Incorporating plan complexity into the statistical process control of volumetric modulated arc therapy pre-treatment verifications

BACKGROUND

Statistical process control (SPC) is a powerful statistical tool for process monitoring that has been highly recommended in healthcare applications, including radiation therapy quality assurance (QA). The AAPM TG-218 report described the clinical implementation of SPC for Volumetric Modulated Arc Therapy (VMAT) pre-treatment verifications, pointing out the need to adjust tolerance limits based on plan complexity. However, the quantification of plan complexity and its integration into SPC remains an unresolved challenge.

PURPOSE

The primary aim of this study is to investigate the incorporation of plan complexity into the SPC framework for VMAT pre-treatment verifications. The study explores and evaluates various strategies for this incorporation, discussing their merits and limitations, and provides recommendations for clinical application.

METHODS

A retrospective analysis was conducted on 309 VMAT plans from diverse anatomical sites using the PTW OCTAVIUS 4D device for QA measurements. Gamma Passing Rates (GPR) were obtained, and lower control limits were computed using both the conventional Shewhart method and three heuristic methods (scaled weighted variance, weighted standard deviations, and skewness correction) to accommodate non-normal data distributions. The 'Identify-Eliminate-Recalculate' method was employed for robust analysis. Eight complexity metrics were analyzed and two distinct strategies for incorporating plan complexity into SPC were assessed. The first strategy focused on establishing control limits for different treatment sites, while the second was based on the determination of control limits as a function of individual plan complexity. The study extensively examines the correlation between control limits and plan complexity and assesses the impact of complexity metrics on the control process.

RESULTS

The control limits established using SPC were strongly influenced by the complexity of treatment plans. In the first strategy, a clear correlation was found between control limits and average plan complexity for each site. The second approach derived control limits based on individual plan complexity metrics, enabling tailored tolerance limits. In both strategies, tolerance limits inversely correlated with plan complexity, resulting in all highly complex plans being classified as in control. In contrast, when plans were collectively analyzed without considering complexity, all the out-of-control plans were highly complex.

CONCLUSIONS

Incorporating plan complexity into SPC for VMAT verifications requires meticulous and comprehensive analysis. To ensure overall process control, we advocate for stringent control and minimization of plan complexity during treatment planning, especially when control limits are adjusted based on plan complexity.

Radiochromic film dosimetry in radiotherapy: a survey of current practice in the United Kingdom

OBJECTIVES

To establish the variation in film dosimetry usage in radiotherapy centres across the United Kingdom. To identify consensus and highlight areas of potential improvement to enhance radiotherapy dosimetry verification with film.

METHODS

A survey questionnaire was designed by members of the Institute of Physics and Engineering in Medicine Interdepartmental Dosimetry Audit Group via Microsoft Forms and distributed to all Heads of Radiotherapy Physics in the United Kingdom. The survey was open from June 19, 2023, to July 31, 2023.

RESULTS

Forty responses were received from the 62 radiotherapy centres in the United Kingdom, of which 58% were currently using film dosimetry and a further 7 were keen to commence use. Many reported film use had decreased in recent years but was still valuable particularly for commissioning and implementing new techniques. The variation and consensus of methods for film dosimetry calibration, measurement, and application was established. A review of barriers to implementation and methods to reduce uncertainty were included in the assessment.

CONCLUSIONS

A comprehensive assessment of film dosimetry usage in radiotherapy in the United Kingdom has been collated, which demonstrates a wide variation in methods, across typical clinical users, but maintains film as a valuable dosimetry option.

ADVANCES IN KNOWLEDGE

This research provides a snapshot of current film dosimetry use across the United Kingdom. It examines the variation and consensus of practice to which individual users can compare their systems, and identifies opportunities to improvement in the accuracy of film dosimetry.

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.

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.

Pretreatment patient-specific quality assurance prediction based on 1D complexity metrics and 3D planning dose: classification, gamma passing rates, and DVH metrics

PURPOSE

Highly modulated radiotherapy plans aim to achieve target conformality and spare organs at risk, but the high complexity of the plan may increase the uncertainty of treatment. Thus, patient-specific quality assurance (PSQA) plays a crucial role in ensuring treatment accuracy and providing clinical guidance. This study aims to propose a prediction model based on complexity metrics and patient planning dose for PSQA results.

MATERIALS AND METHODS

Planning dose, measurement-based reconstructed dose and plan complexity metrics of the 687 radiotherapy plans of patients treated in our institution were collected for model establishing. Global gamma passing rate (GPR, 3%/2mm,10% threshold) of 90% was used as QA criterion. Neural architecture models based on Swin-transformer were adapted to process 3D dose and incorporate 1D metrics to predict QA results. The dataset was divided into training (447), validation (90), and testing (150) sets. Evaluation of predictions was performed using mean absolute error (MAE) for GPR, planning target volume (PTV) HI and PTV CI, mean absolute percentage error (MAPE) for PTV D95, PTV D2 and PTV Dmean, and the area under the receiver operating characteristic (ROC) curve (AUC) for classification. Furthermore, we also compare the prediction results with other models based on either only 1D or 3D inputs.

RESULTS

In this dataset, 72.8% (500/687) plans passed the pretreatment QA under the criterion. On the testing set, our model achieves the highest performance, with the 1D model slightly surpassing the 3D model. The performance results are as follows (combine, 1D, and 3D transformer): The AUCs are 0.92, 0.88 and 0.86 for QA classification. The MAEs of prediction are 0.039, 0.046, and 0.040 for 3D GPR, 0.018, 0.021, and 0.019 for PTV HI, and 0.075, 0.078, and 0.084 for PTV CI. Specifically, for cases with 3D GPRs greater than 90%, the MAE could achieve 0.020 (combine). The MAPE of prediction is 1.23%, 1.52%, and 1.66% for PTV D95, 2.36%, 2.67%, and 2.45% for PTV D2, and 1.46%, 1.70%, and 1.71% for PTV Dmean.

