A comparison of the gamma index analysis in various commercial IMRT/VMAT QA systems

From 2D to 3D gamma passing rate tolerance and action limits for patient-specific quality assurance in volumetric-modulated arc therapy

BACKGROUND

Volumetric modulated arc therapy (VMAT) requires an accurate patient-specific quality assurance (PSQA) program. In clinical practice, this is usually performed using the γ-index and the two-dimensional gamma passing rate (2D %GP). A three-dimensional (3D) index incorporating the patient anatomy could be more useful for the 3D dose distribution verification.

PURPOSE

The current study demonstrates a thorough investigation of VMAT PSQA treatment plans by examining the correlation between 3D Gamma passing rate (%GP) and 2D %GP. The aim was to establish the tolerance limits (TL) and action limits (AL) that could be adopted in clinical practice.

MATERIALS AND METHODS

PSQA was performed for 67 head and neck (H&N) and 69 prostate treatment plans, using an appropriate phantom and the γ-index method. The 3%/2  mm acceptance criterion was used. Treatment plans' 2D% GP and 3D %GP values were collected and correlated with individual 3D %GP values of planning target volume (PTV) and organs at risk (OARs). Institutional TL and AL of both 2D %GP and 3D %GP were established using 30 prostate and 30 H&N treatment plans, as per recommendations proposed by AAPM TG-218.

RESULTS

A moderate correlation was observed between 2D %GP and 3D %GP of the treatment plans. Τhe correlations demonstrated a stronger association for the 3D %GP than for the 2D %GP with respect to the 3D %GP of the individual structures considered. The TL for the 3D %GP (both plan and individual) and the plans' 2D %GP were generally more stringent, while the AL showed a wider range compared to the corresponding limits suggested by the TG-218 protocol for plan 2D %GP.

CONCLUSIONS

Institution-specific 3D %GP as well as TL and AL for treatment plan, PTV and OARs could be incorporated in the PSQA procedure in synergy with the 2D evaluation, as they can provide a more-in-depth-view of the treatment quality.

Quantifying radiotherapy beam quality: an analysis using gamma passing rates

Purpose. PDD and profile curves play a crucial role in analyzing the beam quality and energy stability of accelerators. The aim of this study was to assess the efficacy of GPR in machine QA and compare it with traditional methods for analyzing dose outputs.Methods. GPRs were employed to assess the quality of radiation beams by comparing 1D and 2D Profile metrics and PDD data against commissioning data. The data used were obtained from the ASCII data files derived from the water tank. GPRs were calculated for all plots with a lower percentage dose cutoff of 10%. The local GPRs and dose influence for the 2D PDD metrics and dose influence were calculated for an open field 10 × 10 cm2photon beam at SSD = 100 cm. In both 1D and 2D GPRs analyses, criterion of 1%/1 mm was adopted, as this approach allows for the capture of more subtle variations in the data. To substantiate the viability of the study, a comparative analysis was conducted by comparing the outcomes of the gamma analysis with those derived from traditional methods, such as manual machine quality assurance checks.Results. GPRs demonstrated a superior capability for comprehensive data analysis compared to traditional methods. For the 1D curves, the passing rates (γ≤ 1) are 96.19%, 100%, and 93.46%, respectively. With respect to the 2D dose influence, the PDD image passing rate was 99.57%, and significant dose differences were observed at the four corners of the open field, indicating areas that require further investigation.Conclusions. Compared to traditional methods, GPRs are more sensitive to subtle changes in the data, providing valuable insights into the accelerator beam status.

A StarGAN and transformer-based hybrid classification-regression model for multi-institution VMAT patient-specific quality assurance

BACKGROUND

The field of artificial intelligence (AI)-based patient-specific quality assurance (PSQA) for volumetric modulated arc therapy (VMAT) faces challenges in terms of developing general models across institutions due to the prevalence of multi-institution data collection and multivariate heterogeneity. Building a general model that is capable of handling diverse multi-institution data is critical for enabling large-scale integration and analysis.

PURPOSE

This study aims to develop a star generative adversarial network (StarGAN) and transformer-based hybrid classification-regression PSQA framework to address unification of heterogeneous data from different institutions.

METHODS

A StarGAN and transformer-based hybrid classification-regression model was developed as a general PSQA framework to predict gamma passing rates (GPRs) and classify quality assurance (QA) results as "Pass" or "Fail" at multiple institutions. A total of 1815 VMAT plans were collected from eight institutions to develop the general PSQA framework and perform clinical commissioning and implementation. Among them, 20 independent clinical plans from each of eight institutions, for a total of 160 plans, were used for the clinical commissioning, and 205 new clinical plans from eight institutions were used for clinical implementation.

RESULTS

For the 3%/3, 3%/2, and 2%/2 mm gamma criteria, the sensitivity of the proposed PSQA framework with pretraining was 90.13%, 92.03%, and 95.84%, respectively, while the specificity was 76.01%, 76.12%, and 85.34%, respectively. The mean absolute errors (MAEs) of the proposed PSQA framework with pretraining were 1.36%, 2.37%, and 3.96%, respectively, while the root-mean-square errors (RMSEs) were 2.31%, 3.89%, and 5.17%, respectively. The results demonstrated visible improvement at multiple institutions. For clinical commissioning, the deviations between the predicted and measured results were all within 3% for 3%/3 and 3%/2 mm at eight institutions. For clinical implementation, all failure plans were correctly identified by the proposed PSQA framework.

CONCLUSIONS

The general PSQA framework enables diverse clinical data sources to be handled to achieve enhanced model performance and generalizability, and provides a solution to the unification of heterogeneous data from different institutions to construct robust QA models. This approach can be clinically deployed for VMAT QA.

