Correlation between gamma index passing rate and clinical dosimetric difference for pre-treatment 2D and 3D volumetric modulated arc therapy dosimetric verification

Development of a quasi-3D dosimeter using radiochromic plastic for patient-specific quality assurance

BACKGROUND

Patient-specific QA verification ensures patient safety and treatment by verifying radiation delivery and dose calculations in treatment plans for errors. However, a two-dimensional (2D) dose distribution is insufficient for detecting information on the three-dimensional (3D) dose delivered to the patient. In addition, 3D radiochromic plastic dosimeters (RPDs) such as PRESAGE® represent the volume effect in which the dosimeters have different sensitivities according to the size of the dosimeters. Therefore, to solve the volume effect, a Quasi-3D dosimetry system was proposed to perform patient-specific QA using predetermined-sized and multiple RPDs.

PURPOSE

For patient-specific quality assurance (QA) in radiation treatment, this study aims to assess a quasi-3D dosimetry system using an RPD.

METHODS

Gamma analysis was performed to verify the agreement between the measured and estimated dose distributions of intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). We fabricated cylindrical RPDs and a quasi-3D dosimetry phantom. A practicability test for a pancreatic patient utilized a quasi-3D dosimetry device, an in-house RPD, and a quasi-3D phantom. The dose distribution of the VMAT design dictated the placement of nine RPDs. Moreover, a 2D diode array detector was used for 2D gamma analysis (MapCHECK2). The patient-specific QA was performed for IMRT, VMAT, and stereotactic ablative radiotherapy (SABR) in 20 prostate and head-and-neck patients. For each patient, six RPDs were positioned according to the dose distribution. VMAT SABR and IMRT/VMAT plans employed a 2%/2 mm gamma criterion, whereas IMRT/VMAT plans used a 3%/2 mm gamma criterion, a 10% threshold value, and a 90% passing rate tolerance. 3D gamma analysis was conducted using the 3D Slicer software.

RESULTS

The average gamma passing rates with 2%/2 mm and 3%/3 mm criteria for relative dose distribution were 91.6% ± 1.4% and 99.4% ± 0.7% for the 3D gamma analysis using the quasi-3D dosimetry system, respectively, and 97.5% and 99.3% for 2D gamma analysis using MapCHECK2, respectively. The 3D gamma analysis for patient-specific QA of 20 patients showed passing rates of over 90% with 2%/2 mm, 3%/2 mm, and 3%/3 mm criteria.

CONCLUSIONS

The quasi-3D dosimetry system was evaluated by performing patient-specific QAs with RPDs and quasi-3D phantom. The gamma indices for all RPDs showed more than 90% for 2%/2 mm, 3%/2 mm, and 3%/3 mm criteria. We verified the feasibility of a quasi-3D dosimetry system by performing the conventional patient-specific QA with the quasi-3D dosimeters.

Integrating plan complexity and dosiomics features with deep learning in patient-specific quality assurance for volumetric modulated arc therapy

PURPOSE

To investigate the feasibility and performance of deep learning (DL) models combined with plan complexity (PC) and dosiomics features in the patient-specific quality assurance (PSQA) for patients underwent volumetric modulated arc therapy (VMAT).

METHODS

Total of 201 VMAT plans with measured PSQA results were retrospectively enrolled and divided into training and testing sets randomly at 7:3. PC metrics were calculated using house-built algorithm based on Matlab. Dosiomics features were extracted and selected using Random Forest (RF) from planning target volume (PTV) and overlap regions with 3D dose distributions. The top 50 dosiomics and 5 PC features were selected based on feature importance screening. A DL DenseNet was adapted and trained for the PSQA prediction.

RESULTS

The measured average gamma passing rate (GPR) of these VMAT plans was 97.94% ± 1.87%, 94.33% ± 3.22%, and 87.27% ± 4.81% at the criteria of 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. Models with PC features alone demonstrated the lowest area under curve (AUC). The AUC and sensitivity of PC and dosiomics (D) combined model at 2%/2 mm were 0.915 and 0.833, respectively. The AUCs of DL models were improved from 0.943, 0.849, 0.841 to 0.948, 0.890, 0.942 in the combined models (PC + D + DL) at 3%/3 mm, 3%/2 mm and 2%/2 mm, respectively. A best AUC of 0.942 with a sensitivity, specificity and accuracy of 100%, 81.8%, and 83.6% was achieved with combined model (PC + D + DL) at 2%/2 mm.

CONCLUSIONS

Integrating DL with dosiomics and PC metrics is promising in the prediction of GPRs in PSQA for patients underwent VMAT.

Evaluation of the dataset quality in gamma passing rate predictions using machine learning methods

OBJECTIVE

Gamma passing rate (GPR) predictions using machine learning methods have been explored for treatment verification of radiotherapy plans. However, these methods presented datasets with unbalanced number of plans having different treatment conditions (heterogeneous datasets), such as anatomical sites or dose per fractions, leading to lower model interpretability and prediction performance.

METHODS

We investigated the impact of the dataset composition on GPR binary classification (pass/fail) using random forest (RF), XG-boost, and neural network (NN) models. 945 plans were used to create one reference dataset (randomly assembled) and 24 customized datasets that considered four heterogeneity factors independently (anatomical region, number of arcs, dose per fraction, and treatment unit). 309 predictor features were extracted and calculated from plan parameters, modulation complexity metrics, and radiomic analysis (leave-trajectory maps, 3D dose distributions, and portal dosimetry images). The models' performances were measured using the area under the curve from the receiver operating characteristic (ROC-AUC).

RESULTS

Radiomics features for reference models increased ROC-AUC values up to 13%, 15%, and 5% for RF, XG-Boost, and NN, respectively. The datasets with higher heterogeneous conditions presented the lower ROC-AUC values (RF: 0.72 ± 0.11, XG-Boost: 0.67 ± 0.1, NN: 0.89 ± 0.05) compared to models with less heterogeneous treatment conditions (RF: 0.88 ± 0.06, XG-Boost: 0.89 ± 0.07, NN: 0.98 ± 0.01). The ten most important features for each heterogeneity dataset group demonstrated their correlation with the treatments' physical aspects and GPR prediction.

CONCLUSION

Improvements in data generalization and model performances can be associated with datasets having similar treatment conditions. This analysis might be implemented to evaluate the dataset quality and model consistency of further ML applications in radiotherapy.

ADVANCES IN KNOWLEDGE

Dataset heterogeneities decrease ML model performance and reliability.

Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images

Machine learning (ML) methods have been implemented in radiotherapy to aid virtual specific-plan verification protocols, predicting gamma passing rates (GPR) based on calculated modulation complexity metrics because of their direct relation to dose deliverability. Nevertheless, these metrics might not comprehensively represent the modulation complexity, and automatically extracted features from alternative predictors associated with modulation complexity are needed. For this reason, three convolutional neural networks (CNN) based models were trained to predict GPR values (regression and classification), using respectively three predictors: (1) the modulation maps (MM) from the multi-leaf collimator, (2) the relative monitor units per control point profile (MUcp), and (3) the composite dose image (CDI) used for portal dosimetry, from 1024 anonymized prostate plans. The models' performance was assessed for classification and regression by the area under the receiver operator characteristic curve (AUC_ROC) and Spearman's correlation coefficient (r). Finally, four hybrid models were designed using all possible combinations of the three predictors. The prediction performance for the CNN-models using single predictors (MM, MUcp, and CDI) were AUC_ROC = 0.84 ± 0.03, 0.77 ± 0.07, 0.75 ± 0.04, andr= 0.6, 0.5, 0.7. Contrastingly, the hybrid models (MM + MUcp, MM + CDI, MUcp+CDI, MM + MUcp+CDI) performance were AUC_ROC = 0.94 ± 0.03, 0.85 ± 0.06, 0.89 ± 0.06, 0.91 ± 0.03, andr= 0.7, 0.5, 0.6, 0.7. The MP, MUcp, and CDI are suitable predictors for dose deliverability models implementing ML methods. Additionally, hybrid models are susceptible to improving their prediction performance, including two or more input predictors.

