AAPM Task Group Report 307: Use of EPIDs for Patient-Specific IMRT and VMAT QA

Working thresholds for in-vivo dosimetry in EPIGray based on a clinical, anatomically-stratified study

PURPOSE

To obtain tolerance levels for working with the EPID-based EPIgray in vivo dosimetry system.

METHODS

Dose differences between planned and delivered treatments in various anatomical areas, including the gastro-intestinal, urological, rectum and anal canal, gynecological, breast, head and neck, and lung regions, were analyzed across 5,791 fractions. Whether or not the dose differences at each location are symmetrical with respect to zero and adhere to a normal distribution is then checked. Linear regression analysis was applied to check for temporal drift in lung and head and neck treatments. A water equivalent phantom and another with a water-polystyrene interface is used to estimate the dose difference intrinsic to the measurement system. Furthermore, appropriate dose distribution in two treatments is verified using radiochoromic film.

RESULTS

Normal distribution was not observed in any region, and only two showed symmetry around zero. The mean dose differences were: (0.33 ± 6.32) % for the gastro-intestinal system, (-1.31 ± 3.16) % for the gynaecological area, (0.79 ± 4.55) % for VMAT-breast, (3.48 ± 4.00) % for 3DCRT-breast, (0.70 ± 3.20) % for head and neck, (5.63 ± 5.48)% for lung, (-1.36 ± 2.98) % for rectum and anal canal, and (0.13 ± 3.53) % for the urological system.

CONCLUSION

EPIgray should support tolerance levels asymmetric with respect to zero, given the positive deviation observed in mean dose for lung, breast, and head and neck regions. Additionally, the system's ability to detect dose variations during treatment could help identify changes in tumor volume.

Rapid in vivo EPID image prediction using a combination of analytically calculated attenuation and AI predicted scatter

BACKGROUND

The electronic portal imaging device (EPID) can be used in vivo, to detect on-treatment errors by evaluating radiation exiting a patient. To detect deviations from the planning intent, image predictions need to be modeled based on the patient's anatomy and plan information. To date in vivo transit images have been predicted using Monte Carlo (MC) algorithms. A deep learning approach can make predictions faster than MC and only requires patient information for training.

PURPOSE

To test the feasibility and reliability of creating a deep-learning model with patient data for predicting in vivo EPID images for IMRT treatments.

METHODS

In our approach, the in vivo EPID image was separated into contributions from primary and scattered photons. A primary photon attenuation function was determined by measuring attenuation factors for various thicknesses of solid water. The scatter component of in vivo EPID images was estimated using a convolutional neural network (CNN). The CNN input was a 3-channel image comprised of the non-transit EPID image and ray tracing projections through a pretreatment CBCT. The predicted scatter component was added to the primary attenuation component to give the full predicted in vivo EPID image. We acquired 193 IMRT fields/images from 93 patients treated on the Varian Halcyon. Model training:validation:test dataset ratios were 133:20:40 images. Additional patient plans were delivered to anthropomorphic phantoms, yielding 75 images for further validation. We assessed model accuracy by comparing model-calculated and measured in vivo images with a gamma comparison.

RESULTS

Comparing the model-calculated and measured in vivo images gives a mean gamma pass rate for the training:validation:test datasets of 95.4%:94.1%:92.9% for 3%/3 mm and 98.4%:98.4%:96.8% for 5%/3 mm. For images delivered to phantom data sets the average gamma pass rate was 96.4% (3%/3 mm criteria). In all data sets, the lower passing rates of some images were due to CBCT artifacts and patient motion that occurred between the time of CBCT and treatment.  CONCLUSIONS: The developed deep-learning-based model can generate in vivo EPID images with a mean gamma pass rate greater than 92% (3%/3 mm criteria). This approach provides an alternative to MC prediction algorithms. Image predictions can be made in 30 ms on a standard GPU. In future work, image predictions from this model can be used to detect in vivo treatment errors and on-treatment changes in patient anatomy, providing an additional layer of patient-specific quality assurance.

