Quantified difference of the collapsed cone convolution (CCC) and Monte Carlo (MC) algorithms based on DVH and gamma analysis for cervical cancer radiation therapy

OBJECTIVE

To quantify the difference between the (collapsed cone convolution) CCC algorithm and the (Monte Carlo) MC algorithm and remind that the planners should pay attention to some possible uncertainties of the two algorithms when employing the two algorithms.

METHODS

Thirty patients' cervical cancer VMAT plans were designed with a Pinnacle TPS (Philips) and divided equally into two groups: the simple group (SG, target volume was only the PTV) and the complex group (CG, target volume included the PTV and PGTV). The plans from the Pinnacle TPS were transferred to the Monaco TPS (Elekta). The plans' parameters all remained unchanged, and the dose was recalculated. Gamma passing rates (GPRs) obtained from dose distribution from Pinnacle TPS compared with that from Monaco TPS with SNC software based on three triaxial planes (transverse, sagittal and coronal). GPRs and DVH were used to quantify the difference between the CCC algorithm in pinnacle TPS and the MC algorithm in Monaco TPS.

RESULTS

Among the statistical dose indexes in DVHs from the Pinnacle and Monaco TPSs, there were 7(7/15) dose indexes difference with statistically significant differences in the SG, and 10(10/18) dose indexes difference with statistically significant differences in the CG. With 3%/3 mm criterion, the most (5/6) GPRs were greater than 95% from the SG and CG. But with 2%/2 mm criterion, the most (5/6) GPRs were less than 90% from the two groups. In addition, we found that GPRs were also related to the selected triaxial planes and the complexity of the plan (GPRs varied with the SG and CG).

CONCLUSIONS

Obvious difference between the CCC and MC algorithms from Pinnacle and Monaco TPS. DVH maybe better than 2D gamma analysis on quantifying difference of the CCC and MC algorithms. Some attention should be paid to the uncertainty of the TPS algorithm, especially when the indicator on the DVH is at the critical point of the threshold value, because the algorithm used may overestimate or underestimate the DVH indicator.

Commissioning and clinical evaluation of a novel high-resolution quality assurance digital detector array for SRS and SBRT

PURPOSE

We aimed to perform the commissioning and clinical evaluation of myQA SRS detector array for patient-specific quality assurance (PSQA) of stereotactic radiosurgery (SRS)/ stereotactic body radiotherapy (SBRT) plans.

METHODS

To perform the commissioning of myQA SRS, its dose linearity, dose-rate dependence, angular dependence, and field-size dependence were investigated. Ten SBRT plans were selected for clinical evaluation: 1) Common clinical deviations based on the original SBRT plan (Plan0), including multileaf collimator (MLC) positioning deviation and treatment positioning deviation were introduced. 2) Compared the performance of the myQA SRS and a high-resolution EPID dosimetry system in PSQA measurement for the SBRT plans. Evaluation parameters include gamma passing rate (GPR) and distance-to-agreement (DTA) pass rate (DPR).

RESULTS

The dose linearity, angle dependence, and field-size dependence of myQA SRS system exhibit excellent performance. The myQA SRS is highly sensitive in the detection of MLC deviations. The GPR of (3%/1 mm) decreases from 90.4% of the original plan to 72.7%/62.9% with an MLC outward/inward deviation of 3 mm. Additionally, when the setup error deviates by 1 mm in the X, Y, and Z directions with the GPR of (3%/1 mm) decreasing by an average of -20.9%, -25.7%, and -24.7%, respectively, and DPR (1 mm) decreasing by an average of -33.7%, -32.9%, and -29.8%. Additionally, the myQA SRS has a slightly higher GPR than EPID for PSQA, However, the difference is not statistically significant with the GPR of (3%/1 mm) of (average 90.4%% vs. 90.1%, p = 0.414).

CONCLUSION

Dosimetry characteristics of the myQA SRS device meets the accuracy and sensitivity requirement of PSQA for SRS/SBRT treatment. The dose rate dependence should be adequately calibrated before its application and a more stringent GPR (3%/1 mm) evaluation criterion is suggested when it is used for SRS/SBRT QA.

Assessing quality assurance of multi-leaf collimator using the structural similarity index

PURPOSE

This study aims to evaluate the viability of utilizing the Structural Similarity Index (SSI*) as an innovative imaging metric for quality assurance (QA) of the multi-leaf collimator (MLC). Additionally, we compared the results obtained through SSI* with those derived from a conventional Gamma index test for three types of Varian machines (Trilogy, Truebeam, and Edge) over a 12-week period of MLC QA in our clinic.

METHOD

To assess sensitivity to MLC positioning errors, we designed a 1 cm slit on the reference MLC, subsequently shifted by 0.5-5 mm on the target MLC. For evaluating sensitivity to output error, we irradiated five 25 cm × 25 cm open fields on the portal image with varying Monitor Units (MUs) of 96-100. We compared SSI* and Gamma index tests using three linear accelerator (LINAC) machines: Varian Trilogy, Truebeam, and Edge, with MLC leaf widths of 1, 0.5, and 0.25 mm. Weekly QA included VMAT and static field modes, with Picket fence test images acquired. Mechanical uncertainties related to the LINAC head, electronic portal imaging device (EPID), and MLC during gantry rotation and leaf motion were monitored.

RESULTS

The Gamma index test started detecting the MLC shift at a threshold of 4 mm, whereas the SSI* metric showed sensitivity to shifts as small as 2 mm. Moreover, the Gamma index test identified dose changes at 95MUs, indicating a 5% dose difference based on the distance to agreement (DTA)/dose difference (DD) criteria of 1 mm/3%. In contrast, the SSI* metric alerted to dose differences starting from 97MUs, corresponding to a 3% dose difference. The Gamma index test passed all measurements conducted on each machine. However, the SSI* metric rejected all measurements from the Edge and Trilogy machines and two from the Truebeam.

CONCLUSIONS

Our findings demonstrate that the SSI* exhibits greater sensitivity than the Gamma index test in detecting MLC positioning errors and dose changes between static and VMAT modes. The SSI* metric outperformed the Gamma index test regarding sensitivity across these parameters.

A TPS integrated machine learning tool for predicting patient-specific quality assurance outcomes in volumetric-modulated arc therapy

PURPOSE

Machine learning (ML) models have been demonstrated to be beneficial for optimizing the workload of patient-specific quality assurance (PSQA). Implementing them in clinical routine frequently requires third-party applications beyond the treatment planning system (TPS), slowing down the workflow. To address this issue, a PSQA outcomes predictive model was carefully selected and validated before being fully integrated into the TPS.

MATERIALS AND METHODS

Nine ML algorithms were evaluated using cross-validation. The learning database was built by calculating complexity metrics (CM) and binarizing PSQA results into "pass"/"fail" classes for 1767 VMAT arcs. The predictive performance was evaluated using area under the ROC curve (AUROC), sensitivity, and specificity. The ML model was integrated into the TPS via a C# script. Script-guided reoptimization impact on PSQA and dosimetric results was evaluated on ten VMAT plans with "fail"-predicted arcs. Workload reduction potential was also assessed.

RESULTS

The selected model exhibited an AUROC of 0.88, with a sensitivity and specificity exceeding 50 % and 90 %, respectively. The script-guided reoptimization of the ten evaluated plans led to an average improvement of 1.4 ± 0.9 percentage points in PSQA results, while preserving the quality of the dose distribution. A yearly savings of about 140 h with the use of the script was estimated.

CONCLUSIONS

The proposed script is a valuable complementary tool for PSQA measurement. It was efficiently integrated into the clinical workflow to enhance PSQA outcomes and reduce PSQA workload by decreasing the risk of failing QA and thereby, the need for repeated replanning and measurements.

Delta4-based Dosimetric Error Detection in Volumetric-modulated Arc Therapy: Clinical Significance and Implications

Background

Volumetric-modulated arc therapy (VMAT) is an efficient method of administering intensity-modulated radiotherapy beams. The Delta4 device was employed to examine patient data.

Aims and Objectives

The utility of the Delta4 device in identifying errors for patient-specific quality assurance of VMAT plans was studied in this research.

Materials and Methods

Intentional errors were purposely created in the collimator rotation, gantry rotation, multileaf collimator (MLC) position displacement, and increase in the number of monitor units (MU).

Results

The results show that when the characteristics of the treatment plans were changed, the gamma passing rate (GPR) decreased. The largest percentage of erroneous detection was seen in the increasing number of MU, with a GPR ranging from 41 to 92. Gamma analysis was used to compare the dose distributions of the original and intentional error designs using the 2%/2 mm criteria. The percentage of dose errors (DEs) in the dose-volume histogram (DVH) was also analyzed, and the statistical association was assessed using logistic regression. A modest association (Pearson's R-values: 0.12-0.67) was seen between the DE and GPR in all intentional plans. The findings indicated a moderate association between DVH and GPR. The data reveal that Delta4 is effective in detecting mistakes in treatment regimens for head-and-neck cancer as well as lung cancer.

Conclusion

The study results also imply that Delta4 can detect errors in VMAT plans, depending on the details of the defects and the treatment plans employed.