Efficient dose-volume histogram-based pretreatment patient-specific quality assurance methodology with combined deep learning and machine learning models for volumetric modulated arc radiotherapy

BACKGROUND

Weak correlation between gamma passing rates and dose differences in target volumes and organs at risk (OARs) has been reported in several studies. Evaluation on the differences between planned dose-volume histogram (DVH) and reconstructed DVH from measurement was adopted and incorporated into patient-specific quality assurance (PSQA). However, it is difficult to develop a methodology allowing the evaluation of errors on DVHs accurately and quickly.

PURPOSE

To develop a DVH-based pretreatment PSQA for volumetric modulated arc therapy (VMAT) with combined deep learning (DL) and machine learning models to overcome the limitation of conventional gamma index (GI) and improve the efficiency of DVH-based PSQA.

METHODS

A DL model with a three-dimensional squeeze-and-excitation residual blocks incorporated into a modified U-net was developed to predict the measured PSQA DVHs of 208 head-and-neck (H&N) cancer patients underwent VMAT between 2018 and 2021 from two hospitals, in which 162 cases was randomly selected for training, 18 for validation, and 28 for testing. After evaluating the differences between treatment planning system (TPS) and PSQA DVHs predicted by DL model with multiple metrics, a pass or fail (PoF) classification model was developed using XGBoost algorithm. Evaluation of domain experts on dose errors between TPS and reconstructed PSQA DVHs was taken as ground truth for PoF classification model training.

RESULTS

The prediction model was able to achieve a good agreement between predicted, measured, and TPS doses. Quantitative evaluation demonstrated no significant difference between predicted PSQA dose and measured dose for target and OARs, except for D_mean of PTV6900 (p = 0.001), D₅₀ of PTV6000 (p = 0.014), D₂ of PTV5400 (p = 0.009), D₅₀ of left parotid (p = 0.015), and D_max of left inner ear (p = 0.007). The XGBoost model achieved an area under curves, accuracy, sensitivity, and specificity of 0.89 versus 0.88, 0.89 versus 0.86, 0. 71 versus 0.71, and 0.95 versus 0.91 with measured and predicted PSQA doses, respectively. The agreement between domain experts and the classification model was 86% for 28 test cases.

CONCLUSIONS

The successful prediction of PSQA doses and classification of PoF for H&N VMAT PSQA indicating that this DVH-based PSQA method is promising to overcome the limitations of GI and to improve the efficiency and accuracy of VMAT delivery.

Implementation of TG-218 for patient specific QA Tolerance and Action Limits determination: Gamma passing rates evaluation using 3DVH software

PURPOSE

To determine the tolerance (TL) and action limits (AL) of gamma passing rates (%GP) for Volumetric-Modulated Arc Therapy (VMAT) patient-specific quality assurance (PSQA), according to the AAPM TG-218 recommendations, and to evaluate comparatively the clinical relevance of 2D%GP and 3D%GP.

MATERIALS AND METHODS

PSQA was performed for 100 head and neck (H&N) and 73 prostate cancer VMAT treatment plans. Measurements were acquired using a cylindrical water equivalent phantom, hollow in the center, allowing measurements with homogeneous or heterogeneous inserts. LINAC delivered dose distributions were compared to the ones calculated from the treatment planning system (TPS) through gamma index. TL and AL were determined through the computation of 2D%GP, using the recommended acceptance criteria. Dose-volume histograms (DVH) were reconstructed from the measurements using a commercially available software, to detect the dosimetric differences (%DE) between the compared dose distributions. Utilizing the estimated dose on the patient anatomy, structure specific %GP (3D%GP) were calculated. The 3D%GP were compared to the 2D%GP ones, based on their correlation with the %DE. Each metric's sensitivity was determined through receiver operator characteristic (ROC) analysis.

RESULTS

TL and AL were in concordance with the universal ones, regarding the prostate cancer cases, but were lower for the H&N cases. Evaluation of %DE did not deem the plans unacceptable. The 2D%GP and the 3D%GP did not differ significantly regarding their correlation with %DE. For prostate plans, %GP sensitivity was higher than for H&N cases.

CONCLUSIONS

Determination of institutional specific TL and AL allow the monitoring of the PSQA procedure, yet for plans close to the limits clinically relevant metrics should be used before they are deemed unacceptable, for the process to be of higher sensitivity and efficiency. This article is protected by copyright. All rights reserved.

DIR-based models to predict weekly anatomical changes in head and neck cancer proton therapy

Objective. We proposed two anatomical models for head and neck patients to predict anatomical changes during the course of radiotherapy.Approach. Deformable image registration was used to build two anatomical models: (1) the average model (AM) simulated systematic progressive changes across the patient cohort; (2) the refined individual model (RIM) used a patient's CT images acquired during treatment to update the prediction for each individual patient. Planning CTs and weekly CTs were used from 20 nasopharynx patients. This dataset included 15 training patients and 5 test patients. For each test patient, a spot scanning proton plan was created. Models were evaluated using CT number differences, contours, proton spot location deviations and dose distributions.Main results. If no model was used, the CT number difference between the planning CT and the repeat CT at week 6 of treatment was on average 128.9 Hounsfield Units (HU) over the test population. This can be reduced to 115.5 HU using the AM, and to 110.5 HU using the RIM3(RIM, updated at week (3). When the predicted contours from the models were used, the average mean surface distance of parotid glands can be reduced from 1.98 (no model) to 1.16 mm (AM) and 1.19 mm (RIM3) at week 6. Using the proton spot range, the average anatomical uncertainty over the test population reduced from 4.47 ± 1.23 (no model) to 2.41 ± 1.12 mm (AM), and 1.89 ± 0.96 mm (RIM3). Based on the gamma analysis, the average gamma index over the test patients was improved from 93.87 ± 2.48 % (no model) to 96.16 ± 1.84% (RIM3) at week 6.Significance. The AM and the RIM both demonstrated the ability to predict anatomical changes during the treatment. The RIM can gradually refine the prediction of anatomical changes based on the AM. The proton beam spots provided an accurate and effective way for uncertainty evaluation.

Comparative performance analysis of 2D and 3D gamma metrics for patient specific QA in VMAT using Octavius 4D with 2D-Array 1500

INTRODUCTION

Gamma pass percentage (GPP) is the predominant metric used for Patient Specific Quality Assurance (PSQA) in radiation therapy. The dimensionality of the measurement geometry in PSQA has evolved from 2D planar to 3D planar, and presently to state-of-the-art 3D volumetric geometry. We aim to critically examine the performance of the three-dimensional gammas vis-à-vis the older gamma metrics of lower dimensionality to determine their mutual fungibility in PSQA, using clinically approved Volumetric Arc Therapy (VMAT) plans.

METHODS AND MATERIALS

Gamma pass percentages derived from PSQA for VMAT plans using Octavius 4D phantom with 2D-Array 1500 and its proprietary software were recorded. 2D planar, 3D planar, and 3D volumetric gamma pass percentages were retrospectively extracted for multiple treatment plans at three sites, using three acceptance limits, and for two modes of normalization. The differences in mean pass percentages, and the pairwise correlation between geometries were calculated within limits of statistical significance.

RESULTS

A significant increase in mean pass rates was observed from 2D planar to 3D planar geometries. The difference was less pronounced from 3D planar to 3D volumetric. 2D planar v/s 3D planar showed a significant degree of correlation among themselves, which was not seen against most of the 3D volumetric pass rates.

