Quality Assurance Results Research Articles

Long-term beam output stability of an accelerator-based boron neutron capture therapy system.

Accelerator-based boron neutron capture therapy (AB-BNCT) systems are becoming commercially available and are expected to be widely used in hospitals. To ensure the safety of BNCT, establishing a quality assurance (QA) program and properly managing the stability of the system are necessary. In particular, a high level of beam output stability is required to avoid accidents because beam output is a major factor in patient dose. However, no studies have analyzed the long-term beam output stability of AB-BNCT systems. This study aimed to retrospectively analyze the long-term stability of the beam output by statistical process control (SPC) based on the QA results over 3 years. The data analyzed are the results of daily QA (DQA) and weekly QA (WQA) in an AB-BNCT system and were taken between June 2020 and September 2023. The evaluation of the stability of the beam output was based on the reaction rate between gold and neutrons calculated using the activation foil method using a gold foil. In DQA, which can be performed in a short time, the gold foil was applied directly to the beam irradiation aperture in air. In WQA, measurements were performed at the phantom surface, 2-cm depth, and 6-cm depth using a dedicated water phantom. The acquired data were retrospectively analyzed by individuals and a moving range chart (I-MR chart), exponentially weighted moving average control chart (EWMA chart), and several process capability indexes (PCIs). Over 99% of the DQA I-MR chart results were within control limits, whereas the WQA I-MR chart results showed that 1.8%, 4.1%, and 2.0% of the measurements exceeded the control limits at the surface, 2-cm depth, and 6-cm depth, respectively. The variation in the reaction rate of the gold foil before and after the replacement of the target was<0.5%. The EWMA chart results revealed no significant beam output drift for either DQA or WQA. Most measured data were normal based on the results of the Anderson-Darling test and met the requirements for PCI evaluation; most PCI values were>1.0; however, the Cpmk of DQA and the 2- and 6-cm depth WQAs between August 2021 and November 2022 in treatment course 2 were 0.83, 0.77, and 0.87, respectively, which were<1.0. The long-term stability of beam output was confirmed using SPC in an AB-BNCT system. The results of the control chart revealed no significant variation or drift in the beam output, and the quantitative evaluation using PCI revealed high stability. A routine QA program will enable us to provide safe BNCT.

Commissioning and validation of a single photon beam model in RayStation for multiple matched Elekta Linacs.

A single treatment planning system (TPS) model for matched linacs provides flexible clinical workflows from patient treatment to intensity-modulated radiation therapy (IMRT) quality assurance (QA) measurement. Since general guidelines for building a single TPS model and its validation for matched linacs are not well established, we present our RayStation photon TPS modeling strategy for matched Elekta VersaHD linacs. The four linacs installed from 2013 to 2020 were matched in terms of Percent Depth Dose (PDD), profile, output factor and wedge factors for 6-MV, 10-MV, 15-MV, and 6-MV-FFF, and maintained following TG-142 recommendations until RayStation commissioning. The RayStation single model was built to represent all four linacs within the tolerance limits recommended by MPPG-5.a. The comprehensive validation tests were performed for one linac following MPPG-5.a and TG-119 guidelines, and spot checks for the other three. Our TPS modeling/validation method was evaluated by re-analyzing the previous 103 patient-specific IMRT/volumetric modulated arc therapy (VMAT) QA measurements with the calculated planar doses by the single model in comparison with the analysis results using four individual Pinnacle TPS models. For all energies, our single model PDDs were within 1% agreement of the four-linac commissioning measurements. The MPPG-5.a validation tests from 5.1 through 7.5 and all TG-119 measurements passed within the recommended tolerance limits. The IMRT QA results (mean±standard deviation) for RayStation single model versus Pinnacle individual models were 98.9%±1.3% and 98.0%±1.4% for 6-MV, 99.9%±0.1% and 99.1%±1.9% for 10-MV, and 98.2%±1.3% and 97.9%±1.8% for 6-MV-FFF, respectively. We successfully built and validated a single photon beam model in RayStation for four Elekta Linacs. The proposed new validation methods were proven to be both efficient and effective.