Patient specific quality assurance in SBRT: a systematic review of measurement-based methods

This topical review focuses on Patient-Specific Quality Assurance (PSQA) approaches to stereotactic body radiation therapy (SBRT). SBRT requires stricter accuracy than standard radiation therapy due to the high dose per fraction and the limited number of fractions. The review considered various PSQA methods reported in 36 articles between 01/2010 and 07/2022 for SBRT treatment. In particular comparison among devices and devices designed for SBRT, sensitivity and resolution, verification methodology, gamma analysis were specifically considered. The review identified a list of essential data needed to reproduce the results in other clinics, highlighted the partial miss of data reported in scientific papers, and formulated recommendations for successful implementation of a PSQA protocol.

Extracting the gradient component of the gamma index using the Lie derivative method

Objective. The gamma index (γ) has been extensively investigated in the medical physics and applied in clinical practice. However,γhas a significant limitation when used to evaluate the dose-gradient region, leading to inconveniences, particularly in stereotactic radiotherapy (SRT). This study proposes a novel evaluation method combined withγto extract clinically problematic dose-gradient regions caused by irradiation including certain errors.Approach. A flow-vector field in the dose distribution is obtained when the dose is considered a scalar potential. Using the Lie derivative from differential geometry, we definedL,S, andUto evaluate the intensity, vorticity, and flow amount of deviation between two dose distributions, respectively. These metrics multiplied byγ(γL,γS,γU), along with the threshold valueσ, were verified in the ideal SRT case and in a clinical case of irradiation near the brainstem region using radiochromic films. Moreover, Moran's gradient index (MGI), Bakai's χ factor, and the structural similarity index (SSIM) were investigated for comparisons.Main results. A highL-metric value mainly extracted high-dose-gradient induced deviations, which was supported by highSandUmetrics observed as a robust deviation and an influence of the dose-gradient, respectively. TheS-metric also denotes the measured similarity between the compared dose distributions. In theγdistribution,γLsensitively detected the dose-gradient region in the film measurement, despite the presence of noise. The thresholdσsuccessfully extracted the gradient-error region whereγ> 1 analysis underestimated, andσ= 0.1 (plan) andσ= 0.001 (film measurement) were obtained according to the compared resolutions. However, the MGI, χ, and SSIM failed to detect the clinically interested region.Significance. Although further studies are required to clarify the error details, this study demonstrated that the Lie derivative method provided a novel perspective for the identifying gradient-induced error regions and enabled enhanced and clinically significant evaluations ofγ.

Exploring contrast generalisation in deep learning-based brain MRI-to-CT synthesis

BACKGROUND

Synthetic computed tomography (sCT) has been proposed and increasingly clinically adopted to enable magnetic resonance imaging (MRI)-based radiotherapy. Deep learning (DL) has recently demonstrated the ability to generate accurate sCT from fixed MRI acquisitions. However, MRI protocols may change over time or differ between centres resulting in low-quality sCT due to poor model generalisation.

PURPOSE

investigating domain randomisation (DR) to increase the generalisation of a DL model for brain sCT generation.

METHODS

CT and corresponding T1-weighted MRI with/without contrast, T2-weighted, and FLAIR MRI from 95 patients undergoing RT were collected, considering FLAIR the unseen sequence where to investigate generalisation. A "Baseline" generative adversarial network was trained with/without the FLAIR sequence to test how a model performs without DR. Image similarity and accuracy of sCT-based dose plans were assessed against CT to select the best-performing DR approach against the Baseline.

RESULTS

The Baseline model had the poorest performance on FLAIR, with mean absolute error (MAE) = 106 ± 20.7 HU (mean ±σ). Performance on FLAIR significantly improved for the DR model with MAE = 99.0 ± 14.9 HU, but still inferior to the performance of the Baseline+FLAIR model (MAE = 72.6 ± 10.1 HU). Similarly, an improvement in γ-pass rate was obtained for DR vs Baseline.

CONCLUSION

DR improved image similarity and dose accuracy on the unseen sequence compared to training only on acquired MRI. DR makes the model more robust, reducing the need for re-training when applying a model on sequences unseen and unavailable for retraining.

Impact of log file source and data frequency on accuracy of log file-based patient specific quality assurance

Performing phantom measurements for patient-specific quality assurance (PSQA) adds a significant amount of time to the adaptive radiotherapy procedure. Log file based PSQA can be used to increase the efficiency of this process. This study compared the dosimetric accuracy of high-frequency linear accelerator (Linac) log files and low-frequency log data stored in the oncology information system (OIS). Thirty patients were included, that were recently treated in the head and neck (HN), brain, and prostate region with volumetric modulated arc therapy (VMAT) and an additional ten patients treated using stereotactic body radiation therapy (SBRT) with 3D-conformal radiotherapy (3D-CRT) technique. Log data containing a single fraction were used to calculate the dose distributions. The dosimetric differences between Linac log files and OIS logs were evaluated with a gamma analysis with 2%/2 mm criterion and dose threshold of 30%. The original treatment plan was used as a reference. Moreover, DVH parameters of D_98%, D_50%, and D_2% of the planning-target volume (PTV) and dose to several organs at risk (OARs) were reported. Significant differences in dose distributions between the two log types and the original dose were observed for PTV D_98% and D_2% (r < 0.001) for HN cases, PTV D_98% (r = 0.005) for brain cases, and PTV D_50% (r = 0.015) for prostate cases. No significant differences were found between the two log types with respect to D_50%. The root mean square (RMS) error of the leaf positions of the OIS log was approximately twice the RMS error of the Linac log file for VMAT plans, but identical for 3D-CRT plans. The relationship between the gamma pass rate and the RMS error showed a moderate correlation for the Linac log files (r = -0.58, p < 0.001) and strong correlation for OIS logs (r = -0.71, p < 0.001). Furthermore, all doses calculated using Linac log files and OIS log data had a GPR >90% for an RMS error < 3.3 mm. Based on these findings, a tolerance limit of RMS error of 3.3 mm for considering OIS log based PSQA was established. Nevertheless, the OIS log data quality should be improved to achieve adequate PSQA.

Electronic Portal Imaging Device in Pre-Treatment Patient-Specific Quality Assurance of volumetric-modulated arc therapy delivery

Background:

Radiotherapy treatment delivery is evaluated by a pre-treatment patient-specific quality assurance (PSQA) procedure to ensure the patient receives an accurate radiation dose. The current PSQA practice by using conventional phantoms requires more set-up time and cost of purchasing the tools. Therefore, this study aimed to investigate the efficiency of an electronic portal imaging device (EPID) of linear accelerator (LINAC) as a PSQA tool for volumetric-modulated arc therapy (VMAT) planning technique for nasopharyngeal carcinoma (NPC) treatment delivery.

Methods:

A NPC VMAT plan on a Rando phantom was performed by following the Radiation Therapy Oncology Group (RTOG) 0615 protocol. The gamma passing rate of the EPID and PSQA phantom (ArcCHECK) were compared among the gamma criteria of 3%/3 mm, 2%/2 mm and 1%/1 mm, respectively.

Results:

Both EPID and ArcCHECK phantom had distinguishable gamma passing rates in 3%/3 mm and 2%/2 mm with a difference of 0·87% and 0·30%, respectively. Meanwhile, the EPID system had a lower gamma passing rate than the ArcCHECK phantom in 1%/1 mm (21·23% difference). Furthermore, the sensitivity of the EPID system was evaluated and had the largest deviation in gamma passing rate from the reference position in gamma criteria of 2%/2 mm (41·14%) compared to the 3%/3 mm (25·45%) and 1%/1 mm (31·78%), discretely. The best fit line of the linear regression model for EPID was steeper than the ArcCHECK phantom in 3%/3 mm and 2%/2 mm, and vice versa in gamma criteria of 1%/1 mm. This indicates that the EPID had a higher sensitivity than the ArcCHECK phantom in 3%/3 mm and 2%/2 mm but less sensitivity in 1%/1 mm.

Conclusions:

The EPID system was efficient in performing the PSQA test of VMAT treatment in HUSM with the gamma criteria of 3%/3 mm and 2%/2 mm.

Evaluation of dosimetric effects of metallic artifact reduction and tissue assignment on Monte Carlo dose calculations for 125 I prostate implants

PURPOSE

Monte Carlo (MC) simulation studies, aimed at evaluating the magnitude of tissue heterogeneity in ¹²⁵ I prostate permanent seed implant brachytherapy (BT), customarily use clinical post-implant CT images to generate a virtual representation of a realistic patient model (virtual patient model). Metallic artifact reduction (MAR) techniques and tissue assignment schemes (TAS) are implemented on the post-implant CT images to mollify metallic artifacts due to BT seeds and to assign tissue types to the voxels corresponding to the bright seed spots and streaking artifacts, respectively. The objective of this study is to assess the combined influence of MAR and TAS on MC absorbed dose calculations in post-implant CT-based phantoms. The virtual patient models used for ¹²⁵ I prostate implant MC absorbed dose calculations in this study are derived from the CT images of an external radiotherapy prostate patient without BT seeds and prostatic calcifications, thus averting the need to implement MAR and TAS.