CONCLUSION

The mean gamma pass rates show conclusive evidence of the benefits of shifting from 2D planar to higher dimensions measurement geometries, but the benefits of using 3D volumetric compared to 3D planar is not always unequivocal. The correlations show mixed results regarding the interdependence of pass percentages at different geometries.

Dosimetric verification of stereotactic body radiotherapy treatment plan via ArcCHECK-3DVH system

OBJECTIVES

To study the feasibility of ArcCHECK-3DVH system in dosimetric verification for stereotactic body radiaotherapy (SBRT) with flattening filter free (FFF) model.

METHODS

SBRT treatment plans for 57 patients were introduced into ArcCHECK phantom and recalculated. The calculated dose distribution of treatment planning system and the measured dose distribution of ArcCHECK phantom were compared by γ analysis. Then the 3 dimensional dose distribution of target and organs at risk was reconstructed by 3DVH software. The reconstructed dose and calculated dose with treatment planning system (TPS) were compared, and the dose volume γ pass rate and deviation of dose volume parameters to the target and organs at risk were quantitatively valuated.

RESULTS

Based on the threshold criteria (3%, 3 mm, 10%), namely the deviation of measuring points between the planned value and the measured value was less than 3%, and the proportion of points with similar values in the plane or sphere with the center of the point and the radius of 3 mm was 10%, the relative and absolute dose pass rates of SBRT treatment plans in ArcCHECK system via γ analysis were greater than 95%. Based on the stricter threshold criteria (2%, 2 mm, 10%), the relative and absolute dose pass rates of SBRT treatment plan in ArcCHECK system via γ analysis were about 93%. In 3DVH dose verification, the γ pass rate of target and organs at risk was exceed 97%, and the deviations in 3DVH of the target and organs at risk were less than ±5%.

CONCLUSIONS

The ArcCHECK-3DVH system in dose verification can provide more comprehensive dose distribution information to reasonably evaluate the SBRT plan, with more significance for guiding clinical treatment.

IMRT QA and gamma comparisons: The impact of detector geometry, spatial sampling, and delivery technique on gamma comparison sensitivity

PURPOSE

To separately quantify sensitivity differences in patient-specific quality assurance comparisons analyzed with the gamma comparison for different measurement geometries, spatial samplings, and delivery techniques [intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT)].

METHODS

Error-free calculations for 20 IMRT and 20 VMAT cases were compared to calculations with known induced errors of varying magnitudes, using gamma comparisons. Five error types (MU scaling, three different MLC errors, and collimator errors) were induced in plan calculations on three different detector geometries - ArcCHECK, MapCHECK, and Delta 4. To study detector geometry sensitivity effects alone, gamma comparisons were made with 1 mm error-free calculations compared to 1 mm error-induced calculations for each device. Effects of spatial sampling were studied by making the same gamma comparisons, but down-sampling the error-induced calculations to the real spatial sampling of each device. Additionally, 1 mm vs 1 mm comparisons between the IMRT and VMAT cases were compared to investigate sensitivity differences between IMRT and VMAT using IMRT and VMAT cohorts with similar ranges of plan complexity and average aperture size. For each case, induced error type, and device, five different gamma criteria were studied to ensure sensitivity differences between devices, spatial sampling scenarios, and delivery technique were not gamma criterion specific, resulting in over 36,000 gamma comparisons.

RESULTS

For IMRT cases, Delta4 and MapCHECK devices had similar error sensitivities for lagging leaf, bank shift, and MU errors, while the ArcCHECK had considerably lower sensitivity than the planar-type devices. For collimator errors and perturbational leaf errors the ArcCHECK had higher error sensitivity than planar-type devices. This behavior was independent of gamma parameters (percent dose difference, distance-to-agreement, and low dose threshold), though use of local normalization resulted in error sensitivites that were markedly similar between all three devices. Differences between detector geometries were less pronounced for VMAT deliveries. Error sensitivity for a given gamma criterion when comparing IMRT and VMAT deliveries on the same devices showed that VMAT plans were more sensitive to some specific error types and less sensitive to others, when compared to IMRT plans. For the ArcCHECK device, the sensitivity of IMRT and VMAT cases was quite similar, whereas this was not the case for the planar-type devices. When comparing error sensitivity between 1 mm vs 1 mm calculations and 1 mm vs the real spatial sampling for each device, results showed that increased spatial sampling did not systematically increase error sensitivity.

CONCLUSIONS

Noticeable differences in error sensitivity were observed for different detector geometries, but differences were dependent on induced error type, and a particular device geometry did not offer universal improvements in error sensitivity across studied error types. This study demonstrates that the sensitivity of the gamma comparison does not largely hinge on detector spatial sampling. VMAT deliveries were generally less sensitive to errors when compared to IMRT plans for the planar-type devices, while similar sensitivities were observed between delivery techniques for the ArcCHECK device. Results of this work suggest that a universal gamma criterion is inappropriate for IMRT QA and that the percent pixels passing is an insufficient metric for evaluating quality assurance checks in the clinic.

Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis

Institutions use a range of different detector systems for patient-specific quality assurance (QA) measurements conducted to assure that the dose delivered by a patient's radiotherapy treatment plan matches the calculated dose distribution. However, the ability of different detectors to detect errors from different sources is often unreported. This study contains a systematic evaluation of Sun Nuclear's ArcCHECK in terms of the detectability of potential machine-related treatment errors. The five investigated sources of error were multileaf collimator (MLC) leaf positions, gantry angle, collimator angle, jaw positions, and dose output. The study encompassed the clinical treatment plans of 29 brain cancer patients who received stereotactic ablative radiotherapy (SABR). Six error magnitudes were investigated per source of error. In addition, the Eclipse AAA beam model dosimetric leaf gap (DLG) parameter was varied with four error magnitudes. Error detectability was determined based on the area under the receiver operating characteristic (ROC) curve (AUC). Detectability of DLG errors was good or excellent (AUC >0.8) at an error magnitude of at least ±0.4 mm, while MLC leaf position and gantry angle errors reached good or excellent detectability at error magnitudes of at least 1.0 mm and 0.6°, respectively. Ideal thresholds, that is, gamma passing rates, to maximize sensitivity and specificity ranged from 79.1% to 98.7%. The detectability of collimator angle, jaw position, and dose output errors was poor for all investigated error magnitudes, with an AUC between 0.5 and 0.6. The ArcCHECK device's ability to detect errors from treatment machine-related sources was evaluated, and ideal gamma passing rate thresholds were determined for each source of error. The ArcCHECK was able to detect errors in DLG value, MLC leaf positions, and gantry angle. The ArcCHECK was unable to detect the studied errors in collimator angle, jaw positions, and dose output.

A method for quantitative evaluations of scanning-proton dose distributions

PURPOSE

Patient-Specific Quality Assurance (PSQA) measurement analysis depends on generating metrics representative of calculation and measurement agreement. Considering the heightened capability of discrete spot scanning protons to modulate individual dose voxels, a dose plane comparison approach that maintained all of the capabilities of the well-established γ test, but that also provided a more intuitive error parameterization, was desired.

METHODS

Analysis was performed for 300 dose planes compared by searching all calculated points within a fixed radius around each measured pixel to determine the dose deviation. Dose plane agreement is reported as the dose difference minimum (DDM) within an empirically established search radius: ΔDmin(r). This per-pixel metric is aggregated into a histogram binned by dose deviation. Search-radius criteria were based on a weighted-beamlet 3σ spatial deviation from imaging isocenter. Equipment setup error was mitigated during analysis using tracked image registration, ensuring beamlet deviations to be the dominant source of spatial error. The percentage of comparison points with <3% dose difference determined pass rate.

