Predicting gamma evaluation results of patient-specific head and neck volumetric-modulated arc therapy quality assurance based on multileaf collimator patterns and fluence map features: A feasibility study.

The purpose of this study was to develop a predictive model for patient-specific VMAT QA results using multileaf collimator (MLC) effect and texture analysis. The MLC speed, acceleration and texture analysis features were extracted from 106 VMAT plans as predictors. Gamma passing rate (GPR) was collected as a response class with gamma criteria of 2%/2 mm and 3%/2 mm. The model was trained using two machine learning methods: AdaBoost classification and bagged regression trees model. GPR was classified into the "PASS" and "FAIL" for the classification model using the institutional warning level. The accuracy of the model was assessed using sensitivity and specificity. In addition, the accuracy of the regression model was determined using the difference between predicted and measured GPR. For the AdaBoost classification model, the sensitivity/specificity was 94.12%/100% and 63.63%/53.13% at gamma criteria of 2%/2 mm and 3%/2 mm, respectively. For the bagged regression trees model, the sensitivity/specificity was 94.12%/91.89% and 61.18%/68.75% at gamma criteria of 2%/2 mm and 3%/2 mm, respectively. The root mean square error (RMSE) of difference between predicted and measured GPR was found at 2.44 and 1.22 for gamma criteria of 2%/2 mm and 3%/2 mm, respectively. The promising result was found at tighter gamma criteria 2%/2 mm with 94.12% sensitivity (both bagged regression trees and AdaBoost classification model) and 100% specificity (AdaBoost classification model).

Predictive quality assurance of a linear accelerator based on the machine performance check application using statistical process control and ARIMA forecast modeling.

PURPOSE: A predictive linac quality assurance system based on the output of the Machine Performance Check (MPC) application was developed using statistical process control and autoregressive integrated moving average forecast modeling. The aim of this study is to demonstrate the feasibility of predictive quality assurance based on MPC tests that allow proactive preventative maintenance procedures to be carried out to better ensure optimal linac performance and minimize downtime. METHOD AND MATERIALS: Daily MPC data were acquired for a total of 490 measurements. The initial 85% of data were used in prediction model learning with the autoregressive integrated moving average technique and in calculating upper and lower control limits for statistical process control analysis. The remaining 15% of data were used in testing the accuracy of the predictions of the proposed system. Two types of prediction were studied, namely, one-step-ahead values for predicting the next day's quality assurance results and six-step-ahead values for predicting up to a week ahead. Results that fall within the upper and lower control limits indicate a normal stage of machine performance, while the tolerance, determined from AAPM TG-142, is the clinically required performance. The gap between the control limits and the clinical tolerances (as the warning stage) provides a window of opportunity for rectifying linac performance issues before they become clinically significant. The accuracy of the predictive model was tested using the root-mean-square error, absolute error, and average accuracy rate for all MPC test parameters. RESULTS: The accuracy of the predictive model is considered high (average root-mean-square error and absolute error for all parameters of less than 0.05). The average accuracy rate for indicating the normal/warning stages was higher than 85.00%. CONCLUSION: Predictive quality assurance with the MPC will allow preventative maintenance, which could lead to improved linac performance and a reduction in unscheduled linac downtime.

A novel and independent method for time-resolved gantry angle quality assurance for VMAT.

Volumetric-modulated arc therapy (VMAT) treatment delivery requires three key dynamic components; gantry rotation, dose rate modulation, and multi-leaf collimator motion, which are all simultaneously varied during the delivery. Misalignment of the gantry angle can potentially affect clinical outcome due to the steep dose gradients and complex MLC shapes involved. It is essential to develop independent gantry angle quality assurance (QA) appropriate to VMAT that can be performed simultaneously with other key VMAT QA testing. In this work, a simple and inexpensive fully independent gantry angle measurement methodology was developed that allows quantitation of the gantry angle accuracy as a function of time. This method is based on the analysis of video footage of a "Double dot" pattern attached to the front cover of the linear accelerator that consists of red and green circles printed on A4 paper sheet. A standard mobile phone is placed on the couch to record the video footage during gantry rotation. The video file is subsequently analyzed and used to determine the gantry angle from each video frame using the relative position of the two dots. There were two types of validation tests performed including the static mode with manual gantry angle rotation and dynamic mode with three complex test plans. The accuracy was 0.26° ± 0.04° and 0.46° ± 0.31° (mean ± 1 SD) for the static and dynamic modes, respectively. This method is user friendly, cost effective, easy to setup, has high temporal resolution, and can be combined with existing time-resolved method for QA of MLC and dose rate to form a comprehensive set of procedures for time-resolved QA of VMAT delivery system.