Clair W, Pokhrel D. Automated hippocampal sparing whole brain radiotherapy with simultaneous integrated boost for multiple brain metastases: Halcyon, HyperArc on TrueBeam, and coplanar TrueBeam

PURPOSE

To demonstrate the ease and feasibility that hippocampal sparing whole brain (WB) simultaneous integrated boost (HSWB-SIB) plans can be generated using knowledge-based planning and Eclipse Scripting Application Programming Interface (ESAPI) for three different modalities, HyperArc on TrueBeam (TB-HA), a coplanar beam arrangement on TrueBeam (TB-Co), and the ring-mounted Halcyon LINAC (Hal).

METHODS

Twelve patients with 2-14 brain metastases were retrospectively replanned for HSWB-SIB using a published HSWB RapidPlan model with modifications for the automated addition of SIB to metastases. Prescribed dose was 30 Gy to the WB planning target volume (PTV) and 50 Gy to the metastases in 10 fractions. Eclipse treatment planning system (v16.1) was used with a 6 MV-FFF beam and Acuros XB dose algorithm.

RESULTS

The methodology was successfully used for all modalities, generating plans in under 30 min. The plan doses were normalized to the WB PTV D95% receiving 30 Gy. Reporting values in the order of Hal, TB-Co, and TB-HA: The WB PTV received a V48 Gy of 4.58, 3.98, and 4.45 cc with statistically insignificant differences (p = 0.806). The boost PTVs received a D95% of 50.60, 50.43, and 51.13 Gy with statistically significant comparisons between TB-HA and the other two modalities (p = 0.005). The hippocampus maximum dose was 11.81, 11.51, and 11.13 Gy with no statistically significant comparisons (p = 0.105). All other oragns-at-risk (OAR) doses were clinically acceptable. The modalities were evaluated using a dosimetric scorecard, achieving average scores of 84.85%, 86.45%, and 87.39%. End-to-end testing ensured the deliverability of the HSWB-SIB plans for all modalities.

CONCLUSION

The novel modification of the preexisting HSWB RapidPlan model with the automated inclusion of SIB objectives allows for easy, intuitive planning of complex HSWB-SIB treatments. All modalities demonstrated can be used with clinically comparable results. Other institutions are recommended to pursue and validate this HSWB-SIB technique to increase the accessibility of a single-course of high-quality treatment for patients with multiple brain lesions.

Long-term performance monitoring of a-Si 1200 electronic portal imaging device for dosimetric applications

PURPOSE

Recently, dosimetri applications of the electronic portal imaging device (EPID) in radiotherapy have gained popularity. Confidence in the robust and reliable dosimetric performance of EPID detectors is essential for their clinical use. This study aimed to evaluate the dosimetric performance of the a-Si 1200 EPID and assess the long-term stability of its response.

METHODS

Weekly measurements were performed on two clinically used TrueBeam linear accelerators (linacs) equipped with a-Si 1200 EPID detectors over a 2-year period. They included dark and flood calibration fields, and EPID response to an open field corrected for the long-term machine output drift measured with the secondary absolute dosimeters: an ion chamber and an ion chamber array. All measurements were performed using five photon beam energies and two imaging modes: continuous and dosimetry. The measurements were analyzed for constancy and the presence of long-term trends. Comparisons were made between the two linacs for each beam energy. Pixel sensitivity matrices (PSM) were determined semi-annually and analyzed for long-term constancy for both treatment machines.

RESULTS

The long-term variation of the dark and flood field signals, integrated across the EPID plane, over the entire observation period did not exceed 0.17% and 0.79%, respectively. The output-corrected EPID response showed long-term variation from 0.28% to 0.36%, depending on beam energy, while the short-term variation was 0.04%-0.07% for EPID and 0.02%-0.06% for secondary dosimeters. The long-term variation of secondary dosimeters was 0.2%-0.3%. PSMs were found to be stable to within 1% for 97.8% of pixels and 2% for 100% of pixels.

CONCLUSION

Techniques to monitor and assess the long-term performance of the a-Si 1200 EPID as a dosimeter were developed and implemented using two TrueBeam linacs. The long-term variation of the EPID response was within clinical tolerance indicated in AAPM TG-142 report, and the detector was shown to be stable and reproducible for routine clinical dosimetry.