CONCLUSION

The model based on 1D complexity metrics and 3D planning dose could predict pretreatment PSQA results with high accuracy and the complexity metrics play a leading role in the model. Furthermore, dose-volume metric deviations of PTV could be predicted and more clinically valuable information could be provided.

Sensitivity and specificity of Monte Carlo based independent secondary dose computation for detecting modulation-related dose errors in intensity modulated radiotherapy

BACKGROUND

The recent availability of Monte Carlo based independent secondary dose calculation (ISDC) for patient-specific quality assurance (QA) of modulated radiotherapy requires the definition of appropriate, more sensitive action levels, since contemporary recommendations were defined for less accurate ISDC dose algorithms.

PURPOSE

The objective is to establish an optimum action level and measure the efficacy of a Monte Carlo ISDC software for pre-treatment QA of intensity modulated radiotherapy treatments.

METHODS

The treatment planning system and the ISDC were commissioned by their vendors from independent base data sets, replicating a typical real-world scenario. In order to apply Receiver-Operator-Characteristics (ROC), a set of treatment plans for various case classes was created that consisted of 190 clinical treatment plans and 190 manipulated treatment plans with dose errors in the range of 1.5-2.5%. All 380 treatment plans were evaluated with ISDC in the patient geometry. ROC analysis was performed for a number of Gamma (dose-difference/distance-to-agreement) criteria. QA methods were ranked according to Area under the ROC curve (AUC) and optimum action levels were derived via Youden's J statistics.

RESULTS

Overall, for original treatment plans, the mean Gamma pass rate (GPR) for Gamma(1%, 1 mm) was close to 90%, although with some variation across case classes. The best QA criterion was Gamma(2%, 1 mm) with GPR > 90% and an AUC of 0.928. Gamma criteria with small distance-to-agreement had consistently higher AUC. GPR of original treatment plans depended on their modulation degree. An action level in terms of Gamma(1%, 1 mm) GPR that decreases with modulation degree was the most efficient criterion with sensitivity = 0.91 and specificity = 0.95, compared with Gamma(3%, 3 mm) GPR > 99%, sensitivity = 0.73 and specificity = 0.91 as a commonly used action level.

CONCLUSIONS

ISDC with Monte Carlo proves highly efficient to catch errors in the treatment planning process. For a Monte Carlo based TPS, dose-difference criteria of 2% or less, and distance-to-agreement criteria of 1 mm, achieve the largest AUC in ROC analysis.

Image-based features in machine learning to identify delivery errors and predict error magnitude for patient-specific IMRT quality assurance

OBJECTIVE

To identify delivery error type and predict associated error magnitude by image-based features using machine learning (ML).

METHODS

In this study, a total of 40 thoracic plans (including 208 beams) were selected, and four error types with different magnitudes were introduced into the original plans, including 1) collimator misalignment (COLL), 2) monitor unit (MU) variation, 3) systematic multileaf collimator misalignment (MLCS), and 4) random MLC misalignment (MLCR). These dose distributions of portal dose predictions for the original plans were defined as the reference dose distributions (RDD), while those for the error-introduced plans were defined as the error-introduced dose distributions (EDD). Both distributions were calculated for all beams with portal dose image prediction (PDIP). Besides, 14 image-based features were extracted from RDD and EDD of portal dose predictions to obtain the feature vectors. In addition, a random forest was adopted for the multiclass classification task, and regression prediction for error magnitude.

RESULTS

The top five features extracted with the highest weight included 1) the relative displacement in the x direction, 2) the ratio of the absolute minimum residual error to the maximal RDD value, 3) the product of the maximum and minimum residuals, 4) the ratio of the absolute maximum residual error to the maximal RDD value, and 5) the ratio of the absolute mean residual value to the maximal RDD value. The relative displacement in the x direction had the highest weight. The overall accuracy of the five-class classification model was 99.85% for the validation set and 99.30% for the testing set. This model could be applied to the classification of the error-free plan, COLL, MU, MLCS, and MLCR with an accuracy of 100%, 98.4%, 99.9%, 98.0%, and 98.3%, respectively. MLCR had the worst performance in error magnitude prediction (70.1-96.6%), while others had better performance in error magnitude prediction (higher than 93%). In the error magnitude prediction, the mean absolute error (MAE) between predicted error magnitude and actual error ranged from 0.03 to 0.33, with the root mean squared error (RMSE) varying from 0.17 to 0.56 for the validation set. The MAE and RMSE ranged from 0.03 to 0.50 and 0.44 to 0.59 for the test set, respectively.

CONCLUSION

It could be demonstrated in this study that the image-based features extracted from RDD and EDD can be employed to identify different types of delivery errors and accurately predict error magnitude with the assistance of ML techniques. They can be used to associate traditional gamma analysis with clinically based analysis for error classification and magnitude prediction in patient-specific IMRT quality assurance.

A hybrid method to improve efficiency of patient specific SRS and SBRT QA using 3D secondary dose verification

PURPOSE

Patient Specific QA (PSQA) by direct phantom measurement for all intensity modulated radiation therapy (IMRT) cases is labor intensive and an inefficient use of the Medical Physicist's time. The purpose of this work was to develop a hybrid quality assurance (QA) technique utilizing 3D dose verification as a screening tool to determine if a measurement is necessary.