Machine learning and deep learning prediction of patient specific quality assurance in breast IMRT radiotherapy plans using Halcyon specific complexity indices

IntroductionNew radiotherapy machines such as Halcyon are capable of delivering dose-rate of 600 monitor-units per minute, allowing large numbers of patients treated per day. However, patient-specific quality assurance (QA) is still required, which dramatically decrease machine availability. Innovative artificial intelligence (AI) algorithms could predict QA result based on complexity metrics. However, no AI solution exists for Halcyon machines and the complexity metrics to be used have not been definitively determined. The aim of this study was to develop an AI solution capable of firstly determining the complexity indices to be obtained and secondly predicting patient-specific QA in a routine clinical setting. MethodsThree hundred and eighteen beams from 56 patients with breast cancer were used. The seven complexity indices named Modulation-Complexity-Score (MCS), Small-Aperture-Score (SAS10), Beam-Area (BA), Beam-Irregularity (BI), Beam-Modulation (BM), Gantry and Collimator angles were used as input to the AI model. Machine learning (ML) and deep learning (DL) models using tensorflow were set up to predict DreamDose QA conformance. ResultsMCS, BI, gantry and collimator angle are not correlated with QA compliance. Therefore, ML and DL models were trained using SAS10, BA and BM complexity indices. ROC analyses enabled to find best predicted probability threshold to increase specificity and sensitivity. ML models did not show satisfactory performance with an area under-the-curve (AUC) of 0.75 and specificity and sensitivity of 0.88 and 0.86. However, optimised DL model showed better performance with an AUC of 0.95 and specificity and sensitivity of 0.98 and 0.97. ConclusionThe DL model demonstrated a high degree of accuracy in its predictions of the quality assurance (QA) results. Our online predictive QA-platform offers significant time savings in terms of accelerator occupancy and working time.

Dosimetric Systems in Pre-Treatment QA for Stereotactic Treatments: Correlation Agreements and Target Volume Dependency.

This study comprehensively investigated pre-treatment quality assurance (QA) for 100 cancer patients undergoing stereotactic treatments (SRS/SRT) using various detectors. The study conducted QA for SRS/SRT treatments planned with a 6MV SRS beam at a dose rate of 1,000 MU/min, utilizing Eclipse v13.6 Treatment Planning System (TPS). Point dose measurements employed 0.01cm3 and 0.13cm3 cylindrical ionization chambers, while planar dose verification utilized Gafchromic EBT-XD Film and Portal Imager (aS1000). Plans were categorized by target volume, and a thorough analysis compared point dose agreements, planar dose gamma pass rates, and their correlations with chamber volume mean dose, detector type, and point dose agreement. Additionally, the consistency between different ionization chambers was assessed. Point dose agreement generally improved with increasing target volume, except for volumes over 10cm3 with 0.01cm3 chambers, showing a contrary trend. Significant differences (p<0.05) were observed between TPS and measured doses for both chambers. Gamma pass rate improved with increasing target volume in EBT XD and aS1000 analyses, except for the >10cm3 group in EBT XD. EBT XD demonstrated better agreement with TPS for target volumes up to 10cm3 compared to aS1000, with a statistically significant difference (p<0.05) between the detectors. Strong correlations were found between chamber point dose and chamber volume mean dose agreement, as well as between the two gamma criteria analyses of the same detector type in the planar dose correlation analysis. However, weak correlations were discovered for other analyses. This study found weak correlation between different detector types in pre-treatment QA for point dose and planar dose evaluation. However, within a specific detector type, strong correlation was observed for different point dose evaluation methods and gamma criteria. This highlights the importance of cautious interpretation of QA results, particularly for SRS QA, due to the lack of correlation between detector types.

The performance of a new type accelerator uRT-linac 506c evaluated by a quality assurance automation system.