Unifying gamma passing rates in patient-specific QA for VMAT lung cancer treatment based on data assimilation

This study aimed to identify systematic errors in measurement-, calculation-, and prediction-based patient-specific quality assurance (PSQA) methods for volumetric modulated arc therapy (VMAT) on lung cancer and to standardize the gamma passing rate (GPR) by considering systematic errors during data assimilation. This study included 150 patients with lung cancer who underwent VMAT. VMAT plans were generated using a collapsed-cone algorithm. For measurement-based PSQA, ArcCHECK was employed. For calculation-based PSQA, Acuros XB was used to recalculate the plans. In prediction-based PSQA, GPR was forecasted using a previously developed GPR prediction model. The representative GPR value was estimated using the least-squares method from the three PSQA methods for each original plan. The unified GPR was computed by adjusting the original GPR to account for systematic errors. The range of limits of agreement (LoA) were assessed for the original and unified GPRs based on the representative GPR using Bland-Altman plots. For GPR (3%/2 mm), original GPRs were 94.4 ± 3.5%, 98.6 ± 2.2% and 93.3 ± 3.4% for measurement-, calculation-, and prediction-based PSQA methods and the representative GPR was 95.5 ± 2.0%. Unified GPRs were 95.3 ± 2.8%, 95.4 ± 3.5% and 95.4 ± 3.1% for measurement-, calculation-, and prediction-based PSQA methods, respectively. The range of LoA decreased from 12.8% for the original GPR to 9.5% for the unified GPR across all three PSQA methods. The study evaluated unified GPRs that corrected for systematic errors. Proposing unified criteria for PSQA can enhance safety regardless of the methods used.

Deep learning for patient-specific quality assurance of volumetric modulated arc therapy: Prediction accuracy and cost-sensitive classification performance

PURPOSE

To evaluate a deep learning model's performance in predicting and classifying patient-specific quality assurance (PSQA) results for volumetric modulated arc therapy (VMAT), aiming to streamline PSQA workflows and reduce the onsite measurement workload.

METHODS

A total of 761 VMAT plans were analyzed using 3D-MResNet to process multileaf collimator images and monitor unit data, with the gamma passing rate (GPR) as the output. Thresholds for the predicted GPR (Th-p) and measured GPR (Th-m) were established to aid in PSQA decision-making, using cost curves and error rates to assess classification performance.

RESULTS

The mean absolute errors of the model for the test set were 1.63 % and 2.38 % at 3 %/2 mm and 2 %/2 mm, respectively. For the classification of the PSQA results, Th-m was 88.3 % at 2 %/2 mm and 93.3 % at 3 %/2 mm. The lowest cost-sensitive error rates of 0.0127 and 0.0925 were obtained when Th-p was set as 91.2 % at 2 %/2 mm and 96.4 % at 3 %/2 mm, respectively. Additionally, the 2 %/2 mm classifier also achieved a lower total expected cost of 0.069 compared with 0.110 for the 3 %/2 mm classifier. The deep learning classifier under the 2 %/2 mm gamma criterion had a sensitivity and specificity of 100 % (10/10) and 83.5 % (167/200), respectively, for the test set.

CONCLUSIONS

The developed 3D-MResNet model can accurately predict and classify PSQA results based on VMAT plans. The introduction of a deep learning model into the PSQA workflow has considerable potential for improving the VMAT PSQA process and reducing workloads.

From plan to delivery: Machine learning based positional accuracy prediction of multi-leaf collimator and estimation of delivery effect in volumetric modulated arc therapy

PURPOSE

The positional accuracy of MLC is an important element in establishing the exact dosimetry in VMAT. We comprehensively analyzed factors that may affect MLC positional accuracy in VMAT, and constructed a model to predict MLC positional deviation and estimate planning delivery quality according to the VMAT plans before delivery.

METHODS

A total of 744 "dynalog" files for 23 VMAT plans were extracted randomly from treatment database. Multi-correlation was used to analyzed the potential influences on MLC positional accuracy, including the spatial characteristics and temporal variability of VMAT fluence, and the mechanical wear parameters of MLC. We developed a model to forecast the accuracy of MLC moving position utilizing the random forest (RF) ensemble learning method. Spearman correlation was used to further investigate the associations between MLC positional deviation and dosage deviations as well as gamma passing rates.

RESULTS

The MLC positional deviation and effective impact factors show a strong multi-correlation (R = 0.701, p-value < 0.05). This leads to the development of a highly accurate prediction model with average variables explained of 95.03% and average MSE of 0.059 in the 5-fold cross-validation, and MSE of 0.074 for the test data was obtained. The absolute dose deviations caused by MLC positional deviation ranging from 12.948 to 210.235 cGy, while the relative volume deviation remained small at 0.470%-5.161%. The average MLC positional deviation correlated substantially with gamma passing rates (with correlation coefficient of -0.506 to -0.720 and p-value < 0.05) but marginally with dosage deviations (with correlation coefficient < 0.498 and p-value > 0.05).

CONCLUSIONS

The RF predictive model provides a prior tool for VMAT quality assurance.

Monte Carlo Simulation for the Radixact™ Tomotherapy Linac Using EGSnrc

Purpose

When exact information regarding the treatment head and initial electron beam is available, the Monte Carlo (MC) approach can properly simulate any linear accelerator. However, manufacturers seldom offer information such as the incident electron beam's energy, radial intensity (spot size), or angular spread. This research aims to forecast these features and verify an MC-simulated linear accelerator model using measurements.

Materials and Methods

The BEAMnrc code simulated a 6 MV photon beam from a Radixact™ Tomotherapy Linac. Percentage depth dose and beam profile calculations were conducted using DOSYXZnrc by various electron energies and spot sizes and compared to measurements using a Gamma index with two distinct criterion sets. Furthermore, the fine-tuned electron energy and spot size profiles were created to minimize any disparities using distinct angle spreads. Finally, the output factors (OFs) for various field sizes were compared.

