Determination of inflection points of CyberKnife dose profiles within acceptability criteria of deviations in measurements.

AIM: The aim of this study was to determine the Inflection Points (IPs) of flattening filter free (FFF) CyberKnife dose profiles for cone-based streotactic radiotherapy. In addition, dosimetric field sizes were determined. BACKGROUND: The increased need for treatment in the early stages of cancer necessitated the treatment of smaller tumors. However, efforts in that direction required the modeling accuracy of the beam. Removal of the flattening filter (FF) from the path of x-ray beam has provided the solution to those efforts, but required a different normalization approach for the beam to ensure the delivery of the dose accurately. As a solution, researchers proposed a normalization factor based on IPs. MATERIALS AND METHODS: Measurements using microDiamond (PTW 60019), Diode SRS (PTW 60018) and Monte Carlo (MC) calculations of dose profiles were completed at SAD 80 cm and 5 cm depth for 15-60 mm cones. Performance analysis of detectors with respect to MC calculation was carried out. Gamma evaluation method was used to determine achievable acceptability criteria for FFF CyberKnife beams. RESULTS: Acceptability within (3%-0.5 mm) was found to be anachievable criterion for all dose profile measurements of the cone beams used in this study. To determine the IP, the first and second derivatives of the dose profile were determined via the cubic spline interpolation technique. CONCLUSION: Derivatives of the interpolated profiles showed that locations of IPs and 50% isodose points coincide.

Technical note: A modified gamma evaluation method for dose distribution comparisons.

PURPOSE: In this work we have developed a novel method of dose distribution comparison, the inverse gamma (IG) evaluation, by modifying the commonly used gamma evaluation method. METHODS: The IG evaluation calculates the gamma criteria (dose difference criterion, ΔD, or distance-to-agreement criterion, Δd) that are needed to achieve a predefined pass rate or gamma agreement index (GAI). In-house code for evaluating IG with a fixed ΔD of 3% was developed using Python (v3.5.2) and investigated using treatment plans and measurement data from 25 retrospective patient specific quality assurance tests (53 individual arcs). RESULTS: It was found that when the desired GAI was set to 95%, approximately three quarters of the arcs tested were able to achieve Δd within 1 mm (mean Δd: 0.7 ± 0.5 mm). The mean Δd required in order for all points to pass the gamma evaluation (i.e., GAI = 100%) was 4.5 ± 3.1 mm. The possibility of evaluating IG by fixing the Δd or ΔD/Δd, instead of fixing the ΔD at 3%, was also investigated. CONCLUSION: The IG method and its indices have the potential to be implemented clinically to quantify the minimum dose and distance criteria based on a specified GAI. This method provides additional information to augment standard gamma evaluation results during patient specific quality assurance testing of individual treatment plans. The IG method also has the potential to be used in retrospective audits to determine an appropriate set of local gamma criteria and action levels based on a cohort of patient specific quality assurance plans.

Analysis of dose comparison techniques for patient-specific quality assurance in radiation therapy.

PURPOSE: Gamma evaluation is the most commonly used technique for comparison of dose distributions for patient-specific pretreatment quality assurance in radiation therapy. Alternative dose comparison techniques have been developed but not widely implemented. This study aimed to compare and evaluate the performance of several previously published alternatives to the gamma evaluation technique, by systematically evaluating a large number of patient-specific quality assurance results. METHODS: The agreement indices (or pass rates) for global and local gamma evaluation, maximum allowed dose difference (MADD) and divide and conquer (D&C) techniques were calculated using a selection of acceptance criteria for 429 patient-specific pretreatment quality assurance measurements. Regression analysis was used to quantify the similarity of behavior of each technique, to determine whether possible variations in sensitivity might be present. RESULTS: The results demonstrated that the behavior of D&C gamma analysis and MADD box analysis differs from any other dose comparison techniques, whereas MADD gamma analysis exhibits similar performance to the standard global gamma analysis. Local gamma analysis had the least variation in behavior with criteria selection. Agreement indices calculated for 2%/2 mm and 2%/3 mm, and 3%/2 mm and 3%/3 mm were correlated for most comparison techniques. CONCLUSION: Radiation oncology treatment centers looking to compare between different dose comparison techniques, criteria or lower dose thresholds may apply the results of this study to estimate the expected change in calculated agreement indices and possible variation in sensitivity to delivery dose errors.