The purpose of this study was to evaluate the performance of our quality assurance (QA) automation system and to evaluate the machine performance of a new type linear accelerator uRT-linac 506c within 6months using this system. This QA automation system consists of a hollow cylindrical phantom with 18 steel balls in the phantom surface and an analysis software to process electronic portal imaging device (EPID) measurement image data and report the results. The performance of the QA automation system was evaluated by the tests of repeatability, archivable precision, detectability of introduced errors, and the impact of set-up errors on QA results. The performance of this linac was evaluated by 31 items using this QA system over 6months. This QA system was able to automatically deliver QA plan, EPID image acquisition, and automatic analysis. All images acquiring and analysis took approximately 4.6min per energy. The preset error of 0.1mm in multi-leaf collimator (MLC) leaf were detected as 0.12±0.01mm for Bank A and 0.10±0.01mm in Bank B. The 2mm setup error was detected as -1.95±0.01mm, -2.02±0.01mm, 2.01±0.01mm for X, Y, Z directions, respectively. And data from the tests of repeatability and detectability of introduced errors showed the standard deviation were all within 0.1mm and 0.1°. and data of the machine performance were all within the tolerance specified by AAPM TG-142. The QA automation system has high precision and good performance, and it can improve the QA efficiency. The performance of the new accelerator has also performed very well during the testing period.

Complexity Metrics and Planning Dose-Based Pretreatment Patient-Specific Quality Assurance Prediction: Classification, Gamma Passing Rates, and DVH Deviation

Patient-specific quality assurance (QA) prediction before treatment is beneficial to the clinical resource allocation and the dosimetric monitoring of the patient plans. The aim of this study is to investigate the potential of complexity metrics of radiotherapy plan and patient planning dose to predict QA result, gamma passing rates and dose-volume indices deviation. Planning dose from treatment planning system (TPS), reconstructed dose from a vendor provided QA phantom and complexity metrics of the 499 radiotherapy plans of patients in our institution from March 2022 to September 2022 were used for methodology verification. Gamma passing rate (3%/2mm,10% threshold) 90% was regarded as criterion of QA pass or fail. A deep learning model ResNet-50 was modified to 3D dose processing and a multilayer perceptron (MLP) with three layers were adopted to extract features from 3D dose and 1D metrics in two parallel ways, then, the features were concatenate together to predict QA results. The dataset was split into 349 for train, 50 for validation and 100 for testing. Evaluation of predictions was based on absolute value deviation and area under the curves (AUC) of receiver operator characteristic (ROC) curve. In this dataset, 71% (355/499) plans pass the pretreatment QA test. For QA passing prediction in 100 testing cases, the AUC of ROC could achieve 0.92. For gamma passing rates prediction, a mean absolute error (MAE) of 1.8% could be observed for cases with gamma passing rates bigger than 90%, and a MAE of 4.5% deviation could be observed for cases with gamma passing rates from 80% to 90%. For PTV ΔD95 (%) and PTV ΔHI (%), the MAE of prediction and ground truth is 1%. The model with only complexity metrics and only 3D dose could achieve the AUC of ROC 0.91 and 0.84, respectively. The complexity metrics and 3D planning dose-based model could predict pretreatment patient specific QA results with high accuracy and the complexity metrics play a leading role in the model. Dose-volume metrics deviations of PTV could be predicted and more clinically useful information could be provided.

Implementation of a Patient Specific QA Protocol for a Novel Dedicated Stereotactic Radiosurgery Linear Accelerator