METHODS

This study utilized Sun Nuclear DoseCHECK (DC), a 3D secondary verification software, and Fraction 0, a trajectory log IMRT QA software. Twenty-two Lung stereotactic body radiation therapy (SBRT) and thirty single isocentre multi-lesion SRS (MLSRS) plans were retrospectively analysed in DC. Agreement of DC and the TPS dose for selected dosimetric criteria was recorded. Calculated 95% confidence limits (CL) were used to establish action limits. All cases were delivered and measured using the Sun Nuclear stereotactic radiosurgery (SRS) MapCheck. Trajectory logs of the delivery were used to calculate Fraction 0 results for the same criteria calculated by DC. Correlation of DC and Fraction 0 results were calculated. Phantom measured QA was compared to Fraction 0 QA results for the cases which had DC criteria action limits exceeded.

RESULTS

Correlation of DC and Fraction 0 results were excellent, demonstrating the same action limits could be used for both and DC can predict Fraction 0 results. Based on the calculated action limits, zero lung SBRT cases and six MLSRS cases were identified as requiring a measurement. All plans that passed the DC screening had a passing measurement based PSQA and agreed with Fraction 0 results.

CONCLUSION

Using 95% CL action limits of dosimetric criteria, a 3D secondary dose verification can be used to determine if a measurement is required for PSQA. This method is efficient for it is part of the normal clinical workflow when verifying any clinical treatment. In addition, it can drastically reduce the number of measurements needed for PSQA.

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

BACKGROUND

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A clinically relevant online patient QA solution with daily CT scans and EPID-based in vivo dosimetry: a feasibility study on rectal cancer

Objective. Adaptive radiation therapy (ART) could protect organs at risk (OARs) while maintain high dose coverage to targets. However, there is still a lack of efficient online patient quality assurance (QA) methods, which is an obstacle to large-scale adoption of ART. We aim to develop a clinically relevant online patient QA solution for ART using daily CT scans and EPID-based in vivo dosimetry. Approach. Ten patients with rectal cancer at our center were included. Patients’ daily CT scans and portal images were collected to generate reconstructed 3D dose distributions. Contours of targets and OARs were recontoured on these daily CT scans by a clinician or an auto-segmentation algorithm, then dose-volume indices were calculated, and the percent deviation of these indices to their original plans were determined. This deviation was regarded as the metric for clinically relevant patient QA. The tolerance level was obtained using a 95% confidence interval of the QA metric distribution. These deviations could be further divided into anatomically relevant or delivery relevant indicators for error source analysis. Finally, our QA solution was validated on an additional six clinical patients. Main results. In rectal cancer, the 95% confidence intervals of the QA metric for PTV ΔD 95 (%) were [−3.11%, 2.35%], and for PTV ΔD 2 (%) were [−0.78%, 3.23%]. In validation, 68% for PTV ΔD 95 (%), and 79% for PTV ΔD 2 (%) of the 28 fractions are within tolerances of the QA metrics. one patient’s dosimetric impact of anatomical variations during treatment were observed through the source of error analysis. Significance. The online patient QA solution using daily CT scans and EPID-based in vivo dosimetry is clinically feasible. Source of error analysis has the potential for distinguishing sources of error and guiding ART for future treatments.

Comprehensive clinical evaluation of TomoEQA for patient-specific pre-treatment quality assurance in helical tomotherapy

Background

Based on a previous study on the feasibility of TomoEQA, an exit detector-based patient-specific pre-treatment quality assurance (QA) method for helical tomotherapy, an in-depth clinical evaluation was conducted.

Methods

Data of one hundred patients were analyzed to evaluate the clinical usefulness of TomoEQA for patient-specific pre-treatment QA in comparison with the conventional phantom-based method. Additional investigations were also performed under unusual measurement conditions to validate the off-axis region. In addition to the clinical evaluation of TomoEQA, a statistical analysis was conducted to determine the plan parameters that affect the pass/failure results of pre-treatment QA.

Results

The average and standard deviations of the gamma passing rate and point dose error for TomoEQA were comparable to those of the conventional QA method. For TomoEQA, the average values of the gamma passing rate and point dose error were 96.32% (standard deviation (1 sigma) = 3.94; 95% confidence interval (CI), 95.55 to 97.09) and − 1.12% (standard deviation (1 sigma) = 1.04; CI, − 1.32 to − 0.92), respectively. For the conventional QA method, the average values of the gamma passing rate and point dose error were 95.95% (standard deviation (1 sigma) = 4.35; 95% confidence interval (CI), 95.10 to 96.80) and − 1.20% (standard deviation (1 sigma) = 1.61; CI, − 1.52 to − 0.88), respectively. Further experiments on the off-axis region demonstrated that TomoEQA can provide accurate results for 3D dose analysis, which is inherently difficult in the conventional QA method. Through a statistical analysis based on the results of TomoEQA, it was validated that the total fraction (Total Fx), monitor units, beam-on-time, leaf-of-time below 100 ms, and planning target volume diameter were statistically significant for the pass/failure of the pre-treatment QA results.

Conclusions

TomoEQA is a clinically beneficial alternative to the conventional phantom-based QA method.

What is the optimal input information for deep learning-based pre-treatment error identification in radiotherapy?

•

The choice of dose comparison method impacts deep learning error identification accuracy most.

•

Simple dose comparison methods are more beneficial than gamma analysis and alternative methods.

•

Mean/standard deviation normalization and high image resolution improve error identification.