Three-dimensional dosimetry using multiple-energy delivery and a single-layer detector for quality assurance in proton pencil beam scanning

BACKGROUND

In Proton Therapy, the presence of implants along the beam path is known to potentially affect the dose distribution. The way such implants are managed in the planning process can vary in the different treatment planning systems (TPSs) and different centers. A specific validation procedure should be accomplished to verify the accuracy of TPS computation in these conditions and accept the applied process before treating patients.

PURPOSE

The aim of this study is to present a quality assurance (QA) tool in pencil beam scanning proton therapy by a method based on multiple-energy delivery and a single-layer two-dimensional detector and to apply it for verifying three-dimensional dose computation and correcting CT calibration in the presence of implants.

METHODS

Multiple-energy delivery with a single-layer detector (MESL) acquisitions were performed for 80 energy layers (70-150MeV), composed of equally weighted pencil beam spots. MESL measures were acquired using a two-dimensional MatriXX-IBA detector. A transformation of the energy modulation to spatial modulation was obtained by using the power-law relationship of initial energy and range. The setup design involved a reference configuration, allowing to compensate for potential offsets, and the same configuration with an additional phantom to be measured. Both setups were imaged by a CT scanner, and the dose was computed by the TPS. The comparison of TPS-computed and MESL-measured data of the phantom was performed by producing a 2D map of range-error. For testing the procedure, plastic slabs and rods made of tissue equivalent materials (TEMs), with known water equivalent path length (WEPL), were used. Range error mapping was then applied to verify dose computation with a titanium cylinder and a titanium implant. Numerical procedures were obtained by modifying at the TPS the segmented volume, or the value in the CT calibration curve for the titanium objects. The optimal values were then determined by identifying the one that minimizes residual range error.

RESULTS

The results of the consistency test on the plastic slabs and the TEM rods showed differences between measured and expected WEPL below 1%, confirming the reliability of the method and the energy-spatial transformation. In the titanium cylinder, the optimal volume and the point in the calibration curve (relative to the titanium saturated value), to be used for TPS simulation is about the real size of the cylinder and the tabulated stopping power value. However, the optimal value to be assigned to the CT calibration curve might depend on the type and shape of the object, as they were different for the cylinder and the implant with screws.

CONCLUSIONS

The availability of a QA tool, like the one presented, paves the way for systematic studies of all the parameters that impact computation accuracy, and the methods to improve the accuracy of TPS computation.

Development of a new VMAT QA framework for Mobius3D using control-point specific EPID images

Purpose

This study presents novel quality assurance (QA) approach for volumetric modulated arc therapy (VMAT) that leverages frame-by-frame electronic portal imaging device (EPID) images integrated into Mobius3D for accurate three-dimensional dose calculations.

Methods

Sequential EPID images for VMAT plans were acquired every 0.4-second by iView system and processed through iterative deconvolution to mitigate blurring from photon scattering. Deconvolved images were binarized to define multi-leaf collimator (MLC) positions. Pre-acquired box fluences determined optimal threshold for binarization and adjusted for detector shift depending on gantry and collimator angles. Sequential EPID images were re-scaled using pixel scaling factor (PSF) and converted to monitor unit (MU) proportional values. Generated EPID-based log file, including control-point specific MLC and monitor units (MU) information, were analyzed in Mobius3D for Gamma passing rate (GPR) of VMAT plans from 18 patients. Plan complexity indices were calculated and correlated with GPR.

Results

Clinically appropriate threshold was defined to be 20000 that can extract accurate MLC data from the deconvolved binarized EPID images. Positional deviations due to gantry and collimator rotations were observed to be up to 4.5 pixels. Recalibrated EPID pixel values showed linearity with MU regardless of changes in dose rate. Consequently, average GPR for 18 patients evaluated using Mobius3D reached 95.2% ± 3.7%%, based on 3% dose difference and 3mm distance-to-agreement criterion. It was found that two plan complexity indices showed statistically significant correlation with GPR.