METHODS

The geometry of the IsoSeed I25.S17plus source is validated by comparing the MC calculated results of the TG-43 parameters for the line source approximation with the TG-43U1S2 consensus data. Four MC absorbed dose calculations are performed in two virtual patient models using the egs_brachy MC code: (1) TG-43-based D_{w,w-TG 43} , (2) D_w,w-MBDC that accounts for interseed scattering and attenuation (ISA), (3) D_m,m that examines ISA and tissue heterogeneity by scoring absorbed dose in tissue, and (4) D_w,m that unlike D_m,m scores absorbed dose in water. The MC absorbed doses (1) and (2) are simulated in a TG-43 patient phantom derived by assigning the densities of every voxel to 1.00 g cm^-3 (water), whereas MC absorbed doses (3) and (4) are scored in the TG-186 patient phantom generated by mapping the mass density of each voxel to tissue according to a CT calibration curve. The MC absorbed doses calculated in this study are compared with VariSeed v8.0 calculated absorbed doses. To evaluate the dosimetric effect of MAR and TAS, the MC absorbed doses of this work (independent of MAR and TAS) are compared to the MC absorbed doses of different ¹²⁵ I source models from previous studies that were calculated with different MC codes using post-implant CT-based phantoms generated by implementing MAR and TAS on post-implant CT images.

RESULTS

The very good agreement of TG-43 parameters of this study and the published consensus data within 3% validates the geometry of the IsoSeed I25.S17plus source. For the clinical studies, the TG-43-based calculations show a D₉₀ overestimation of more than 4% compared to the more realistic MC methods due to ISA and tissue composition. The results of this work generally show few discrepancies with the post-implant CT-based dosimetry studies with respect to the D₉₀ absorbed dose metric parameter. These discrepancies are mainly Type B uncertainties due to the different ¹²⁵ I source models and MC codes.

CONCLUSIONS

The implementation of MAR and TAS on post-implant CT images have no dosimetric effect on the ¹²⁵ I prostate MC absorbed dose calculation in post-implant CT-based phantoms.

Prediction of VMAT delivery accuracy using plan modulation complexity score and log-files analysis

The purpose of this study was to develop a predictive model based on plan complexity metrics and linac log-files analysis to classify the dosimetric accuracy of VMAT plans. A total of 612 VMAT plans, corresponding to 1224 arcs, were analyzed. All VMAT arcs underwent pre-treatment verification that was performed by means of the dynamic log-files generated by the linac. The comparison of predicted (by TPS) and measured (by log-files) integral fluences was performed using γ-analysis in terms of the percentage of points with γ-value smaller than one (γ%) and using a stringent 2%(local)/2mm criteria. This γ-analysis was performed by a commercial software LinacWatch. The action limits (AL) were derived from the mean values, standard deviations and the confidence limit (CL) of the γ% distribution. A plan complexity metric, the modulation complexity score (MCS), based on the aperture beam area variability and leaf sequence variability was used as input variable of the model. A binary logistic regression (LR) model was developed to classify QA results as "pass" (γ%≥AL) or "fail" (γ%<AL). Receiver operator characteristics (ROC) curves were used to determine the optimal MCS threshold to flag "failed" plans that need to be re-optimized. The model reliability was evaluated stratifying the plans in training, validation and testing groups. The confidence and action limits for γ% were found 20.1% and 79.9%, respectively. The accuracy of the model for the training and testing dataset was 97.4% and 98.0%, respectively. The optimal MCS threshold value for the identification of failed plans was 0.142, providing a true positive rate able to flag the plans failing QA of 91%. In clinical routine, the use of this MCS threshold may allow the prompt identification of overly modulated plans, then reducing the number of QA failures and improving the quality of VMAT plans used for treatment.

Evaluating suggested stricter gamma criteria for linac-based patient-specific delivery QA in the conventional and SBRT environments

PURPOSE

To evaluate AAPM TG-218 recommended tolerances for IMRT QA for conventional and SBRT delivery.

METHODS

QA analysis was repeated for 150 IMRT/VMAT patients with varying gamma criteria. True composite delivery was utilized, corrected for detector and output variation. Universal tolerance (TL_univ) and action limits (AL_univ) were compared with statistical process control (SPC) TL_SPC and AL_SPC values. Analysis was repeated as a function of plan complexity for 250 non-stereotactic body radiotherapy (SBRT) VMAT patients at 3%/2mm and a threshold of 10% and for 75 SBRT VMAT patients at 2%/2 mm and a threshold of 50% with results plotted as a function of PTV volume. Regions of failure were dose-scaled on the planning CT data sets based on delivery results.

RESULTS

The IMRT/VMAT TL_SPC and AL_SPC for gamma criteria of 3%/3 mm were 96.5% and 95.6% and for 3%/2 mm were 91.2% and 89.2%, respectively. Correlation with plan complexity for conventional fractionation VMAT was "low" for all sites with pelvis having the highest r value at -0.35. The equivalent SBRT PTV diameter ranged from 2.0 cm to 5.6 cm. Negative low correlation was found for 38 of 75 VMAT cases below AL_univ.

CONCLUSIONS

The AL_univ and AL_SPC are similar for 3%/2 mm. However, our 5% failure rate for AL_univ, may result in treatment start delays approximately 2 times/month, given 40 new cases/month. VMAT QA failure at stricter criteria did not correlate strongly with plan complexity. Site-specific action limits vary less than 3% from the average. SBRT QA results do not strongly correlate with target size over the range studied.

Isodoses-a set theory-based patient-specific QA measure to compare planned and delivered isodose distributions in photon radiotherapy

BACKGROUND

The gamma index and dose-volume histogram (DVH)-based patient-specific quality assurance (QA) measures commonly applied in radiotherapy planning are unable to simultaneously deliver detailed locations and magnitudes of discrepancy between isodoses of planned and delivered dose distributions. By exploiting statistical classification performance measures such as sensitivity or specificity, compliance between a planned and delivered isodose may be evaluated locally, both for organs-at-risk (OAR) and the planning target volume (PTV), at any specified isodose level. Thus, a patient-specific QA tool may be developed to supplement those presently available in clinical radiotherapy.

MATERIALS AND METHODS

A method was developed to locally establish and report dose delivery errors in three-dimensional (3D) isodoses of planned (reference) and delivered (evaluated) dose distributions simultaneously as a function the dose level and of spatial location. At any given isodose level, the total volume of delivered dose containing the reference and the evaluated isodoses is locally decomposed into four subregions: true positive-subregions within both reference and evaluated isodoses, true negative-outside of both of these isodoses, false positive-inside the evaluated isodose but not the reference isodose, and false negatives-inside the reference isodose but not the evaluated isodose. Such subregions may be established over the whole volume of delivered dose. This decomposition allows the construction of a confusion matrix and calculation of various indices to quantify the discrepancies between the selected planned and delivered isodose distributions, over the complete range of values of dose delivered. The 3D projection and visualization of the spatial distribution of these discrepancies facilitates the application of the developed method in clinical practice.

RESULTS

Several clinical photon radiotherapy plans were analyzed using the developed method. In some plans at certain isodose levels, dose delivery errors were found at anatomically significant locations. These errors were not otherwise highlighted-neither by gamma analysis nor by DVH-based QA measures. A specially developed 3D projection tool to visualize the spatial distribution of such errors against anatomical features of the patient aids in the proposed analysis of therapy plans.

CONCLUSIONS

The proposed method is able to spatially locate delivery errors at selected isodose levels and may supplement the presently applied gamma analysis and DVH-based QA measures in patient-specific radiotherapy planning.

Optimizing the Region for Evaluation of Global Gamma Analysis for Nasopharyngeal Cancer (NPC) Pretreatment IMRT QA by COMPASS: A Retrospective Study

Background

The global gamma passing rate is the most commonly used metric for patient-specific pretreatment quality assurance in radiation therapy. However, the optimal region for evaluation and specific action limits (ALs) need to be explored. Therefore, this study was carried out to explore the optimal region for evaluation of the global gamma passing rate and define ALs by using the COMPASS software.

Methods

A total of 93 intensity-modulated radiation therapy (IMRT) plans for nasopharyngeal cancer (NPC) patients, including 61 original plans and 32 multileaf collimator (MLC) error-introduced test plans, were selected for retrospective analysis. Firstly, the dose distribution was divided into six isodose regions (“≥10%”, “≥20%”, “≥30%”, “≥40%”, “≥50%”, and “≥60%”) based on the prescribed dose and one clinically oriented region for evaluation (“whole”) to perform the three-dimensional (3D) global gamma reanalysis. Meanwhile, the percentage gamma passing rate (%GP), mean gamma index (μGI) based on 3%/2 mm criteria, and percentage dose error (%DE) of the dose–volume histogram (DVH) metrics were recorded by COMPASS application. Secondly, the Pearson’s correlation coefficient was used to analyze the correlation between %GP and %DE and between μGI and %DE in different regions. Additionally, receiver operating characteristic (ROC) methodology was applied to quantify the fraction of patient-specific plans evaluated as “fail” and “pass”. In order to improve the correlation between gamma analysis result and clinical criteria, ROC analysis was carried out in accordance with hybridization analysis criteria (%DE ≤3%, %GP ≥90% and %DE ≤3%, μGI ≤0.6). ROC was performed for two purposes: 1) to analyze the sensitivity and specificity of %GP and μGI in different regions for evaluation and 2) to define the ALs of %GP and μGI in the optimal region for evaluation. Finally, the plans introduced with MLC errors were prepared for validation. Moreover, we also compared the positive rate of ALs of both %GP and μGI in detecting MLC error-introduced plans in different regions.