Background and purpose

Deep learning (DL) provides high sensitivity for detecting and identifying errors in pre-treatment radiotherapy quality assurance (QA). This work’s objective was to systematically evaluate the impact of different dose comparison and image preprocessing methods on DL model performance for error identification in pre-treatment QA.

Materials and methods

For 53 volumetric modulated arc therapy (VMAT) and 69 stereotactic body radiotherapy (SBRT) treatment plans of lung cancer patients, mechanical errors were simulated (MLC leaf positions, monitor unit scaling, collimator rotation). Two classification levels were assessed: error type (Level 1) and error magnitude (Level 2). Portal dose images with and without errors were compared using standard (gamma analysis), simple (absolute/relative dose difference, ratio) and alternative (distance-to-agreement, structural similarity index, gradient) dose comparison methods. For preprocessing, different normalization methods (min/max and mean/standard deviation) and image resolutions (32 × 32, 64 × 64 and 128 × 128) were evaluated. All possible combinations of classification level, dose comparison, normalization method and image size resulted in 144 input datasets for DL networks for error identification.

Results

Average accuracy was highest for simple dose comparison methods (Level 1: 97.7%, Level 2: 78.1%) while alternative methods scored lowest (Level 1: 91.6%, Level 2: 71.2%). Mean/stdev normalization particularly improved Level 2 classification. Higher image resolution improved error identification, although for SBRT lower image resolution was also sufficient.

Conclusions

The choice of dose comparison method has the largest impact on error identification for pre-treatment QA using DL, compared to image preprocessing. Model performance can improve by using simple dose comparison methods, mean/stdev normalization and high image resolution.

Artificial intelligence in radiotherapy

Radiotherapy is a discipline closely integrated with computer science. Artificial intelligence (AI) has developed rapidly over the past few years. With the explosive growth of medical big data, AI promises to revolutionize the field of radiotherapy through highly automated workflow, enhanced quality assurance, improved regional balances of expert experiences, and individualized treatment guided by multi-omics. In addition to independent researchers, the increasing number of large databases, biobanks, and open challenges significantly facilitated AI studies on radiation oncology. This article reviews the latest research, clinical applications, and challenges of AI in each part of radiotherapy including image processing, contouring, planning, quality assurance, motion management, and outcome prediction. By summarizing cutting-edge findings and challenges, we aim to inspire researchers to explore more future possibilities and accelerate the arrival of AI radiotherapy.

AAPM MEDICAL PHYSICS PRACTICE GUIDELINE 5.b: Commissioning and QA of treatment planning dose calculations-Megavoltage photon and electron beams

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education, and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guidelines and technical standards by those entities not providing these services is not authorized. The following terms are used in the AAPM practice guidelines:

Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. While must is the term to be used in the guidelines, if an entity that adopts the guideline has shall as the preferred term, the AAPM considers that must and shall have the same meaning.

Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances.

Transit-guided radiation therapy: proof of concept of an on-line technique for correcting position errors using transit portal images

Objective. Transit in vivo dosimetry methods monitor that the dose distribution is delivered as planned. However, they have a limited ability to identify and to quantify the cause of a given disagreement, especially those caused by position errors. This paper describes a proof of concept of a simple in vivo technique to infer a position error from a transit portal image (TPI). Approach. For a given treatment field, the impact of a position error is modeled as a perturbation of the corresponding reference (unperturbed) TPI. The perturbation model determines the patient translation, described by a shift vector, by comparing a given in vivo TPI to the corresponding reference TPI. Patient rotations can also be determined by applying this formalism to independent regions of interest over the patient. Eight treatment plans have been delivered to an anthropomorphic phantom under a large set of couch shifts (<15 mm) and rotations (<10°) to experimentally validate this technique, which we have named Transit-Guided Radiation Therapy (TGRT). Main results. The root mean squared error (RMSE) between the determined and the true shift magnitudes was 1.0/2.4/4.9 mm for true shifts ranging between 0–5/5–10/10–15 mm, respectively. The angular accuracy of the determined shift directions was 12° ± 14°. The RMSE between the determined and the true rotations was 0.5°. The TGRT technique decoupled translations and rotations satisfactorily. In 96% of the cases, the TGRT technique decreased the existing position error. The detection threshold of the TGRT technique was around 1 mm and it was nearly independent of the tumor site, delivery technique, beam energy or patient thickness. Significance. TGRT is a promising technique that not only provides reliable determinations of the position errors without increasing the required equipment, acquisition time or patient dose, but it also adds on-line correction capabilities to existing methods currently using TPIs.

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%.

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.

Dosimetric assessment of patient dose calculation on a deep learning-based synthesized computed tomography image for adaptive radiotherapy

Purpose

Dose computation using cone beam computed tomography (CBCT) images is inaccurate for the purpose of adaptive treatment planning. The main goal of this study is to assess the dosimetric accuracy of synthetic computed tomography (CT)‐based calculation for adaptive planning in the upper abdominal region. We hypothesized that deep learning‐based synthetically generated CT images will produce comparable results to a deformed CT (CTdef) in terms of dose calculation, while displaying a more accurate representation of the daily anatomy and therefore superior dosimetric accuracy.

Methods

We have implemented a cycle‐consistent generative adversarial networks (CycleGANs) architecture to synthesize CT images from the daily acquired CBCT image with minimal error. CBCT and CT images from 17 liver stereotactic body radiation therapy (SBRT) patients were used to train, test, and validate the algorithm.