Conclusion

This study successfully implemented novel measurement-based VMAT QA framework based on control-point specific EPID, based upon accurate MLC and MU data at each frame.

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

INTRODUCTION

New 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.

METHODS

Three 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.

RESULTS

MCS, 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.

CONCLUSION

The 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.

Quality and Safety Considerations for Adaptive Radiation Therapy: An ASTRO White Paper

PURPOSE

Adaptive radiation therapy (ART) is the latest topic in a series of white papers published by the American Society for Radiation Oncology addressing quality processes and patient safety. ART widens the therapeutic index by improving the precision of radiation dose to targets, allowing for dose escalation and/or minimization of dose to normal tissue. ART is performed via offline or online methods; offline ART is the process of replanning a patient's treatment plan between fractions, whereas online ART involves plan adjustment with the patient on the treatment table. This is achieved with in-room imaging capable of assessing anatomic changes and the ability to reoptimize the treatment plan rapidly during the treatment session. Although ART has occurred in its simplest forms in clinical practice for decades, recent technological developments have enabled more clinical applications of ART. With increased clinical prevalence, compressed timelines, and the associated complexity of ART, quality and safety considerations are an important focus area.

METHODS

The American Society for Radiation Oncology convened an interdisciplinary task force to provide expert consensus on key workflows and processes for ART. Recommendations were created using a consensus-building methodology, and task force members indicated their level of agreement based on a 5-point Likert scale, from "strongly agree" to "strongly disagree." A prespecified threshold of ≥75% of raters selecting "strongly agree" or "agree" indicated consensus. Content not meeting this threshold was removed or revised.

SUMMARY

Establishing and maintaining an adaptive program requires a team-based approach, appropriately trained and credentialed specialists, significant resources, specialized technology, and implementation time. A comprehensive quality assurance program must be developed, using established guidance, to make sure all forms of ART are performed in a safe and effective manner. Patient safety when delivering ART is everyone's responsibility, and professional organizations, regulators, vendors, and end users must demonstrate a clear commitment to working together to deliver the highest levels of quality and safety.

Off-iso Winston-Lutz test on seven linear accelerators

PURPOSE

The aim of this study is to find optimal gantry, collimator, and couch angles for performing single isocenter, multiple target stereotactic radiosurgery (SIMT-SRS). Nineteen angle sets were tested across seven linear accelerators for radiation-isocenter coincidence and off-isocenter coincidence. The off-isocenter Winston-Lutz test was performed to evaluate the accuracy of isocenter alignment for each angle set, and optimal angle sets as well as maximum off-isocenter distance to target for each angle set was determined. The influence of simulated patient weight on off-iso Winston-Lutz test accuracy was also inspected.

METHOD

The SNC MultiMet-WL phantom and MultiMet-WL QA Software v2.1 were used for the direct measurement and analysis of the off-iso Winston-Lutz test (also referred to as Winston-Lutz-Gao test). A two-step method was developed to ensure precise initial placement of the target. Nineteen beams were delivered at 6X energy and 2 × 2 cm field size to each of six targets on the MultiMet Cube with couch kicks at five cardinal angles (90°, 45°, 0°, 315°, and 270°). To reduce imaging uncertainty, only EPID was used in target alignment and test image acquisition. A total of 200 Ibs (90.7 kg) of weight was also used to mimic patient weight. All tests were performed on both the free table and the weighted table.

RESULTS

For two new TrueBeam machines, the maximum offset was within the 1 mm tolerance when the off-iso distance is less than 7 cm. Two older VitalBeam machines exhibited unfavorable gantry, couch, and collimator (GCC) angle sets: Linac No. 3 at (0,90,0), (0,270,0) and Linac No. 4 at (0,45,45) and (0,90,0). The C-Series Linacs failed in the majority of GCC angle sets, with Linac No. 5 exhibiting a maximum offset of 1.53 mm. Four of seven machines show a clear trend that offset increases with off-isocenter distance. Additionally, the IGRT table was less susceptible to the addition of simulated patient weight than the ExactCouch.