A method for evaluating treatment quality using in vivo EPID dosimetry and statistical process control in radiation therapy.

Purpose Due to increasing complexity, modern radiotherapy techniques require comprehensive quality assurance (QA) programmes, that to date generally focus on the pre-treatment stage. The purpose of this paper is to provide a method for an individual patient treatment QA evaluation and identification of a "quality gap" for continuous quality improvement. Design/methodology/approach A statistical process control (SPC) was applied to evaluate treatment delivery using in vivo electronic portal imaging device (EPID) dosimetry. A moving range control chart was constructed to monitor the individual patient treatment performance based on a control limit generated from initial data of 90 intensity-modulated radiotherapy (IMRT) and ten volumetric-modulated arc therapy (VMAT) patient deliveries. A process capability index was used to evaluate the continuing treatment quality based on three quality classes: treatment type-specific, treatment linac-specific, and body site-specific. Findings The determined control limits were 62.5 and 70.0 per cent of the χ pass-rate for IMRT and VMAT deliveries, respectively. In total, 14 patients were selected for a pilot study the results of which showed that about 1 per cent of all treatments contained errors relating to unexpected anatomical changes between treatment fractions. Both rectum and pelvis cancer treatments demonstrated process capability indices were less than 1, indicating the potential for quality improvement and hence may benefit from further assessment. Research limitations/implications The study relied on the application of in vivo EPID dosimetry for patients treated at the specific centre. Sampling patients for generating the control limits were limited to 100 patients. Whilst the quantitative results are specific to the clinical techniques and equipment used, the described method is generally applicable to IMRT and VMAT treatment QA. Whilst more work is required to determine the level of clinical significance, the authors have demonstrated the capability of the method for both treatment specific QA and continuing quality improvement. Practical implications The proposed method is a valuable tool for assessing the accuracy of treatment delivery whilst also improving treatment quality and patient safety. Originality/value Assessing in vivo EPID dosimetry with SPC can be used to improve the quality of radiation treatment for cancer patients.

Interobserver delineation variability of computed tomography-based radiomic features of the parotid gland.

PURPOSE: To assess the interobserver delineation variability of radiomic features of the parotid gland from computed tomography (CT) images and evaluate the correlation of these features for head and neck cancer (HNC) radiotherapy patients. MATERIALS AND METHODS: Contrast-enhanced CT images of 20 HNC patients were utilized. The parotid glands were delineated by treating radiation oncologists (ROs), a selected RO and AccuContour auto-segmentation software. Dice similarity coefficients (DSCs) between each pair of observers were calculated. A total of 107 radiomic features were extracted, whose robustness to interobserver delineation was assessed using the intraclass correlation coefficient (ICC). Pearson correlation coefficients (r) were calculated to determine the relationship between the features. The influence of excluding unrobust features from normal tissue complication probability (NTCP) modeling was investigated for severe oral mucositis (grade ≥3). RESULTS: The average DSC was 0.84 (95% confidence interval, 0.83-0.86). Most of the shape features demonstrated robustness (ICC ≥0.75), while the first-order and texture features were influenced by delineation variability. Among the three observers investigated, 42 features were sufficiently robust, out of which 36 features exhibited weak correlation (|r|<0.8). No significant difference in the robustness level was found when comparing manual segmentation by a single RO or automated segmentation with the actual clinical contour data made by treating ROs. Excluding unrobust features from the NTCP model for severe oral mucositis did not deteriorate the model performance. CONCLUSION: Interobserver delineation variability had substantial impact on radiomic features of the parotid gland. Both manual and automated segmentation methods contributed similarly to this variation.

Design of 3D-printed universal oral stent for tongue immobilization in head and neck radiotherapy.