Results

The synthetically generated images showed increased signal‐to‐noise ratio, contrast resolution, and reduced root mean square error, mean absolute error, noise, and artifact severity. Superior edge matching, sharpness, and preservation of anatomical structures from the CBCT images were observed for the synthetic images when compared to the CTdef registration method. Three verification plans (CBCT, CTdef, and synthetic) were created from the original treatment plan and dose volume histogram (DVH) statistics were calculated. The synthetic‐based calculation shows comparatively similar results to the CTdef‐based calculation with a maximum mean deviation of 1.5%.

Conclusions

Our findings show that CycleGANs can produce reliable synthetic images for the adaptive delivery framework. Dose calculations can be performed on synthetic images with minimal error. Additionally, enhanced image quality should translate into better daily alignment, increasing treatment delivery accuracy.

Remote sensing array (RSA) for linac beam monitoring

The purpose of the present work is to evaluate the feasibility of a novel real-time beam monitoring device for medical linacs which remotely senses charge carriers produced in air by the beam without intersecting and attenuating the beamline. The primary goal is to elaborate a theoretical concept of a possible detector geometry and underlying physical model that allows for determination of clinically relevant beam data in real time, namely MLC leaf positions and dose rate. The detector consists of two opposing electrode arrays arranged in two possible orientations around the beamline. Detection of charge carriers is governed by electromagnetic principles described by Shockley–Ramo theorem. Ions produced by ionization of the air column upstream of patient move laterally in an external electric field. According to the method of images, mirror charges and mirror currents are formed in the strip electrodes. Determination of MU rate and MLC positions using the measured signal requires solution of an inverse problem. In the present work we adopted a Least-Square approach and characterized detector response and sensitivity to detection of beam properties for different electrode geometries and MLC shapes. Results were dependent on MLC field shape and the leaf position within the active volume. The accuracy of determination of leaf positions were in the sub-mm range (up to 0.25–1 mm). Additionally, detector sensitivity was quantified by simulating ions/pulse delivered with a radiation transport deterministic computation in 1D in CEPXS/ONEDANT. For a 6 MV linac pulse, signal amplitude per pulse was estimated to be in the lower pA to fA range. We computationally demonstrated feasibility of the remote sensing detector capable of measuring beam parameters such as MLC leaf positions and dose range for each pulse. Future work should focus on optimizing the electrode geometry to increase sensitivity and better reconstruction algorithms to provide more accurate solutions of the inverse problem.

Sensitivity of Three Patient-Specific Quality Assurance Systems to MLC Aperture Errors With Volumetric Modulated Arc Therapy

Purpose: To compare the sensitivity of ArcCHECK (AC), portal dosimetry (PD), and an in-house logfile-based system (LF) to multileaf collimators (MLC) aperture errors and the ability to identify these errors. Methods and Materials: For 12 retrospective original head and neck volumetric modulated arc therapy (VMAT) plans, MLC aperture errors of ± 0.4mm, ± 1.2mm, ± 2mm, and ± 3mm were introduced for each plan, resulting in 96 plans with errors. AC, PD, and LF were used for the gamma evaluation at 3%/3mm, 3%/2mm, and 2%/2mm criteria. Gradient analysis was used to evaluate the sensitivity to MLC aperture errors. The area under the curve (AUC) obtained from the receiver operating characteristic (ROC) curve was used to evaluate the ability to identify MLC aperture errors and dose errors, and the optimal cut-off value to identify the error was obtained. Results: The gamma pass rate (%GP) of LF had the smallest descent gradient as the MLC error increases in any case. The descent gradient of PD was larger than AC, except for the case at the 2%/2mm criteria. For the 3%/3mm criteria, the MLC aperture errors that can be perfectly identified by AC, PD, and LF were ± 3mm, ± 2mm, and ± 1.2mm, respectively, and the average percent dose error (%DEs) of dose metrics in targets that can be perfectly identified were 4% to 5%, 3% to 4%, and 2% to 3%, respectively. For the 3%/2mm criteria, the errors that AC, PD, and LF can perfectly identify were the same as the 3%/3mm criteria. For the 2%/2mm criteria, AC can perfectly identify the MLC error of ± 2mm and the %DE of 3% to 4%. PD and LF can identify the MLC error of ± 1.2mm and the %DE of 2% to 3%. Conclusion: Different patient-specific quality assurance (PSQA) systems have different sensitivity and recognition abilities to MLC aperture errors. Institutions should formulate their own customized %GP limits based on their PSQA process through ROC or other methods.

Analysis of clinical patient-specific pre-treatment quality assurance with the new helical tomotherapy platform, following the AAPM TG-218 report

Purpose

This study presents patient-specific quality assurance (QA) results from the first 395 clinical cases for the new helical TomoTherapy® platform (Radixact) coupled with dedicated Precision TPS.

Methods

The passing rate of the Gamma Index (GP%) of 395 helical QA of patient-specific tomotherapy, acquired with ArcCHECK, is presented, analysed and correlated to various parameters of the plan. Following TG-218 recommendations, the clinic specific action limit (AL_cs) and tolerance limit (TL_cs) were calculated for our clinic and monitored during the analysed period.

Results

The mean values ​​(± 1 standard deviation) of GP% (3%/2 mm) (both global and local normalization) are: 97.6% and 90.9%, respectively. The proposed AL_cs and TL_cs, after a period of two years’ process monitoring are 89.4% and 91.1% respectively.

Conclusions

The phantom measurements closely match the planned dose distributions, demonstrating that the calculation accuracy of the new Precision TPS and the delivery accuracy of the Radixact unit are adequate, with respect to international guidelines and reports. Furthermore, a first correlation with the planning parameters was made. Action and tolerance limits have been set for the new Radixact Linac.