To describe the patient specific QA (Quality Assurance) protocol implemented for plan integrity verification, in stereotactic radiosurgery (SRS) and radiotherapy (SRT) treatments performed on a novel dedicated frameless image guided radiosurgery system using conical collimator, and a combination of yoked gimbals to cover near2pi solid angle. Startup and commissioning results obtained for planned vs measured dose distributions with several detectors are presented. The patient specific QA protocol includes: A) Review of the approved plan based on AAPM TG 275 report recommendations B) 1D verification using small volume ionization chambers inside an anthropomorphic head phantom C) 2D dose verification of a coronal and sagittal dose plan performed with high resolution 2D Array and respective phantom apparatus D) In-house independent MU (Monitor Unit) calculation using the same formalism of the vendor TPS (Treatment Planning Systems) RayTracing dose-calculation algorithm E) Monte Carlo based secondary dose check & plan QA. A retrospective analysis of the results of the first 15 patients treated is presented, focusing on plan complexity vs QA results. The 1D results obtained for the 15 SRS plans were within ±5% for all reported cases, with a mean percent difference of -1,25%, confirming an overall good agreement and, as expected, a partial volume effect in plans with smaller collimators. For the 2D dose verifications, with a 10% dose threshold, gamma passing rates of 97,5% (coronal) and 96,78 (sagittal) with 3% 1mm criteria, 95,1% (coronal) and 94,3% (sagittal) for 2% 1 mm criteria and 90,7% (coronal) and 90,0% (sagittal) for 1% 1mm criteria were obtained. Moreover, the results showed a correlation between lesion volume or number of collimators used with gamma passing rates. All MU verification results were within ±0,3% and provides an efficient risk mitigation approach for this new delivery technique. The verification results of the first 15 treated SRS plans confirmed point dose and planar measurements in agreement with TPS calculations, with superior results for planes with smaller lesions and fewer collimators. This also represents an integral validation of the image-based alignment system and fine treatment couch movements, as treatments are intrinsically multi-isocentric.

Evaluation and improvement of angular response for a commercial 2D detector array for patient-specific QA.

MatriXX ionization chamber array has been widely used for the composite dose verification of IMRT/VMAT plans. However, in addition to its dose response dependence on gantry angle, there seems to be an offset between the beam axis and measured dose profile by MatriXX for oblique beam incidence at various gantry angles, leading to unnecessary quality assurance (QA) fails. In this study, we investigated the offset at various setup conditions and how to eliminate or decrease it to improve the accuracy of MatriXX for IMRT/VMAT plan verification with original gantry angles. We measured profiles for a narrow beam with MatriXX located at various depths in increments of 0.5mm from the top to bottom of the sensitive volume of the array detectors and gantry angles from 0° to 360°. The optimal depth for QA measurement was determined at the depth where the measured profile had minimum offset. The measured beam profile offset varies with incident gantry angle, increasing from vertical direction to lateral direction, and could be over 3cm at vendor-recommended depth for near lateral direction beams. The offset also varies with depth, and the minimum offset (almost 0 for most oblique beams) was found to be at a depth of ∼2.5mm below the vendor suggested depth, which was chosen as the optimal depth for all QA measurements. Using the optimal depth we determined, QA results (3%/2mm Gamma analysis) were largely improved with an average of 99.4% gamma passing rate (no fails for 95% criteria) for 10 IMRT and VMAT plans with original gantry angles compared to 94.1% using the vendor recommended depth. The improved accuracy and passing rate for QA measurement performed at the optimal depth with original gantry angles would lead to reduction in unnecessary repeated QA or plan changes due to QA system errors.

Technical note: Comprehensive evaluations of gantry and couch rotation isocentricities for implementing proton stereotactic radiosurgery.

Mechanical accuracy should be verified before implementing a proton stereotactic radiosurgery (SRS) program. Linear accelerator (Linac)-based SRS systems often use electronic portal imaging devices (EPIDs) to verify beam isocentricity. Because proton therapy systems do not have EPID, beam isocentricity tests of proton SRS may still rely on films, which are not efficient. To validate that our proton SRS system meets mechanical precision requirements and to present an efficient method to evaluate the couch and gantry's rotational isocentricity for our proton SRS system. A dedicated applicator to hold brass aperture for proton SRS system was designed. The mechanical precision of the system was tested using a metal ball and film for 11 combinations of gantry and couch angles. A more efficient quality assurance (QA) procedure was developed, which used a scintillator device to replace the film. The couch rotational isocentricity tests were performed using orthogonal kV x-rays with the couch rotated isocentrically to five positions (0°, 315°, 270°, 225°, and 180°). At each couch position, the distance between the metal ball in kV images and the imaging isocenter was measured. The gantry isocentricity tests were performed using a cone-shaped scintillator and proton beams at five gantry angles (0°, 45°, 90°, 135°, and 180°), and the isocenter position and the distance of each beam path to the isocenter were obtained. Daily QA procedure was performed for 1month to test the robustness and reproducibility of the procedure. The gantry and couch rotational isocentricity exhibited sub-mm precision, with most measurements within ±0.5mm. The 1-month QA results showed that the procedure was robust and highly reproducible to within ±0.2mm. The gantry isocentricity test using the cone-shaped scintillator was accurate and sensitive to variations of ±0.2mm. The QA procedure was efficient enough to be completed within 30min. The 1-month isocentricity position variations were within 0.5mm, which demonstrating that the overall proton SRS system was stable and precise. The proton SRS Winston-Lutz QA procedure using a cone-shaped scintillator was efficient and robust. We were able to verify radiation delivery could be performed with sub-mm mechanical precision.

