The purpose of this study was to develop a predictive model for patient‐specific VMAT QA results using multileaf collimator (MLC) effect and texture analysis. The MLC speed, acceleration and texture analysis features were extracted from 106 VMAT plans as predictors. Gamma passing rate (GPR) was collected as a response class with gamma criteria of 2%/2 mm and 3%/2 mm. The model was trained using two machine learning methods: AdaBoost classification and bagged regression trees model. GPR was classified into the “PASS” and “FAIL” for the classification model using the institutional warning level. The accuracy of the model was assessed using sensitivity and specificity. In addition, the accuracy of the regression model was determined using the difference between predicted and measured GPR. For the AdaBoost classification model, the sensitivity/specificity was 94.12%/100% and 63.63%/53.13% at gamma criteria of 2%/2 mm and 3%/2 mm, respectively. For the bagged regression trees model, the sensitivity/specificity was 94.12%/91.89% and 61.18%/68.75% at gamma criteria of 2%/2 mm and 3%/2 mm, respectively. The root mean square error (RMSE) of difference between predicted and measured GPR was found at 2.44 and 1.22 for gamma criteria of 2%/2 mm and 3%/2 mm, respectively. The promising result was found at tighter gamma criteria 2%/2 mm with 94.12% sensitivity (both bagged regression trees and AdaBoost classification model) and 100% specificity (AdaBoost classification model).
The purpose of this study was to compare three computed tomography (CT) images under different conditions—average intensity projection (AIP), free breathing (FB), mid‐ventilation (MidV)—used for radiotherapy contouring and planning in lung cancer patients. Two image sets derived from four‐dimensional CT (4DCT) acquisition (AIP and MidV) and three‐dimensional CT with FB were generated and used to plan for 29 lung cancer patients. Organs at risk (OARs) were delineated for each image. AIP images were calculated with 3D conformal radiotherapy (3DCRT) and intensity‐modulated radiation therapy (IMRT). Planning with the same target coverage was applied to the FB and MidV image sets. Plans with small and large tumors were compared regarding OAR volumes, geometrical center differences in OARs, and dosimetric indices. A gamma index analysis was also performed to compare dose distributions. There were no significant differences (P > 0.05) in OAR volumes, the geometrical center differences, maximum and mean doses of the OARs between both tumor sizes. For 3DCRT, the gamma analysis results indicated an acceptable dose distribution agreement of 95% with 2%/2 mm criteria. Although, the gamma index results show distinct contrast of dose distribution outside the planning target volume (PTV) in IMRT, but within the PTV, it was acceptable. All three images could be used for OAR delineation and dose calculation in lung cancer. AIP image sets seemed to be suitable for dose calculation while patient movement between series acquisition of FB images should be considered when defining target volumes on 4DCT images.
The study’s purpose was to develop and validate Electronic Portal Imaging Device (EPID)-based dosimetry for Stereotactic Radiosurgery (SRS) and Stereotactic Radiation Therapy (SRT) patient-specific Quality Assurance (QA). The co-operation between extended Source-to-Imager Distance (SID) to reduce the saturation effect and simplify the EPID-based dosimetry model was used to perform patient-specific QA in SRS and SRT plans. The four parameters were included for converting the image to dose at depth 10 cm; dose-response linearity with MU, beam profile correction, collimator scatter and water kernel. The model accuracy was validated with 10 SRS/SRT plans. The traditional diode arrays with MapCHECK were also used to perform patient-specific QA for assuring model accuracy. The 150 cm-SID was found a possibility to reduce the saturation effect. The result of model accuracy was found good agreement between our EPID-based dosimetry and TPS calculation with GPR more than 98% for gamma criteria of 3%/3 mm, more than 95% for gamma criteria of 2%/2 mm, and the results related to the measurement with MapCHECK. This study demonstrated the method to perform SRT and SRT patient-specific QA using EPID-based dosimetry in the FFF beam by co-operating between the extended SID that can reduce the saturation effect and estimate the planar dose distribution with the in-house model.