The primary treatment for head and neck cancer is radiotherapy, which can cause complications and effects, such as the ability to speak, taste, produce saliva, and swallow. An oral stent is an immobilization tool for minimizing the dose in the tongue (or hard palate) by locking the tongue position during radiation delivery. It can improve the treatment accuracy due to less uncertainty caused by tongue position uncertainty between treatment fractions. However, commercial oral stents are not widely adopted in developing countries due to their unaffordable price. This study aimed to design the universal oral stent (UOS) to achieve high efficiency, ease to use, and low-cost fabrication based on 3D printing technology. There were five experiments to evaluate the UOS design and fabrication versus the modified cut syringe, including finite element analysis (FEA), the usability test, the micro Vickers hardness test, single beam dose analysis, and dose calculation on treatment plan simulations. The proposed UOS design and fabrication presented a high capability to apply for clinical use.

Predicting Three-Dimensional Dose Distribution of Prostate Volumetric Modulated Arc Therapy Using Deep Learning.

BACKGROUND: Volumetric modulated arc therapy (VMAT) planning is a time-consuming process of radiation therapy. With a deep learning approach, 3D dose distribution can be predicted without the need for an actual dose calculation. This approach can accelerate the process by guiding and confirming the achievable dose distribution in order to reduce the replanning iterations while maintaining the plan quality. METHODS: In this study, three dose distribution predictive models of VMAT for prostate cancer were developed, evaluated, and compared. Each model was designed with a different input data structure to train and test the model: (1) patient CT alone (PCT alone), (2) patient CT and generalized organ structure (PCTGOS), and (3) patient CT and specific organ structure (PCTSOS). The generative adversarial network (GAN) model was used as a core learning algorithm. The models were trained slice-by-slice using 46 VMAT plans for prostate cancer, and then used to predict and evaluate the dose distribution from 8 independent plans. RESULTS: VMAT dose distribution was generated with a mean prediction time of approximately 3.5 s per patient, whereas the PCTSOS model was excluded due to a mean prediction time of approximately 17.5 s per patient. The highest average 3D gamma passing rate was 80.51 ± 5.94, while the lowest overall percentage difference of dose-volume histogram (DVH) parameters was 6.01 ± 5.44% for the prescription dose from the PCTGOS model. However, the PCTSOS model was the most reliable for the evaluation of multiple parameters. CONCLUSIONS: This dose prediction model could accelerate the iterative optimization process for the planning of VMAT treatment by guiding the planner with the desired dose distribution.

Can the Risk of Dysphagia in Head and Neck Radiation Therapy Be Predicted by an Automated Transit Fluence Monitoring Process During Treatment? A First Comparative Study of Patient Reported Quality of Life and the Fluence-Based Decision Support Metric.

PURPOSE/OBJECTIVE(S): The additional personnel and imaging procedures required for Adaptive Radiation Therapy (ART) pose a challenge for a broad implementation. We hypothesize that a change in transit fluence during the treatment course is correlated with the change of quality of life and thus can be used as a replanning trigger. MATERIALS/METHODS: Twenty-one head and neck cancer (HNC) patients filled out an MD Anderson Dysphagia Inventory (MDADI) questionnaire, before-and-after the radiotherapy treatment course. The transit fluence was measured by the Watchdog (WD) in-vivo portal dosimetry system. The patients were monitored with daily WD and weekly CBCTs. The region of interest (ROI) of each patient was defined as the outer contour of the patient between approximate spine levels C1 to C4, essentially the neck and mandible inside the beam's eye view. The nth day integrated transit fluence change, Δϕn, and the volume change, ΔVROI, of the ROI of each patient was calculated from the corresponding WD and CBCT measurements. The correlation between MDADI scores and age, gender, planning mean dose to salivary glands , weight change ΔW, ΔVROI, and Δϕn, were analyzed using the ranked-Pearson correlation. RESULTS: No statistically significant correlation was found for age, gender and ΔW. was found to have clinically important correlation with functional MDADI (ρ = -0.39, P = 0.081). ΔVROI was found to have statistically significant correlation of 0.44, 0.47 and 0.44 with global, physical and functional MDADI (P-value < 0.05). Δϕn was found to have statistically significant ranked-correlation (-0.46, -0.46 and -0.45) with physical, functional and total MDADI (P-value < 0.05). CONCLUSION: A transit fluence based decision support metric (DSM) is statistically correlated with the dysphagia risk. It can not only be used as an early signal in assisting clinicians in the ART patient selection for replanning, but also lowers the resource barrier of ART implementation.