CONCLUSION

Among the seven linear accelerators addressed, newer model machines such as the Varian TrueBeam were more precise than older models, especially in comparison to the C-Series Linacs. The newer machines are more suitable for delivering SIMT-SRS procedures in all GCC angle sets, and the results indicate that newer TrueBeams are capable of performing SIMT-SRS procedures at all angle sets for targets of off-iso distances up to 7 cm. The trend that offset between the target center and radiation field center increases with off-iso distance, however, does not always hold true across machines. This may be comprised by the EPID's severe off-axis horn effect. Lastly, the IGRT couch was less susceptible to patient weight compared to ExactCouch in the off-isocenter Winston-Lutz test.

Opportunities and challenges of upright patient positioning in radiotherapy

Objective.Upright positioning has seen a surge in interest as a means to reduce radiotherapy (RT) cost, improve patient comfort, and, in selected cases, benefit treatment quality. In particle therapy (PT) in particular, eliminating the need for a gantry can present massive cost and facility footprint reduction. This review discusses the opportunities of upright RT in perspective of the open challenges.Approach.The clinical, technical, and workflow challenges that come with the upright posture have been extracted from an extensive literature review, and the current state of the art was collected in a synergistic perspective from photon and particle therapy. Considerations on future developments and opportunities are provided.Main results.Modern image guidance is paramount to upright RT, but it is not clear which modalities are essential to acquire in upright posture. Using upright MRI or upright CT, anatomical differences between upright/recumbent postures have been observed for nearly all body sites. Patient alignment similar to recumbent positioning was achieved in small patient/volunteer cohorts with prototype upright positioning systems. Possible clinical advantages, such as reduced breathing motion in upright position, have been reported, but limited cohort sizes prevent resilient conclusions on the treatment impact. Redesign of RT equipment for upright positioning, such as immobilization accessories for various body regions, is necessary, where several innovations were recently presented. Few clinical studies in upright PT have already reported promising outcomes for head&neck patients.Significance.With more evidence for benefits of upright RT emerging, several centers worldwide, particularly in PT, are installing upright positioning devices or have commenced upright treatment. Still, many challenges and open questions remain to be addressed to embed upright positioning firmly in the modern RT landscape. Guidelines, professionals trained in upright patient positioning, and large-scale clinical studies are required to bring upright RT to fruition.

In vivo EPID-based daily treatment error identification for volumetric-modulated arc therapy in head and neck cancers with a hierarchical convolutional neural network: a feasibility study

We proposed a deep learning approach to classify various error types in daily VMAT treatment of head and neck cancer patients based on EPID dosimetry, which could provide additional information to support clinical decisions for adaptive planning. 146 arcs from 42 head and neck patients were analyzed. Anatomical changes and setup errors were simulated in 17,820 EPID images of 99 arcs obtained from 30 patients using in-house software for model training, validation, and testing. Subsequently, 141 clinical EPID images from 47 arcs belonging to the remaining 12 patients were utilized for clinical testing. The hierarchical convolutional neural network (HCNN) model was trained to classify error types and magnitudes using EPID dose difference maps. Gamma analysis with 3%/2 mm (dose difference/distance to agreement) criteria was also performed. The F1 score, a combination of precision and recall, was utilized to evaluate the performance of the HCNN model and gamma analysis. The adaptive fractioned doses were calculated to verify the HCNN classification results. For error type identification, the overall F1 score of the HCNN model was 0.99 and 0.91 for primary type and subtype identification, respectively. For error magnitude identification, the overall F1 score in the simulation dataset was 0.96 and 0.70 for the HCNN model and gamma analysis, respectively; while the overall F1 score in the clinical dataset was 0.79 and 0.20 for the HCNN model and gamma analysis, respectively. The HCNN model-based EPID dosimetry can identify changes in patient transmission doses and distinguish the treatment error category, which could potentially provide information for head and neck cancer treatment adaption.

