for predicting vendor 2 measured dose in water tank. Then, the performance of the new EM was compared to the VM for auditing of 54 IMRT fields from four vendor 2 facilities. Statistical significance of using vendor specific models was determined.ResultsObserved dosimetry differences between the two vendors suggested developing an EM would be beneficial. The EM performed better than VM for vendor 2 square and IMRT fields. The IMRT audit gamma pass rates were (99.8 ± 0.5)%, (98.6 ± 2.3)% and (97.0 ± 3.0)% at respectively 3%/3 mm, 3%/2 mm and 2%/2 mm with improvements at most fields compared with using the VM. For the pilot audit, the difference between gamma results of the two vendors was reduced when using vendor specific models (VM: P < 0.0001, vendor specific models: P = 0.0025).ConclusionA new model was derived to convert images from vendor 2 EPIDs to dose for remote auditing vendor 2 deliveries. Using vendor specific models is recommended to remotely audit systems from different vendors, however, the improvements found were not major.

Classification by Artificial Neural Network according to the values affecting Electricity Generation

Predicting the amount of electricity produced in a power plant is very important for today’s economy. Oven Power (MW), Boiler Input Gas Temperature, Superheated Steam Amount, ID-Fan Speed, Feeding Water Tank data affect the electricity production. In this article, Etikrom A.Ş. The electricity production amount to be produced in Elazığ Etikrom A.Ş. was estimated by using the data of Oven Power (MW), Water Inlet Gas Temperature, Steam Vapor Volume, ID-Fan Speed, Feeding Water Tank data. Electricity generation amount is used as verification data. That is, by the k-means clustering method, the electricity generation amount is divided into 3 classes (low, medium, and high). 3621 data including Oven Power (MW), Boiler Input Gas Temperature, Superheated Steam Amount, ID-Fan Speed, and Feeding Water Tank data were used after class 3 separation. With the K-means clustering method, 2742 of these data were clustered as low electricity, 296 as medium electricity and 583 as high electricity. This clustered data was given to the Artifical Neural Network classifier. The success rate obtained as a result of this classification is 85.81%. Classified data were analyzed by ROC curve.

Classification by Artificial Neural Network according to the values affecting Electricity Generation

Predicting the amount of electricity produced in a power plant is very important for today’s economy. Oven Power (MW), Boiler Input Gas Temperature, Superheated Steam Amount, ID-Fan Speed, Feeding Water Tank data affect the electricity production. In this article, Etikrom A.Ş. The electricity production amount to be produced in Elazig Etikrom A.Ş. was estimated by using the data of Oven Power (MW), Water Inlet Gas Temperature, Steam Vapor Volume, ID-Fan Speed, Feeding Water Tank data.

A Parametric Level Set Method for Electrical Impedance Tomography.

This paper presents an image reconstruction method based on parametric level set (PLS) method using electrical impedance tomography. The conductivity to be reconstructed was assumed to be piecewise constant and the geometry of the anomaly was represented by a shape-based PLS function, which we represent using Gaussian radial basis functions (GRBF). The representation of the PLS function significantly reduces the number of unknowns, and circumvents many difficulties that are associated with traditional level set (TLS) methods, such as regularization, re-initialization and use of signed distance function. PLS reconstruction results shown in this article are some of the first ones using experimental EIT data. The performance of the PLS method was tested with water tank data for two-phase visualization and with simulations which demonstrate the most popular biomedical application of EIT: lung imaging. In addition, robustness studies of the PLS method w.r.t width of the Gaussian function and GRBF centers were performed on simulated lung imaging data. The experimental and simulation results show that PLS method has significant improvement in image quality compared with the TLS reconstruction.

SU‐D‐209‐02: Percent Depth Dose Curves for Fluoroscopic X‐Ray Beam Qualities Incorporating Copper Filtration

Purpose:The purpose of this investigation was to quantify percent depth dose (PDD) curves for fluoroscopic x‐ray beam qualities incorporating added copper filtration.Methods:A PTW (Freiburg, Germany) MP3 water tank was used with a Standard Imaging (Middleton, WI) Exradin Model 11 Spokas Chamber to measure PDD curves for 60, 80, 100 and 120 kVp x‐ray beams with copper filtration ranging from 0.0–0.9 mm at 22cm and 42cm fields of view from 0 to 150 mm of water. A free‐in‐air monitor chamber was used to normalize the water tank data to fluctuations in output from the fluoroscope. The measurements were acquired on a Siemens (Erlangen, Germany) Artis ZeeGo fluoroscope. The fluoroscope was inverted from the typical orientation providing an x‐ray beam originating from above the water tank. The water tank was positioned so that the water level was located at 60cm from the focal spot; which also represents the focal spot to interventional reference plane distance for that fluoroscope.Results:PDDs for 60, 80, 100, and 120 kVp with 0 mm of copper filtration compared well to previously published data by Fetterly et al. [Med Phys, 28, 205 (2001)] for those beam qualities given differences in fluoroscopes, geometric orientation, type of ionization chamber, and the water tank used for data collection. PDDs for 60, 80, 100, and 120 kVp with copper filtration were obtained and are presented, which have not been previously investigated and published.Conclusion:The equipment and processes used to acquire the reported data were sound and compared well with previously published data for PDDs without copper filtration. PDD data for the fluoroscopic x‐ray beams incorporating copper filtration can be used as reference data for estimating organ or soft tissue dose at depth involving similar beam qualities or for comparison with mathematical models.