Effect of VERO pan-tilt motion on the dose distribution.

Tumor tracking is an option for intra-fractional motion management in radiotherapy. The VERO gimbal tracking system creates a unique beam geometry and understanding the effect of the gimbal motion in terms of dose distribution is important to assess the dose deviation from the reference conditions. Beam profiles, output factors (OF) and percentage depth doses (PDD) were measured and evaluated to investigate this effect. In order to find regions affected by the pan-tilt motion, synthesized 2D dose distributions were generated. An evaluation of the 2D dose distribution with the reference position was done using dose difference criteria 1%-4%. The OF and point dose at central axis were measured and compared with the reference position. Furthermore, the PDDs were measured using a special monitoring approach to filtering inaccurate points during the acquisition. Beam profiles evaluation showed that the effect of pan-tilt at inline direction was stronger than at the crossline direction. The maximum average deviation of the full width half maximum (FWHM), flatness, symmetry, penumbra left and right were 0.39 ± 0.25 mm, 0.62 ± 0.50%, 0.76 ± 0.59%, 0.22 ± 0.16 mm, and 0.19 ± 0.15 mm respectively. The ÔF and the measured dose average deviation were <0.5%. The mechanical accuracies during the PDD measurements were 0.28 ± 0.09 mm and 0.21 ± 0.09 mm for pan and tilt and pan or tilt position. The PDD average deviations were 0.58 ± 0.26 % and 0.54 ± 0.25 % for pan-or-tilt and pan-and-tilt position respectively. All the results showed that the deviation at pan and tilt position are higher than pan or tilt. The most influences were observed for the penumbra region and the shift of radiation beam path.

Virtual pretreatment patient-specific quality assurance of volumetric modulated arc therapy using deep learning.

BACKGROUND: Automatic patient-specific quality assurance (PSQA) is recently explored using artificial intelligence approaches, and several studies reported the development of machine learning models for predicting the gamma pass rate (GPR) index only. PURPOSE: To develop a novel deep learning approach using a generative adversarial network (GAN) to predict the synthetic measured fluence. METHODS AND MATERIALS: A novel training method called "dual training," which involves the training of the encoder and decoder separately, was proposed and evaluated for cycle GAN (cycle-GAN) and conditional GAN (c-GAN). A total of 164 VMAT treatment plans, including 344 arcs (training data: 262, validation data: 30, and testing data: 52) from various treatment sites, were selected for prediction model development. For each patient, portal-dose-image-prediction fluence from TPS was used as input, and measured fluence from EPID was used as output/response for model training. Predicted GPR was derived by comparing the TPS fluence with the synthetic measured fluence generated by the DL models using gamma evaluation of criteria 2%/2 mm. The performance of dual training was compared against the traditional single-training approach. In addition, we also developed a separate classification model specifically designed to detect automatically three types of errors (rotational, translational, and MU-scale) in the synthetic EPID-measured fluence. RESULTS: Overall, the dual training improved the prediction accuracy of both cycle-GAN and c-GAN. Predicted GPR results of single training were within 3% for 71.2% and 78.8% of test cases for cycle-GAN and c-GAN, respectively. Moreover, similar results for dual training were 82.7% and 88.5% for cycle-GAN and c-GAN, respectively. The error detection model showed high classification accuracy (>98%) for detecting errors related to rotational and translational errors. However, it struggled to differentiate the fluences with "MU scale error" from "error-free" fluences. CONCLUSION: We developed a method to automatically generate the synthetic measured fluence and identify errors within them. The proposed dual training improved the PSQA prediction accuracy of both the GAN models, with c-GAN demonstrating superior performance over the cycle-GAN. Our results indicate that the c-GAN with dual training approach combined with error detection model, can accurately generate the synthetic measured fluence for VMAT PSQA and identify the errors. This approach has the potential to pave the way for virtual patient-specific QA of VMAT treatments.