Results

1) In our study, a number of DVH-based metrics were found to be correlated with the evaluation parameters. The corresponding number was 4, 2, 1, 1, 1, 1, and 3 in γ_whole, γ_10%, γ_20%, γ_30%, γ_40%, γ_50%, and γ_60%, respectively, and 5, 3, 0, 1, 1, 4, and 2 in μGI_whole, μGI_10%, μGI_20%, μGI_30%, μGI_40%, μGI_50%, and μGI_60%, respectively. The results by COMPASS have revealed that the %DE of specific structures has a slightly higher correlation with both %GP and μGI of the “whole” region compared with that of any other region. However, it is a moderate correlation (0.5 ≤ |r| < 0.8). 2) The areas under the curves (AUCs) of γ_whole, μGI_whole, μGI_40%, μGI_50%, and μGI_60% were >0.7 based on 3%/2 mm criteria. According to the Youden coefficient, we defined the ALs of γ_whole ≥92%, μGI_{whole ≤}0.36, μGI_40% ≤0.43, and μGI_60% ≤0.40 based on 3%/2 mm criteria. 3) In the validation, for original plans, the accuracy of AL_γwhole, AL_γ10%, AL_μGIwhole, AL_μGI40%, AL_μGI50%, and AL_μGI60% was 23%, 9.8%, 90%, 80.3%, 9.8%, and 88.5%, respectively. For test plans with systematic MLC errors smaller than 0.8 mm, the positive rates of AL_γwhole, AL_γ10%, AL_μGIwhole, AL_μGI40%, AL_μGI50%, and AL_μGI60% were 25%, 58%, 92%, 92%, 42%, and 100%, respectively. For the plans with systematic MLC errors higher than 0.8 mm, the positive rates of all AL_%GP and AL_μGI were 100%. From the COMPASS validation results, the accuracy of γ_whole, μGI_whole, μGI_40%, and μGI_60% was higher than that of the conventional γ_10% and commonly used μGI_50%.

Conclusions

Compared with the traditional evaluation region (i.e., the criteria with a threshold of 10% or a threshold of 50%, it was the same with the isodose regions of “≥10%”, “≥50%” based on the prescribed dose in our study), the “whole” region is more meaningful to the clinic by COMPASS. The accuracy of μGI_whole is higher than that of the conventional γ_10% and the commonly used μGI_50%.

Assessment of Statistical Process Control Based DVH Action Levels for Systematic Multi-Leaf Collimator Errors in Cervical Cancer RapidArc Plans

Background

In the patient-specific quality assurance (QA), DVH is a critical clinically relevant parameter that is finally used to determine the safety and effectiveness of radiotherapy. However, a consensus on DVH-based action levels has not been reached yet. The aim of this study is to explore reasonable DVH-based action levels and optimal DVH metrics in detecting systematic MLC errors for cervical cancer RapidArc plans.

Methods

In this study, a total of 148 cervical cancer RapidArc plans were selected and measured with COMPASS 3D dosimetry system. Firstly, the patient-specific QA results of 110 RapidArc plans were retrospectively reviewed. Then, DVH-based action limits (AL) and tolerance limits (TL) were obtained by statistical process control. Secondly, systematic MLC errors were introduced in 20 RapidArc plans, generating 380 modified plans. Then, the dose difference (%DE) in DVH metrics between modified plans and original plans was extracted from measurement results. After that, the linear regression model was used to investigate the detection limits of DVH-based action levels between %DE and systematic MLC errors. Finally, a total of 180 test plans (including 162 error-introduced plans and 18 original plans) were prepared for validation. The error detection rate of DVH-based action levels was compared in different DVH metrics of 180 test plans.

Results

A linear correlation was found between systematic MLC errors and %DE in all DVH metrics. Based on linear regression model, the systematic MLC errors between -0.94 mm and 0.88 mm could be caught by the TL of PTV₉₅ ([-1.54%, 1.51%]), and the systematic MLC errors between -1.00 mm and 0.80 mm could also be caught by the TL of PTV_mean ([-2.06%, 0.38%]). In the validation, for original plans, PTV₉₅ showed the minimum error detection rate of 5.56%. For error-introduced plans with systematic MLC errors more than 1mm, PTV_mean showed the maximum error detection rate of 88.89%, and then was followed by PTV₉₅ (86.67%). All the TL of DVH metrics showed a poor error detection rate in identifying error-induced plans with systematic MLC errors less than 1mm.

Conclusion

In 3D quality assurance of cervical cancer RapidArc plans, process-based tolerance limits showed greater advantages in distinguishing plans introduced with systematic MLC errors more than 1mm, and reasonable DVH-based action levels can be acquired through statistical process control. During DVH-based verification, main focus should be on the DVH metrics of target volume. OARs in low-dose regions were found to have a relatively higher dose sensitivity to smaller systematic MLC errors, but may be accompanied with higher false error detection rate.

Correlation Between Average Segment Width and Gamma Passing Rate as a Function of MLC Position Error in Volumetric Modulated Arc Therapy

Objective:

This study analyzed the correlation between the average segment width (ASW) and gamma passing rate according to the multi-leaf collimator (MLC) position error.

Method:

To evaluate the changes in the gamma passing rate according to the MLC position error, 21 volumetric modulated arc therapy (VMAT) plans were generated using pelvic lymph node metastatic prostate cancer patient's data which is sensitive to MLC position errors as they involve several long, narrow, irregular fields. The ASW for each VMAT plan was calculated using our own code developed using Visual Basic for Applications (VBA). The gamma passing rate of the VMAT plan according to the MLC position error was evaluated using ArcCHECK (Sun Nuclear, Melbourne, FL, USA) while inducing symmetric MLC position errors in 0.25 mm intervals from −1 mm to +1 mm in the infinity medical linear accelerator (Elekta AB, Stockholm, Sweden). Finally, we examined the correlation between the change in the passing rate (γgradient) due to the MLC position error and the ASW in VMAT through linear regression analysis using the least squares method.

Results:

The ASW and γgradient were found to have a linear correlation according to the MLC position error, and the coefficient of determination was 0.88. For a 1 mm position error of MLC in VMAT, the gamma passing rate improved by approximately 11.9% as the ASW increased by 10 mm.

Conclusion:

These results are expected to be employed as guidelines to minimize the dose uncertainty due to MLC position error in VMAT.

Evaluation of the ability of three commercially available dosimeters to detect systematic delivery errors in step-and-shoot IMRT plans

Background

There is limited data on error detectability for step-and-shoot intensity modulated radiotherapy (sIMRT) plans, despite significant work on dynamic methods. However, sIMRT treatments have an ongoing role in clinical practice. This study aimed to evaluate variations in the sensitivity of three patient-specific quality assurance (QA) devices to systematic delivery errors in sIMRT plans.

Materials and methods

Four clinical sIMRT plans (prostate and head and neck) were edited to introduce errors in: Multi-Leaf Collimator (MLC) position (increasing field size, leaf pairs offset (1-3 mm) in opposite directions; and field shift, all leaves offset (1-3 mm) in one direction); collimator rotation (1-3 degrees) and gantry rotation (0.5-2 degrees). The total dose for each plan was measured using an ArcCHECK diode array. Each field, excluding those with gantry offsets, was also measured using an Electronic Portal Imager and a MatriXX Evolution 2D ionisation chamber array. 132 plans (858 fields) were delivered, producing 572 measured dose distributions. Measured doses were compared to calculated doses for the no-error plan using Gamma analysis with 3%/3 mm, 3%/2 mm, and 2%/2 mm criteria (1716 analyses).

Results

Generally, pass rates decreased with increasing errors and/or stricter gamma criteria. Pass rate variations with detector and plan type were also observed. For a 3%/3 mm gamma criteria, none of the devices could reliably detect 1 mm MLC position errors or 1 degree collimator rotation errors.

Conclusions

This work has highlighted the need to adapt QA based on treatment plan type and the need for detector specific assessment criteria to detect clinically significant errors.

Retrospective analysis of portal dosimetry pre-treatment quality assurance of intracranial SRS/SRT VMAT treatment plans

Background:

The complexity associated with the treatment planning and delivery of stereotactic radiosurgery (SRS) or stereotactic radiotherapy (SRT) volumetric modulated arc therapy (VMAT) plans which employs continuous dynamic modulation of dose rate, field aperture and gantry speed necessitates diligent pre-treatment patient-specific quality assurance (QA). Numerous techniques for pre-treatment VMAT treatment plans QA are currently available with the aid of several different devices including the electronic portal imager (EPID). Although several studies have provided recommendations for gamma criteria for VMAT pre-treatment QA, there are no specifics for SRS/SRT VMAT QA. Thus, we conducted a study to evaluate intracranial SRS/SRT VMAT QA to determine clinical action levels for gamma criteria based on the institutional estimated means and standard deviations.