RESULTS

The mean beamlet radial deviation was 0.38mm from x-ray isocenter, with a standard deviation of 0.19mm, such that 99.9% of relevant pencil beams were within 1 mm of nominal. The dose-plane comparison data showed no change in passing rate between a 3%/1mm ΔDmin(r) analysis (97.6 +/- 3.6%) and a 3%/2mm γ test (97.7 +/- 3.2%).

CONCLUSIONS

PSQA dose-comparison agreements corresponding to a search radius outside of machine performance limits are likely false positives. However, the elliptical shape of the γ test is too dose-restrictive with a spatial-error threshold set at 1 mm. This work introduces a cylindrical search shape, proposed herein as more relevant to plan quality, as part of the new DDM planar-dose comparison algorithm. DDM accepts all pixels within a given dose threshold inside the search radius, and carries forward plan-quality metrics in a straightforward manner for evaluation.

A patient-specific QA comparison between 2D and 3D diode arrays for single-lesion SRS and SBRT treatments

The purpose of this study is to compare patient-specific quality assurance (PSQA) results between two dimensional (2D) diode (SRS MapCHECK^®) and 3D diode (ArcCHECK^®) arrays. Twenty-eight intracranial stereotactic radiosurgery (SRS) and 26 lung stereotactic body radiation therapy (SBRT) clinical plans with a single lesion were selected and categorized into 4 groups: 20 SRS dynamic conformal arc therapy (DCAT) plans (Group A), 8 SRS volumetric modulated arc therapy (VMAT) plans (Group B), 6 SBRT DCAT plans (Group C) and 20 SBRT VMAT plans (Group D). An individual field of each plan was delivered on SRS MapCHECK and ArcCHECK and QA analysis was performed using 4 gamma criteria of dose difference/distance-to-agreement of 3%/3 mm, 3%/2 mm, 2%/2 mm and 2%/1 mm. Statistical analysis was performed to compare PSQA results between the 2 QA devices. For all 4 groups and all 4 gamma criteria, average gamma passing rates were higher with SRS MapCHECK.

Cross verification of independent dose recalculation, log files based, and phantom measurement-based pretreatment quality assurance for volumetric modulated arc therapy

Independent treatment planning system (TPS) check with Mobius3D software, log files based quality assurance (QA) with MobiusFX, and phantom measurement‐based QA with ArcCHECK were performed and cross verified for head‐and‐neck (17 patients), chest (16 patients), and abdominal (19 patients) cancer patients who underwent volumetric modulated arc therapy (VMAT). Dosimetric differences and percentage gamma passing rates (%GPs) were evaluated and compared for this cross verification. For the dosimetric differences in planning target volume (PTV) coverage, there was no significant difference among TPS vs. Mobius3D, TPS vs. MobiusFX, and TPS vs. ArcCHECK. For the dosimetric differences in organs at risks (OARs), the number of metrics with an average dosimetric differences higher than ±3% for TPS vs Mobius3D, TPS vs MobiusFX, and TPS vs ArcCHECK were 1, 1, 7; 2, 1, 4; 1, 1, 5 for the patients with head‐and‐neck, abdomen, and chest cancer, respectively. The %GPs of global gamma indices for Mobius3D and MobiousFX were above 97%, while it ranged from 92% to 96% for ArcCHECK. The %GPs of individual volume‐based gamma indices were around 98% for Mobius3D and MobiousFX, except for γPTV for chest and abdominal cancer (88.9% to 92%); while it ranged from 86% to 99% for ArcCHECK. In conclusion, some differences in dosimetric metrics and gamma passing rates were observed with ArcCHECK measurement‐based QA in comparison with independent dosecheck and log files based QA. Care must be taken when considering replacing phantom measurement‐based IMRT/VMAT QA.

A comprehensive and clinical-oriented evaluation criteria based on DVH information and gamma passing rates analysis for IMRT plan 3D verification

Purpose

To accomplish the 3D dose verification to IMRT plan by incorporating DVH information and gamma passing rates (GPs) (DVH_GPs) so as to better correlate the patient‐specific quality assurance (QA) results with clinically relevant metrics.

Materials and methods

DVH_GPs analysis was performed to specific structures of 51 intensity‐modulated radiotherapy (IMRT) treatment plans (17 plans each for oropharyngeal neoplasm, esophageal neoplasm, and cervical neoplasm) with Delta4 3D dose verification system. Based on the DVH action levels of 5% and GPs action levels of 90% (3%/2 mm), the evaluation results of DVH_GPs analysis were categorized into four regions as follows: the true positive (TP) (%DE> 5%, GPs < 90%), the false positive (FP) (%DE ≤ 5%, GPs < 90%), the false negative (FN) (%DE> 5%, GPs ≥ 90%), and the true negative (TN) (%DE ≤ 5%, GPs ≥ 90%). Considering the actual situation, the final patient‐specific QA determination was made based on the DVH_GPs evaluation results. In order to exclude the impact of Delta4 phantom on the DVH_GPs evaluation results, 5 cm phantom shift verification was carried out to structures with abnormal results (femoral heads, lung, heart).

Results

In DVH_GPs evaluation, 58 cases with FN, 5 cases with FP, and 2 cases with TP were observed. After the phantom shift verification, the extremely abnormal FN of both lung (%DE = 21.52%±8.20%) and heart (%DE = 19.76%) in the oropharyngeal neoplasm plans and of the bilateral formal heads (%DE = 26.41%±13.45%) in cervical neoplasm plans disappeared dramatically. DVH_GPs analysis was performed to all evaluation results in combination with clinical treatment criteria. Finally, only one TP case from the oropharyngeal neoplasm plans and one FN case from the esophageal neoplasm plans did not meet the treatment requirements, so they needed to be replanned.

Conclusion

The proposed DVH_GPs evaluation method first make up the deficiency of conventional gamma analysis regarding intensity information and space information. Moreover, it improves the correlation between the patient‐specific QA results and clinically relevant metrics. Finally, it can distinguish the TP, TN, FP, and FN in the evaluation results. They are affected by many factors such as the action levels of DVH and GPs, the feature of the specific structure, the QA device, etc. Therefore, medical physicist should make final patient‐specific QA decision not only by taking into account the information of DVH and GPs, but also the practical situation.

Three-dimensional dose reconstruction-based pretreatment dosimetric verification in volumetric modulated arc therapy for prostate cancer

Purpose

We performed three-dimensional (3D) dose reconstruction-based pretreatment verification to evaluate gamma analysis acceptance criteria in volumetric modulated arc therapy (VMAT) for prostate cancer.

Materials and Methods

Pretreatment verification for 28 VMAT plans for prostate cancer was performed using the COMPASS system with a dolphin detector. The 3D reconstructed dose distribution of the treatment planning system calculation (TC) was compared with that of COMPASS independent calculation (CC) and COMPASS reconstruction from the dolphin detector measurement (CR). Gamma results (gamma failure rate and average gamma value [GFR and γAvg]) and dose-volume histogram (DVH) deviations, 98%, 2% and mean dose-volume difference (DD_98%, DD_2% and DD_mean), were evaluated. Gamma analyses were performed with two acceptance criteria, 2%/2 mm and 3%/3 mm.

Results

The GFR in 2%/2 mm criteria were less than 8%, and those in 3%/3 mm criteria were less than 1% for all structures in comparisons between TC, CC, and CR. In the comparison between TC and CR, GFR and γAvg in 2%/2 mm criteria were significantly higher than those in 3%/3 mm criteria. The DVH deviations were within 2%, except for DD_mean (%) for rectum and bladder.

Conclusions

The 3%/3 mm criteria were not strict enough to identify any discrepancies between planned and measured doses, and DVH deviations were less than 2% in most parameters. Therefore, gamma criteria of 2%/2 mm and DVH related parameters could be a useful tool for pretreatment verification for VMAT in prostate cancer.