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.

Investigation of optimum minimum segment width on VMAT plan quality and deliverability: A comprehensive dosimetric and clinical evaluation using DVH analysis

Purpose

Minimum segment width (MSW) plays a fundamental role in the shaping of optimized apertures and creation of segments of varying sizes and shapes in complex radiotherapy treatment plans. The purpose of this work was to study the effect of MSW on dose distribution in patients planned with VMAT for various treatment sites using dose volume histogram (DVH) analysis.

Materials and methods

For the validation of optimum MSW, 125 clinical treatment plans were evaluated. Five groups were identified (brain, head and neck, thorax, pelvis, and extremity), and five cases were chosen from each group. For each case, five plans were created with different MSW (0.5, 0.8, 1.0, 1.25, and 1.5 cm). The quality of treatment plans created using different MSW were compared using dosimetric indicators such as target coverage (D₉₈—dose to 98% of the planning target volume (PTV), maximum dose (D₂—maximum dose to 2% of the PTV), monitor units (MU), and DVH parameters related to organs at risk (OAR). The effect of the MSW on delivery accuracy was quantitatively analyzed using the measured fluence utilizing ionization chamber‐based transmission detector and model‐based dose verification system. Traditional global gamma analysis (2%, 2 mm) and dose volume information was gathered for the PTV and organs at risk and compared for different MSWs.

Results

A total of 125 plans were created and compared across five groups. In terms of treatment plan quality, the plans using MSW of 0.5 cm was found to be superior in all groups. PTV coverage (D₉₈) decreased significantly (p < 0.05) as the MSW increased. Similarly, the maximum dose (D₂) was found to be increased significantly (p < 0.05) as the MSW increased from 0.5 cm, with MSW of 1.5 cm being the least in terms of plan quality for both PTVs and OARs. In terms of plan deliverability using DVH analysis, treatment planning system (TPS) compared to measured fluence, VMAT plans produced with MSW of 0.5 cm showed a better dosimetric index and a smaller deviation for both PTVs and OARs. The deliverability of the plans deteriorated as the MSW increased.

Conclusion

Dose volume histogram (DVH) analysis demonstrated that treatment plans with minimal MSW showed better plan quality and deliverability and provided clinical relevance as compared to gamma index analysis.

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.

Are gamma passing rate and dose-volume histogram QA metrics correlated?

PURPOSE

The quality of a measured distribution of dose delivered against its corresponding radiotherapy plan is routinely assessed by gamma index (GI) and dose-volume histogram (DVH) metrics. Any correlation between error detection rates, as based on either of these approaches, while argued, has never been convincingly demonstrated. The dependence of the strength of correlation between the GI passing rate ( γ P ) and DVH quality assurance (QA) metrics on various elements of the therapy plan has not been systematically investigated.

METHODS

A formal analysis of the relation between γ P and DVH metrics has been undertaken, leading to a relationship which may partly approximate γ P with respect to the DVH. This relationship was further validated by studying examples of simulated clinical radiotherapy plans and by studying the correlation between γ P and the derived relationship using a simple two-dimensional representations of the planning target volume (PTV) and organs at risk (OAR), where penumbra regions, distance-to-agreement tolerances and dose delivery errors were systematically varied.

RESULTS

It is shown formally that there cannot be any correlation between γ P and other commonly applied DVH-derived QA measures. However, γ P may be partly approximated given the planned and measured DVH. The derived γ P approximation (the " γ -slope indicator") may be clinically useful in some practical cases of radiotherapy plan QA.

CONCLUSIONS

In formal terms, there cannot be any correlation between γ P and any common DVH-calculated patient-specific measures, with respect to PTV or OAR. However, as demonstrated analytically and further confirmed in our simulation studies, the γ P approximation derived in this study (the " γ -slope indicator") may in some cases offer a degree of correlation between γ P and the PTV and OAR DVH QA metrics in measured and planned patient-specific dose distributions-which may be potentially useful in clinical practice.

Automatic 3D Monte-Carlo-based secondary dose calculation for online verification of 1.5 T magnetic resonance imaging guided radiotherapy

•

First implementation of an independent 3D-secondary dose calculation (3D-SDC).

•

Validation of the 3D-SDC solution using patient plans and experimental plan QA.

•

Online SDC of central targets is feasible with a median calculation time of 1:23 min.

•

Peripheral targets with small beam numbers need alternative validation strategies.

Background and purpose

Hybrid magnetic resonance linear accelerator (MR-Linac) systems represent a novel technology for online adaptive radiotherapy. 3D secondary dose calculation (SDC) of online adapted plans is required to assure patient safety. Currently, no 3D-SDC solution is available for 1.5T MR-Linac systems. Therefore, the aim of this project was to develop and validate a method for online automatic 3D-SDC for adaptive MR-Linac treatments.

Materials and methods

An accelerator head model was designed for an 1.5T MR-Linac system, neglecting the magnetic field. The use of this model for online 3D-SDC of MR-Linac plans was validated in a three-step process: (1) comparison to measured beam data, (2) investigation of performance and limitations in a planning phantom and (3) clinical validation using n = 100 patient plans from different tumor entities, comparing the developed 3D-SDC with experimental plan QA.

Results

The developed model showed median gamma passing rates compared to MR-Linac base data of 84.7%, 100% and 99.1% for crossplane, inplane and depth-dose-profiles, respectively. Comparison of 3D-SDC and full dose calculation in a planning phantom revealed that with ⩾5 beams gamma passing rates >95% can be achieved for central target locations. With a median calculation time of 1:23 min, 3D-SDC of online adapted clinical MR-Linac plans demonstrated a median gamma passing rate of 98.9% compared to full dose calculation, whereas experimental plan QA reached 99.5%.