Materials and methods:

We conducted a retrospective analysis of 118 EPID patient-specific pre-treatment QA dosimetric measurements of 47 brain SRS/SRT VMAT treatment plans using the integrated Varian solution (RapidArcTM planning, EPID and Portal dosimetry system) for planning, delivery and EPID QA analysis. We evaluated the maximum gamma (γmax), average gamma (γave) and percentage gamma passing rate (%GP) for different distance-to-agreement/dose difference (DTA/DD) criteria and low-dose thresholds.

Results:

The gamma index analysis shows that for patient-specific SRS/SRT VMAT QA with the portal dosimetry, the mean %GP is ≥98% for 2–3 mm/1–3% and Field+0%, +5% and +10% low-dose thresholds. When applying stricter spatial criteria of 1 mm, the mean %GP is >90% for DD of 2–3% and ≥88% for DD of 1%. The mean γmax ranges: 1·32 ± 1·33–2·63 ± 2·35 for 3 mm/1–3%, 1·57 ± 1·36–2·87 ± 2·29 for 2 mm/1–3% and 2·36 ± 1·83–3·58 ± 2·23 for 1 mm/1–3%. Similarly the mean γave ranges: 0·16 ± 0·06–0·19 ± 0·07 for 3 mm/1–3%, 0·21 ± 0·08–0·27 ± 0·10 for 2 mm/1–3% and 0·34 ± 0·14–0·49 ± 0·17 for 1 mm/1–3%. The mean γmax and mean γave increase with increased DTA and increased DD for all low-dose thresholds.

Conclusions:

The establishment of gamma criteria local action levels for SRS/SRT VMAT pre-treatment QA based on institutional resources is imperative as a useful tool for standardising the evaluation of EPID-based patient-specific SRS/SRT VMAT QA. Our data suggest that for intracranial SRS/SRT VMAT QA measured with the EPID, a stricter gamma criterion of 1 mm/2% or 1 mm/3% with ≥90% %GP could be used while still maintaining an in-control QA process with no extra burden on resources and time constraints.

Virtual Patient-Specific Quality Assurance of IMRT Using UNet++: Classification, Gamma Passing Rates Prediction, and Dose Difference Prediction

The dose verification in radiotherapy quality assurance (QA) is time-consuming and places a heavy workload on medical physicists. To provide a clinical tool to perform patient specific QA accurately, the UNet++ is investigated to classify failed or pass fields (the GPR lower than 85% is considered “failed” while the GPR higher than 85% is considered “pass”), predict gamma passing rates (GPR) for different gamma criteria, and predict dose difference from virtual patient-specific quality assurance in radiotherapy. UNet++ was trained and validated with 473 fields and tested with 95 fields. All plans used Portal Dosimetry for dose verification pre-treatment. Planar dose distribution of each field was used as the input for UNet++, with QA classification results, gamma passing rates of different gamma criteria, and dose difference were used as the output. In the test set, the accuracy of the classification model was 95.79%. The mean absolute error (MAE) were 0.82, 0.88, 2.11, 2.52, and the root mean squared error (RMSE) were 1.38, 1.57, 3.33, 3.72 for 3%/3mm, 3%/2 mm, 2%/3 mm, 2%/2 mm, respectively. The trend and position of the predicted dose difference were consistent with the measured dose difference. In conclusion, the Virtual QA based on UNet++ can be used to classify the field passed or not, predict gamma pass rate for different gamma criteria, and predict dose difference. The results show that UNet++ based Virtual QA is promising in quality assurance for radiotherapy.

Evaluation of 4-Hz log files and secondary Monte Carlo dose calculation as patient-specific quality assurance for VMAT prostate plans

Purpose

In this study, 4‐Hz log files were evaluated with an independent secondary Monte Carlo dose calculation algorithm to reduce the workload for patient‐specific quality assurance (QA) in clinical routine.

Materials and Methods

A total of 30 randomly selected clinical prostate VMAT plans were included. The used treatment planning system (TPS) was Monaco (Elekta, Crawley), and the secondary dose calculation software was SciMoCa (Scientific‐RT, Munich). Monaco and SciMoCa work with a Monte Carlo algorithm. A plausibility check of Monaco and SciMoCa was performed using an ionization chamber in the BodyPhantom (BP). First, the original Monaco RT plans were verified with SciMoCa (pretreatment QA). Second, the corresponding 4‐Hz log files were converted into RT log file plans and sent to SciMoCa as on‐treatment QA. MLC shift errors were introduced for one prostate plan to determine the sensitivity of on‐treatment QA. For pretreatment and on‐treatment QA, a gamma analysis (2%/1mm/20%) was performed and dosimetric values of PTV and OARs were ascertained in SciMoCa.

Results

Plausibility check of TPS Monaco vs. BP measurement and SciMoCa vs. BP measurement showed valid accuracy for clinical VMAT QA. Using SciMoCa, there was no significant difference in PTV Dmean between RT plan and RT log file plan. Between pretreatment and on‐treatment QA, PTV metrics, femur right and left showed no significant dosimetric differences as opposed to OARs rectum and bladder. The overall gamma passing rate (GPR) ranged from 96.10% to 100% in pretreatment QA and from 93.50% to 99.80% in on‐treatment QA. MLC shift errors were identified for deviations larger than −0.50 mm and +0.75 mm using overall gamma criterion and PTV Dmean.

Conclusion

SciMoCa calculations of Monaco RT plans and RT log file plans are in excellent agreement to each other. Therefore, 4‐Hz log files and SciMoCa can replace labor‐intensive phantom‐based measurements as patient‐specific QA.

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.

Edge area metric complexity scoring of volumetric modulated arc therapy plans

Background and purpose

Aperture-based complexity metrics have been suggested as a method to score complexity of volumetric modulated arc therapy (VMAT) plans. The purpose of this study was to evaluate the edge area metric (EAM) for clinical VMAT plans on a control point and treatment plan level.

Materials and methods

EAM on a control point level was evaluated based on film measurements of 18 static beam openings originating from VMAT plans. EAM on a treatment plan level (arithmetic mean value of EAM scores for control points) was evaluated based on measurements with the Delta⁴® for 200 VMAT plans for four different treatment sites: pelvic, thorax, head and neck, and prostate. Measurements were compared to calculations and dose difference and gamma pass rates were evaluated.

Results

EAM scores on a control point level correlated with Pearson's r-values of -0.96 and -0.77 to dose difference and gamma pass rates, respectively. The prostate plans had the highest average EAM score. A connection between smaller PTVs and higher EAM scores was found. No correlation between the evaluation result and EAM on a plan level was found.

Conclusions

EAM on a control point level was shown to correlate to the difference between measured and calculated 2D dose distributions of clinical VMAT beam openings. No correlation was found for EAM on a plan level for clinical treatment plans.

Dosimetric Validation of a GAN-Based Pseudo-CT Generation for MRI-Only Stereotactic Brain Radiotherapy

PURPOSE

Stereotactic radiotherapy (SRT) has become widely accepted as a treatment of choice for patients with a small number of brain metastases that are of an acceptable size, allowing for better target dose conformity, resulting in high local control rates and better sparing of organs at risk. An MRI-only workflow could reduce the risk of misalignment between magnetic resonance imaging (MRI) brain studies and computed tomography (CT) scanning for SRT planning, while shortening delays in planning. Given the absence of a calibrated electronic density in MRI, we aimed to assess the equivalence of synthetic CTs generated by a generative adversarial network (GAN) for planning in the brain SRT setting.

METHODS

All patients with available MRIs and treated with intra-cranial SRT for brain metastases from 2014 to 2018 in our institution were included. After co-registration between the diagnostic MRI and the planning CT, a synthetic CT was generated using a 2D-GAN (2D U-Net). Using the initial treatment plan (Pinnacle v9.10, Philips Healthcare), dosimetric comparison was performed using main dose-volume histogram (DVH) endpoints in respect to ICRU 91 guidelines (Dmax, Dmean, D2%, D50%, D98%) as well as local and global gamma analysis with 1%/1 mm, 2%/1 mm and 2%/2 mm criteria and a 10% threshold to the maximum dose. t-test analysis was used for comparison between the two cohorts (initial and synthetic dose maps).

RESULTS

184 patients were included, with 290 treated brain metastases. The mean number of treated lesions per patient was 1 (range 1-6) and the median planning target volume (PTV) was 6.44 cc (range 0.12-45.41). Local and global gamma passing rates (2%/2 mm) were 99.1 CI95% (98.1-99.4) and 99.7 CI95% (99.6-99.7) respectively (CI: confidence interval). DVHs were comparable, with no significant statistical differences regarding ICRU 91's endpoints.