Radio-luminescent imaging for rapid, high-resolution eye plaque loading verification.

BACKGROUND: Eye plaque brachytherapy is currently an optimal therapy for intraocular cancers. Due to the lack of an effective and practical technique to measure the seed radioactivity distribution, current quality assurance (QA) practice according to the American Association of Physicists in Medicine TG129 only stipulates that the plaque assembly be visually inspected. Consequently, uniform seed activity is routinely adopted to avoid possible loading mistakes of differential seed loading. However, modulated dose delivery, which represents a general trend in radiotherapy to provide more personalized treatment for a given tumor and patient, requires differential activities in the loaded seeds. PURPOSE: In this study, a fast and low-cost radio-luminescent imaging and dose calculating system to verify the seed activity distribution for differential loading was developed. METHODS: A proof-of-concept system consisting of a thin scintillator sheet coupled to a camera/lens system was constructed. A seed-loaded plaque can be placed directly on the scintillator surface with the radioactive seeds facing the scintillator. The camera system collects the radioluminescent signal generated by the scintillator on its opposite side. The predicted dose distribution in the scintillator's sensitive layer was calculated using a Monte Carlo simulation with the planned plaque loading pattern of I-125 seeds. Quantitative comparisons of the distribution of relative measured signal intensity and that of the relative predicted dose in the sensitive layer were performed by gamma analysis, similar to intensity-modulated radiation therapy QA. RESULTS: Data analyses showed high gamma (3%/0.3 mm, global, 20% threshold) passing rates for correct seed loadings and low passing rates with distinguished high gamma value area for incorrect loadings, indicating that possible errors may be detected. The measurement and analysis only required a few extra minutes, significantly shorter than the time to assay the extra verification seeds the physicist already must perform as recommended by TG129. CONCLUSIONS: Radio-luminescent QA can be used to facilitate and assure the implementation of intensity-modulated, customized plaque loading.

A structure-based gamma evaluation method for identifying clinically relevant dose differences in organs at risk.

Gamma evaluation is currently the most widely used dose comparison method for patient specific quality assurance (PSQA). However, existing methods for normalising the dose difference, using either the dose at the global maximum dose point or at each local point, can respectively lead to under- and over-sensitivity to dose differences in organ-at-risk structures. This may be of concern for plan evaluation from clinical perspectives. This study has explored and proposed a new method called structural gamma, which takes structural dose tolerances into consideration while performing gamma analysis for PSQA. As a demonstration of the structural gamma method, a total of 78 retrospective plans on four treatment sites were re-calculated on an in-house Monte Carlo system and compared with doses calculated from the treatment planning system. Structural gamma evaluations were performed using both QUANTEC dose tolerances and radiation oncologist specified dose tolerances, then compared with conventional global and local gamma evaluations. Results demonstrated that structural gamma evaluation is especially sensitive to errors in structures with restrictive dose constraints. The structural gamma map provides both geometric and dosimetric information on PSQA results, allowing straightforward clinical interpretation. The proposed structure-based gamma method accounts for dose tolerances for specific anatomical structures. This method can provide a clinically useful method to assess and communicate PSQA results, offering radiation oncologists a more intuitive way of examining agreement in surrounding critical normal structures.

Exit fluence analysis using portal dosimetry in volumetric modulated arc therapy.

AIM: In measuring exit fluences, there are several sources of deviations which include the changes in the entrance fluence, changes in the detector response and patient orientation or geometry. The purpose of this work is to quantify these sources of errors. BACKGROUND: The use of the volumetric modulated arc therapy treatment with the help of image guidance in radiotherapy results in high accuracy of delivering complex dose distributions while sparing critical organs. The transit dosimetry has the potential of Verifying dose delivery by the linac, Multileaf collimator positional accuracy and the calculation of dose to a patient or phantom. MATERIALS AND METHODS: The quantification of errors caused by a machine delivery is done by comparing static and arc picket fence test for 30 days. A RapidArc plan, created for the pelvis site was delivered without and with Rando phantom and exit portal images were acquired. The day to day dose variation were analysed by comparing the daily exit dose images during the course of treatment. The gamma criterion used for analysis is 3% dose difference and 3 mm distance to agreement with a threshold of 10% of maximum dose. RESULTS: The maximum standard deviation for the static and arc picket fence test fields were 0.19 CU and 1.3 CU, respectively. The delivery of the RapidArc plans without a phantom shows the maximum standard deviation of 1.85 CU and the maximum gamma value of 0.59. The maximum gamma value for the RapidArc plan delivered with the phantom was found to be 1.2. The largest observed fluence deviation during the delivery to patient was 5.7% and the maximum standard deviation was 4.1 CU. CONCLUSION: It is found from this study that the variation due to patient anatomy and interfraction organ motion is significant.

