Patient-specific Quality Assurance Results Research Articles

932: Forecasting model for qualitative prediction of the results of patient-specific quality assurance.

932: Forecasting model for qualitative prediction of the results of patient-specific quality assurance.

Forecasting model for qualitative prediction of the results of patient-specific quality assurance based on planning and complexity metrics and their interrelations. Pilot study.

The purpose was to analyse the interrelations between planning and complexity metrics and gamma passing rates (GPRs) obtained from VMAT treatments and build the forecasting models for qualitative prediction (QD) of GPRs results. 802 treatment arcs from the plans prepared for the head and neck, thorax, abdomen, and pelvic cancers were analysed. The plans were verified by portal dosimetry and analysed twice using the gamma method with 3%|2mm and 2%|2mm acceptance criteria. The tolerance limit of GPR was 95%. Red, yellow, and green QDs were established for GPR examination. The interrelations were examined, as well as the analysis of effective differentiation of QD. Three models for QD forecasting based on discriminant analysis (DA), random decision forest (RDF) methods, and the hybrid model (HM) were built and evaluated. Most of the interrelations were small or moderate. The exception is correlations of the join function with the average number of monitor units per control point (R = 0.893) and the beam aperture with planning target volume (R = 0.897). While many metrics allow for the effective separation of the QDs from each other, the study shows that predicting the values of the QD is possible only through multi-component forecasting models, of which the HM is the most accurate (0.894). Of the three models explored in this study, the HM, which uses DA methods to predict red QD and RDF methods to predict green and yellow QDs, is the most promising one.

Prediction of patient-specific quality assurance for volumetric modulated arc therapy using radiomics-based machine learning with dose distribution.

We sought to develop machine learning models to predict the results of patient-specific quality assurance (QA) for volumetric modulated arc therapy (VMAT), which were represented by several dose-evaluation metrics-including the gamma passing rates (GPRs)-and criteria based on the radiomic features of 3D dose distribution in a phantom. A total of 4,250 radiomic features of 3D dose distribution in a cylindrical dummy phantom for 140 arcs from 106 clinical VMAT plans were extracted. We obtained the following dose-evaluation metrics: GPRs with global and local normalization, the dose difference (DD) in 1% and 2% passing rates (DD1% and DD2%) for 10% and 50% dose threshold, and the distance-to-agreement in 1-mm and 2-mm passing rates (DTA1 mm and DTA2 mm) for 0.5%/mm and 1.0%.mm dose gradient threshold determined by measurement using a diode array in patient-specific QA. The machine learning regression models for predicting the values of the dose-evaluation metrics using the radiomic features were developed based on the elastic net (EN) and extra trees (ET) models. The feature selection and tuning of hyperparameters were performed with nested cross-validation in which four-fold cross-validation is used within the inner loop, and the performance of each model was evaluated in terms of the root mean square error (RMSE), the mean absolute error (MAE), and Spearman's rank correlation coefficient. The RMSE and MAE for the developed machine learning models ranged from<1% to nearly<10% depending on the dose-evaluation metric, the criteria, and dose and dose gradient thresholds used for both machine learning models. It was advantageous to focus on high dose region for predicating global GPR, DDs, and DTAs. For certain metrics and criteria, it was possible to create models applicable for patients' heterogeneity by training only with dose distributions in phantom. The developed machine learning models showed high performance for predicting dose-evaluation metrics especially for high dose region depending on the metric and criteria. Our results demonstrate that the radiomic features of dose distribution can be considered good indicators of the plan complexity and useful in predicting measured dose evaluation metrics.