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

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

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

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. 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. 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. 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.

An independent Monte Carlo-based IMRT QA tool for a 0.35T MRI-guided linear accelerator.

To develop an independent log file-based intensity-modulated radiation therapy (IMRT) quality assurance (QA) tool for the 0.35T magnetic resonance-linac (MR-linac) and investigate the ability of various IMRT plan complexity metrics to predict the QA results. Complexity metrics related to tissue heterogeneity were also introduced. The tool for particle simulation (TOPAS) Monte Carlo code was utilized with a previously validated linac head model. A cohort of 29 treatment plans was selected for IMRT QA using the developed QA tool and the vendor-supplied adaptive QA (AQA) tool. For 27 independent patient cases, various IMRT plan complexity metrics were calculated to assess the deliverability of these plans. A correlation between the gamma pass rates (GPRs) from the AQA results and calculated IMRT complexity metrics was determined using the Pearson correlation coefficients. Tissue heterogeneity complexity metrics were calculated based on the gradient of the Hounsfield units. The median and interquartile range for the TOPAS GPRs (3%/3mm criteria) were 97.24% and 3.75%, respectively, and were 99.54% and 0.36% for the AQA tool, respectively. The computational time for TOPAS ranged from 4 to 8h to achieve a statistical uncertainty of <1.5%, whereas the AQA tool had an average calculation time of a few minutes. Of the 23 calculated IMRT plan complexity metrics, the AQA GPRs had correlations with 7 out of 23 of the calculated metrics. Strong correlations (|r|>0.7) were found between the GPRs and the heterogeneity complexity metrics introduced in this work. An independent MC and log file-based IMRT QA tool was successfully developed and can be clinically deployed for offline QA. The complexity metrics will supplement QA reports and provide information regarding plan complexity.

Predictive gamma passing rate of 3D detector array-based volumetric modulated arc therapy quality assurance for prostate cancer via deep learning.

To predict the gamma passing rate (GPR) of the three-dimensional (3D) detector array-based volumetric modulated arc therapy (VMAT) quality assurance (QA) for prostate cancer using a convolutional neural network (CNN) with the 3D dose distribution. One hundred thirty-five VMAT plans for prostate cancer were selected: 110 plans were used for training and validation, and 25 plans were used for testing. Verification plans were measured using a helical 3D diode array (ArcCHECK). The dose distribution on the detector element plane of these verification plans was used as input data for the CNN model. The measured GPR (mGPR) values were used as the training data. The CNN model comprises eighteen layers and predicted GPR (pGPR) values. The mGPR and pGPR values were compared, and a cumulative frequency histogram of the prediction error was created to clarify the prediction error tendency. The correlation coefficients of pGPR and mGPR were 0.67, 0.69, 0.66, and 0.73 for 3%/3-mm, 3%/2-mm, 2%/3-mm, and 2%/2-mm gamma criteria, respectively. The respective mean±standard deviations of pGPR-mGPR were -0.87±2.18%, -0.65±2.93%, -0.44±2.53%, and -0.71±3.33%. The probabilities of false positive error cases (pGPR < mGPR) were 72%, 60%, 68%, and 56% for each gamma criterion. We developed a deep learning-based prediction model of the 3D detector array-based VMAT QA for prostate cancer, and evaluated the accuracy and tendency of prediction GPR. This model can provide a proactive estimation for the results of the patient-specific QA before the verification measurement.