Results

The MC model's fine-tuned electron energy was determined to be 5.8 MeV, with 88.6% of the calculation points passing the 1%/1 mm γ test. A circular radial intensity of 1.4 mm best represented the 6 MV photon beam regarding spot size. Furthermore, a mean angular spread of 0.05 reduced the disparity in cross-field profile between computation and measurement. The most considerable disparities between the MC model OFs and observations were 1.5%.

Conclusion

Using the BEAMnrc code, a reliable MC model of the Radixact™ Tomotherapy Linac can be created, as shown in this paper. This model can be used to compute dose distributions with confidence.

The impact of plan complexity on calculation and measurement-based pre-treatment verifications for sliding-window intensity-modulated radiotherapy

Background and purpose

In sliding-window intensity-modulated radiotherapy, increased plan modulation often leads to increased plan complexities and dose uncertainties. Dose calculation and/or measurement checks are usually adopted for pre-treatment verification. This study aims to evaluate the relationship among plan complexities, calculated doses and measured doses.

Materials and methods

A total of 53 plan complexity metrics (PCMs) were selected, emphasizing small field characteristics and leaf speed/acceleration. Doses were retrieved from two beam-matched treatment devices. The intended dose was computed employing the Anisotropic Analytical Algorithm and validated through Monte Carlo (MC) and Collapsed Cone Convolution (CCC) algorithms. To measure the delivered dose, 3D diode arrays of various geometries, encompassing helical, cross, and oblique cross shapes, were utilized. Their interrelation was assessed via Spearman correlation analysis and principal component linear regression (PCR).

Results

The correlation coefficients between calculation-based (CQA) and measurement-based verification quality assurance (MQA) were below 0.53. Most PCMs showed higher correlation rpcm-QA with CQA (max: 0.84) than MQA (max: 0.65). The proportion of rpcm-QA  ≥ 0.5 was the largest in the pelvis compared to head-and-neck and chest-and-abdomen, and the highest rpcm-QA occurred at 1 %/1mm. Some modulation indices for the MLC speed and acceleration were significantly correlated with CQA and MQA. PCR's determination coefficients (R2 ) indicated PCMs had higher accuracy in predicting CQA (max: 0.75) than MQA (max: 0.42).

Conclusions

CQA and MQA demonstrated a weak correlation. Compared to MQA, CQA exhibited a stronger correlation with PCMs. Certain PCMs related to MLC movement effectively indicated variations in both quality assurances.

A prospective study on the effect of tumor shrinkage on exit fluence gamma pass rate in high precision radiotherapy and influence of phantom setup error in patient-specific quality assurance

PURPOSE

Objective parameters for decision on adaptive radiotherapy depend on patient, tumor and treatment related factors. Present study reports geometric uncertainties occurring during high precision radiotherapy, beam fluence analysis and serial exit dose measurement as a patient-specific tool for adaptive radiotherapy.

MATERIALS AND METHODS

Serial exit dose fluence of 24 patients (at baseline and mid-treatment) undergoing IMRT/VMAT treatment were measured. Baseline and midtreatment exit dose evaluation was done using gafchromic films in predefined region of interest. Difference of volume of GTV at baseline (from simulation CT scan) and midtreatment CBCT scan was calculated (ΔGTV).

RESULTS

Population based systematic errors (mm) were 4.15, 2.26, 0.88 and random errors (mm) were 2.56, 3.69, and 2.03 in mediolateral (ML), craniocaudal (CC) and anteroposterior (AP) directions respectively. Gamma pass rate reduced with incremental shift. For a 5 mm shift, maximum deviation was found in anteroposterior axis (22.16 ± 7.50) and lowest in mediolateral axis (12.85 ± 4.95). On serial measurement of exit dose fluence, tumor shrinkage significantly influenced gamma pass rate. The mean gamma pass rate was significantly different between groups with 50% shrinkage of tumor volume (86.36 vs 96.24, P = 0.008, on multivariate analysis P = 0.026).

CONCLUSION

Rapid fall of gamma pass rate was observed for set up error of ≥3 mm. Serial measurement of exit dose fluence by radiochromic film is a feasible method of exit dose comparison in IMRT/VMAT, where EPID dosimetry is not available with linear accelerator configuration. Our study suggests that there is a significant difference between gamma pass rates of baseline and mid treatment exit dose fluence with greater than 50% tumor shrinkage.

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.

Comparison of deep learning models for building two-dimensional non-transit EPID Dosimetry on Varian Halcyon

Background

This study compared the effectiveness of five deep learning models in constructing non-transit dosimetry with an a-Si electronic portal imaging device (EPID) on Varian Halcyon. Deep learning model is increasingly used to support prediction and decision-making in several fields including oncology and radiotherapy.

Materials and methods

Forty-seven unique plans of data obtained from breast cancer patients were calculated using Eclipse treatment planning system (TPS) and extracted from DICOM format as the ground truth. Varian Halcyon was then used to irradiate the a-Si 1200 EPID detector without an attenuator. The EPID and TPS images were augmented and divided randomly into two groups of equal sizes to distinguish the validation and training-test data. Five different deep learning models were then created and validated using a gamma index of 3%/3 mm.

Results

Four models successfully improved the similarity of the EPID images and the TPS-generated planned dose images. Meanwhile, the mismatch of the constituent components and number of parameters could cause the models to produce wrong results. The average gamma pass rates were 90.07 ± 4.96% for A-model, 77.42 ± 7.18% for B-model, 79.60 ± 6.56% for C-model, 80.21 ± 5.88% for D-model, and 80.47 ± 5.98% for E-model.

Conclusion

The deep learning model is proven to run fast and can increase the similarity of EPID images with TPS images to build non-transit dosimetry. However, more cases are needed to validate this model before being used in clinical activities.

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.