Patient-Specific Quality Assurance in Pencil Beam Scanning by 2-Dimensional Array

PurposeThis study aimed to determine the characteristics of 2D ionization chamber array and the confidence limits of the gamma passing rate in pencil beam scanning proton therapy. Materials and Methods:The Varian ProBeam Compact spot-scanning system and the PTW OCTAVIUS 1500XDR array were used as a proton therapy system and detector, respectively. Our methods consisted of 2 parts: (1) the characteristics of the detector were tested and (2) patient-specific quality assurance was performed and evaluated by gamma analysis using dose-difference and distance-to-agreement criteria of 3% and 2 mm, respectively, with 123 treatment plans in head and neck, breast, chest, abdomen, and pelvic regions. Results:The PTW OCTAVIUS 1500XDR array had good reproducibility, uniformity, linearity, repetition rate, and monitor unit per spot within 0.1%, with accuracy, energy dependence, and measurement depth within 0.5%. The overall uncertainty of the PTW OCTAVIUS 1500XDR array was 2.49%. For field size and range shifter, using gamma analysis, the passing rate was 100%. The overall results of patient-specific quality assurance with the gamma evaluation were 98.9% ± 1.6% in 123 plans and confidence limit was 95.7%. Conclusion:The PTW OTAVIUS 1500XDR offered effective performance in pencil beam scanning proton therapy.

Feasibility and Safety of Single-Isocenter/Multi-Lesion (SIML) HyperArc Brain SRT: Clinical Implementation and Early Outcomes

Patients with multiple brain metastases may not tolerate relatively longer treatment times for traditional stereotactic radiation therapy (SRT) with individual isocenter plans for each lesion due to discomfort or co-morbidities. SRT using a single-isocenter/multi-lesion (SIML) HyperArc volumetric modulated arc therapy (VMAT) plan with flattening filter free (FFF) beam could significantly shorten overall treatment time, and improve patient comfort, compliance, and clinic efficiency. We report early clinical results of treating multiple brain metastases with SIML HyperArc SRT. Twenty-three patients with multiple brain metastatic tumors (range, 2-9 lesions; total treated lesions, n = 96) were simulated using Encompass support and Q-fix mask, and treated with a highly-conformal SIML VMAT SRT plans via non-coplanar HyperArc geometry. Mean tumor distance to isocenter was 5.3 cm, maximum up to 7 cm. Common prescriptions were 25-30 Gy/5 fractions, 24-27 Gy/3 fractions, and 20 Gy/1 fraction prescribed to each planning target volume (PTV) using 2 mm margin around standard gross tumor volume (GTV) delineated on contrasted enhanced MP-RAGE MRI fusion. Acuros dose calculation for 6MV-FFF beam was used for tissue heterogeneity corrections. Alliance A071801 criteria was used for dose constraints to organs at risk (OAR) and target conformality. Treatment was delivered every other day with CBCT-guidance, adjustments made with 6DOF couch corrections on a medical linear accelerator, and treatment delivery time within 15 minutes. Local control rates were reported, and toxicity profile rated based on CTCAE v5.0 for brain radionecrosis, optic neuropathy, and brainstem dysfunction. All plans met Alliance A071801 requirements for each tumor coverage, dose to OAR including optic apparatus, brainstem, and spinal cord. Mean GTV and PTV volume were 9.4 cc (range, 0.3-54.8 cc) and 16.13 cc (range, 1.0-80.2 cc). Patient-specific quality assurance results were 98.3% for gamma passing criteria of 2%/2mm. Independent in-house Monte Carlo physics second check agreed with HyperArc plans by ±3.0%. Mean follow up was 6 months (range, 0.0-18.6 months). Of the 23 patients treated, 17 (74%) had post-treatment MRI imaging to assess local control and toxicity. Local control was achieved in 69/73 (95%) of treated and followed lesions. CTCAE grade 2 radionecrosis occurred in 2 patients and were managed with dexamethasone. No CTCAE grade 3+ events of radionecrosis, optic pathway dysfunction, or brainstem toxicity were observed. SIML HyperArc Brain SRT for multiple brain metastases has excellent local control and low toxicity profile in our patients. It can significantly reduce treatment delivery time as compared to traditional multiple-isocenter brain SRT or chronologically separate treatment courses and thus, help to improve patient comfort, compliance, ease of care, and clinic workflow. Longer median follow up of SIML brain SRT on larger patient cohort is warranted.

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.

Improvement Using Planomics Features on Prediction and Classification of Patient-Specific Quality Assurance Using Head and Neck Volumetric Modulated Arc Therapy Plan.