Dosimetric effect of modelling non-homogeneous LINAC couch using cone-beam computed tomography on quality assurance (QA) results

Abstract Aim: To evaluate the dosimetric effect of modelling a non-homogeneous couch on patients’ quality assurance (QA) gamma pass rates for intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) techniques. Materials and Methods: A non-homogeneous treatment couch (TxT 550 TTM, CIVCO, USA) was imaged using the LINAC mounted cone-beam computer tomography (CBCT) system. Modelling this couch in different situations, including incomplete (homogeneous model), correct model and not defined situations in the treatment planning system (TPS), was performed based on the geometrical and material densities data extracted from the CBCT images. Calculated gamma pass rates between TPS dose calculations and the measurements in a phantom for different couch models were obtained and compared at two gamma criteria (2%-2 mm and 3%-3 mm). Results: Comparing TPS calculations for the correct modelled couch and the measurements showed high gamma pass rates for both the IMRT and VMAT techniques (96·5 ± 0·9%, 99·2 ± 0·5% for IMRT in 2%-2 mm and 3%-3 mm criteria; 97·5 ± 0·8%, 99·4 ± 0·5% for VMAT). The overall gamma pass rate of the IMRT plan QAs was reduced by about 2% and 3% on average for incomplete and no couch modelling, respectively. These reductions for VMAT techniques were 2·5% and 4·3%, respectively. Conclusions: Non-homogeneous couches have different parts with different attenuations, which can be correctly defined using LINAC CBCT. Modelling of treatment couch has a significant effect on patient QA results for VMAT and IMRT plans, especially in radiation fields/subfield transmitting from the couch. We suggest using LINAC CBCTs as an appropriate device for couch modelling in modulated radiotherapy techniques.

Performance-based climatic zoning method for building energy efficiency applications using cluster analysis

Climatic zoning for buildings is an important topic in the field of building energy efficiency. Defining climatic zones is challenging, as it involves many variables sparsely distributed in time and space. Many methods exist today to define climatic zoning, most of them focused on weather-centred definitions. The actual response of buildings in terms of performance is rarely considered in the climatic zoning definition, leading to significant levels of misclassification. Early initiatives of performance-based climatic zoning show the large potential of this approach. However, these initiatives have shortcomings on handling complex building-stocks, defining boundaries between zones, and quality-assurance of results. This paper proposes a performance-based approach for climatic zoning addressing these shortcomings, relying on the intensive use of archetypes, building performance simulation, and GIS. The method was tested in south-eastern USA, using simulation results for 52 building models from the USA Department of Energy (DOE) building stock for 95 locations. Results were clustered using the k-means method considering 3 different zoning levels. An existing climatic zoning performance indicator, the Mean Percentage of Misclassified Areas (MPMA), was calculated for each alternative. The best-case scenario (3-zones) reached less than 2% of MPMA, which is low when compared with existing methods (10% for ASHRAE169-2013, 15% for ASHRAE169-2009).

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

BackgroundIn the patient-specific quality assurance (QA), DVH is a critical clinically relevant parameter that is finally used to determine the safety and effectiveness of radiotherapy. However, a consensus on DVH-based action levels has not been reached yet. The aim of this study is to explore reasonable DVH-based action levels and optimal DVH metrics in detecting systematic MLC errors for cervical cancer RapidArc plans.MethodsIn this study, a total of 148 cervical cancer RapidArc plans were selected and measured with COMPASS 3D dosimetry system. Firstly, the patient-specific QA results of 110 RapidArc plans were retrospectively reviewed. Then, DVH-based action limits (AL) and tolerance limits (TL) were obtained by statistical process control. Secondly, systematic MLC errors were introduced in 20 RapidArc plans, generating 380 modified plans. Then, the dose difference (%DE) in DVH metrics between modified plans and original plans was extracted from measurement results. After that, the linear regression model was used to investigate the detection limits of DVH-based action levels between %DE and systematic MLC errors. Finally, a total of 180 test plans (including 162 error-introduced plans and 18 original plans) were prepared for validation. The error detection rate of DVH-based action levels was compared in different DVH metrics of 180 test plans.ResultsA linear correlation was found between systematic MLC errors and %DE in all DVH metrics. Based on linear regression model, the systematic MLC errors between -0.94 mm and 0.88 mm could be caught by the TL of PTV95 ([-1.54%, 1.51%]), and the systematic MLC errors between -1.00 mm and 0.80 mm could also be caught by the TL of PTVmean ([-2.06%, 0.38%]). In the validation, for original plans, PTV95 showed the minimum error detection rate of 5.56%. For error-introduced plans with systematic MLC errors more than 1mm, PTVmean showed the maximum error detection rate of 88.89%, and then was followed by PTV95 (86.67%). All the TL of DVH metrics showed a poor error detection rate in identifying error-induced plans with systematic MLC errors less than 1mm.ConclusionIn 3D quality assurance of cervical cancer RapidArc plans, process-based tolerance limits showed greater advantages in distinguishing plans introduced with systematic MLC errors more than 1mm, and reasonable DVH-based action levels can be acquired through statistical process control. During DVH-based verification, main focus should be on the DVH metrics of target volume. OARs in low-dose regions were found to have a relatively higher dose sensitivity to smaller systematic MLC errors, but may be accompanied with higher false error detection rate.