CONCLUSIONS

Our study is the first to compare GAN-generated CT scans from diagnostic brain MRIs with initial CT scans for the planning of brain stereotactic radiotherapy. We found high similarity between the planning CT and the synthetic CT for both the organs at risk and the target volumes. Prospective validation is under investigation at our institution.

Correlation of the gamma passing rates with the differences in the dose-volumetric parameters between the original VMAT plans and actual deliveries of the VMAT plans

Purpose

The aim of this study was to investigate the correlations of the gamma passing rates (GPR) with the dose-volumetric parameter changes between the original volumetric modulated arc therapy (VMAT) plans and the actual deliveries of the VMAT plans (DV errors). We compared the correlations of the TrueBeam STx system to those of a C-series linac.

Methods

A total of 20 patients with head and neck (H&N) cancer were retrospectively selected for this study. For each patient, two VMAT plans with the TrueBeam STx and Trilogy (C-series linac) systems were generated under similar modulation degrees. Both the global and local GPRs with various gamma criteria (3%/3 mm, 2%/2 mm, 2%/1 mm, 1%/2 mm, and 1%/1 mm) were acquired with the 2D dose distributions measured using the MapCHECK2 detector array. During VMAT deliveries, the linac log files of the multi-leaf collimator positions, gantry angles, and delivered monitor units were acquired. The DV errors were calculated with the 3D dose distributions reconstructed using the log files. Subsequently, Spearman’s rank correlation coefficients (r_s) and the corresponding p values were calculated between the GPRs and the DV errors.

Results

For the Trilogy system, the r_s values with p < 0.05 showed weak correlations between the GPRs and the DV errors (r_s<0.4) whereas for the TrueBeam STx system, moderate or strong correlations were observed (r_s≥0.4). The DV errors in the V_20Gy of the left parotid gland and those in the mean dose of the right parotid gland showed strong correlations (always with r_s > 0.6) with the GPRs with gamma criteria except 3%/3 mm. As the GPRs increased, the DV errors decreased.

Conclusion

The GPRs showed strong correlations with some of the DV errors for the VMAT plans for H&N cancer with the TrueBeam STx system.

Description and evaluation of a new volumetric-modulated arc therapy plan complexity metric

This study describes a new plan complexity metric for volumetric-modulated arc therapy (VMAT) and evaluates the relationship of this metric with the VMAT dosimetric accuracy. The new modulation complexity score for VMAT (NMCSv) that is based on the aperture shape and multi-leaf collimator (MLC) leaf travel is described. Its performance is evaluated through correlation and receiver operating characteristic (ROC) analyses with patient-specific gamma passing rates using 2 3-dimensional diode arrays. For comparison, the following metrics are evaluated using the same correlation analyses: average field width, average leaf travel, modulation complexity score, and leaf travel modulation complexity score. Spearman's rank correlation analysis is performed to examine any relationships between the complexity metrics and the patient-specific gamma passing rates. ROC curves are used to assess the performance of the plan metrics using a gamma passing rate of 3%/3 mm criterion with a 95% tolerance level. In both the diode arrays, the gamma passing rates (3%/3 mm and 2%/2 mm) for patient-specific dosimetric verification of VMAT plans are moderately or weakly correlated to all the complexity metrics. NMCSv demonstrates the highest correlation with the passing rates (r = 0.652, p < 0.001 for Delta4 and r = 0.499, p < 0.001 for ArcCheck) and the highest area under the curve value (0.809, p < 0.01 for Delta4 and 0.734, p < 0.01 for ArcCheck). While using the Delta4 system, NMCSv exhibits an excellent classification performance with area under the curves of 0.926 (sensitivity: 0.913; specificity: 0.860; p < 0.01) and 0.918 (sensitivity: 0.943; specificity: 0.720; p < 0.01) for rectal and cervical cancer plans, respectively. NMCSv as a novel potential clinical plan complexity metric is moderately correlated with the gamma passing rate. It demonstrates the best performance with respect to distinguishing the dosimetric accuracy of VMAT plans among the evaluated metrics. The classification performance of complexity metrics can be affected by various dosimetry verification devices and treatment sites.

Error sensitivity of a log file analysis tool compared with a helical diode array dosimeter for VMAT delivery quality assurance

PURPOSE

Integrating log file analysis with LINACWatch® (LW) into clinical routine as part of the quality assurance (QA) process could be a time-saving strategy that does not compromise on quality. The purpose is to determine the error sensitivity of log file analysis using LINACWatch® compared with a measurement device (ArcCHECK®, AC) for VMAT delivery QA.

MATERIALS AND METHODS

Multi-leaf collimator (MLC) errors, collimator angle errors, MLC shift errors and dose errors were inserted to analyze error detection sensitivity. A total of 36 plans were manipulated with different magnitudes of errors. The gamma index protocols for AC were 3%/3 mm/Global and 2%/2 mm/Global, as well as 2%/2 mm/Global, and 1.5%/1.5 mm/Global for LW. Additionally, deviations of the collimator and monitor units between TPS and log file were calculated as RMS values. A 0.125 cm³ ionization chamber was used to independently examine the effect on dose.

RESULTS

The sensitivity for AC was 20.4% and 49.6% vs 63.0% and 86.5% for LW, depending on the analysis protocol. For MLC opening and closing errors, the detection rate was 19.0% and 47.7% for AC vs 50.5% and 75.5% for LW. For MLC shift errors, it was 29.6% and 66.7% for AC vs 66.7% and 83.3% for LW. AC could detect 25.0% and 44.4% of all collimator errors. Log file analysis detected all collimator errors using 1° detection level. 13.2% and 42.4% of all dose errors were detected by AC vs 59.0% and 92.4% for LW using gamma analysis. Using RMS value, all dose errors were detected by LW (1% detection level).

CONCLUSION

The results of this study clearly show that log file analysis is an excellent complement to phantom-based delivery QA of VMAT plans. We recommend a 1.5%/1.5 mm/Global criteria for log file-based gamma calculations. Log file analysis was implemented successfully in our clinical routine for VMAT delivery QA.

Temperature dependence and temporal stability of stacked radiochromic sheets for three-dimensional dose verification

PURPOSE

Recently a novel radiochromic sheet dosimeter, termed as PRESAGE sheets, consisting of leuco crystal violet dye and radical initiator had been developed and characterized. This study examines the dosimeter's temporal stability and storage temperature dependence postirradiation, and its applicability for dose verification in three dimensions (3D) as a stack dosimeter.

METHODS

PRESAGE sheets were irradiated using 6 MV photons at a dose range of 0-20 Gy with the change in optical density measured using a flatbed scanner. Following their irradiation, PRESAGE sheets were stored in different temperature environments (-18 °C, 4 °C, and 22 °C) and scanned at different time points, ranging from 1 to 168 h postirradiation, to track changes in measured signal and linearity of dose response. Multiple PRESAGE sheets were bound together to create a 12 × 13 × 8.7 cm³ film stack, with EBT3 film inserted between the sheets in the central region of the stack, that was treated using a clinical VMAT plan. Based on the results from the time and storage temperature study, two-dimensional (2D) relative dose distribution measurements in PRESAGE were acquired promptly following irradiation at selected planes in the coronal, sagittal, and axial orientation of the film stack and compared to the treatment planning system calculations in their respective axes. Dose distribution measurements on the coronal axis of the stack dosimeter were also independently verified using EBT3 film.

RESULTS

The dose response was observed to be linear (R² > 0.995) with sheets stored in colder temperatures retaining their signal and dose response sensitivity for extended periods postirradiation. Sheets stored in 22 °C environment should be measured within an hour postirradiation. Sheets stored in a 4 °C and -18 °C environment can be scanned up to 20- and 72 h postirradiation, respectively, while preserving the integrity of their dose response sensitivity and linearity of dose response within a mean absolute percent error of 2.0%. For instance, at 20 h postirradiation the dose response sensitivity for sheets stored in a -18 °C, 4 °C, and 22 °C temperature environment was measured to be 97%, 91%, and 77% of their original values measured within an hour postirradiation, respectively. The 2D gamma pass rate for central slices exceed 95% for PRESAGE film stack compared with treatment planning system on selected planes in the axial, coronal, and sagittal orientation and EBT3 film in the coronal orientation using a 2D gamma index of 2%/2mm. The gamma pass rate in comparing the calculated dose distribution with the measured dose distribution from PRESAGE-LCV was observed to decrease in sheets scanned at later elapsed times postirradiation. In one example, the gamma pass rate for 2%/2mm criteria in the coronal plane was observed to decrease from 97.7% pass rate when scanned within an hour postirradiation to 92.1% pass rate when scanned at 20 h postirradiation under room temperature conditions.

CONCLUSIONS

This is the first study to demonstrate that the temporal stability of PRESAGE sheets can be enhanced through its storage in colder temperature environments postirradiation and that sheets as a film stack dosimeter hold promise for precise relative dose distribution measurements in 3D where advanced optical CT is unavailable.

Study on the ability of 3D gamma analysis and bio-mathematical model in detecting dose changes caused by dose-calculation-grid-size (DCGS)

Objective

To explore the efficacy and sensitivity of 3D gamma analysis and bio-mathematical model for cervical cancer in detecting dose changes caused by dose-calculation-grid-size (DCGS).