Purpose: This study aimed to evaluate the utility of a new plan feature (planomics feature) for predicting the results of patient-specific quality assurance using the head and neck (H&N) volumetric modulated arc therapy (VMAT) plan.Methods: One hundred and thirty-one H&N VMAT plans in our institution from 2019 to 2021 were retrospectively collected. Dosimetric verification for all plans was carried out using the portal dosimetry system integrated into the Eclipse treatment planning system based on the electronic portal imaging devices. Gamma passing rates (GPR) were analyzed using three gamma indices of 3%/3 mm, 3%/2 mm, and 2%/2 mm with a 10% dose threshold. Forty-eight conventional features affecting the dose delivery accuracy were used in the study, and 2,476 planomics features were extracted based on the radiotherapy plan file. Three prediction and classification models using conventional features (CF), planomics features (PF), and hybrid features (HF) combining two sets of features were constructed by the gradient boosting regressor (GBR) and Ridge classifier for each GPR of 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. The absolute prediction error (APE) and the area under the curve (AUC) were adopted for assessing the performance of prediction and classification models.Results: In the GPR prediction, the average APE of the models using CF, PF, and HF was 1.3 ± 1.2%/3.6 ± 3.0%, 1.7 ± 1.5%/3.8 ± 3.5%, and 1.1 ± 1.0%/4.1 ± 3.1% for 2%/2 mm; 0.7 ± 0.6%/2.0 ± 2.0%, 1.0±1.1%/2.2 ± 1.8%, and 0.6 ± 0.6%/2.2 ± 1.9% for 3%/2 mm; and 0.4 ± 0.3%/1.2 ± 1.2%, 0.4±0.5%/1.3 ± 1.0%, and 0.3±0.3%/1.2 ± 1.1% for 3%/3 mm, respectively. In the regression prediction, three models give a similar modeling performance for predicting the GPR. The classification results were 0.67 ± 0.03/0.66 ± 0.07, 0.77 ± 0.03/0.73 ± 0.06, and 0.78 ± 0.02/0.75 ± 0.04 for 3%/3 mm, respectively. For 3%/2 mm, the AUCs of the training and testing cohorts were 0.64 ± 0.03/0.62 ± 0.07, 0.70 ± 0.03/0.67 ± 0.06, and 0.75 ± 0.03/0.71 ± 0.07, respectively, and for 2%/2 mm, the average AUCs of the training and testing cohorts were 0.72 ± 0.03/0.72 ± 0.06, 0.78 ± 0.04/0.73 ± 0.07, and 0.81 ± 0.03/0.75 ± 0.06, respectively. In the classification, the PF model has a better classification performance than the CF model. Moreover, the HF model provides the best result among the three classifications models.Conclusions: The planomics features can be used for predicting and classifying the GPR results and for improving the model performance after combining the conventional features for the GPR classification.

Suitability Assessment of an Indigenous Heterogeneous Thoracic Phantom for Patient-Specific Quality Assurance in Radiotherapy.

Objective: Patient-specific quality assurance (PSQA) assumes a vital role in precise and accurate radiation delivery to cancer patients. Since the patient body comprises heterogeneous media, the present study aimed to fabricate a heterogeneous thoracic phantom for PSQA. Materials and Methods: Heterogeneous thoracic (HT) phantom was fabricated using rib cage made up of bone equivalent material, kail-wood to mimic lungs and wax to mimic the various body parts. The physical density of all these materials used in phantom fabrication was measured and compared with that of the corresponding part of the actual human thorax. One beam was planned on the computed tomography (CT) images of the phantom and actual patient thorax region. Dose distribution in both the plans was measured and analyzed. Results: The estimated densities of heart, lung, ribs, scapula, spine, and chest wall tissues were 0.804 ± 0.007, 0.186 ± 0.010, 1.796 ± 0.061, 2.017 ± 0.026, 2.106 ± 0.029 and 0.739 ± 0.028 respectively in case of HT phantom while 1.038 ± 0.010, 0.199 ± 0.031, 1.715 ± 0.040, 2.006 ± 0.019, 1.929 ± 0.065 and 0.816 ± 0.028 g/cc, respectively in case of actual human thorax region.The depths of isodose curves in HT phantom were also comparable to the isodose curve’s depths in real patient. The PSQA results were within ± 3% for flat beam (FB) and flattening filtered free beam (FFFB) of 6 megavolts (MV) energy.Conclusion: The density and the dose distribution pattern in the HT phantom were similar to that in the actual human thorax region. Thus, fabricated HT phantom can be utilized for radiation dosimetry in thoracic cancer patients. The materials used to develop HT phantom are easily available in the market at an affordable price and easy to craft.