Modified volumetric modulated arc therapy technique with reduced planning and treatment time for craniospinal irradiation utilising two isocentres.

IntroductionPaediatric patients (individuals below 18 years of age) requiring cranial‐spinal irradiation (CSI) at our institution are commonly planned and treated using a three isocentre (3‐ISO) volumetric modulated arc therapy (VMAT) technique. A modified two isocentre (2‐ISO) VMAT technique was investigated with the aim to improve workflow and reduce planning and treatment time.MethodsFive CSI paediatric patients previously treated with a 3‐ISO VMAT technique were retrospectively replanned using a 2‐ISO VMAT technique. The 2‐ISO VMAT plans were reviewed and approved by a radiation oncologist (RO) before undergoing patient‐specific quality assurance (QA) procedures, performed by a radiation oncology medical physicist (ROMP). Planning target volume (PTV) coverage, organ‐at‐risk (OAR) dose as well as planning and treatment durations of the first five patients utilising 2‐ISO technique were compared with 3‐ISO technique.ResultsThe average percentage difference in PTV coverage by 95% reference dose between the 2‐ISO and 3‐ISO is 0.14%, and the average difference in OAR median dose is 0.68 Gy. Conformity and homogeneity indices have the same averages at 1.18 and 0.4 respectively. Patient‐specific physics QA results were all comparable with the 3‐ISO averages at 98.84% and the 2‐ISO at 98.71%. Planning duration for the 2‐ISO was reduced by up to 75%, and daily treatment duration was reduced by up to 50%. Of all the previously treated CSI patients using a 3‐ISO technique, 45% were suitable for the 2‐ISO technique.ConclusionThe 2‐ISO VMAT technique provided comparable dose distribution based on PTV coverage, OAR dose and plan metric indices. Reduced planning and treatment duration with the 2‐ISO technique facilitated improved workflow with decreased sedation time for paediatric patients requiring a general anaesthesia.

Deep Multimodal Neural Network Based on Data-Feature Fusion for Patient-Specific Quality Assurance.

Patient-specific quality assurance (QA) for Volumetric Modulated Arc Therapy (VMAT) plans is routinely performed in the clinical. However, it is labor-intensive and time-consuming for medical physicists. QA prediction models can address these shortcomings and improve efficiency. Current approaches mainly focus on single cancer and single modality data. They are not applicable to clinical practice. To assess the accuracy of QA results for VMAT plans, this paper presents a new model that learns complementary features from the multi-modal data to predict the gamma passing rate (GPR). According to the characteristics of VMAT plans, a feature-data fusion approach is designed to fuse the features of imaging and non-imaging information in the model. In this study, 690 VMAT plans are collected encompassing more than ten diseases. The model can accurately predict the most VMAT plans at all three gamma criteria: 2%/2 mm, 3%/2 mm and 3%/3 mm. The mean absolute error between the predicted and measured GPR is 2.17%, 1.16% and 0.71%, respectively. The maximum deviation between the predicted and measured GPR is 3.46%, 4.6%, 8.56%, respectively. The proposed model is effective, and the features of the two modalities significantly influence QA results.