Toward real-time verification for MLC tracking treatments using time-resolved EPID imaging.

PURPOSE: In multileaf collimator (MLC) tracking, the MLC positions from the original treatment plan are continuously modified to account for intrafraction tumor motion. As the treatment is adapted in real time, there is additional risk of delivery errors which cannot be detected using traditional pretreatment dose verification. The purpose of this work is to develop a system for real-time geometric verification of MLC tracking treatments using an electronic portal imaging device (EPID). METHODS: MLC tracking was utilized during volumetric modulated arc therapy (VMAT). During these deliveries, treatment beam images were taken at 9.57 frames per second using an EPID and frame grabber computer. MLC positions were extracted from each image frame and used to assess delivery accuracy using three geometric measures: the location, size, and shape of the radiation field. The EPID-measured field location was compared to the tumor motion measured by implanted electromagnetic markers. The size and shape of the beam were compared to the size and shape from the original treatment plan, respectively. This technique was validated by simulating errors in phantom test deliveries and by comparison between EPID measurements and treatment log files. The method was applied offline to images acquired during the LIGHT Stereotactic Ablative Body Radiotherapy (SABR) clinical trial, where MLC tracking was performed for 17 lung cancer patients. The EPID-based verification results were subsequently compared to post-treatment dose reconstruction. RESULTS: Simulated field location errors were detected during phantom validation tests with an uncertainty of 0.28 mm (parallel to MLC motion) and 0.38 mm (perpendicular), expressed as a root-mean-square error (RMSError ). For simulated field size errors, the RMSError was 0.47 cm2 and field shape changes were detected for random errors with standard deviation ≥ 2.5 mm. For clinical lung SABR deliveries, field location errors of 1.6 mm (parallel MLC motion) and 4.9 mm (perpendicular) were measured (expressed as a full-width-half-maximum). The mean and standard deviation of the errors in field size and shape were 0.0 ± 0.3 cm2 and 0.3 ± 0.1 (expressed as a translation-invariant normalized RMS). No correlation was observed between geometric errors during each treatment fraction and dosimetric errors in the reconstructed dose to the target volume for this cohort of patients. CONCLUSION: A system for real-time delivery verification has been developed for MLC tracking using time-resolved EPID imaging. The technique has been tested offline in phantom-based deliveries and clinical patient deliveries and was used to independently verify the geometric accuracy of the MLC during MLC tracking radiotherapy.

An inter-centre statistical scale standardisation for quantitatively evaluating prostate tissue on T2-weighted MRI.

Magnetic resonance images (MRI) require intensity standardisation if they are used for the purpose of quantitative analysis as inherent variations in image intensity levels between different image sets are manifest due to technical factors. One approach is to standardise the image intensity values using a statistically applied biological reference tissue. The aim of this study is to compare the performance of differing candidate biological reference tissues for standardising T2WI intensity distributions. Fifty-one prostate cancer patients across two centres with different scanners were evaluated using the percentage interpatient coefficient of variation (%interCV) for four different biological references; femoral bone marrow, ischioanal fossa, obturator-internus muscle and bladder urine. The tissue with the highest reproducibility (lowest %interCV) in both centres was used for intensity standardisation of prostate T2WI using three different statistical measures (mean, Z-score, median + Interquartile Range). The performance of different standardisation methods was evaluated from the assessment of image intensity histograms and the percentage normalised root mean square error (%NRSME) of the healthy peripheral zone tissue. Ischioanal fossa as a reference tissue demonstrated the highest reproducibility with %interCV of 18.9 for centre1 and 11.2 for centre2. Using ischioanal fossa for statistical intensity standardisation and the median + Interquartile Range method demonstrated the lowest %NRMSE across centres for healthy peripheral zone tissues. This study demonstrates ischioanal fossa as a preferred reference tissue for standardising intensity values from T2WI of the prostate. Subsequent image standardisation using the median + Interquartile Range intensity of the reference tissue demonstrated a robust and reliable standardisation method for quantitative image assessment.

The accuracy and precision of Kilovoltage Intrafraction Monitoring (KIM) six degree-of-freedom prostate motion measurements during patient treatments.