Survey of patient-specific quality assurance practice for IMRT and VMAT.

A first‐time survey across 15 cancer centers in Ontario, Canada, on the current practice of patient‐specific quality assurance (PSQA) for intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) delivery was conducted. The objectives were to assess the current state of PSQA practice, identify areas for potential improvement, and facilitate the continued improvement in standardization, consistency, efficacy, and efficiency of PSQA regionally. The survey asked 40 questions related to PSQA practice for IMRT/VMAT delivery. The questions addressed PSQA policy and procedure, delivery log evaluation, instrumentation, measurement setup and methodology, data analysis and interpretation, documentation, process, failure modes, and feedback. The focus of this survey was on PSQA activities related to routine IMRT/VMAT treatments on conventional linacs, including stereotactic body radiation therapy but excluding stereotactic radiosurgery. The participating centers were instructed to submit answers that reflected the collective view or opinion of their department and represented the most typical process practiced. The results of the survey provided a snapshot of the current state of PSQA practice in Ontario and demonstrated considerable variations in the practice. A large majority (80%) of centers performed PSQA measurements on all VMAT plans. Most employed pseudo‐3D array detectors with a true composite (TC) geometry. No standard approach was found for stopping or reducing frequency of measurements. The sole use of delivery log evaluation was not widely implemented, though most centers expressed interest in adopting this technology. All used the Gamma evaluation method for analyzing PSQA measurements; however, no universal approach was reported on how Gamma evaluation and pass determination criteria were determined. All or some PSQA results were reviewed regularly in two‐thirds of the centers. Planning related issues were considered the most frequent source for PSQA failures (40%), whereas the most frequent course of action for a failed PSQA was to review the result and decide whether to proceed to treatment.

Exploring the gamma surface: A new method for visualising modulated radiotherapy quality assurance results.

This work presents a novel method of visualising the results of patient-specific quality assurance (QA) for modulated radiotherapy treatment plans, using a three-dimensional distribution of gamma pass rates, referred to as the "gamma surface". The method was developed to aid in comparing borderline and failing QA plans, and to better compare patient-specific QA results between departments. Gamma surface plots were created for a representative sample of situations encountered during patient-specific QA. To produce a gamma surface plot, for each QA result, gamma pass rates were plotted as a heat map, with dose difference on one axis and distance-to-agreement on the other. This involved the calculation of 100×100 gamma pass rates over a dose difference and distance-to-agreement grid. As examples, five 220×680 arrays of dose points from radiotherapy treatment plans were compared against measurement data consisting of 21×66 arrays of dose points spaced 10mm apart. The gamma surface plots facilitated the rapid evaluation of criteria combinations for each plan, clearly highlighting the difference between plans that are modelled and delivered well, and those that are not. Large scale features were also evident in each surface, hinting at potential over-modulation, systematic dose errors, and small or large scale areas of disagreement in the distributions. Gamma surface plots are a useful tool for investigating QA failures and borderline results, and have the capacity to grant insights into treatment plan QA performance that may otherwise be missed.