Use of a DVH overlay technique for quality assurance of deformable image registration‐based dose accumulation

We present a DVH overlay technique as a quality assurance (QA) metric for deformable image registration-based dose accumulation (DIR-DA). We use the technique to estimate the uncertainty in a DIR-DA for a revised treatment plan, and to compare two different DIR algorithms. The required inputs to the DVH overlay workflow are deformably registered primary and secondary images, primary regions-of-interest (ROIs), and secondary dose distribution. The primary ROIs were forward warped to the secondary image, the secondary dose was inversely warped to the primary image, and the DVHs for each image were compiled. Congruent DVHs imply minimal inverse consistency error (ICE) within an ROI. For a pancreas case re-planned after 21 fractions of a 29-fraction course, the workflow was used to quantify dose accumulation error attributable to ICE, based on a hybrid contour-and-intensity-based DIR. The usefulness of the workflow was further demonstrated by assessing the performance of two DIR algorithms (one free-form intensity-based, FFIB, the other using normalized correlation coefficients, NCC, over small neighborhood patches) as applied toward kilovoltage computed tomography (kVCT)-to-megavoltage computed tomography (MVCT) registration and five-fraction dose accumulation of ten male pelvis cases. For the re-planned pancreas case, when applying the DVH-overlay-based uncertainties the resulting accumulated dose remained compliant with all but two of the original plan objectives. Among the male pelvis cases, FFIB and NCC DIR showed good invertibility within the planning target volume (PTV), according to the DVH overlay QA results. NCC DIR exhibited better invertibility for the bladder and rectum compared with FFIB. However, compared with FFIB, NCC DIR exhibited less regional deformation for the bladder and a tendency for increased local contraction of the rectum ROI. For the five-fraction summations, ICE for the PTV V100%Rx is comparable for both algorithms (FFIB 0.8±0.7%, NCC 0.7±0.3%). For the bladder and rectum V70%Rx , ICE is greater for FFIB (1.8±0.7% for bladder, 1.7±0.6% for rectum) than for NCC (1.0±0.3% for bladder, 1.0±0.4% for rectum). The DVH overlay technique identified instances in which a DIR exhibits favorable invertibility, implying low ICE in a DIR-based dose accumulation. Differences in the overlaid DVHs can also estimate dose accumulation errors attributable to ICE for given ROIs.

Study on the established customized limits for the daily quality assurance procedure.

Since there are no corresponding specification limits for some new daily quality assurance (QA) items in the TG-142, it is a compromise that the specification limits used in the monthly or annual QA procedures are used for the daily QA procedure in work. But there is no basis for whether this is feasible. The purpose of this article is to analyze QA results using SPC to determine the tolerance limits at our institution, and to present the usefulness of the analysis method using SPC. The data of three groups daily QA processes performed with Daily QA3 in three years were analyzed using statistical process control (SPC). For calculating capability indices (Cp, Cpk, Cpm and Cpmk) of processes, the appropriate number of calculation points was analyzed firstly. Then, in calculating the capability indices for output, limits ±3% of the daily QA in the TG-142 were used as the specification limit, while for flatness and symmetry, an annual QA limits of ±1% was used. For putting forward measures to solve the problem, customized tolerance and action limits were established for each process. And the process control charts calculated using data measured by the five therapists and a medical physicist were compared. At least six to eight weeks of control daily check data points (i.e. 30–40 points) should be used for calculating the individuals and moving range (I-MR) control chart to ensure the stability of control lines. Process capability indices of output were all ≥1, some were up to 3–4. While for symmetry, some processes failed to meet the requirements that capability indices were < 1. For different processes of the same daily QA items, the calculated customized limits were quite different. The range of upper control line (UCL) and lower control line (LCL) was smaller for output and the CL was closer to the target value of 0 for flatness and symmetry in the I-MR control chart calculated using data measured by one staff. For different quality control processes without management by the SPC method at our institution, calculated tolerance and action limits of the same measurement item were quite different. And in most measurement items, the specification limits used in the monthly or annual QA procedures in the TG-142 are not suitable to the daily QA procedure. So the analysis method using SPC is useful and necessary.