Methods

17 patients’ plans for cervical cancer were enrolled (Pinnacle TPS, VMAT), and the DCGS was changed from 2.0 mm to 5.0 mm to calculate the planned dose respectively. The dose distribution calculated by DCGS = 2.0 mm as the “reference” data set (RDS), the dose distribution calculated by the rest DCGS as the“measurement”data set (MDS), the 3D gamma passing rates and the (N) TCPs of the all structures under different DCGS were obtained, and then analyze the ability of 3D gamma analysis and (N) TCP model in detecting dose changes and what factors affect this ability.

Results

The effect of DCGS on planned dose was obvious. When the gamma standard was 1.0 mm, 1.0 and 10.0%, the difference of the results of the DCGS on dose-effect could be detected by 3D gamma analysis (all p value < 0.05). With the decline of the standard, 3D gamma analysis’ ability to detect this difference shows weaker. When the standard was 1.0 mm, 3.0 and 10.0%, the p value of > 0.05 accounted for the majority. With DCGS = 2.0 mm being RDS, ∆gamma-passing-rate presented the same trend with ∆(N) TCPs of all structures except for the femurs only when the 1.0 mm, 1.0 and 10.0% standards were adopted for the 3D gamma analysis.

Conclusions

The 3D gamma analysis and bio-mathematical model can be used to analyze the effect of DCGS on the planned dose. For comparison, the former’s detection ability has a lot to do with the designed standard, and the latter’s capability is related to the parameters and calculated accuracy instrinsically.

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 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.

Characterization of robust optimization for VMAT plan for liver cancer

Purpose

We investigated the feasibility of robust optimization for volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) for liver cancer in comparison with planning target volume (PTV)-based optimized plans. Treatment plan quality, robustness, complexity, and accuracy of dose delivery were assessed.

Methods

Ten liver cancer patients were selected for this study. PTV-based optimized plans with an 8-mm PTV margin and robust optimized plans with an 8-mm setup uncertainty were generated. Plan perturbed doses were evaluated using a setup error of 8 mm in all directions from the isocenter. The dosimetric comparison parameters were clinical target volume (CTV) doses (D_98%, D_50%, and D_2%), liver doses, and monitor unit (MU). Plan complexity was evaluated using the modulation complexity score for VMAT (MCSv).

Results

There was no significant difference between the two optimizations with respect to CTV doses and MUs. Robust optimized plans had a higher liver dose than did PTV-based optimized plans. Plan perturbed dose evaluations showed that doses to the CTV for the robust optimized plans had small variations. Robust optimized plans were less complex than PTV-based optimized plans. Robust optimized plans had statistically significant fewer leaf position errors than did PTV-based optimized plans.

Conclusions

Comparison of treatment plan quality, robustness, and plan complexity of both optimizations showed that robust optimization could be feasibile for VMAT of liver cancer.

Evaluation of Delta4DVH Anatomy in 3D Patient-Specific IMRT Quality Assurance

Purpose:

To evaluate the performance of Delta^4DVH Anatomy in patient-specific intensity-modulated radiotherapy quality assurance.

Materials and Methods:

Dose comparisons were performed between Anatomy doses calculated with treatment plan dose measured modification and pencil beam algorithms, treatment planning system doses, film doses, and ion chamber measured doses in homogeneous and inhomogeneous geometries. The sensitivity of Anatomy doses to machine errors and output calibration errors was also investigated.

Results:

For a Volumetric Modulated Arc Therapy (VMAT) plan evaluated on the Delta⁴ geometry, the conventional gamma passing rate was 99.6%. For a water-equivalent slab geometry, good agreements were found between dose profiles in film, treatment planning system, and Anatomy treatment plan dose measured modification and pencil beam calculations. Gamma passing rate for Anatomy treatment plan dose measured modification and pencil beam doses versus treatment planning system doses was 100%. However, gamma passing rate dropped to 97.2% and 96% for treatment plan dose measured modification and pencil beam calculations in inhomogeneous head & neck phantom, respectively. For the 10 patients’ quality assurance plans, good agreements were found between ion chamber measured doses and the planned ones (deviation: 0.09% ± 1.17%). The averaged gamma passing rate for conventional and Anatomy treatment plan dose measured modification and pencil beam gamma analyses in Delta⁴ geometry was 99.6% ± 0.89%, 98.54% ± 1.60%, and 98.95% ± 1.27%, respectively, higher than averaged gamma passing rate of 97.75% ± 1.23% and 93.04% ± 2.69% for treatment plan dose measured modification and pencil beam in patients’ geometries, respectively. Anatomy treatment plan dose measured modification dose profiles agreed well with those in treatment planning system for both Delta⁴ and patients’ geometries, while pencil beam doses demonstrated substantial disagreement in patients’ geometries when compared to treatment planning system doses. Both treatment planning system doses are sensitive to multileaf collimator and monitor unit (MU) errors for high and medium dose metrics but not sensitive to the gantry and collimator rotation error smaller than 3°.

Conclusions:

The new Delta^4DVH Anatomy with treatment plan dose measured modification algorithm is a useful tool for the anatomy-based patient-specific quality assurance. Cautions should be taken when using pencil beam algorithm due to its limitations in handling heterogeneity and in high-dose gradient regions.

PSEUDO-3D IMRT VERIFICATION WITH EBT3 RADIOCHROMIC FILM

This work proposes a new method for pseudo-3D verification of intensity-modulated radiation therapy (IMRT) dose distributions. Unlike commercial solutions, it uses measured doses only for gamma evaluation. Its resolution is far better than with electronic detectors within the measured plane and comparable in other directions. It is readily available at clinics because it uses existing resources-a slab phantom and EBT3 films. The method was tested on six IMRT clinical cases. An in-house code for 2D and pseudo-3D gamma analysis was written in MATLAB and compared to OmniPro I'mRT.

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.

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.

Impact of delivery characteristics on dose delivery accuracy of volumetric modulated arc therapy for different treatment sites

This study aimed to investigate the impact of delivery characteristics on the dose delivery accuracy of volumetric modulated arc therapy (VMAT) for different treatment sites. The pretreatment quality assurance (QA) results of 344 VMAT patients diagnosed with gynecological (GYN), head and neck (H&N), rectal or prostate cancer were randomly chosen in this study. Ten metrics reflecting VMAT delivery characteristics were extracted from the QA plans. Compared with GYN and rectal plans, H&N and prostate plans had higher aperture complexity and monitor units (MU), and smaller aperture area. Prostate plans had the smallest aperture area and lowest leaf speed compared with other plans (P < 0.001). No differences in gantry speed were found among the four sites. The gamma passing rates (GPRs) of GYN, rectal and H&N plans were inversely associated with union aperture area (UAA) and leaf speed (Pearson's r: -0.39 to -0.68). GPRs of prostate plans were inversely correlated with aperture complexity, MU and small aperture score (SAS) (absolute Pearson's r: 0.34 to 0.49). Significant differences in GPR between high SAS and low SAS subgroups were found only when leaf speed was <0.42 cm s-1 (P < 0.001). No association of GPR with gantry speed was found in four sites. Leaf speed was more strongly associated with UAA. Aperture complexity and MU were more strongly associated with SAS. VMAT plans from different sites have distinct delivery characteristics. Affecting dose delivery accuracy, leaf speed is the key factor for GYN, rectal and H&N plans, while aperture complexity, MU and small apertures have a higher influence on prostate plans.

Machine Learning for Patient-Specific Quality Assurance of VMAT: Prediction and Classification Accuracy

PURPOSE

To assess the accuracy of machine learning to predict and classify quality assurance (QA) results for volumetric modulated arc therapy (VMAT) plans.

METHODS AND MATERIALS

Three hundred three VMAT plans, including 176 gynecologic cancer and 127 head and neck cancer plans, were chosen in this study. Fifty-four complexity metrics were extracted from the QA plans and considered as inputs. Patient-specific QA was performed, and gamma passing rates (GPRs) were used as outputs. One Poisson lasso (PL) regression model was developed, aiming to predict individual GPR, and 1 random forest (RF) classification model was developed to classify QA results as "pass" or "fail." Both technical validation (TV) and clinical validation (CV) were used to evaluate the model reliability. GPR prediction accuracy of PL and classification performance of PL and RF were evaluated.

RESULTS

In TV, the mean prediction error of PL was 1.81%, 2.39%, and 4.18% at 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. No significant differences in prediction errors between TV and CV were observed. In QA results classification, PL had a higher specificity (accurately identifying plans that can pass QA), whereas RF had a higher sensitivity (accurately identifying plans that may fail QA). By using 90% as the action limit at a 3%/2 mm criterion, the specificity of PL and RF was 97.5% and 87.7% in TV and 100% and 71.4% in CV, respectively. The sensitivity of PL and RF was 31.6% and 100% in TV and 33.3% and 100% in CV, respectively. With 100% sensitivity, the QA workload of 81.2% of plans in TV and 62.5% of plans in CV could be reduced by RF.