Comparison of global and local gamma evaluation results using isodose levels.

The aim of this study is to evaluate the behaviour of global and local gamma analyses with isodose levels. Global and local gamma evaluation were performed on patient-specific quality assurance (PSQA) data from 100 volumetric modulated arc therapy (VMAT) arcs and 100 helical tomotherapy (HT) plans, using an in-house gamma code. Gamma pass rates versus isodose levels were plotted and evaluated. Other than a slightly increased skew towards higher pass rates for the global gamma evaluation, minimal differences were observed between the results of evaluating all VMAT arcs separately and the results of evaluating over VMAT treatment plans by combining arcs from each plan. Generally, the VMAT results showed average pass rates that increase with decreasing isodose level, for both global and local gamma evaluations. The HT results differed systematically from the VMAT results, with the results of performing global and local gamma evaluations agreeing more closely at all isodose levels and with the highest gamma pass rates being achieved at intermediate dose levels, between the 40 and 70% isodose levels. These results demonstrate the complex of relationships between global and local gamma evaluation results that can arise when clinical PSQA data are analysed and exemplify how the local gamma evaluation does not necessarily produce disproportionately reduced gamma pass rates in low dose regions. Performing gamma evaluation with different isodose levels is suggested as a useful method to improve understanding of specific PSQA data and as well as the broader features of gamma evaluation results.

Anatomy-corresponding method of IMRT verification.

BACKGROUND: During a proper execution of dMLC plans, there occurs an undesired but frequent effect of the dose locally accumulated by tissue being significantly different than expected. The conventional dosimetric QA procedures give only a partial picture of the quality of IMRT treatment, because their solely quantitative outcomes usually correspond more to the total area of the detector than the actually irradiated volume. AIM: The aim of this investigation was to develop a procedure of dynamic plans verification which would be able to visualize the potential anomalies of dose distribution and specify which tissue they exactly refer to. MATERIALS & METHODS: The paper presents a method discovered and clinically examined in our department. It is based on a Gamma Evaluation concept and allows accurate localization of deviations between predicted and acquired dose distributions, which were registered by portal as well as film dosimetry. All the calculations were performed on the self-made software GammaEval, the γ-images (2-dimensional distribution of γ-values) and γ-histograms were created as quantitative outcomes of verification. RESULTS: Over 150 maps of dose distribution have been analyzed and the cross-examination of the gamma images with DRRs was performed. CONCLUSIONS: It seems, that the complex monitoring of treatment would be possible owing to the images obtained as a cross-examination of γ-images and corresponding DRRs.

Characteristics of inverse gamma histograms.

This work explores the characteristics of the inverse gamma histogram and its potential use as part of the patient specific quality assurance (PSQA) program for volumetric modulated arc therapy (VMAT). ArcCheck measured dose files and TPS predicted dose files were imported and analysed using the in-house inverse gamma code developed in the Python package. Inverse gamma with fixed distance-to-agreement of 2 mm were calculated for 23 VMAT arcs. Dose difference histograms were plotted for six arbitrarily selected arcs with the 95th and 90th percentile values calculated. Dose difference histograms enabled visualisation of the dose difference distribution information. The 95th and 90th percentile values are equivalent to the dose difference criteria where the gamma pass rate is 95% and 90% respectively. These values can be used as a guide to assess plan acceptability, especially for plans that failed the initial gamma evaluation. The inverse gamma histograms are demonstrated to be a useful tool for plan evaluation in addition to the traditional gamma evaluation method. It contains dose difference or distance-to-agreement distribution information, which could be clinically useful for plan evaluation.