Analysis of dose distribution reproducibility based on a fluence map of in vivo transit dose using an electronic portal imaging device

Morphological changes can affect distribution of dose in patients. Determination of the dose distribution changes for each fraction radiotherapy can be done by relativein vivodosimetry (IVD). This study analysed the distribution of doses per fraction based on the fluence map recorded by the electronic portal imaging device (EPID) of the patient's transit dose. This research examined cases involving the cervix, breast, and nasopharynx. Transit dose analysis was performed by calculating the gamma index (GI) with composite and field-by-field methods. The gamma passing rate (GPR) value was assessed for its correlation with the subject's body weight. In the case of the nasopharynx, breast, and cervix, the GPR value decreased as the fraction increased. In the case of the nasopharynx, the correlation between the GPR and fraction radiotherapy showed no difference when using either composite or field-by-field methods. However, in cases involving the cervix and breast, there was a difference in the correlation values between the composite and field-by-field methods, where the subject had a significant correlation (p< 0.05) when it was done using a field-by-field method. In addition, the nasopharynx had the highest number of subjects with significant correlation (p< 0.05) between GPR and body weight, followed by the cervix and breast. In the nasopharynx, breast, and cervix, the reproducibility of the dose distribution decreased. This decreased reproducibility was associated with changes in body weight.

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.

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.

Overcoming Problems Caused by Offset Distance of Multiple Targets in Single-isocenter Volumetric Modulated Arc Therapy Planning for Stereotactic Radiosurgery

Purpose

The purpose of the study is to investigate the impact of large target offset distances on the dose distribution and gamma passing rate (GPR) in single-isocenter multiple-target stereotactic radiosurgery (SIMT SRS) using volumetric modulated arc therapy (VMAT) with a flattening filter-free (FFF) beam from a linear accelerator.

Methods

Two targets with a diameter of 1 cm were offset by "±2, ±4, and ±6 cm from the isocenter in a verification phantom for head SRS (20 Gy/fr). The VMAT plans were created using collimator angles that ensured the two targets did not share a leaf pair from the multi-leaf collimator. To evaluate the low-dose spread intermediate dose spill (R50%), GPRs were measured with a criterion of 3%/2 mm using an electronic portal imaging device and evaluated using monitor unit (MU), modulation complexity score for VMAT (MCSv), and leaf travel (LT) parameters.

Results

For offsets of 2, 4, and 6 cm, the respective parameters were: R50%, 4.75 ± 0.36, 5.13 ± 0.36, and 5.11 ± 0.33; GPR, 95.01%, 93.82%, and 90.67%; MU, 5893 ± 186, 5825 ± 286, and 5810 ± 396; MCSv, 0.24, 0.16, and 0.13; and LT, 189.21 ± 36.04, 327.69 ± 67.01, and 430.39 ± 114.34 mm. There was a spread in the low-dose region from offsets of ≥4 cm and the GPR negatively correlated with LT (r = -0.762). There was minimal correlation between GPR and MU or MCSv.

Conclusions

In SIMT SRS VMAT plans with an FFF beam from a linear accelerator, target offsets of <4 cm from the isocenter can minimize the volume of the low-dose region receiving 10 Gy or more. During treatment planning, it is important to choose gantry, couch, and collimator angles that minimize LT and thereby improve the GPR.

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.

Locally advanced non-small cell lung cancer: current issues and recent trends

The focus of this paper was to review and summarise the current issues and recent trends within the framework of locally advanced (LA) non-small cell lung cancer (NSCLC). The recently proposed 8^th tumour-node-metastases (TNM) staging system exhibited significant amendments in the distribution of the T and M descriptors. Every revision to the TNM classification should contribute to clinical improvement. This is particularly necessary regarding LA NSCLC stratification, therapy and outcomes. While several studies reported the superiority of the 8^th TNM edition in comparison to the previous 7^th TNM edition, in terms of both the discrimination ability among the various T subgroups and clinical outcomes, others argued against this interpretation. Synergistic cytotoxic chemotherapy with radiotherapy is most prevalent in treating LA NSCLC. Clinical trial experience from multiple references has reported that the risk of locoregional relapse and distant metastasis was less evident for patients treated with concomitant radiochemotherapy than radiotherapy alone. Nevertheless, concern persists as to whether major incidences of toxicity may occur due to the addition of chemotherapy. Cutting-edge technologies such as four-dimensional computed tomography (4D-CT) and volumetric modulated arc therapy (VMAT) should yield therapeutic gains due to their capability to conform radiation doses to tumours. On the basis of the preceding notion, the optimum radiotherapy technique for LA NSCLC has been a controversial and much-disputed subject within the field of radiation oncology. Notably, no single-perspective research has been undertaken to determine the optimum radiotherapy modality for LA NSCLC. The landscape of immunotherapy in lung cancer is rapidly expanding. Currently, the standard of care for patients with inoperable LA NSCLC is concurrent chemoradiotherapy followed by maintenance durvalumab according to clinical outcomes from the PACIFIC trial. An estimated 42.9% of patients randomly assigned to durvalumab remained alive at five years, and free of disease progression, thereby establishing a new benchmark for the standard of care in this setting.

A virtual audit system for intensity-modulated radiation therapy credentialing in Japan Clinical Oncology Group clinical trials: A pilot study

PURPOSE

The Medical Physics Working Group of the Radiation Therapy Study Group at the Japan Clinical Oncology Group is currently developing a virtual audit system for intensity-modulated radiation therapy dosimetry credentialing. The target dosimeters include films and array detectors, such as ArcCHECK (Sun Nuclear Corporation, Melbourne, Florida, USA) and Delta4 (ScandiDos, Uppsala, Sweden). This pilot study investigated the feasibility of our virtual audit system using previously acquired data.

METHODS

We analyzed 46 films (32 and 14 in the axial and coronal planes, respectively) from 29 institutions. Global gamma analysis between measured and planned dose distributions used the following settings: 3%/3 mm criteria (the dose denominator was 2 Gy), 30% threshold dose, no scaling of the datasets, and 90% tolerance level. In addition, 21 datasets from nine institutions were obtained for array evaluation. Five institutions used ArcCHECK, while the others used Delta4. Global gamma analysis was performed with 3%/2 mm criteria (the dose denominator was the maximum calculated dose), 10% threshold dose, and 95% tolerance level. The film calibration and gamma analysis were conducted with in-house software developed using Python (version 3.9.2).