Conclusion

Here, we describe the first technical 3D-SDC solution for online adaptive MR-guided radiotherapy. For clinical situations with peripheral targets and a small number of beams additional verification appears necessary. Further improvement may include 3D-SDC with consideration of the magnetic field.

Routine pretreatment patient-specific IMRT QA (PS-IMRT-QA) should be discontinued and replaced with a real-time on-board beam monitoring system (BMS)

In an era of automated measurements and analysis, the time and resource intensive process of dosimetric plan verification for intensity modulated radiation therapy treatments would seem to be ripe for improvement. In this Point-Counterpoint contribution, the authors debate benefits of methods both hypothetical and established. I offer thanks to our contributors and note that they are writing in the classic style of a debate, the opinions that they argue may or may not reflect their personal views."

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.

Technical Note: Three-dimensional QA of simultaneous integrated boost radiotherapy treatments by a dose-volume histogram methodology and its comparison with 3D gamma results

PURPOSE

Intensity-modulated radiotherapy with simultaneous integrated boost (SIB) presents several attractive advantages to be employed in clinical practice. Its secure application demands a rigorous quality assurance (QA) procedure, ideal for three-dimensional (3D) dose distribution measurements. Thus, a gel dosimetry methodology to evaluate the dose delivery of SIB treatments is presented and compared to conventional gamma evaluation.

METHODS

MAGIC-f gel dosimeter with magnetic resonance images for dose reading were used following its standard procedures. Four SIB QA plans created in gel dosimeter phantoms were used. The gel measured and treatment planning system (TPS) calculated doses were compared using 3D gamma analyses (3%/3mm/15% threshold). Two structures were artificially on the TPS dose distribution expected on the phantom by converting the 1.7 and 2.0 Gy isodose levels into structures to represent the treatment. The gel and TPS dose-volume histogram (DVH) were compared based on five dose points: D95%, D90%, D50%, D10%, and D5%.

RESULTS

Approvals of 93%, 96%, 98%, and 92% were achieved in the 3D gamma analyses for the plans QA 1, 2, 3, and 4. In the DVH analyses, QA plan 1 measured and expected curves showed a good agreement. QA plan 2 showed deviations in the highest doses for both structures with a maximum deviation (Δ_máx ) of 8.0%. QA plans 3 and 4 showed the highest dose variation between the gel and TPS in the smaller doses of the DVH (Δ_máx of 7.2% and -8.9%, respectively). For QA plan 4, the curves of the 1.7 Gy structure presented a good agreement, but deviations in the smaller dose region of the DVH occurred for the 2 Gy structure (Δ_máx of 7.7%).

CONCLUSIONS

A methodology for 3D dose evaluation of complex SIB treatments was proposed. It provided an important overview of the dose distributions. Their results significantly complemented the usual gamma analysis results.

A Beam Projection-Based Modified Gamma Analysis Scheme for Clinically Interpretable Pre-Treatment Dose Verification

Purpose:

To investigate a novel gamma analysis system for dose verification results in terms of clinical significance.

Methods and Materials:

The modified scheme redefined the computational domain of the conventional gamma analysis with the projections of beams and the regions of interest (ROI). We retrospectively studied 6 patients with the conventional and the modified gamma analysis schemes while compared their performances. The cold spots ratio of the planning target volume (PTV) and the hot spots ratio of the organs at risk (OAR) were also computed by the modified scheme to assess the clinical significance.

Results:

The result of the gamma passing rate in the modified method was conformable to that in the conventional method with a cut-off threshold of 5%. The cold spots ratio of PTV and hot spots ratio of OAR were able to be evaluated by the modified scheme. For an introduced 7.1% dose error, the discrimination ratio in gamma passing rate of the conventional method was lower than 2%, while it was improved to 5% by the modified method.

Conclusions:

The modified gamma analysis scheme had a comparable quality as the conventional scheme in terms of dose inspection. Besides, it could improve the clinical significance of the QA result and provide the assessment for ROI-specific discrepancy. The modified scheme could also be conveniently integrated into the conventional dose verification process, benefiting the less developed regions where high-end 3D dose verification devices are not affordable.

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.

Comparison of global and local gamma evaluation results using isodose levels

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

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.

Patient-specific quality assurance and plan dose errors on breast intensity-modulated proton therapy

PURPOSE

To investigate, in proton therapy, whether the Gamma passing rate (GPR) is related to the patient dose error and whether MU scaling can improve dose accuracy.

METHODS

Among 20 consecutively treated breast patients selected for analysis, two IMPT plans were retrospectively generated: (1) the pencil-beam (PB) plan and (2) the Monte Carlo (MC) plan. Patient-specific QA was performed. A 3%/3-mm Gamma analysis was conducted to compare the TPS-calculated PB algorithm dose distribution with the measured 2D dose. Dose errors were compared between the plans that passed the Gamma testing and those that failed. The MU was then scaled to obtain a better GPR. MU-scaled PB plan dose errors were compared to the original PB plan.

RESULTS

Of the 20 PB plans, 8 were passed Gamma testing (G_pass_group) and 12 failed (G_fail_group). Surprisingly, the G_pass_group had a greater dose error than the G_fail_group. The median (range) of the PTV DVH RMSE and PTV ΔDmean were 1.36 (1.00-1.91) Gy vs 1.18 (1.02-1.80) Gy and 1.23 (0.92-1.71) Gy vs 1.10 (0.87-1.49) Gy for the G_pass_group and the G_fail_group, respectively. MU scaling reduced overall dose error. However, for PTV D99 and D95, MU scaling worsened some cases.