Small field measurements using electronic portal imaging device

Purpose/Objective. Small-field measurement poses challenges. Although many high-resolution detectors are commercially available, the EPID for small-field dosimetry remains underexplored. This study aimed to evaluate the performance of EPID for small-field measurements and to derive tailored correction factors for precise small-field dosimetry verification.Material/Methods. Six high-resolution radiation detectors, including W2 and W1 plastic scintillators, Edge-detector, microSilicon, microDiamond and EPID were utilized. The output factors, depth doses and profiles, were measured for various beam energies (6 MV-FF, 6 MV-FFF, 10 MV-FF, and 10 MV-FFF) and field sizes (10 × 10 cm2, 5 × 5 cm2, 4 × 4 cm2, 3 × 3 cm2, 2 × 2 cm2, 1 × 1 cm2, 0.5 × 0.5 cm2) using a Varian Truebeam linear accelerator. During measurements, acrylic plates of appropriate depth were placed on the EPID, while a 3D water tank was used with five-point detectors. EPID measured data were compared with W2 plastic scintillator and measurements from other high-resolution detectors. The analysis included percentage deviations in output factors, differences in percentage for PDD and for the profiles, FWHM, maximum difference in the flat region, penumbra, and 1D gamma were analyzed. The output factor and depth dose ratios were fitted using exponential functions and fractional polynomial fitting in STATA 16.2, with W2 scintillator as reference, and corresponding formulae were obtained. The established correction factors were validated using two Truebeam machines.Results. When comparing EPID and W2-PSD across all field-sizes and energies, the deviation for output factors ranged from 1% to 15%. Depth doses, the percentage difference beyond dmax ranged from 1% to 19%. For profiles, maximum of 4% was observed in the 100%-80% region. The correction factor formulae were validated with two independent EPIDs and closely matched within 3%.Conclusion. EPID can effectively serve as small-field dosimetry verification tool with appropriate correction factors.

Commissioning and dosimetric verification of volumetric modulated arc therapy for multiple modalities using electronic portal imaging device-based 3D dosimetry system: a novel approach

The purpose of this study was to validate an electronic portal imaging device (EPID) based 3-dimensional (3D) dosimetry system for the commissioning of volumetric modulated arc therapy (VMAT) delivery for flattening filter (FF) and flattening filter free (FFF) modalities based on test suites developed according to American Association of Physicists in Medicine Task Group 119 (AAPM TG 119) and pre-treatment patient specific quality assurance (PSQA).With ionisation chamber, multiple-point measurement in various planes becomes extremely difficult and time-consuming, necessitating repeated exposure of the plan. The average agreement between measured and planned doses for TG plans is recommended to be within 3%, and both the ionisation chamber and PerFRACTION™ measurement were well within this prescribed limit. Both point dose differences with the planned dose and gamma passing rates are comparable with TG reported multi-institution results. From our study, we found that no significant differences were found between FF and FFF beams for measurements using PerFRACTION™ and ion chamber. Overall, PerFRACTION™ produces acceptable results to be used for commissioning and validating VMAT and for performing PSQA. The findings support the feasibility of integrating PerFRACTION™ into routine quality assurance procedures for VMAT delivery. Further multi-institutional studies are recommended to establish global baseline values and enhance the understanding of PerFRACTION™'s capabilities in diverse clinical settings.

Automation to facilitate optimisation of breast radiotherapy treatments using EPID-basedin vivodosimetry

Objective. To use automation to facilitate the monitoring of each treatment fraction using an electronic portal imaging device (EPID) basedin vivodosimetry (IVD) system, allowing optimisation of breast radiotherapy delivery for individual patients and cohorts.Approach. A suite of in-house software was developed to reduce the number of manual interactions with the commercial IVD system, dosimetry check. An EPID specific pixel sensitivity map facilitated use of the EPID panel away from the central axis. Point dose difference and the change in standard deviation in dose were identified as useful dose metrics, with standard deviation used in preference to gamma in the presence of a systematic dose offset. Automated IVD was completed for 3261 fractions across 704 patients receiving breast radiotherapy.Main results. Multiple opportunities for treatment optimisation were identified for individual patients and across patient cohorts as a result of successful implementation of automated IVD. 5.1% of analysed fractions were out of tolerance with 27.1% of these considered true positives. True positive results were obtained on any fraction of treatment and if IVD had only been completed on the first fraction, 84.4% of true positive results would have been missed. This was made possible due to the automation that saved over 800 h of manual intervention and stored data in an accessible database.Significance. An improved EPID calibration to allow off-axis measurement maximises the number of patients eligible for IVD (36.8% of patients in this study). We also demonstrate the importance in selecting context-specific assessment metrics and how these can lead to a managable false positive rate. We have shown that the use of fully automated IVD facilitates use on every fraction of treatment. This leads to identification of areas for treatment improvement for both individuals and across a patient cohort, expanding the uses of IVD from simply gross error detection towards treatment optimisation.