RESULTS

The means ± standard deviations of the gamma passing rates were 99.4 ± 1.5% (range, 92.8%-100%) and 99.2 ± 1.0% (range, 97.0%-100%) in the film and array evaluations, respectively.

CONCLUSION

This pilot study demonstrated the feasibility of virtual audits. The proposed virtual audit system will contribute to more efficient, cheaper, and more rapid trial credentialing than on-site and postal audits; however, the limitations should be considered when operating our virtual audit system.

Correlation between patient-specific quality assurance in volumetric modulated arc therapy and 2D dose image features

In radiotherapy, air-filled ion chamber detectors are ubiquitously used in routine dose measurements for treatment planning. However, its use has been restricted by intrinsic low spatial resolution barriers. We developed one procedure for patient-specific quality assurance (QA) in arc radiotherapy by coalescing two adjacent measurement images into a single image to improve spatial resolution and sampling frequency, and investigated how different spatial resolutions affect the QA results. PTW 729 and 1500 ion chamber detectors were used for dosimetric verification via coalescing two measurements with 5 mm-couch shift and the isocenter, and only isocenter measurement, which we call coalescence and standard acquisition (SA). Statistical process control (SPC), process capability analysis (PCA), and receiver operating characteristic (ROC) curve were used to compare the performance of the two procedures in determining tolerance levels and identifying clinically relevant errors. By analyzing 1256 γ values calculated on interpolated data points, our results indicated that detector 1500 showed higher averages in coalescence cohorts at different tolerance criteria and the dispersion degrees were spread out smaller. Detector 729 yielded a slightly lower process capability of 0.79, 0.76, 1.10, and 1.34, but detector 1500 exhibited somewhat different results of 0.94, 1.42, 1.19, and 1.60 in magnitude. The results of SPC individual control chart showed that cases in coalescence cohorts with γ values lowering its lower control limit (LCL) were greater than those in SA cohorts for detector 1500. A combination of the width of multi-leaf collimator (MLC) leaf, the cross-sectional area of the single detector, and the spacing between adjacent detectors might lead to discrepancies in percent γ values across diverse spatial resolution scenarios. The accuracy of reconstructed volume dose is mainly determined by the interpolation algorithm used in dosimetric systems. The magnitude of filling factor in the ion chamber detectors determined its ability to detect dose deviations. SPC and PCA results indicated that coalescence procedure could detect more potential failure QA results than SA while enhancing action thresholds.

EVALUATION OF PATIENT-SPECIFIC IMRT QUALITY ASSURANCE AND POINT DOSE MEASUREMENT FOR COMPLEX HEAD AND NECK AND BRAIN CANCER USING GAFCHROMIC EBT3 FILM

Patient-specific intensity-modulated radiation therapy (IMRT) quality assurance (QA) is essential for complex radiotherapy treatment as it involves complex intensity modulation and high-dose gradient regions. IMRT QA was performed by point dose verification and two-dimensional (2D) dose distribution measurement using gamma method. Calibrated External Beam Therapy 3 (EBT3) film was used for point dose and pre-treatment verification of 10 IMRT plans, five complex Head and Neck (HN) and five brain cases. The gamma passing rate (GPR) was evaluated for 3%/3 mm gamma criteria and compared with 2D array. Isocentre dose was measured for all 10 IMRT plans on EBT3 film. Percentage deviation of point dose measurement from TPS calculated was found 0.4% for brain cases and 2.9% for HN cases. The GPR for 3%/3 mm criteria was obtained higher than 95% for brain and HN cases. Results suggest that film dosimetry is also a reliable verification system for patient-specific IMRT QA as the 2D array.

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.

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.

Evaluating the effect of high-density measurement mode on patient-specific quality assurance for head and neck cancer with ArcCHECK

The high-density measurement (HDm) mode of the ArcCHECK device can achieve a twofold resolution enhancement compared to the standard measurement (Sm) mode. The aim of this study was to evaluate the effect of HDm on the gamma passing rate (GPR) for the patient-specific quality assurance (PSQA) in head and neck cancer. We retrospectively evaluated 30 patients who underwent volumetric modulated arc therapy (VMAT) for head and neck cancer. Absolute gamma analysis was performed on Sm and HDm data. We also investigated correlations between the modulation complexity score for VMAT (MCSv) and differences in the GPR between the two measurement modes. The global GPR of Sm and HDm was 81.0% ± 8.4% and 82.6% ± 7.6% for the 2%/2 mm criterion, 94.0% ± 4.1% and 94.9% ± 3.6% for the 3%/2 mm criterion, and 96.6% ± 2.4% and 97.0% ± 2.4% for the 3%/3 mm criterion, respectively. HDm slightly improved GPR (p < 0.01) for the 2%/2 mm criterion. Differences in GPR between Sm and HDm for the 2%/2 mm, 3%/2 mm, and 3%/3 mm criteria were 1.6% ± 3.0%, 0.8% ± 2.0%, and 0.4% ± 1.2%, respectively. No correlation was identified between the MCSv and the difference in GPR between Sm and HDm. Despite an improvement in GPR with HDm, the difference in GPR between Sm and HDm was approximately 2% even when the tighter criteria were used. Moreover, the change in the GPR between Sm and HDm did not depend on plan complexity. Thus, the effect of HDm on GPR is limited for the PSQA in VMAT for head and neck cancer.

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.

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.

Does CyberKnife improve dose distribution versus IMRT and VMAT on a linear accelerator in low-risk prostate cancer?

BACKGROUND

Hypofractionated stereotactic body radiation therapy (SBRT) for prostate cancer (PCa) can be delivered with the robot-assisted CyberKnife (CK) system or on a linear accelerator using dynamic intensity-modulated radiotherapy (IMRT) or volumetric arc radiotherapy (VMAT). This retrospective study was performed to determine whether CK offers better dose distribution than IMRT and/or VMAT.