CONCLUSIONS

The PL model could accurately predict GPR for most VMAT plans. The RF model with 100% sensitivity was preferred for QA results classification. Machine learning can be a useful tool to assist VMAT QA and reduce QA workload.

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.

Investigating the effectiveness of monitoring relevant variations during IMRT and VMAT treatments by EPID-based 3D in vivo verification performed using planning CTs

Purpose

The goal of this study was to investigate the effectiveness of monitoring relevant variations during treatments for electronic portal imaging device (EPID)-based 3D in vivo verification performed using planning CTs.

Methods

Experiments on two simple phantoms (uniform and nonuniform phantoms) and a thoracic phantom were analyzed in this study, and six relevant variations including the machine output, planning target volume (PTV) deformation, multileaf collimator (MLC) and Phantom shift (set-up errors), and gantry and couch angle shifts were evaluated. 3D gamma and dose-volume histogram (DVH) methods were used to evaluate the detection sensitivity of the EPID-based 3D in vivo dosimetry and the dose accuracy of the EPID reconstruction, respectively, as affected by the variations, and the results were validated by determining the consistency with TPS simulated results.

Results

The results of the simple phantoms showed that the gamma failure rates and DVH trend of EPID reconstructions were consistent with the results of TPS simulations for machine output and MLC shifts and inconsistent for phantom shift, gantry/couch angle shift and PTV deformation variations. The results of the thoracic phantom showed that CBCT-guided EPID reconstruction sensitively detected 3-mm Phantom shift in thoracic phantom and its gamma failure rates and DVH trend were consistent with the results of TPS simulations.

Conclusion

The variations, such as machine output and MLC shift, that are phantom unrelated and cause changes in the beam of the linear accelerator can be sensitively detected by EPID-based 3D in vivo dosimetry and do not affect the accuracy of the EPID reconstruction dose. Planning CT will limit the detection sensitivity and the accuracy of the reconstruction dose of the EPID-based 3D in vivo dosimetry for phantom-related variations (such as Phantom shift and gantry/couch angle shift). EPID reconstruction combined with IGRT technology is a more effective method to monitor phantom shift variations.

Quality assurance of linear accelerator: a comprehensive system using electronic portal imaging device

Aim

The Electronic Portal Imaging Device (EPID), primarily used for patient setup during radiotherapy sessions is also used for dosimetric measurements. In the present study, the feasibility of EPID in both machine and patient-specific quality assurance (QA) are investigated. We have developed a comprehensive software tool for effective utilisation of EPID in our institutional QA protocol.

Materials and methods

Portal Vision aS1000, amorphous silicon portal detector attached to Clinac iX—Linear Accelerator (LINAC) was used to measure daily profile and output constancy, various Multi-Leaf Collimator (MLC) checks and patient plan verification. Different QA plans were generated with the help of Eclipse Treatment Planning System (TPS) and MLC shaper software. The indigenously developed MATLAB programs were used for image analysis. Flatness, symmetry, output constancy, Field Width at Half Maximum (FWHM) and fluence comparison were studied from images obtained from TPS and EPID dosimetry.

Results

The 3 years institutional data of profile constancy and patient-specific QA measured using EPID were found within the acceptable limits. The daily output of photon beam correlated with the output obtained through solid phantom measurements. The Pearson correlation coefficients are 0.941 (p = 0.0001), 0.888 (p = 0.0188) and 0.917 (p = 0.0007) for the years of 2014, 2015 and 2016, respectively. The accuracy of MLC for shaping complex treatment fields was studied in terms of FWHM at different portions of various fields, showed good agreement between TPS-generated and EPID-measured MLC positions. The comparison of selected patient plans in EPID with an independent 2D array detector system showed statistically significant correlation between these two systems. Percentage difference between TPS computed and EPID measured fluence maps calculated for number of patients using MATLAB code also exhibited the validity of those plans for treatment.

Impact of plan parameters and modulation indices on patient-specific QA results for standard and stereotactic VMAT

PURPOSE

To demonstrate the impact of modulation indices and plan parameters on the gamma passing rates (GPR) of patient-specific quality assurance of standard and stereotactic volumetric modulated arc therapy (VMAT) plans.

METHODS

A total of 758 patients' QA plans were utilized, including standard VMAT plans with Trilogy (n = 87, group A) and TreuBeam STx (n = 332, group B), and 339 stereotactic VMAT plans with TrueBeam STx (group C). Modulation indices were obtained considering the speed and acceleration of the multileaf collimator (MLC) (MI_s, MI_a), and MLC, gantry speed, and dose rate changes (MI_t). The mean aperture size (MA), monitor unit (MU), and amount of jaw tracking (%JT) were acquired. Gamma analysis was performed with 2 mm/2% and 1 mm/2% for the standard and stereotactic VMAT plans, respectively. Statistical analyses were performed to investigate the correlation between modulation index/plan parameters and GPR.

RESULTS

Spearman's rank correlation to GPRs with MI_s, MI_a, and MI_t, were -0.44, -0.45, and -0.46 for group A; -0.39, -0.37, and -0.38 for group B; and -0.04, -0.11, and -0.10 for group C, respectively. While MU and MA showed significant correlations in all groups, %JT showed a significant correlation only with stereotactic VMAT plans. The most influential parameter combinations were MU-MA (r_s = 0.50), MI_s-%JT (r_s = 0.43), and MU-%JT (r_s = 0.38) for groups A, B, and C, respectively.

CONCLUSIONS

MLC modulation mostly affected the GPR in the delivery of standard VMAT plans, while MU and %JT showed more importance in stereotactic VMAT plans.

Modulation indices and plan delivery accuracy of volumetric modulated arc therapy

PURPOSE

We evaluated the performance of various modulation indices (MI) for volumetric modulated arc therapy (VMAT) to predict plan delivery accuracy.

METHODS

The specific indices evaluated were MI quantifying the mechanical uncertainty (MI_t ), MI quantifying the mechanical and dose calculation uncertainties (MI_c ), MI for station parameter optimized radiation therapy (MI_SPORT ), modulation complexity score for VMAT (MCS_v ), leaf travel modulation complexity score (LTMCS), plan averaged beam area (PA), plan averaged beam irregularity (PI), plan averaged beam modulation (PM), and plan normalized monitor unit (PMU) to predict VMAT delivery accuracy. By utilizing 240 VMAT plans generated with the Trilogy and TrueBeam STx, Spearman's rank correlation coefficients (r) were calculated between the MIs and measures of conventional methods.

RESULTS

For the Trilogy system, MI_c showed the highest r values with gamma passing rates (GPRs) (r = -0.624 with P < 0.001 for MapCHECK2 and r = -0.655 with P < 0.001 for ArcCHECK). For TrueBeam STx, MI_c also showed the highest r values with GPRs (r = -0.625 with P < 0.001 for the MapCHECK2 and r = -0.561 with P < 0.001 for the ArcCHECK). The MI_t and MI_c showed the highest r values to the MLC position errors for the Trilogy and TrueBeam STx systems (r = 0.770 with P < 0.001 and r = 0.712 with P < 0.001, respectively). The PA showed the highest percent of r values (P < 0.05) to differences in the dose-volume parameters between original VMAT plans and actual deliveries for the Trilogy systems (30.9%). Both the MI_t and MI_c showed the highest percent of r values (P < 0.05) to differences in the dose-volume parameters between original VMAT plans and actual deliveries for the TrueBeam STx systems (31.8%).

CONCLUSION

To comprehensively review the results, the MI_c showed the best performance to predict the VMAT delivery accuracy.

EPID sensitivity to delivery errors for pre-treatment verification of lung SBRT VMAT plans

PURPOSE

To study the sensitivity of an Electronic Portal Imaging Device (EPID) in detecting delivery errors for VMAT lung stereotactic body radiotherapy (SBRT) using the Collapsed Arc method.

METHODS

Baseline VMAT plans and plans with errors intentionally introduced were generated for 15 lung SBRT patients. Three types of errors were introduced by modifying collimator angles and multi-leaf collimator (MLC) field sizes (MLCFS) and MLC shifts by ±5, ±2, and ±1° or millimeters. A total of 103 plans were measured with EPID on an Elekta Synergy Linear Accelerator (Agility MLC) and compared to both the original treatment planning system (TPS) Collapsed Arc dose matrix and the no-error plan baseline EPID measurements. Gamma analysis was performed using the OmniPro-I'mRT (IBA Dosimetry) software and gamma criteria of 1%/1 mm, 2%/1 mm, 2%/2 mm, and 3%/3.

RESULTS

When the error-introduced EPID measured dose matrices were compared to the TPS matrices, the majority of simulated errors were detected with gamma tolerance of 2%/1 mm and 1%/1 mm. When the error-introduced EPID measured dose matrices were compared to the baseline EPID measurements, all the MLCFS and MLC shift errors, and ±5°collimator errors were detected using 2%/1 mm and 1%/1 mm gamma criteria.

CONCLUSION

This work demonstrates the feasibility and effectiveness of the collapsed arc technique and EPID for pre-treatment verification of lung SBRT VMAT plans. The EPID was able to detect the majority of MLC and the larger collimator errors with sensitivity to errors depending on the gamma tolerances.