Commissioning and cross-comparison of four scanning water tanks

Purpose: Water scanning systems are commonly used for data collection to characterize dosimetric properties of photon and electron beams, and the commissioning of such systems has been previously described. The aim in this study, however, was to investigate tank-specific dependencies as well as conduct a dosimetric comparison between four distinct water scanning systems. Methods: Four water scanning systems were studied including the PTW MP3-M Phantom Tank, the Standard Imaging DoseView 3D, the IBA Blue Phantom, and the Sun Nuclear 3D Scanner. Mechanical accuracy and reproducibility was investigated by driving the chamber holder to nominal positions relative to a zero point and using a leveled caliper with 30 cm range to measure the actual position. Dosimetric measurements were also performed not only to compare percent-depth-dose (PDD) curves and profiles between tanks but also to assess dependencies such as directionality, scanning speed, and reproducibility for each tank individually. A PTW Semiflex 31010 ionization chamber with a sensitive volume of 0.125 cc was used at a Varian Clinac 2300 linear accelerator. Results: Mechanical precision was ensured to within 0.1 mm with the standard deviation (SD) of reproducibility <0.1 mm for measurements made with calipers. Dependencies on scanning direction and speed are presented. 6 MV PDDs between tanks agreed to within 0.6% relative to an averaged PDD beyond d max and within 2.5% in the build-up region. Specifically, the maximum difference was 1.0% between MP3-M and Blue Phantom at 6.1 cm depth. Lateral profiles agreed between tanks within 0.5% in the central 80% of the field. 6 MeV PDD maximum difference was 1.3% occurring at the steepest portion, where the R 50 was nevertheless within 0.6 mm across tanks. Setup uncertainties estimated at ≤1 mm are presumed to have contributed some of the difference between water tank data. Conclusion: Modern water scanning systems have achieved high accuracy across vendors, but commissioning tests nevertheless reveal tank-specific dependencies. This study not only ensures confidence in the individual systems but also provides the medical physicist with an understanding of variation in water tank properties between vendors.

Stochastic Galerkin Finite Element Method with Local Conductivity Basis for Electrical Impedance Tomography

The objective of electrical impedance tomography is to deduce information about the conductivity inside a physical body from electrode measurements of current and voltage at the object boundary. In this work, the unknown conductivity is modeled as a random field parametrized by its values at a set of pixels. The uncertainty in the pixel values is propagated to the electrode measurements by numerically solving the forward problem of impedance tomography by a stochastic Galerkin finite element method in the framework of the complete electrode model. For a given set of electrode measurements, the stochastic forward solution is employed by approximately parametrizing the posterior probability density of the conductivity and contact resistances. Subsequently, the conductivity is reconstructed by computing the maximum a posteriori and conditional mean estimates as well as the posterior covariance. The functionality of this approach is demonstrated with experimental water tank data.

SU‐E‐T‐33: A Comparative Study of Commissioning Data of Two TrueBeam LINACs with TrueBeam Representative Beam Data

Purpose: To compare the commissioning water tank data of the two TrueBeam type linacs with TrueBeam Representative Beam Data. Methods: Three flattening filtered (FF), 6MV, 10MV, and 15MV, and two flattening filtered free (FFF), 6FFF and 10FFF, photon beams of one TrueBeam and one TrueBeam STX Linacs (Varian Medical Systems) are compared to the TrueBeam Representative Beam Data (TRBD) as provided by Varian. All measurements are scanned in Blue Phantom (IBA) with cc04 ion chamber at SSD 100cm at the highest dose rate available for each beam. The TRBD set is the average values of three TrueBeams at a single institution acquired by Iba cc13 ion chamber. To compare the beam quality, the PDD at d10 and d20 and the corresponding PDD 10/20 ratio at field sizes of 3×3, 10×10 and 30×30 cm2 are compared. The flatness of 10×10 and 30×30 cm2 open field profiles at depth of dmax, 10cm and 20cm are also compared. The output factors for square fields are also compared. Results: The PDD difference at both d10 and d20 between all FF and FFF beams and TRBD are within 0.6% and 0.9% respectively. The average PDD ratio difference between all beams and TRBD is within 0.5%. The flatness of all the FF and FFF beams are within 0.4% and 1.0% of TRBD respectively. The output factor differences between the two TrueBeams and RTBD for all beams and field sizes are within 0.8%. Conclusion: All the beam parameters of both the FF and FFF beams of the two Truebeams are within 1% of TRBD. Research grant from Varian Medical Systems

Poster - Thur Eve - 32: Water tank referenced calibration method for detector array devices.