MATERIALS AND METHODS

Treatment plans for three techniques were prepared using the same treatment parameters (36.35 Gy, 7.25 Gy/fr). We evaluated target coverage, conformity index (CI), homogeneity index (HI), gamma index (GI), and organs at risk (OAR) constraints.

RESULTS

The mean planning target volume (PTV) dose for CK (39.58 Gy) was significantly greater than VMAT or IMRT (both 36.25 Gy). However, CK resulted in a wider dose range (31.48 to 45.89 Gy) vs. VMAT and IMRT (34.6-38.76 Gy). The mean dose to the rectum (V36Gy, mm³) was significantly lower (p < 0.001) in the CK plans (219.78 vs. 519.59 and 422.62, respectively). The mean bladder dose (V37Gy, mm³) was significantly greater for CK (3256 vs. 1090.75 for VMAT and 4.5 for IMRT (p < 0.001). CK yielded significantly better CI (1.07 vs. 1.17 and 1.25 for VMAT and IMRT, respectively; p < 0.01) and HI values (1.27 vs. 1.07 and 1.04; p < 0.01). GI values for the δd = 3mm, δ% = 3% criteria were 99.86 (VMAT), 99.07 (IMRT) and 99.99 (CK). For δd = 2mm, δ% = 2%, the corresponding values were 98.3, 93.35, and 97.12, respectively.

CONCLUSIONS

For most variables, CK was superior to both VMAT and IMRT. However, dynamic IMRT techniques, especially VMAT, do not differ significantly from CK plans and are therefore acceptable alternatives to CyberKnife.

Modelling SPECT auto-contouring acquisitions for 177Lu & 131I molecular radiotherapy using new developments in Geant4/GATE

PURPOSE

Monte Carlo modelling of SPECT imaging in Molecular Radiotherapy can improve activity quantification. Until now, SPECT modelling with GATE only considered circular orbit (CO) acquisitions. This cannot reproduce auto-contour acquisitions, where the detector head moves close to the patient to improve image resolution. The aim of this work is to develop and validate an auto-contouring step-and-shoot acquisition mode for GATE SPECT modelling.

METHODS

¹⁷⁷Lu and ¹³¹I SPECT experimental acquisitions performed on a Siemens Symbia T2 and GE Discovery 670 gamma camera, respectively, were modelled. SPECT projections were obtained for a cylindrical Jaszczak phantom and a lung and spine phantom. Detector head parameters (radial positions and acquisition angles) were extracted from the experimental projections to model the non-circular orbit (NCO) detector motion. The gamma camera model was validated against the experimental projections obtained with the cylindrical Jaszczak (¹⁷⁷Lu) and lung and spine phantom (¹³¹I). Then, ¹⁷⁷Lu and ¹³¹I CO and NCO SPECT projections were simulated to validate the impact of explicit NCO modelling on simulated projections.

RESULTS

Experimental and simulated SPECT images were compared using the gamma index, and were in good agreement with gamma index passing rate (GIPR) and gamma_avg of 96.27%, 0.242 (¹⁷⁷Lu) and 92.89%, 0.36 (¹³¹I). Then, simulated ¹⁷⁷Lu and ¹³¹I CO and NCO SPECT projections were compared. The GIPR, gamma_avg between the two gamma camera motions was 99.85%, 0.108 for ¹⁷⁷Lu and 75.58%, 0.6 for ¹³¹I.

CONCLUSION

This work thereby justifies the need for auto-contouring modelling for isotopes with high septal penetration.

Development of a virtual source model for Monte Carlo-based independent dose calculation for varian linac

Monte Carlo (MC) independent dose calculations are often based on phase-space files (PSF), as they can accurately represent particle characteristics. PSF generally are large and create a bottleneck in computation time. In addition, the number of independent particles is limited by the PSF, preventing further reduction of statistical uncertainty. The purpose of this study is to develop and validate a virtual source model (VSM) to address these limitations. Particles from existing PSF for the Varian TrueBeam medical linear accelerator 6X, 6XFFF, 10X, and 10XFFF beam configurations were tallied, analyzed, and used to generate a dual-source photon VSM that includes electron contamination. The particle density distribution, kinetic energy spectrum, particle direction, and the correlations between characteristics were computed. The VSM models for each beam configuration were validated with water phantom measurements as well as clinical test cases against the original PSF. The new VSM requires 67 MB of disk space for each beam configuration, compared to 50 GB for the PSF from which they are based and effectively remove the bottleneck set by the PSF. At 3% MC uncertainty, the VSM approach reduces the calculation time by a factor of 14 on our server. MC doses obtained using the VSM approach were compared against PSF-generated doses in clinical test cases and measurements in a water phantom using a gamma index analysis. For all tests, the VSMs were in excellent agreement with PSF doses and measurements (>90% passing voxels between doses and measurements). Results of this study indicate the successful derivation and implementation of a VSM model for Varian Linac that significantly saves computation time without sacrificing accuracy for independent dose calculation.

A High-Throughput In Vitro Radiobiology Platform for Megavoltage Photon Linear Accelerator Studies

We designed and developed a multiwell tissue culture plate irradiation setup, and intensity modulated radiotherapy plans were generated for 96-, 24-, and 6-well tissue culture plates. We demonstrated concordance between planned and measured/imaged radiation dose profiles using radiochromic film, a 2D ion chamber array, and an electronic portal-imaging device. Cell viability, clonogenic potential, and g-H2AX foci analyses showed no significant differences between intensity-modulated radiotherapy and open-field, homogeneous irradiations. This novel platform may help to expedite radiobiology experiments within a clinical environment and may be used for wide-ranging ex vivo radiobiology applications.