Commissioning and clinical evaluation of a novel high-resolution quality assurance digital detector array for SRS and SBRT

PURPOSE

We aimed to perform the commissioning and clinical evaluation of myQA SRS detector array for patient-specific quality assurance (PSQA) of stereotactic radiosurgery (SRS)/ stereotactic body radiotherapy (SBRT) plans.

METHODS

To perform the commissioning of myQA SRS, its dose linearity, dose-rate dependence, angular dependence, and field-size dependence were investigated. Ten SBRT plans were selected for clinical evaluation: 1) Common clinical deviations based on the original SBRT plan (Plan0), including multileaf collimator (MLC) positioning deviation and treatment positioning deviation were introduced. 2) Compared the performance of the myQA SRS and a high-resolution EPID dosimetry system in PSQA measurement for the SBRT plans. Evaluation parameters include gamma passing rate (GPR) and distance-to-agreement (DTA) pass rate (DPR).

RESULTS

The dose linearity, angle dependence, and field-size dependence of myQA SRS system exhibit excellent performance. The myQA SRS is highly sensitive in the detection of MLC deviations. The GPR of (3%/1 mm) decreases from 90.4% of the original plan to 72.7%/62.9% with an MLC outward/inward deviation of 3 mm. Additionally, when the setup error deviates by 1 mm in the X, Y, and Z directions with the GPR of (3%/1 mm) decreasing by an average of -20.9%, -25.7%, and -24.7%, respectively, and DPR (1 mm) decreasing by an average of -33.7%, -32.9%, and -29.8%. Additionally, the myQA SRS has a slightly higher GPR than EPID for PSQA, However, the difference is not statistically significant with the GPR of (3%/1 mm) of (average 90.4%% vs. 90.1%, p = 0.414).

CONCLUSION

Dosimetry characteristics of the myQA SRS device meets the accuracy and sensitivity requirement of PSQA for SRS/SBRT treatment. The dose rate dependence should be adequately calibrated before its application and a more stringent GPR (3%/1 mm) evaluation criterion is suggested when it is used for SRS/SBRT QA.

Optimization of a commercial portal dose image prediction algorithm for pre-treatment verifications of plans using unflattened photon beams

Background

The aim was to improve the portal dosimetry-based quality assurance results of conventional treatment plans by adjusting the multileaf collimator (MLC) dosimetric leaf gap (DLG) and transmission (T) values of the anisotropic analytic algorithm (AAA) used for portal dose image prediction (PDIP).

Materials and methods

The AAA-based PDIP v. 16.1 algorithm (PDIP-AAA) of the Eclipse TPS was configured for 6 MV FFF energy. Optimal DLG and T values were achieved for this algorithm by comparing predicted versus measured portal images of the Chair pattern. Twenty clinical plans using 6 MV FFF beams were verified using the optimal PDIP-AAA algorithm and the standard PDIP v. 16 algorithm (PDIP-vE), configured using the van Esch package. The 3% global/2 mm gamma passing rates (GPRs) and average gamma indexes (AGIs) were computed for each acquired image. For each plan, the mean GPR (GPRmean) and mean GAI (GAImean) were compared for both algorithms. A 2-tailed Student t-test (α = 0.05) was used to evaluate whether there was a statistically significant difference.