A deep learning-based prediction model for gamma evaluation in patient-specific quality assurance.

PURPOSE: Patient-specific quality assurance (QA) measurement is conducted to confirm the accuracy of dose delivery. However, measurement is time-consuming and places a heavy workload on the medical physicists and radiological technologists. In this study, we proposed a prediction model for gamma evaluation, based on deep learning. We applied the model to a QA measurement dataset of prostate cancer cases to evaluate its practicality. METHODS: Sixty pretreatment verification plans from prostate cancer patients treated using intensity modulated radiation therapy were collected. Fifteen-layer convolutional neural networks (CNN) were developed to learn the sagittal planar dose distributions from a RT-3000 QA phantom (R-TECH.INC., Tokyo, Japan). The percentage gamma passing rate (GPR) was measured using GAFCHROMIC EBT3 film (Ashland Specialty Ingredients, Covington, USA). The input training data also included the volume of the PTV (planning target volume), rectum, and overlapping region, measured in cm3 , and the monitor unit values for each field. The network produced predicted GPR values at four criteria: 2%(global)/2 mm, 3%(global)/2 mm, 2%(global)/3 mm, and 3%(global)/3 mm. Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, was used for learning and for optimizing the CNN-based model. Fivefold cross-validation was applied to validate the performance of the proposed method. Forty cases were used for training and validation set in fivefold cross-validation, and the remaining 20 cases were used for the test set. The predicted and measured GPR values were compared. RESULTS: A linear relationship was found between the measured and predicted values, for each of the four criteria. Spearman rank correlation coefficients in validation set between measured and predicted GPR values at four criteria were 0.73 at 2%/2 mm, 0.72 at 3%/2 mm, 0.74 at 2%/3 mm, and 0.65 at 3%/3 mm, respectively (P < 0.01). The Spearman rank correlation coefficients in the test set were 0.62 (P < 0.01) at 2%/2 mm, 0.56 (P < 0.01) at 3%/2 mm, 0.51 (P = 0.02) at 2%/3 mm, and 0.32 (P = 0.16) at 3%/3 mm. These results demonstrated a strong or moderate correlation between the predicted and measured values. CONCLUSIONS: We developed a CNN-based prediction model for patient-specific QA of dose distribution in prostate treatment. Our results suggest that deep learning may provide a useful prediction model for gamma evaluation of patient-specific QA in prostate treatment planning.

Correlation analysis between 2D and quasi-3D gamma evaluations for both intensity-modulated radiation therapy and volumetric modulated arc therapy.

The aim of this work was to investigate correlations between 2D and quasi-3D gamma passing rates. A total of 20 patients (10 prostate cases and 10 head and neck cases, H&N) were retrospectively selected. For each patient, both intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. For each plan, 2D gamma evaluation with radiochromic films and quasi-3D gamma evaluation with fluence measurements were performed with both 2%/2 mm and 3%/3 mm criteria. Gamma passing rates were grouped together according to delivery techniques and treatment sites. Statistical analyses were performed to examine the correlation between 2D and quasi-3D gamma evaluations. Statistically significant difference was observed between delivery techniques only in the quasi-3D gamma passing rates with 2%/2 mm. Statistically significant differences were observed between treatment sites in the 2D gamma passing rates (differences of less than 8%). No statistically significant correlations were observed between 2D and quasi-3D gamma passing rates except the VMAT group and the group including both IMRT and VMAT with 3%/3 mm (r = 0.564 with p = 0.012 for theVMAT group and r = 0.372 with p = 0.020 for the group including both IMRT and VMAT), however, those were not strong. No strong correlations were observed between 2D and quasi-3D gamma evaluations.

Gamma analysis with a gamma criterion of 2%/1 mm for stereotactic ablative radiotherapy delivered with volumetric modulated arc therapy technique: a single institution experience.