Improvement in sensitivity of radiochromic 3D dosimeter based on rigid polyurethane resin by incorporating tartrazine

We investigated the influence of incorporating tartrazine on the dose response characteristics of radiochromic 3D dosimeters based on polyurethane resin. We use three types of polyurethane resins with different Shore hardness values: 30 A, 50 A, and 80 D. PRESAGE dosimeters are fabricated with different chemical components and concentrations. Tartrazine (Yellow No. 5) helps incorporate a yellow dye to fabricate the dosimeter. Elemental composition is analyzed with the Z_eff. Three sets of six different PRESAGE dosimeters were fabricated to investigate the effects of incorporating yellow dye on the dose response characteristics of the dosimeter. The dose response curve was obtained by measuring the optical absorbance using a spectrometer and optical density using optical CT, respectively. The energy and dose rate dependences are evaluated for the dosimeter with the highest sensitivity. For the optical density measurement, significant sensitivity enhancements of 36.6% and 32.7% were achieved in polyurethane having a high Shore hardness of 80 D and 50 A by incorporating tartrazine, respectively. The same results were obtained in the optical absorbance measurements. The ratio of the Z_eff of the dosimeter with 80 D Shore hardness to water was 1.49. The polyurethane radiochromic dosimeter with a Shore hardness of 80 D showed the highest sensitivity and energy and dose rate independence upon the incorporation of tartrazine.

Implementation of the structural SIMilarity (SSIM) index as a quantitative evaluation tool for dose distribution error detection

PURPOSE

To apply an imaging metric of the structural SIMilarity (SSIM) index to the radiotherapy dose verification field and evaluate its capability to reveal the different types of errors between two dose distributions.

METHOD

The SSIM index consists of three sub-indices: luminance, contrast, and structure. Given two images, luminance analysis compares the local mean result, contrast analysis compares the local standard deviation, and the structure index represents the local Pearson correlation. Three test error patterns (absolute dose error, dose gradient error, and dose structure error) were designed to characterize the response of SSIM and its sub-indices and establish the correlation between the indices and different dose error types. After establishing the correlation, four radiotherapy plans (one MLC picket-fence test plan, one brain stereotactic radiotherapy plan, and two head-and-neck plans) were tested by computing each index and compared with the gamma analysis results to determine their similarities and differences.

RESULTS

Among the three test error patterns, the luminance index decreased from 1 to 0.1 when the absolute dose agreement fell from 100% to 5%, the contrast index decreased from 1 to 0.36 when the dose gradient agreement fell from 100% to 10%, and the structure index decreased from 1 to 0.23 when the periodical dose pattern shifted (leading to a lower correlation). Thus, the luminance, contrast and structure index can detect the absolute dose error, gradient discrepancy, and dose structure error, respectively. For the four clinical cases, the sub-indices can reveal the type of error when gamma analysis only provided limited information.

CONCLUSIONS

The correlation between the subcomponents of the SSIM index and the error types of the dose distribution were established. The SSIM index provides additional error information compared to that provided by gamma analysis.

Prediction of VMAT delivery accuracy with textural features calculated from fluence maps

Background

Comprehensively textural feature performance test from volumetric modulated arc therapy (VMAT) fluences to predict plan delivery accuracy.

Methods

A total of 240 VMAT plans for various treatment sites were analyzed, with Trilogy and TrueBeam STx systems. Fluence maps superposed fluences at each control point per plan. The textural features were the angular second moment (ASM), inverse difference moment (IDM), contrast, variance, correlation, and entropy, calculated from fluence maps using three displacement distances. Correlation analysis of textural feature performance as predictors of VMAT delivery accuracy used global gamma passing rates with MapCHECK2 and ArcCHECK dosimeters, and mechanical delivery errors calculated from machine log files.

Results

Spearman’s rank correlation coefficients (r) of the ASM (d = 10) to the gamma passing rates with 1%/2 mm using the MapCHECK2 were 0.358 and 0.519, respectively (p <  0.001). For the ArcCHECK, they were 0.273 (p = 0.001) and 0.259 (p = 0.009), respectively. The r-values of the ASM (d = 10) to the Trilogy and TrueBeam STx MLC errors were − 0.843 and − 0.859, respectively (p <  0.001), and those to the MU delivery errors were − 0.482 and − 0.589, respectively (p <  0.001). The ASM (d = 10) showed better performance in predicting VMAT delivery accuracy.

Conclusions

The ASM (d = 10) calculated from VMAT plan fluence maps were strongly correlated with global gamma passing rates and MLC delivery errors, and can predict VMAT delivery accuracy.

Two-dimensional solid-state array detectors: A technique for in vivo dose verification in a variable effective area

PURPOSE

We introduce a technique that employs a 2D detector in transmission mode (TM) to verify dose maps at a depth of dmax in Solid Water. TM measurements, when taken at a different surface-to-detector distance (SDD), allow for the area at dmax (in which the dose map is calculated) to be adjusted.

METHODS

We considered the detector prototype "MP512" (an array of 512 diode-sensitive volumes, 2 mm spatial resolution). Measurements in transmission mode were taken at SDDs in the range from 0.3 to 24 cm. Dose mode (DM) measurements were made at dmax in Solid Water. We considered radiation fields in the range from 2 × 2 cm2 to 10 × 10 cm2 , produced by 6 MV flattened photon beams; we derived a relationship between DM and TM measurements as a function of SDD and field size. The relationship was used to calculate, from TM measurements at 4 and 24 cm SDD, dose maps at dmax in fields of 1 × 1 cm2 and 4 × 4 cm2 , and in IMRT fields. Calculations were cross-checked (gamma analysis) with the treatment planning system and with measurements (MP512, films, ionization chamber).

RESULTS

In the square fields, calculations agreed with measurements to within ±2.36%. In the IMRT fields, using acceptance criteria of 3%/3 mm, 2%/2 mm, 1%/1 mm, calculations had respective gamma passing rates greater than 96.89%, 90.50%, 62.20% (for a 4 cm SSD); and greater than 97.22%, 93.80%, 59.00% (for a 24 cm SSD). Lower rates (1%/1 mm criterion) can be explained by submillimeter misalignments, dose averaging in calculations, noise artifacts in film dosimetry.

CONCLUSIONS

It is possible to perform TM measurements at the SSD which produces the best fit between the area at dmax in which the dose map is calculated and the size of the monitored target.

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.

Pre-treatment 2D and 3D dosimetric verification of volumetric arc therapy. A correlation study between gamma index passing rate and clinical dose volume histogram

OBJECTIVES

To evaluate methods for the pre-treatment verification of volumetric modulated arc therapy (VMAT) based on the percentage gamma passing rate (%GP) and its correlation and sensitivity with percentage dosimetric errors (%DE).

METHODS

A total of 25 patients with prostate cancer and 15 with endometrial cancer were analysed. The %GP values of 2D and 3D verifications with different acceptance criteria (1%/1 mm, 2%/2 mm, and 3%/3 mm) were obtained using OmniPro and Compass. The %DE was calculated using a planned dose volume histogram (DVH) created in Monaco's treatment planning system (TPS), which relates radiation dose to tissue and the patient's predicted dose volume histogram in Compass. Statistical correlation between %GP and %DE was verified using Pearson's correlation coefficient. Sensitivity was calculated based on the receiver operating characteristics (ROC) curve. Plans were calculated using Collapsed Cone Convolution and the Monte Carlo algorithm.

RESULTS

The t-test results of the planned and estimated DVH showed that the mean values were comparable (P > 0.05). For the 3%/3 mm criterion, the average %GP was acceptable for the prostate and endometrial cancer groups, with average rates of 99.68 ± 0.49% and 99.03 ± 0.59% for 2D and 99.86 ± 0.39% and 99.53 ± 0.44% for 3D, respectively. The number of correlations was poor for all analysed data. The mean Pearson's R-values for prostate and endometrial cancer were < 0.45 and < 0.43, respectively. The area under the ROC curve for the prostate and endometrial cancer groups, was lower than 0.667.