BACKGROUND AND PURPOSE: To perform a quantitative analysis of the accuracy and precision of Kilovoltage Intrafraction Monitoring (KIM) six degree-of-freedom (6DoF) prostate motion measurements during treatments. MATERIAL AND METHODS: Real-time 6DoF prostate motion was acquired using KIM for 14 prostate cancer patients (377 fractions). KIM outputs the 6DoF prostate motion, combining 3D translation and 3D rotational motion information relative to its planning position. The corresponding groundtruth target motion was obtained post-treatment based on kV/MV triangulation. The accuracy and precision of the 6DoF KIM motion estimates were calculated as the mean and standard deviation differences compared with the ground-truth. RESULTS: The accuracy ±â€¯precision of real-time 6DoF KIM-measured prostate motion were 0.2 ±â€¯1.3° for rotations and 0.1 ±â€¯0.5 mm for translations, respectively. The magnitude of KIM-measured motion was well-correlated with the magnitude of ground-truth motion resulting in Pearson correlation coefficients of  ≥0.88 in all DoF. CONCLUSIONS: The results demonstrate that KIM is capable of providing the real-time 6DoF prostate target motion during patient treatments with an accuracy ±â€¯precision of within 0.2 ±â€¯1.3° and 0.1 ±â€¯0.5 mm for rotation and translation, respectively. As KIM only requires a single X-ray imager, which is available on most modern cancer radiotherapy devices, there is potential for widespread adoption of this technology.

Commissioning and quality assurance for VMAT delivery systems: An efficient time-resolved system using real-time EPID imaging.

PURPOSE: An ideal commissioning and quality assurance (QA) program for Volumetric Modulated Arc Therapy (VMAT) delivery systems should assess the performance of each individual dynamic component as a function of gantry angle. Procedures within such a program should also be time-efficient, independent of the delivery system and be sensitive to all types of errors. The purpose of this work is to develop a system for automated time-resolved commissioning and QA of VMAT control systems which meets these criteria. METHODS: The procedures developed within this work rely solely on images obtained, using an electronic portal imaging device (EPID) without the presence of a phantom. During the delivery of specially designed VMAT test plans, EPID frames were acquired at 9.5 Hz, using a frame grabber. The set of test plans was developed to individually assess the performance of the dose delivery and multileaf collimator (MLC) control systems under varying levels of delivery complexities. An in-house software tool was developed to automatically extract features from the EPID images and evaluate the following characteristics as a function of gantry angle: dose delivery accuracy, dose rate constancy, beam profile constancy, gantry speed constancy, dynamic MLC positioning accuracy, MLC speed and acceleration constancy, and synchronization between gantry angle, MLC positioning and dose rate. Machine log files were also acquired during each delivery and subsequently compared to information extracted from EPID image frames. RESULTS: The largest difference between measured and planned dose at any gantry angle was 0.8% which correlated with rapid changes in dose rate and gantry speed. For all other test plans, the dose delivered was within 0.25% of the planned dose for all gantry angles. Profile constancy was not found to vary with gantry angle for tests where gantry speed and dose rate were constant, however, for tests with varying dose rate and gantry speed, segments with lower dose rate and higher gantry speed exhibited less profile stability. MLC positional accuracy was not observed to be dependent on the degree of interdigitation. MLC speed was measured for each individual leaf and slower leaf speeds were shown to be compensated for by lower dose rates. The test procedures were found to be sensitive to 1 mm systematic MLC errors, 1 mm random MLC errors, 0.4 mm MLC gap errors and synchronization errors between the MLC, dose rate and gantry angle controls systems of 1°. In general, parameters measured by both EPID and log files agreed with the plan, however, a greater average departure from the plan was evidenced by the EPID measurements. CONCLUSION: QA test plans and analysis methods have been developed to assess the performance of each dynamic component of VMAT deliveries individually and as a function of gantry angle. This methodology relies solely on time-resolved EPID imaging without the presence of a phantom and has been shown to be sensitive to a range of delivery errors. The procedures developed in this work are both comprehensive and time-efficient and can be used for streamlined commissioning and QA of VMAT delivery systems.

Investigation of a real-time EPID-based patient dose monitoring safety system using site-specific control limits.