To report a single-institution experience of gamma evaluations with 2%/1 mm for stereotactic ablative radiotherapy (SABR) delivered with volumetric modulated arc therapy (VMAT) technique, from January 2014 to January 2016. A total of 168 SABR VMAT plans were analyzed with a gamma criterion of 2%/1 mm, a threshold value of 10%, and a tolerance level of 90%. Of the 168 cases, four cases failed with 2%/1 mm. The average passing rate was 97.0% ± 2.5%. Three of the four failed cases showed passing rates higher than 90%, which was achieved by shifting the measuring device by 1 mm in the left-to-right or anterior-to-posterior directions. One failed case showed a passing rate higher than 90%, which was achieved by changing the threshold value from 10% to 5%, leading to an increase in the number of tested points from 26 to 51. Concerns regarding the high susceptibility of the gamma criterion of 2%/1 mm to setup errors of the measuring device are unnecessary based on our two-year experience, since only four cases failed with the 2%/1 mm from a total of 168 clinical cases. Therefore, the gamma criterion of 2%/1 mm could be successfully applied in the clinic with its high sensitivity to detect errors in VMAT plans.

Impact of dose rate on accuracy of intensity modulated radiation therapy plan delivery using the pretreatment portal dosimetry quality assurance and setting up the workflow at hospital levels.

The aim of this study was to examine the impact of dose rate on accuracy of intensity modulated radiation therapy (IMRT) plan delivery by comparing the gamma agreement between the calculated and measured portal doses by pretreatment quality assurance (QA) using electronic portal imaging device dosimetry and creating a workflow for the pretreatment IMRT QA at hospital levels. As the improvement in gamma agreement leads to increase in the quality of IMRT treatment delivery, gamma evaluation was carried out for the calculated and the measured portal images for the criteria of 3% dose difference and 3 mm distance-to-agreement (DTA). Three gamma parameters: Maximum gamma, average gamma, and percentage of the field area with a gamma value>1.0 were analyzed. Three gamma index parameters were evaluated for 40 IMRT plans (315 IMRT fields) which were calculated for 400 monitor units (MU)/min dose rate and maximum multileaf collimator (MLC) speed of 2.5 cm/s. Gamma parameters for all 315 fields are within acceptable limits set at our center. Further, to improve the gamma results, we set an action level for this study using the mean and standard deviation (SD) values from the 315 fields studied. Forty out of 315 IMRT fields showed low gamma agreement (gamma parameters>2 SD as per action level of the study). The parameters were recalculated and reanalyzed for the dose rates of 300, 400 and 500 MU/min. Lowering the dose rate helped in getting an enhanced gamma agreement between the calculated and measured portal doses of complicated fields. This may be attributed to the less complex motion of MLC over time and the MU of the field/segment. An IMRT QA work flow was prepared which will help in improving the quality of IMRT delivery.

Efficiency Study of 2D Diode Array Detector for IMRT Quality Assurance / 의학물리

In this study, we evaluated the effect of grid size on dose calculation accuracy using 2 head & neck and 2 prostate IMRT cases and based on this study's findings, we also evaluated the efficiency of a 2D diode array detector for IMRT quality assurance. Dose distributions of four IMRT plan data were calculated at four calculation grid sizes (1.25, 2.5, 5, and 10 mm) and the calculated dose distributions were compared with measured dose distributions using 2D diode array detector. Although there was no obvious difference in pass rate of gamma analysis with 3 mm/3% acceptance criteria for the others except 10 mm grid size, we found that the pass rates of 2.5, 5 and 10 mm grid size were decreased 5%, 20% and 31.53% respectively according to the application of the fine acceptance criteria, 3 mm/3%, 2 mm/2% and 1 mm/1%. The calculation time were about 11.5 min, 4.77 min, 2.95 min, and 11.5 min at 1.25, 2.5, 5, and 10 mm, respectively and as the grid size increased to double, the calculation time decreased about one-half. The grid size effect was observed more clearly in the high gradient area than the low gradient area. In conclusion, 2.5 mm grid size is considered acceptable for most IMRT plans but at least in the high gradient area, 1.25 mm grid size is required to accurately predict the dose distribution. These results are exactly same as the precious studies' results and theory. So we confirmed that 2D array diode detector was suitable for the IMRT QA.