CONCLUSIONS

Analysis of the %GP versus %DE values revealed only weak correlations between 2D and 3D verifications. DVH results obtained using the Compass system will be helpful in confirming that the analysed plans respect dosimetric constraints.

Use of metrics to quantify IMRT and VMAT treatment plan complexity: A systematic review and perspectives

PURPOSE

Fixed-field intensity modulated radiation therapy (FF-IMRT) or volumetric modulated arc therapy (VMAT) beams complexity is due to fluence fluctuation. Pre-treatment Quality Assurance (PTQA) failure could be linked to it. Several plan complexity metrics (PCM) have been published to quantify this complexity but in a heterogeneous formalism. This review proposes to gather different PCM and to discuss their eventual PTQA failure identifier abilities.

METHODS AND MATERIALS

A systematic literature search and outcome extraction from MEDLINE/PubMed (National Center for Biotechnology Information, NCBI) was performed. First, a list and a synthesis of available PCM is made in a homogeneous formalism. Second, main results relying on the link between PCM and PTQA results but also on other uses are listed.

RESULTS

A total of 163 studies were identified and n = 19 were selected after inclusion and exclusion criteria application. Difference is made between fluence and degree of freedom (DOF)-based PCM. Results about the PCM potential as PTQA failure identifier are described and synthesized. Others uses are also found in quality, big data, machine learning and audit procedure.

CONCLUSIONS

A state of the art is made thanks to this homogeneous PCM classification. For now, PCM should be seen as a planning procedure quality indicator although PTQA failure identifier results are mitigated. However limited clinical use seems possible for some cases. Yet, addressing the general PTQA failure prediction case could be possible with the big data or machine learning help.

Improvements in treatment planning calculations motivated by tightening IMRT QA tolerances

Implementing tighter intensity modulated radiation therapy (IMRT) quality assurance (QA) tolerances initially resulted in high numbers of marginal or failing QA results and motivated a number of improvements to our calculational processes. This work details those improvements and their effect on results. One hundred eighty IMRT plans analyzed previously were collected and new gamma criteria were applied and compared to the original results. The results were used to obtain an estimate for the number of plans that would require additional dose volume histogram (DVH)‐based analysis and therefore predicted workload increase. For 2 months and 133 plans, the established criteria were continued while the new criteria were applied and tracked in parallel. Because the number of marginal or failing plans far exceeded the predicted levels, a number of calculational elements were investigated: IMRT modeling parameters, calculation grid size, and couch top modeling. After improvements to these elements, the new criteria were clinically implemented and the frequency of passing, questionable, and failing plans measured for the subsequent 15 months and 674 plans. The retrospective analysis of selected IMRT QA results demonstrated that 75% of plans should pass, while 19% of IMRT QA plans would need DVH‐based analysis and an additional 6% would fail. However, after applying the tighter criteria for 2 months, the distribution of plans was significantly different from prediction with questionable or failing plans reaching 47%. After investigating and improving several elements of the IMRT calculation processes, the frequency of questionable plans was reduced to 11% and that of failing plans to less than 1%. Tighter IMRT QA tolerances revealed the need to improve several elements of our plan calculations. As a consequence, the accuracy of our plans have improved, and the frequency of finding marginal or failing IMRT QA results, remains within our practical ability to respond.

Reliability of the gamma index analysis as a verification method of volumetric modulated arc therapy plans

BACKGROUND

We investigate the gamma passing rate (GPR) consistency when applying different types of gamma analyses, linacs, and dosimeters for volumetric modulated arc therapy (VMAT).

METHODS

A total of 240 VMAT plans for various treatment sites, which were generated with Trilogy (140 plans) and TrueBeam STx (100 plans), were retrospectively selected. For each VMAT plan, planar dose distributions were measured with both MapCHECK2 and ArcCHECK dosimeters. During the planar dose distribution measurements, the actual multileaf collimator (MLC) positions, gantry angles, and delivered monitor units were recorded and compared to the values in the original VMAT plans to calculate mechanical errors. For each VMAT plan, both the global and local gamma analyses were performed with 3%/3 mm, 2%/2 mm, 2%/1 mm, 1%/2 mm, and 1%/1 mm. The Pearson correlation coefficients (r) were calculated 1) between the global and the local GPRs, 2) between GPRs with the MapCHECK2 and the ArcCHECK dosimeters, 3) and between GPRs and the mechanical errors during the VMAT delivery.

RESULTS

For the MapCHECK2 measurements, strong correlations between the global and local GPRs were observed only with 1%/2 mm and 1%/1 mm (r > 0.8 with p < 0.001), while weak or no correlations were observed for the ArcCHECK measurement. Between the MapCHECK2 and ArcCHECK measurements, the global GPRs showed no correlations (all with p > 0.05), while the local GPRs showed moderate correlations only with 2%/1 mm and 1%/1 mm for TrueBeam STx (r > 0.5 with p < 0.001). Both the global and local GPRs always showed weak or no correlations with the MLC positional errors except for the GPRs of MapCHECK2 with 1%/2 mm and 1%/1 mm for TrueBeam STx and the GPR of ArcCHECK with 1%/2 mm for Trilogy (r < - 0.5 with p < 0.001).

CONCLUSIONS

The GPRs varied according to the types of gamma analyses, dosimeters, and linacs. Therefore, each institution should carefully establish their own gamma analysis protocol by determining the type of gamma index analysis and the gamma criterion with their own linac and their own dosimeter.

Composite QA for intensity-modulated radiation therapy using individual volume-based 3D gamma indices

The aim of this study was to investigate the feasibility and sensitivity of using individual volume-based 3D gamma indices for composite dose-volume histogram (DVH)-based intensity-modulated radiation therapy (IMRT) quality assurance (QA). Composite IMRT QA for 15 cervical cancer patients was performed with ArcCHECK. The percentage dosimetric errors (%DEs) of DVH metrics when comparing treatment planning system and QA-reconstructed dose distribution, percentage gamma passing rates (%GPs) with different criteria for individual volumes and global gamma indices were evaluated, as well as their correlations. Receiver operating characteristic (ROC) curves were applied in order to study the sensitivities of the global and individual volume gamma indices. Most %DEs of the DVH metrics were within 3%. The γPTV and γrectum were <80% at 2%/2 mm; apart from these two individual volume indices, all other individual volume gamma indices and global indices had acceptable %GPs. For the criteria of 2%/2 mm, 3%/3 mm and 4%/4 mm, individual volume-based %GPs and global %GPs were correlated in 11, 1 and 12 out of 24 %DE metrics, and in 5, 4 and 5 out of 24 %DE metrics, respectively. Individual volume-based %GPs had a higher percentage of correlation with DVH metrics (%DEs) compared with global %GPs in composite IMRT QA. The areas under the curve (AUCs) of individual volume %GPs were higher than those of global %GPs. In conclusion, individual volume-based %GPs had a higher correlation with %DEs of metrics and a higher sensitivity presented by ROC analysis compared with global %GPs for composite IMRT QA. Thus, use of individual volume-based 3D gamma indices was found to be feasible and sensitive for composite IMRT QA.

Real-time high spatial resolution dose verification in stereotactic motion adaptive arc radiotherapy

Purpose

Radiation treatments delivered with real‐time multileaf collimator (MLC) tracking currently lack fast pretreatment or real‐time quality assurance. The purpose of this study is to test a 2D silicon detector, MagicPlate‐512 (MP512), in a complex clinical environment involving real‐time reconfiguration of the MLC leaves during target tracking.