CONCLUSION

For breast IMPT, the PB plans that passed the Gamma testing did not show smaller dose errors compared to the plans that failed. For individual plans, the MU scaling technique leads to overall smaller dose errors. However, we do not suggest use of the MU scaling technique to replace the MC plans when the MC algorithm is available.

A delivery quality assurance tool based on the actual leaf open times in tomotherapy

PURPOSE

To validate a delivery quality assurance (DQA) protocol for tomotherapy based on the measurement of the leaf open times (LOTs). In addition, to show the correlation between the mean relative LOT discrepancy and the dose deviation in the planning target volume (PTV).

MATERIALS AND METHODS

We used a LOT measurement algorithm presented in a previous work on our two tomotherapy treatment units (TOMO1 and TOMO2). We generated TomoPhant plans with intentional random LOT discrepancies following Gaussian distributions of -6%, -4%, -2%, 2%, 4%, and 6%. We irradiated them on the Cheese Phantom with two ion chambers and collected the raw data on both our treatment units. Using the raw data, we measured the actual LOTs and verified that the induced discrepancies were highlightable. Then, we calculated the actual dose using Accuray's standalone dose calculator and verified that the calculated dose agreed with the ion chamber measurement. We randomly chose 60 clinical treatment plans, delivered them in air, and collected the raw detector data. We measured the actual LOTs from the raw data and calculated the corresponding dose distributions using Accuray's standalone dose calculator. We assessed the Pearson coefficient correlation of the deviation between expected and actual dose in the PTV (a) with the mean relative LOT discrepancy and (b) with the γ-index pass rate for different tolerances.

RESULTS

The mean relative discrepancy between actual (measured by the algorithm) and expected LOTs on the modified TomoPhant plans was 1.10 ± 0.05% on TOMO1 and 0.02 ± 0.03% on TOMO2, respectively. The agreement between measured and calculated dose was 0.2 ± 0.3% on TOMO1 and 0.1 ± 0.3% on TOMO2, respectively. On clinical plans, the means of the relative LOT discrepancies ranged from -3.0 % to 1.4%. The dose deviation in the PTVs ranged from -1.6% to 2.4%. The Pearson coefficient correlation between the mean relative LOT discrepancy and the dose deviation in the PTV was 0.76 (P ≈ 10^-15 ) on TOMO1 and 0.65 (P ≈ 10^-10 ) on TOMO2, respectively. There was no correlation between the γ-index pass rate and the dose deviation in the PTV.

CONCLUSION

The method made it possible to measure and to correctly highlight the LOT discrepancies on the TomoPhant plans. The dose subsequently calculated was accurate. On clinical plans, the mean LOT discrepancy correlated with the dose deviation in the PTV. This makes the mean LOT discrepancy a handy indicator of the plan quality.

The impact of 4DCT-ventilation imaging-guided proton therapy on stereotactic body radiotherapy for lung cancer

Functional lung avoidance during radiotherapy can help reduce pulmonary toxicity. This study assessed the potential impact of four-dimensional computed tomography (4DCT)-ventilation imaging-guided proton radiotherapy (PT) on stereotactic body radiotherapy (SBRT) by comparing it with three-dimensional conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT), which employ photon beams. Thirteen lung cancer patients who received SBRT with 3D-CRT were included in the study. 4DCT ventilation was calculated using the patients' 4DCT data, deformable image registration, and a density-change-based algorithm. Three functional treatment plans sparing the functional lung regions were developed for each patient using 3D-CRT, VMAT, and PT. The prescribed doses and dose constraints were based on the Radiation Therapy Oncology Group 0618 protocol. We evaluated the region of interest (ROI) and functional map-based dose-function metrics for 4DCT ventilation and the irradiated dose. Using 3D-CRT, VMAT, and PT, the percentages of the functional lung regions that received ≥ 5 Gy (fV5) were 26.0%, 21.9%, and 10.7%, respectively; the fV10 were 14.4%, 11.4%, and 9.0%, respectively; and fV20 were 6.5%, 6.4%, and 6.6%, respectively, and the functional mean lung doses (fMLD) were 5.6 Gy, 5.2 Gy, and 3.8 Gy, respectively. These results indicated that PT resulted in a significant reduction in fMLD, fV5, and fV10, but not fV20. The use of PT reduced the radiation to highly functional lung regions compared with those for 3D-CRT and VMAT while meeting all dose constraints.

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.

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

Purpose

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

Materials and Methods

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

Results

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

Conclusions

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

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

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

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

PURPOSE

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

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.

Treatment plan verification: A review on the comparison of dose distributions

PURPOSE

The aim of this review article is to provide a useful reference for dose comparison techniques within the frame of treatment plan verification. Each technique is presented with a general description given along with advantages and disadvantage and the rationale for its development.

METHODS

The review was conducted in PubMed from 1993 to 2019 including articles referring to the methodology of dose comparison for treatment plan verification.

RESULTS

The search identified thirty-one dose comparison methods that were categorized according to the number of physical parameters that take into account for dose comparison.

CONCLUSIONS

Among the available methods for the comparison of two dose distributions, the γ-analysis (gamma analysis) has been widely adopted as the gold standard in verification procedures. However, due to various intrinsic limitations of gamma index, the development of a better metric taking into account both statistical and in clinical parameters is required.