The purpose of this study was to develop Electronic Portal Imaging Devices (EPID)-based dosimetry for Flattening-Filter-Free (FFF) beam verification. All radiation measurements were performed with source to imager distances (SID) of 150 cm to reduce saturation effect. EPID images were converted to radiation absorbed dose with our algorithm including four parameters: linearity of dose response with Monitor Unit (MU), beam profile correction, collimator scatter, and scatter kernel. The Calibration Units (CU) of image were scaled to dose (Gy) by using linearity of dose response with MU. Off-axis response differences between EPID and water were reduced with beam profile correction. Scatter kernel was applied to EPID images to reduce the residual error. The algorithm accuracy was validated with 12 arcs of Volumetric Modulated Arc Therapy (VMAT) plans by using gamma analysis comparing between EPID-based dosimetry and a plane dose distribution of Treatment Planning Systems (TPS). Gamma Passing Rates (GPR) were used to determine the dose agreements with criteria of 2%, 2 mm and 3%, 3 mm. The mean of GPR was 97.91%, and 99.62% for criteria of 2%,2 mm and, 3%, 3 mm, respectively. Our EPID-based dosimetry showed good agreement with plane dose distribution in water. These results indicated that our EPID-based dosimetry can perform FFF-beam verification.
The purpose of this study was to investigate error detection sensitivity for three patient-specific volumetric modulated arc therapy (VMAT) quality assurance (QA) systems (Delta4, EPID-based dosimetry, and log file) with three possible scenarios. Ten patient-specific VMAT QA were randomly selected to test their error detection sensitivities. Artificial complex errors were introduced to the original plans then the QA tests were repeated. These errors were simulated into three possible scenarios: uncertainty, miss-calibration, and worst-case scenario. For uncertainty scenario, the random errors (σ) of multi-leaf collimators (MLC) at ± 2.0 mm and gantry angle at ± 2.0 degree were introduced. The systematic errors of +2MU, and the random errors of MLC and gantry angle at ± 2.0 mm and ± 2.0 degree were applied as a miss-calibration scenario. For worst case scenario, errors were integrated between systematic and random variation of MLC and gantry angle at 2±0.5 mm and 2±0.5 degree, respectively. The dosimetric agreements between QA tests on original versus artificial error plans were determined to investigate error detection sensitivity used gamma analysis with 3%, 3 mm criteria. EPID-based dosimetry showed the most sensitive QA tool to detect three possible scenarios. Log file was the second best method, whereas Delta4 was the worst method to detect three possible scenario errors.
Objectives The purpose of this study was to verify the 80% enhanced dynamic wedge (EDW) beam profile using an electronic portal imaging device (EPID). Methods This study investigated symmetric and asymmetric field sizes using a 6 MV photon beam. Verification of the wedge output factor with an 80% beam profile was performed by comparing EPID measurements and treatment planning systems (TPS) calculations in both symmetric and asymmetric field sizes at different wedge angles (15, 30, 45, and 60 degrees). Results For the symmetric field size, the average difference between the measured and calculated beam profile was less than 2% (range 0.57-1.12%). For the asymmetric field size, the difference was also less than 2% (range 0.3-0.52%). Conclusion This study indicates that EPID can be used to verify the 80% enhanced dynamic wedge beam profile at different field sizes and wedge angles. The difference in beam profiles was less than 2% which is in accordance with AAPM TG no.142 recommendations.
Objective: To evaluatethe dosimetric characteristics of electronics portal imaging device (EPID) for 6 and 10 megavoltage(MV) of flattening filter-free (FFF) beams.Material and Method: The EPID characteristicsfor FFF beams have been evaluated as follows; saturation with sourcedetector-distance (SDD), saturation with dose rate, dose linearity response with monitor unit (MU), and the scatterd radiation with field size.Results: The saturation of signal was not occurred at 150 cm and 180 cm SDD for 6 and 10 MV of FFF beams, respectively. When the signals were measured with optimal SSD according to vendor suggestion (150 cm and 180 cm), the standard deviation for all dose rate were ±1.35 and ±1.64 CU for 6 and 10 MV of FFF beams,respectively. The dose linearity response showed that EPID has a good linearity response between signals and MU forthe both of 6 and 10 MV of FFF beams. The results of scatterd radiation with field size were found that FFF beams have different respose from flattening filter (FF) beams with the highest differences of 5.50% and 6.78% for 6 and 10 MV of FFF beams, respectively.Conclusion: EPID has a good characteristic for FFF beams, and an extended SSD can be used to reduce the satured signal effects in FFF beams.
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