Methods

MP512 was placed in the center of a solid water phantom and mounted on a motion platform used to simulate three different patient motions. Electromagnetic target tracking was implemented using the Calypso system (Varian Medical Systems, Palo Alto, CA, USA) and an MLC tracking software. A two‐arc VMAT plan was delivered and 2D dose distributions were reconstructed by MP512, EBT3 film, and the Eclipse treatment planning system (TPS). Dose maps were compared using gamma analysis with 2%/2 mm and 3%/3 mm acceptance criteria. Dose profiles were generated in sup‐inf and lateral directions to show the agreement of MP512 to EBT3 and to highlight the efficacy of the MLC tracking system in mitigating the effect of the simulated patient motion.

Results

Using a 3%/3 mm acceptance criterion for 2D gamma analysis, MP512 to EBT3 film agreement was 99% and MP512 to TPS agreement was 100%. For a 2%/2 mm criterion, the agreement was 95% and 98%, respectively. Full width at half maximum and 80%/20% penumbral width of the MP512 and EBT3 dose profiles agreed within 1 mm and 0.5 mm, respectively. Patient motion increased the measured dose profile penumbral width by nearly 2 mm (with respect to the no‐motion case); however, the MLC tracking strategy was able to mitigate 80% of this effect.

Conclusions

MP512 is capable of high spatial resolution 2D dose reconstruction during adaptive MLC tracking, including arc deliveries. It shows potential as an effective tool for 2D small field dosimetry and pretreatment quality assurance for MLC tracking modalities. These results provide confidence that detector‐based pretreatment dosimetry is clinically feasible despite fast real‐time MLC reconfigurations.

A clinically relevant IMRT QA workflow: Design and validation

PURPOSE

The purpose of this study was to determine clinically relevant pass/question/fail criteria for gamma analysis of intensity-modulated radiation therapy quality assurance (IMRT QA) plans, identify which plans should be further analyzed with dose-volume histogram (DVH) metrics, and create a workflow for performing that DVH-based analysis.

METHODS

A total of 11 plans, 5 prostate and 6 head/neck, were selected to represent known good plans based on their high-passing rate using conventional IMRT QA criteria. These were modified by moving the programmed MLC positions to underdose the target or overdose important structures by varying amounts. Commercially available hardware/software was used to measure and analyze all plans (76 total) using 4%/3 mm, 3%/3 mm, 3%/2 mm, and 2%/2 mm gamma criteria. Two receiver operator characteristic (ROC) curves per criterion were created to assess effective passing rates. One ROC curve was to find a higher threshold that determined a clear pass and the second to find a lower threshold to determine a clear failure. Plans between these two thresholds need DVH-based analysis to assess the clinical consequence of the dose difference. The modified plans were analyzed in the planning system and reconstructed in commercially available DVH-based analysis software to access the accuracy and usefulness of the software.

RESULTS

Analysis of the ROC curves showed optimal pass and fail thresholds for plan error detection per criterion to achieve clinically relevant sensitivity and specificity. Based on measurement uncertainty and pass/fail ranges, 3%/2 mm gamma criteria with a pass threshold of 95% and a fail threshold of 90% were most optimal. DVH analysis showed good agreement with all reconstructed plans except where the changes to the MLC patterns caused the periphery of the target to be underdosed. For questionable plans, comparing the organ-specific DVHs to the physician-provided planning constraints proved to be an efficient and effective workflow since plans for which the target dose was slightly high or where organs at risk were underdosed could be released for the treatment without consulting the physician for a clinical decision.

CONCLUSION

This work indicates the potential for appreciable improvement in error detection for IMRT QA. Using effective pass/fail thresholds to determine plans that need DVH-based analysis minimizes the need for excessive, time-consuming, analysis, and making use of the dosimetric constraints of the plan minimizes the burden on physicians. Overall, DVH-based analysis is a powerful tool that can provide substantial insight over the traditional approach that does not provide structure-specific data.

Correlation between gamma passing rate and complexity of IMRT plan due to MLC position errors

PURPOSE

This study evaluates the correlation between the susceptibility of the γ passing rate of IMRT plans to the multi-leaf collimator (MLC) position errors and a quantitative plan complexity metric.

METHODS

Twenty patients were selected for this study. For each patient, two IMRT plans were generated using sliding window and step-&-shoot techniques, respectively. Modulation complexity score (MCS) was calculated for all IMRT plans, and symmetric MLC leaf bank errors, ranging from 0.3 mm to 1 mm, were introduced. Original and modified plans were delivered using Varian's Clinac iX. The obtained dose distribution using ArcCHECK was then compared with the TPS calculated dose distribution of the original plans. 3D gamma analysis was performed for each verification with passing criteria of 2%/2 mm. The γ passing rate decreasing gradient were calculated to evaluate relationship between variation of γ passing rate due to MLC errors and complexity.

RESULTS

A linear regression analysis was applied between γ gradient and complexity, and the results showed a linear correlation (R² = 0.81 and 0.82 for open and closed MLC error types, respectively) indicating the more complex plans are more susceptible to MLC leaf bank errors. Meanwhile, correlation of re-normalized γ passing rate and complexity for all errors scenarios also presented a strong correlation (r > 0.75).

CONCLUSION

The statistics results revealed variation relationship of dosimetry robust of plans with various complexities to MLC errors. Our results also suggested that the observed susceptibility is independent of the delivery techniques.

Multidimensional correlation among plan complexity, quality and deliverability parameters for volumetric-modulated arc therapy using canonical correlation analysis

A multidimensional exploratory statistical method, canonical correlation analysis (CCA), was applied to evaluate the impact of complexity parameters on the plan quality and deliverability of volumetric-modulated arc therapy (VMAT) and to determine parameters in the generation of an ideal VMAT plan. Canonical correlations among complexity, quality and deliverability parameters of VMAT, as well as the contribution weights of different parameters were investigated with 71 two-arc VMAT nasopharyngeal cancer (NPC) patients, and further verified with 28 one-arc VMAT prostate cancer patients. The average MU and MU per control point (MU/CP) for two-arc VMAT plans were 702.6 ± 55.7 and 3.9 ± 0.3 versus 504.6 ± 99.2 and 5.6 ± 1.1 for one-arc VMAT plans, respectively. The individual volume-based 3D gamma passing rates of clinical target volume (γCTV) and planning target volume (γPTV) for NPC and prostate cancer patients were 85.7% ± 9.0% vs 92.6% ± 7.8%, and 88.0% ± 7.6% vs 91.2% ± 7.7%, respectively. Plan complexity parameters of NPC patients were correlated with plan quality (P = 0.047) and individual volume-based 3D gamma indices γ(IV) (P = 0.01), in which, MU/CP and segment area (SA) per control point (SA/CP) were weighted highly in correlation with γ(IV) , and SA/CP, percentage of CPs with SA < 5 × 5 cm2 (%SA < 5 × 5 cm2) and PTV volume were weighted highly in correlation with plan quality with coefficients of 0.98, 0.68 and -0.99, respectively. Further verification with one-arc VMAT plans demonstrated similar results. In conclusion, MU, SA-related parameters and PTV volume were found to have strong effects on the plan quality and deliverability.