PURPOSE: The aim of this study is to investigate the performance and limitations of a real-time transit electronic portal imaging device (EPID) dosimetry system for error detection during dynamic intensity modulated radiation therapy (IMRT) treatment delivery. Sites studied are prostate, head and neck (HN), and rectal cancer treatments. METHODS: The system compares measured cumulative transit EPID image frames with predicted cumulative image frames in real-time during treatment using a χ comparison with 4 %, 4 mm criteria. The treatment site-specific thresholds (prostate, HN and rectum IMRT) were determined using initial data collected from 137 patients (274 measured treatment fractions) and a statistical process control methodology. These thresholds were then applied to data from 15 selected patients including 5 prostate, 5 HN, and 5 rectum IMRT treatments for system evaluation and classification of error sources. RESULTS: Clinical demonstration of real-time transit EPID dosimetry in IMRT was presented. For error simulation, the system could detect gross errors (i.e. wrong patient, wrong plan, wrong gantry angle) immediately after EPID stabilisation; 2 seconds after the start of treatment. The average rate of error detection was 7.0 % (prostate = 5.6 %, HN= 8.7 % and rectum = 6.7 %). The detected errors were classified as either clinical in origin (e.g. patient anatomical changes), or non-clinical in origin (e.g. detection system errors). Classified errors were 3.2 % clinical and 3.9 % non-clinical. CONCLUSION: An EPID-based real-time error detection method for treatment verification during dynamic IMRT has been developed and tested for its performance and limitations. The system is able to detect gross errors in real-time, however improvement in system robustness is required to reduce the non-clinical sources of error detection.

A cine-EPID based method for jaw detection and quality assurance for tracking jaw in IMRT/VMAT treatments.

A new tool with the potential to verify and track jaw position during delivery has been developed. The method should be suitable for independent quality assurance for jaw position during jaw tracking dynamic IMRT and VMAT treatments. The jaw detection and tracking algorithm developed consists of five main steps. Firstly, the image is enhanced by removing a normalised predicted EPID image (that does not include the collimator transmission) from each cine EPID image. Then, using a histogram clustering technique a global intensity threshold level was determined. This threshold level was used to classify each pixel of the image as either under the jaws or under the MLC. Additionally, the collimator angle was automatically detected and used to rotate the image to vertical direction. Finally, this rotation allows the jaw positions to be determined using vertical and horizontal projection profiles. Nine IMRT fields (with static jaws) and a single VMAT clinical field (with dynamic jaws) were tested by determining the root mean square difference between planned and detected jaw positions. The test results give a detection accuracy of ±1 mm RMS error for static jaw IMRT treatments and ±1.5 mm RMS error for the dynamic jaw VMAT treatment. This method is designed for quality assurance and verification in modern radiation therapy; to detect the position of static jaws or verify the position of tracking jaws in more complex treatments. This method uses only information extracted from EPID images and it is therefore independent from the linear accelerator.

First Experience With Real-Time EPID-Based Delivery Verification During IMRT and VMAT Sessions.

PURPOSE: Gantry-mounted megavoltage electronic portal imaging devices (EPIDs) have become ubiquitous on linear accelerators. WatchDog is a novel application of EPIDs, in which the image frames acquired during treatment are used to monitor treatment delivery in real time. We report on the preliminary use of WatchDog in a prospective study of cancer patients undergoing intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) and identify the challenges of clinical adoption. METHODS AND MATERIALS: At the time of submission, 28 cancer patients (head and neck, pelvis, and prostate) undergoing fractionated external beam radiation therapy (24 IMRT, 4 VMAT) had ≥1 treatment fraction verified in real time (131 fractions or 881 fields). EPID images acquired continuously during treatment were synchronized and compared with model-generated transit EPID images within a frame time (∼0.1 s). A χ comparison was performed to cumulative frames to gauge the overall delivery quality, and the resulting pass rates were reported graphically during treatment delivery. Every frame acquired (500-1500 per fraction) was saved for postprocessing and analysis. RESULTS: The system reported the mean ± standard deviation in real time χ 91.1% ± 11.5% (83.6% ± 13.2%) for cumulative frame χ analysis with 4%, 4 mm (3%, 3 mm) criteria, global over the integrated image. CONCLUSIONS: A real-time EPID-based radiation delivery verification system for IMRT and VMAT has been demonstrated that aims to prevent major mistreatments in radiation therapy.