Optimising tumour coverage and organ at risk sparing for hypofractionated re-irradiation in glioblastoma

BACKGROUND AND PURPOSE

Re-irradiation may be used for recurrent glioblastoma (GBM) patients. In some cases Planning Target Volume (PTV) under-coverage is necessary to meet organ at risk (OAR) constraints. This study aimed to develop a Volumetric Modulated Arc Therapy planning solution for GBM re-irradiation including a means of assessing if target coverage would be achievable and how much PTV 'cropping' would be required to meet OAR constraints, based on PTV volume and OAR proximity.

MATERIALS AND METHODS

For 10 PTVs, 360°, 180°, two coplanar 180° and 180° + non-coplanar 45° arc arrangements were compared using 35 Gy in 10 fractions. Using the preferred arrangement, dose fall-off was modelled to determine the separation required between PTV and OAR to ensure OAR dose constraints were met, with data presented graphically. To evaluate the graph as an aid to planning, seven cases with overlap were replanned in two treatment planning systems (TPSs).

RESULTS

There were no significant dosimetric differences between arc arrangements. 180° was preferred due to shorter treatment times. The graph, which indicated if 95% PTV coverage would be achievable based on PTV volume and OAR proximity, was employed in seven cases to guide planning in two TPSs. Plans were deliverable.

CONCLUSIONS

Re-irradiation treatment planning can be challenging, especially when PTV under-coverage is necessary. 180° was considered optimal. To assist in the planning process, graphical guidance was produced to inform planners whether PTV under-coverage would be necessary and how much PTV 'cropping' would be required to meet constraints during optimisation.

Ultra-Hypofractionated Proton Therapy in Localized Prostate Cancer: Passive Scattering versus Intensity-Modulated Proton Therapy

Few studies have directly compared passive scattering (PS) to intensity-modulated proton therapy (IMPT) in the delivery of ultra-hypofractionated proton beams to the localized prostate cancer (PCa). In this preliminary study involving five patients previously treated with CyberKnife, treatment plans were created for PS and IMPT (36.25 CGE in five fractions with two opposing fields) to compare the dosimetric parameters to the planning target volume (PTV) and organs-at-risk (OAR: rectum, bladder, femoral heads). Both plans met the acceptance criteria. Significant differences were observed in the minimum and maximum doses to the PTV. The mean dose to the PTV was lower for PS (35.62 ± 0.26 vs. 37.18 ± 0.14; p = 0.002). Target coverage (D98%) was better for IMPT (96.79% vs. 99.10%; p = 0.004). IMPT resulted in significantly lower mean doses to the rectum (16.75 CGE vs. 6.88 CGE; p = 0.004) and bladder (17.69 CGE vs. 5.98 CGE p = 0.002). High dose to the rectum (V36.25 CGE) were lower with PS, but not significantly opposite to high dose to the bladder. No significant differences were observed in mean conformity index values, with a non-significant trend towards higher mean homogeneity index values for PS. Non-significant differences in the gamma index for both fields were observed. These findings suggest that both PS and IMPT ultra-hypofractionated proton therapy for PCa are highly precise, offering good target coverage and sparing of normal tissues and OARs.

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.

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.

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.

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.

Define dose field to assess the modulation complexity of intensity-modulated radiation therapy

PURPOSE

Introduce a new concept of dose field to assess the modulation complexity (MC) of intensity-modulated radiation therapy (IMRT).

METHODS

A total of 91 IMRT plans for different diseases were retrospectively retrieved randomly from treatment database. The dose field of plans were calculated and feature values such as force magnitude and diversity were defined and extracted. Correlation analysis between these feature values and execution cost, delivery accuracy of plans was performed, to verify the validity of dose field in characterizing the MC.

RESULTS

The feature values of dose field in different disease own significant differences (p < 0.001). For correlation analysis, number of control point (CP) and cumulative perimeter of CP have the highest correlation with angle entropy (0.815 and 0.848 respectively), while the correlation between number of monitor units(MU), cumulative area of CP and force, force entropy is higher than others (0.797-0.909). However, complexity of CP shape is almost irrelevant to all the dose field features. The gamma passing rate and the dose field features shows a weak negative correlation trend.

CONCLUSIONS

Dose field can be used as a tool to assess the MC of IMRT.

AAPM Task Group 198 Report: An implementation guide for TG 142 quality assurance of medical accelerators

The charges on this task group (TG) were as follows: (a) provide specific procedural guidelines for performing the tests recommended in TG 142; (b) provide estimate of the range of time, appropriate personnel, and qualifications necessary to complete the tests in TG 142; and (c) provide sample daily, weekly, monthly, or annual quality assurance (QA) forms. Many of the guidelines in this report are drawn from the literature and are included in the references. When literature was not available, specific test methods reflect the experiences of the TG members (e.g., a test method for door interlock is self-evident with no literature necessary). In other cases, the technology is so new that no literature for test methods was available. Given broad clinical adaptation of volumetric modulated arc therapy (VMAT), which is not a specific topic of TG 142, several tests and criteria specific to VMAT were added.

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.

Intrinsic detector sensitivity analysis as a tool to characterize ArcCHECK and EPID sensitivity to variations in delivery for lung SBRT VMAT plans

PURPOSE

To investigate intrinsic sensitivity of an electronic portal imaging device (EPID) and the ArcCHECK detector and to use this in assessing their performance in detecting delivery variations for lung SBRT VMAT. The effect of detector spatial resolution and dose matrix interpolation on the gamma pass rate was also considered.

MATERIALS AND METHODS

Fifteen patients' lung SBRT VMAT plans were used. Delivery variations (errors) were introduced by modifying collimator angles, multi-leaf collimator (MLC) field sizes and MLC field shifts by ±5, ±2, and ±1 degrees or mm (investigating 103 plans in total). EPID and ArcCHECK measured signals with introduced variations were compared to measured signals without variations (baseline), using OmniPro-I'mRT software and gamma criteria of 3%/3 mm, 2%/2 mm, 2%/1 mm, and 1%/1 mm, to test each system's basic performance. The measurement sampling resolution for each was also changed to 1 mm and results compared to those with the default detector system resolution.