Electron Paramagnetic Resonance Spectroscopy for Gamma Knife Dosimetry

Alanine chips exposed to high doses of radiation produces long lived free radicals that could be easily measured with electron paramagnetic resonance (EPR) spectrometers. In this study, the feasibility of using alanine dosimeters for performing rapid quality assurance of Leksell Gamma Knife (LGK) treatment plans was demonstrated. A 3D printed grid was placed inside the LGK spherical solid water phantom (SWP) for measurement of doses at isocentre and off-axis points. The EPR spectroscopy was performed on a Magnettech MS-5000 EPR/ESR spectrometer. A set of dose calibration curves were established prior to the use of alanine chips for LGK dosimetry. Absolute dose, transit dose and dose/timer linearity were performed with the alanine chips positioned at the centre of the LGK solid water phantom (SWP). Five patients of different sites were selected, and patient specific quality assurance (PSQA) was performed in the LGK SWP. The absolute dose measured with the EPR alanine dosimeter agreed well within 2% of the ion chamber results and PSQA results were within 2.1%. Alanine-based EPR dosimetry offers rapid dose measurement with high accuracy and can also be used as a dosimeter for Gamma Knife PSQA.

Effect of dose grid resolution on the results of patient-specific quality assurance for intensity-modulated radiation therapy and volumetric modulated arc therapy

Effect of dose grid resolution on the results of patient-specific quality assurance for intensity-modulated radiation therapy and volumetric modulated arc therapy

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

PurposeTo 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 methodsDVH_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).ResultsIn 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.ConclusionThe 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.

Complexity metrics for IMRT and VMAT plans: a review of current literature and applications.

Modulated radiotherapy with multileaf collimators is widely used to improve target conformity and normal tissue sparing. This introduced an additional degree of complexity, studied by multiple teams through different properties. Three categories of complexity metrics were considered in this review: fluence, deliverability and accuracy metrics. The first part of this review is dedicated to the inventory of these complexity metrics. Different applications of these metrics emerged. Influencing the optimizer by integrating complexity metrics into the cost function has been little explored and requires more investigations. In modern treatment planning system, it remains confined to MUs or treatment time limitation. A large majority of studies calculated metrics only for analysis, without plan modification. The main application was to streamline the patient specific quality assurance workload, investigating the capability of complexity metrics to predict patient specific quality assurance results. Additionally complexity metrics were used to analyze behaviour of TPS optimizer, compare TPS, operators and plan properties, and perform multicentre audit. Their potential was also explored in the context of adaptive radiotherapy and automation planning. The second part of the review gives an overview of these studies based on the complexity metrics.

Predicting VMAT patient-specific QA results using a support vector classifier trained on treatment plan characteristics and linac QC metrics

The use of treatment plan characteristics to predict patient-specific quality assurance (QA) measurement results has recently been reported as a strategy to help facilitate automated pre-treatment verification workflows or to provide a virtual assessment of delivery quality. The goal of this work is to investigate the potential of using treatment plan characteristics and linac performance metrics (i.e. quality control test results) in combination with machine learning techniques to predict the results of VMAT patient-specific QA measurements.Using features that describe treatment plan complexity and linac performance metrics, we trained a linear support vector classifier (SVC) to classify the results of VMAT patient-specific QA measurements. The ‘targets’ in this model were simple classes representing median dose difference between measured and expected dose distributions—‘hot’ if the median dose deviation was >1%, ‘cold’ if it was <−1%, and ‘normal’ if it was within ±1%. A total of 1620 unique patient-specific QA measurements were available for model development and testing. 75% of the data were used to develop and cross-validate the model, and the remaining 25% were used for an independent assessment of model performance. For the model development phase, a recursive feature elimination (RFE) cross-validation technique was used to eliminate unimportant features. Model performance was assessed using receiver operator characteristic (ROC) curve metrics.Of the ten features found to be most predictive of patient-specific QA measurement results, half were derived from treatment plan characteristics and half from quality control (QC) metrics characterizing linac performance. The model achieved a micro-averaged area under the ROC curve of 0.93, and a macro-averaged area under the ROC curve of 0.88.This work demonstrates the potential of using both treatment plan characteristics and routine linac QC results in the development of machine learning models for VMAT patient-specific QA measurements.