An independent system for real-time dynamic multileaf collimation trajectory verification using EPID.

A new tool has been developed to verify the trajectory of dynamic multileaf collimators (MLCs) used in advanced radiotherapy techniques using only the information provided by the electronic portal imaging devices (EPID) measured image frames. The prescribed leaf positions are resampled to a higher resolution in a pre-processing stage to improve the verification precision. Measured MLC positions are extracted from the EPID frames using a template matching method. A cosine similarity metric is then applied to synchronise measured and planned leaf positions for comparison. Three additional comparison functions were incorporated to ensure robust synchronisation. The MLC leaf trajectory error detection was simulated for both intensity modulated radiation therapy (IMRT) (prostate) and volumetric modulated arc therapy (VMAT) (head-and-neck) deliveries with anthropomorphic phantoms in the beam. The overall accuracy for MLC positions automatically extracted from EPID image frames was approximately 0.5 mm. The MLC leaf trajectory verification system can detect leaf position errors during IMRT and VMAT with a tolerance of 3.5 mm within 1 s.

Gantry-angle resolved VMAT pretreatment verification using EPID image prediction.

PURPOSE: Pretreatment verification of volumetric modulated arc therapy (VMAT) dose delivery with electronic portal imaging device (EPID) uses images integrated over the entire delivery or over large subarcs. This work aims to develop a new method for gantry-angle-resolved verification of VMAT dose delivery using EPID. METHODS: An EPID dose prediction model was used to calculate EPID images as a function of gantry angle for eight prostate patient deliveries. EPID image frames at 7.5 frames per second were acquired during delivery via a frame-grabber system. The gantry angle for each image was encoded in kV frames which were synchronized to the MV frames. Gamma analysis results as a function of gantry angle were assessed by integrating the frames over 2° subarcs with an angle-to-agreement tolerance of 0.5° about the measured image angle. RESULTS: The model agreed with EPID images integrated over the entire delivery with average Gamma pass-rates at 2%, 2 mm of 99.7% (10% threshold). The accuracy of the kV derived gantry angle for each image was found to be 0.1° (1 SD) using a phantom test. For the gantry-resolved analysis all Gamma pass-rates were greater than 90% at 3%, 3 mm criteria (with only two exceptions), and more than 90% had a 95% pass-rate, with an average of 97.3%. The measured gantry angle lagged behind the predicted angle by a mean of 0.3°±0.3°, with a maximum lag of 1.3°. CONCLUSIONS: The method provides a comprehensive and highly efficient pretreatment verification of VMAT delivery using EPID. Dose delivery accuracy is assessed as a function of gantry angle to ensure accurate treatment.

A system for EPID-based real-time treatment delivery verification during dynamic IMRT treatment.

PURPOSE: To design and develop a real-time electronic portal imaging device (EPID)-based delivery verification system for dynamic intensity modulated radiation therapy (IMRT) which enables detection of gross treatment delivery errors before delivery of substantial radiation to the patient. METHODS: The system utilizes a comprehensive physics-based model to generate a series of predicted transit EPID image frames as a reference dataset and compares these to measured EPID frames acquired during treatment. The two datasets are using MLC aperture comparison and cumulative signal checking techniques. The system operation in real-time was simulated offline using previously acquired images for 19 IMRT patient deliveries with both frame-by-frame comparison and cumulative frame comparison. Simulated error case studies were used to demonstrate the system sensitivity and performance. RESULTS: The accuracy of the synchronization method was shown to agree within two control points which corresponds to approximately ∼1% of the total MU to be delivered for dynamic IMRT. The system achieved mean real-time gamma results for frame-by-frame analysis of 86.6% and 89.0% for 3%, 3 mm and 4%, 4 mm criteria, respectively, and 97.9% and 98.6% for cumulative gamma analysis. The system can detect a 10% MU error using 3%, 3 mm criteria within approximately 10 s. The EPID-based real-time delivery verification system successfully detected simulated gross errors introduced into patient plan deliveries in near real-time (within 0.1 s). CONCLUSIONS: A real-time radiation delivery verification system for dynamic IMRT has been demonstrated that is designed to prevent major mistreatments in modern radiation therapy.