A study on the effect of detector resolution on gamma index passing rate for VMAT and IMRT QA

The main objectives of this study are to (1) analyze the sensitivity of various gamma index passing rates using different types of detectors having different resolutions and (2) investigate the sensitivity of various gamma criteria in intensity‐modulated radiation therapy (IMRT) and volumetrically modulated arc therapy (VMAT) quality assurance (QA) for the detection of systematic multileaf collimator (MLC) errors using an electronic portal imaging device (EPID) and planar (MapCheck2) and cylindrical (ArcCheck) diode arrays. We also evaluated whether the correlation between the gamma passing rate (%GP) and the percentage dose error (%DE) of the dose–volume histogram (DVH) metrics was affected by the finite spatial resolution of the array detectors. We deliberately simulated systematic MLC errors of 0.25 mm, 0.50 mm, 0.75 mm, and 1 mm in five clinical nasopharyngeal carcinoma cases, thus creating 40 plans with systematic MLC errors. All measurements were analyzed field by field using gamma criteria of 3%/3 mm, 3%/2 mm, 3%/1 mm, and 2%/2 mm, with a passing rate of 90% applied as the action level. Our results showed that 3%/1 mm is the most sensitive criterion for the detection of systematic MLC errors when using EPID, with the steepest slope from the best‐fit line and an area under the receiver operating characteristic (ROC) curve >0.95. With respect to the 3%/1 mm criterion, a strong correlation between %GP and %DE of the DVH metrics was observed only when using the EPID. However, with respect to the same criteria, a 0.75 mm systematic MLC error can go undetected when using MapCheck2 and ArcCheck, with an area under the ROC curve <0.75. Furthermore, a lack of correlation between %GP and %DE of the DVH metrics was observed in MapCheck2 and ArcCheck. In conclusion, low‐spatial resolution detectors can affect the results of a per‐field gamma analysis and render the analysis unable to accurately separate erroneous and non‐erroneous plans. Meeting these new sensitive criteria is expected to ensure clinically acceptable dose errors.

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.

Dosimetric advantage of volumetric modulated arc therapy in the treatment of intraocular cancer

Objective

The purpose of this study is to investigate the dosimetric advantages of volumetric modulated arc therapy (VMAT) in the treatment of intraocular cancer by comparing it directly with three-dimensional conformal radiotherapy (CRT) and intensity-modulated radiotherapy (IMRT).

Methods

CRT plan, 7f-IMRT plan, and one-arc VMAT plan were generated for 14 intraocular cancer patients. Dosimetric and biological quality indices for target volume and organs at risks (OARs) were evaluated and compared.

Results

The target coverage presented by V95 for CRT, IMRT and VMAT were 95.02% ± 0.67%, 95.51% ± 2.25%, and 95.92% ± 3.05%, respectively. The homogeneity index (HI) for CRT, IMRT and VMAT were 0.15 ± 0.05, 0.23 ± 0.05, and 0.23 ± 0.06, respectively. IMRT and VMAT greatly decreased the dose to ipsilateral lens compared with CRT with a D1 of 2972.66 ± 1407.12 cGy, 3317.82 ± 915.28 cGy and 4809.54 ± 524.60 cGy for IMRT, VMAT and CRT, respectively. Similar results were observed for ipsilateral eyeballs. IMRT and VMAT also spared better on brainstem, optical nerves and optical chiasm compared CRT. However, CRT achieved lower dose to the eyeballs compared with IMRT and VMAT. VMAT and IMRT showed mixed results on target coverage and OAR sparing. The average MUs and delivery time of IMRT and VMAT were 531.25 ± 81.21 vs. 400.99 ± 61.49 and 5.05 ± 0.53 vs.1.71 ± 0.69 min, respectively.

Conclusions

Although no clear distinction on PTV coverage among CRT, IMRT and VMAT plans was observed in the treatment of intraocular cancer, VMAT and IMRT achieved better homogeneity and conformity for target volume, and delivered fewer doses to ipsilateral lens and eyeballs compared with CRT. However, VMAT and IMRT increased the low dose volume to the contralateral OARs. Although VMAT and IMRT showed mixed results on target coverage and OAR sparing, VMAT decreased MU and delivery time significantly compared with IMRT. VMAT is a promising and feasible external beam radiotherapy technique in the treatment of intraocular cancer patients.

Individual volume-based 3D gamma indices for pretreatment VMAT QA

Although gamma analysis is still a widely accepted quantitative tool to analyze and report patient-specific QA for intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT), the correlation between the 2D percentage gamma passing rate (%GP), and the clinical dosimetric difference for IMRT and VMAT has been questioned. The purpose of this study was to investigate the feasibility of individual volume-based 3D gamma indices for pretreatment VMAT QA. Percentage dosimetric errors (%DE) of dose-volume histogram metrics (includes target volumes and organ at risks) between the treatment planning system and QA-reconstructed dose distribution, %GPs for individual volume and global gamma indices, as well their correlations and sensitivities were investigated for one- and two-arc VMAT plans. The %GPs of individual volumes had a higher percent of correlation with individual 15 %DE metrics compared with global %GPs. For two-arc VMAT at 2%/2 mm, 3%/3 mm, and 4%/4 mm criteria, individual volume %GPs were correlated with 9, 12, and 9 out of 15 %DE metrics, while global %GPs were correlated with only 2 out of 15 %DE metrics, respectively. For one-arc VMAT at 2%/2 mm, 3%/3 mm, and 4%/4 mm criteria, individual volume %GPs were correlated with 18, 16, and 13 out of 23 %DE metrics, and global %GPs were correlated with 19, 12, and 1 out 23 %DE metrics, respectively. The area under curves (AUC) of individual volume %GPs were higher than those of global %GPs for two-arc VMAT plans, but with mixed results for one-arc VMAT plans. In a conclusion, the idea of individual volume %GP was created and investigated to better serve for VMAT QA and individual volume-based %GP had a higher percent of correlation with DVH 15 %DE metrics compared with global %GP for both one- and two-arc VMAT plans.

IMRT QA: Selecting gamma criteria based on error detection sensitivity

PURPOSE

The gamma comparison is widely used to evaluate the agreement between measurements and treatment planning system calculations in patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA). However, recent publications have raised concerns about the lack of sensitivity when employing commonly used gamma criteria. Understanding the actual sensitivity of a wide range of different gamma criteria may allow the definition of more meaningful gamma criteria and tolerance limits in IMRT QA. We present a method that allows the quantitative determination of gamma criteria sensitivity to induced errors which can be applied to any unique combination of device, delivery technique, and software utilized in a specific clinic.

METHODS

A total of 21 DMLC IMRT QA measurements (ArcCHECK®, Sun Nuclear) were compared to QA plan calculations with induced errors. Three scenarios were studied: MU errors, multi-leaf collimator (MLC) errors, and the sensitivity of the gamma comparison to changes in penumbra width. Gamma comparisons were performed between measurements and error-induced calculations using a wide range of gamma criteria, resulting in a total of over 20 000 gamma comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using 36 different gamma criteria.

RESULTS

This study demonstrates that systematic errors and case-specific errors can be detected by the error curve analysis. Depending on the location of the error curve peak (e.g., not centered about zero), 3%/3 mm threshold = 10% at 90% pixels passing may miss errors as large as 15% MU errors and ±1 cm random MLC errors for some cases. As the dose threshold parameter was increased for a given %Diff/distance-to-agreement (DTA) setting, error sensitivity was increased by up to a factor of two for select cases. This increased sensitivity with increasing dose threshold was consistent across all studied combinations of %Diff/DTA. Criteria such as 2%/3 mm and 3%/2 mm with a 50% threshold at 90% pixels passing are shown to be more appropriately sensitive without being overly strict. However, a broadening of the penumbra by as much as 5 mm in the beam configuration was difficult to detect with commonly used criteria, as well as with the previously mentioned criteria utilizing a threshold of 50%.

CONCLUSIONS

We have introduced the error curve method, an analysis technique which allows the quantitative determination of gamma criteria sensitivity to induced errors. The application of the error curve method using DMLC IMRT plans measured on the ArcCHECK® device demonstrated that large errors can potentially be missed in IMRT QA with commonly used gamma criteria (e.g., 3%/3 mm, threshold = 10%, 90% pixels passing). Additionally, increasing the dose threshold value can offer dramatic increases in error sensitivity. This approach may allow the selection of more meaningful gamma criteria for IMRT QA and is straightforward to apply to other combinations of devices and treatment techniques.