RESULTS

Intrinsic detector sensitivity analysis, that is, comparing measurement to baseline measurement, rather than measurement to plan, demonstrated the intrinsic constraints of each detector and indicated the limiting performance that users might expect. Changes in the gamma pass rates for ArcCHECK, for a given introduced error, were affected only by dose difference (DD %) criteria. However, the EPID showed only slight changes when changing DD%, but greater effects when changing distance-to-agreement criteria. This is pertinent for lung SBRT where the minimum dose to the target will drop dramatically with geometric errors. Detector resolution and dose matrix interpolation have an impact on the gamma results for these SBRT plans and can lead to false positives or negatives in error detection if not understood.

CONCLUSION

The intrinsic sensitivity approach may help in the selection of more meaningful gamma criteria and the choice of optimal QA device for site-specific dose verification.

Generation of clinical 177Lu SPECT/CT images based on Monte Carlo simulation with GATE

PURPOSE

Patient-specific dosimetry in MRT relies on quantitative imaging, pharmacokinetic assessment and absorbed dose calculation. The DosiTest project was initiated to evaluate the uncertainties associated with each step of the clinical dosimetry workflow through a virtual multicentric clinical trial. This work presents the generation of simulated clinical SPECT datasets based on GATE Monte Carlo modelling with its corresponding experimental CT image, which can subsequently be processed by commercial image workstations.

METHODS

This study considers a therapy cycle of 6.85 GBq ¹⁷⁷Lu-labelled DOTATATE derived from an IAEA-Coordinated Research Project (E23005) on "Dosimetry in Radiopharmaceutical therapy for personalised patient treatment". Patient images were acquired on a GE Infinia-Hawkeye 4 gamma camera using a medium energy (ME) collimator. Simulated SPECT projections were generated based on experimental time points and validated against experimental SPECT projections using flattened profiles and gamma index. The simulated projections were then incorporated into the patient SPECT/CT DICOM envelopes for processing and their reconstruction within a commercial image workstation.

RESULTS

Gamma index passing rate (2% - 1 pixel criteria) between 95 and 98% and average gamma between 0.28 and 0.35 among different time points revealed high similarity between simulated and experimental images. Image reconstruction of the simulated projections was successful on HERMES and Xeleris workstations, a major step forward for the initiation of a multicentric virtual clinical dosimetry trial based on simulated SPECT/CT images.

CONCLUSIONS

Realistic ¹⁷⁷Lu patient SPECT projections were generated in GATE. These modelled datasets will be circulated to different clinical departments to perform dosimetry in order to assess the uncertainties in the entire dosimetric chain.

Measuring the dose in bone for spine stereotactic body radiotherapy

PURPOSE

Current quality assurance of radiotherapy involving bony regions generally utilises homogeneous phantoms and dose calculations, ignoring the challenges of heterogeneities with dosimetry problems likely occurring around bone. Anthropomorphic phantoms with synthetic bony materials enable realistic end-to-end testing in clinical scenarios. This work reports on measurements and calculated corrections required to directly report dose in bony materials in the context of comprehensive end-to-end dosimetry audit measurements (63 plans, 6 planning systems).

MATERIALS AND METHODS

Radiochromic film and microDiamond measurements were performed in an anthropomorphic spine phantom containing bone equivalent materials. Medium dependent correction factors, k_med, were established using 6 MV and 10 MV Linear Accelerator Monte Carlo simulations to account for the detectors being calibrated in water, but measuring in regions of bony material. Both cortical and trabecular bony material were investigated for verification of dose calculations in dose-to-medium (D_m,m) and dose-to-water (D_w,w) scenarios.

RESULTS

For D_m,m calculations, modelled correction factors for cortical and trabecular bone in film measurements, and for trabecular bone in microDiamond measurements were 0.875(±0.1%), 0.953(±0.3%) and 0.962(±0.4%), respectively. For D_w,w calculations, the corrections were 0.920(±0.1%), 0.982(±0.3%) and 0.993(±0.4%), respectively. In the audit, application of the correction factors improves the mean agreement between treatment plans and measured microDiamond dose from -2.4%(±3.9%) to 0.4%(±3.7%).

CONCLUSION

Monte Carlo simulations provide a method for correcting the dose measured in bony materials allowing more accurate comparison with treatment planning system doses. In verification measurements, algorithm specific correction factors should be applied to account for variations in bony material for calculations based on D_m,m and D_w,w.

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.

Simplification of head and neck volumetric modulated arc therapy patient-specific quality assurance, using a Delta4 PT

Background/Aim

In many facilities, intensity-modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT) use intensity-modulated beams, formed by a multi-leaf collimator (MLC). In IMRT and VMAT, MLC and linear accelerator errors (both geometric and dose), can significantly affect the doses administered to patients. Therefore, IMRT and VMAT treatment plans must include the use of patient-specific quality assurance (QA) before treatment to confirm dose accuracy.

Materials and methods

In this study, we compared and analyzed the results of dose verification using a multi-dimensional dose verification system Delta4 PT, an ionization chamber dosimeter, and gafchromic film, using data from 52 patients undergoing head and neck VMAT as the test material.

Result

Based on the results of the absolute dose verification for the ionization chamber dosimeter and Delta4 PT, taking an axial view, the upper limit of the 95% confidence interval was 3.13%, and the lower limit was -3.67%, indicating good agreement. These results mean that as long as absolute dose verification for the axial view does not deviate from this range, Delta4 PT can be used as an alternative to an ionization chamber dosimeter for absolute dose verification. When we then reviewed dose distribution verification, the pass rate for Delta4 PT was acceptable, and was less varied than that of gafchromic film.

Conclusion

This results in that provided the pass rate result for Delta4 PT does not fall below 96%, it can be used as a substitute for gafchromic film in dose distribution verification. These results indicate that patient-specific QA could be simplified.