Impact of the Use of Homogeneous and Heterogeneous Phantoms in Pretreatment Verification for Volumetric Modulated Arc Radiotherapy

The purpose of this study was to investigate the impact of quality assurance (QA) phantoms designed with different material to verify the accuracy of dose distribution for volumetric modulated arc radiotherapy (VMAT). Homogeneous and heterogeneous QA phantoms are developed to compare the pretreatment verification according to the different materials made in the phantom for routine VMAT of lung cancer. These phantoms have a quadrature rectangular shape with horizontal and vertical lengths of 300 mm and 315 mm, respectively, and with inserts of various slabs. The homogeneous QA phantom was constructed using only polymethyl methacrylate (ρ = 1.19 g/cm3). The heterogeneous QA phantom was constructed using a ceramic fiber board with a density of 0.3 g/cm3, which is similar to that of the lung in human thorax. Overall, the average gamma agreement values for the homogeneous and the heterogeneous QA phantoms were observed to be higher than 94.9% and 95.4% for two energies and the usual criteria. In addition, this study showed that the gamma agreement values obtained for both the homogeneous and the heterogeneous QA phantom agreed to within 2% for both the 2%/2 mm and the 3%/3 mm criteria. Furthermore, no statistically significant difference was observed in the gamma agreement values obtained using the homogeneous and the heterogeneous QA phantoms for both energies and the usual criteria (p > 0.05). Consequentially, this study found that patient specific QA results were not affected by phantoms made of the different materials.

A management method for the statistical results of patient-specific quality assurance for intensity-modulated radiation therapy.

There are many reports concerning patient-specific quality assurance (QA) for intensity-modulated radiation therapy (IMRT). However, reports about the statistical results of QA are lacking. Management methods for the results of the QA are needed, even though we have the ESTRO group recommendation that a tolerance limit of 1.96 standard deviation (SD) be established in each institution. The purpose of this study was to establish a management method for determining the tolerance limit and to report the statistical results of patient-specific QA. From April 2006 to March 2015, five linacs in the National Cancer Center, Tokyo, Japan, were used to treat 1185 patients with IMRT. Patient-specific QA was performed using an ion chamber, films, and some detectors. To establish a management method for the results, differences between the measured and calculated doses in the ion chamber were analyzed for each linac, each phantom, and each treatment site. The overall mean dose difference was 0.5 ± 1.3%, and the mean dose difference in each linac was 0.6 ± 1.2%, 0.9 ± 1.3%, −0.4 ± 1.4%, −0.1 ± 1.2% and −0.1 ± 0.9%. The difference between linacs and between treatment sites was significant (P < 0.001 and 0.01, respectively). The proportion of the dose difference within ±3% was 97.7%, and that was improved from 2006 to 2014. The results of the patient-specific QA should be managed for each linac and each treatment site in order to decide the suitable tolerance limit. Reports of statistical results will be helped if a new tolerance limit and action level will be considered.

Analyzing the performance of ArcCHECK diode array detector for VMAT plan

AimThe aim of this study is to evaluate performance of ArcCHECK diode array detector for the volumetric modulated arc therapy (VMAT) patient specific quality assurance (QA). VMAT patient specific QA results were correlated with ion chamber measurement. Dose response of the ArcCHECK detector was studied. BackgroundVMAT delivery technique improves the dose distribution. It is complex in nature and requires proper QA before its clinical implementation. ArcCHECK is a novel three dimensional dosimetry system. Materials and methodsTwelve retrospective VMAT plans were calculated on ArcCHECK phantom. Point dose and dose map were measured simultaneously with ion chamber (IC-15) and ArcCHECK diode array detector, respectively. These measurements were compared with their respective TPS calculated values. ResultsThe ion chamber measurements are in good agreement with TPS calculated doses. Mean difference between them is 0.50% with standard deviation of 0.51%. Concordance correlation coefficient (CCC) obtained for ion chamber measurements is 0.9996. These results demonstrate a strong correlation between the absolute dose predicted by our TPS and the measured dose. The CCC between ArcCHECK doses and TPS predictions on the CAX was found to be 0.9978. In gamma analysis of dose map, the mean passing rate was 98.53% for 3% dose difference and 3mm distance to agreement. ConclusionsThe VMAT patient specific QA with an ion chamber and ArcCHECK phantom are consistent with the TPS calculated dose. Statistically good agreement was observed between ArcCHECK measured and TPS calculated. Hence, it can be used for routine VMAT QA.