Detector array devices, such as the I'mRT Matrixx (IBA Dosimetry), provide a means of evaluating beam profiles with respect to gantry for a range of dose rates and monitor units. The relative calibration of these devices is typically highly susceptible to even relatively small variations in beam output. An alternative method is proposed here, which directly references the device detector response to water tank data. The Matrixx response was measured at the four cardinal angles for three devices. A calibration factor was determined for each orientation of the Matrixx device by dividing a water tank measured profile by the Matrixx response for the in-plane and cross-plane detectors. A geometric mean of each orientation was used as the estimate of the calibration coefficient. Before calibration, the three-detector average of the deviation from the profile measured in the water tank centered on each of the horns was 0.4% (SD 0.2%); applying the calibration procedure reduced this to 0.1% (SD 0.1%). The energy independence of the proposed relative calibration was also confirmed. A comparison of the linac output for relatively short Matrixx acquisitions to the longer water tank acquisition suggested some difference. This difference was mitigated by averaging. The proposed water tank reference calibration procedure is an effective means of determining the relative calibration of a detector array and mitigates the effect of compound error by avoiding the recursive algorithm of typical calibration methods. In addition it has the benefit of being directly relatable to commissioning beam data.

Monte Carlo electron source model validation for an Elekta Precise linac

Electron radiation therapy is used frequently for the treatment of skin cancers and superficial tumors especially in the absence of kilovoltage treatment units. Head-and-neck treatment sites require accurate dose distribution calculation to minimize dose to critical structures, e.g., the eye, optic chiasm, nerves, and parotid gland. Monte Carlo simulations can be regarded as the dose calculation method of choice because it can simulate electron transport through any tissue and geometry. In order to use this technique, an accurate electron beam model should be used. In this study, a two point-source electron beam model developed for an Elekta Precise linear accelerator was validated. Monte Carlo data were benchmarked against measured water tank data for a set of regular and circular fields and at 95, 100, and 110 cm source-to-skin-distance. EDR2 Film dose distribution data were also obtained for a paranasal sinus treatment case using a Rando phantom and compared with corresponding dose distribution data obtained from Monte Carlo simulations and a CMS XiO treatment planning system. A partially shielded electron field was also evaluated using a solid water phantom and EDR2 film measurements against Monte Carlo simulations using the developed source model. The major findings were that it could accurately replicate percentage depth dose and beam profile data for water measurements at source-to-skin-distances ranging between 95 and 110 cm over beam energies ranging from 4 to 15 MeV. This represents a stand-off between 0 and 15 cm. Most percentage depth dose and beam profile data (better than 95%) agreed within 2%/2 mm and nearly 100% of the data compared within 3%/3 mm. Calculated penumbra data were within 2 mm for the 20 x 20 cm2 field compared to water tank data at 95 cm source-to-skin-distance over the above energy range. Film data for the Rando phantom case showed gamma index map data that is similar in comparison with the treatment planning system and the Monte Carlo source model. The gamma index showed good agreement (2%/2 mm) between the Monte Carlo source model and the film data. Percentage depth dose and beam profile data were in most cases within a tolerance of 2%/2 mm. The biggest discrepancies were in most cases recorded in the first 6 mm of the water phantom. Circular fields showed local dose agreement within 3%/3mm. Good agreement was found between calculated dose distributions for a paranasal sinus case between Monte Carlo, film measurements and a CMS XiO treatment planning system. The electron beam model can be easily implemented in the BEAMnrc or DOSXYZnrc Monte Carlo codes enabling quick calculation of electron dose distributions in complex geometries.

SU-GG-T-216: Utility of 2D Diode Array for Electron Beam QA and Commissioning

Purpose: To assess the utility of a detector consisting of a plane of 445 diodes embedded within a solid water equivalent material (MapCheck) as an alternative to a scanning water tank for a) electron beam commissioning of a radiation treatment planning system (rtps); b) electron beam quality assurance (QA); and c) patient specific electron treatment QA. Method and Materials: Two dimensional dose information was captured at various depths placing solid water equivalent material onto the MapCheck surface. Electron energies of 6, 9, 12, 16 and 20 MeV produced by Varian linear accelerators at fields sizes ranging from 2×2 to 25×25cm2 were scanned. MapCheck was also used to measure electron dose distributions and outputs for patient customized cutouts. Data were collected for the same electron energies, field sizes and patient cut-outs using the scanning water phantom and the results were compared to those obtained from MapCheck. Lastly, the water tank and the previously used electron beam energies and field sizes were modeled on the Pinnacle rtps and the obtained beam profiles and percentage depth dose (%DD) distributions were compared with Mapcheck results. Results: Comparison of %DD and profiles demonstrated good agreement between Mapcheck data, water tank data, and Pinnacle rtps modeled data. High-dose, low-dose-gradient comparisons indicates excellent agreement to within 1% among the three modalities. Field size comparisons show mostly sub-millimeter agreement. Conclusion: Electron beam commissioning and QA typically involves the collection of central axis %DD and profiles at various depths and field sizes. The current gold standard is to use the remote scanning water tank which may be a time consuming procedure. Our results show that the 2D array diode detector known as MapCheck can reliably be used as an alternative to the scanning water tank for beam commissioning, rtps modeling and patient specific QA for electron beams.