Results

Optimal values of DLG = 0.1 mm and T = 0.01 were found for the PDIP-AAA algorithm, providing significantly better values of GPRmean and AGImean than PDIP-vE (p < 0.001). All plans verified with PIDP-AAA showed GPRmean ≥ 95%. In contrast, only 45% of the plans reported GPRmean ≥ 95% with the PDIP-vE algorithm.

Conclusions

The MLC parameters available in the PDIP-AAA model must be tuned to improve the accuracy of the predicted dose image. This work-around is not possible using the standard PDIP algorithm. The adjusted PDIP-AAA resulted in significantly better results than PDIP-vE.

ACPSEM position paper: pre-treatment patient specific plan checks and quality assurance in radiation oncology

The Australasian College of Physical Scientists and Engineers in Medicine (ACPSEM) has not previously made recommendations outlining the requirements for physics plan checks in Australia and New Zealand. A recent workforce modelling exercise, undertaken by the ACPSEM, revealed that the workload of a clinical radiation oncology medical physicist can comprise of up to 50% patient specific quality assurance activities. Therefore, in 2022 the ACPSEM Radiation Oncology Specialty Group (ROSG) set up a working group to address this issue. This position paper authored by ROSG endorses the recommendations of the American Association of Physicists in Medicine (AAPM) Task Group 218, 219 and 275 reports with some contextualisation for the Australia and New Zealand settings. A few recommendations from other sources are also endorsed to complete the position.

In vivo dose measurements for tangential field-in-field ultra-hypofractionated breast radiotherapy

INTRODUCTION

Ultra-hypofractionated radiotherapy (UHF-RT) mandates more accuracy in each part of the treatment cycle to maximize cure rates and minimize toxicities. In vivo dosimetry is a direct method for verifying overall treatment accuracy. This study evaluated uncertainties in the delivered dose of Hypofractionated (HF) and UHF Whole Breast Irradiation (WBI) and to analyze the accuracy of the workflow to pave the way for a wide-scale use of UHF-RT.

METHODS

Thirty-three breast cancer cases, including 16 HF-WBI and 17 UHF-WBI were treated with 3D conformal Radiotherapy (3D-CRT), where 79 fields were analyzed for dose verification. The measurement point was set at the beam entrance (1.5 cm depth). The expected dose at Dmax was calculated via TPS. Before in vivo measurements, diode detectors were tested and calibrated. We developed initial validation measurements for UHF-RT on an anthropomorphic breast phantom for the first time.

RESULTS

For RANDO phantom, the percentage difference between measured and calculated doses showed an average of -0.52 ± 5.4%, in addition to an excellent dose reproducibility within 0.6%. The overall in vivo measurements for studied cases showed that 83.5% of the measured doses were within ±5% and only 1.8% of the measured doses were greater than ±10% of the calculated doses. The percentage accuracy was slightly larger for UHF cohort (84.2%) compared to HF cohort (83.2%). The maximum percentage difference between them was less than 1%.

CONCLUSION

Breast in vivo dosimetry is an adequate tool for treatment verification that improves the accuracy of the treatment cycle. UHF-RT may contribute in reducing the long waiting lists, increasing patient convenience, and saving the available resources for breast cancer patients.

Validation of an in vivo transit dosimetry algorithm using Monte Carlo simulations and ionization chamber measurements

PURPOSE

Transit dosimetry is a safety tool based on the transit images acquired during treatment. Forward-projection transit dosimetry software, as PerFRACTION, compares the transit images acquired with an expected image calculated from the DICOM plan, the CT, and the structure set. This work aims to validate PerFRACTION expected transit dose using PRIMO Monte Carlo simulations and ionization chamber measurements, and propose a methodology based on MPPG5a report.

METHODS

The validation process was divided into three groups of tests according to MPPG5a: basic dose validation, IMRT dose validation, and heterogeneity correction validation. For the basic dose validation, the fields used were the nine fields needed to calibrate PerFRACTION and three jaws-defined. For the IMRT dose validation, seven sweeping gaps fields, the MLC transmission and 29 IMRT fields from 10 breast treatment plans were measured. For the heterogeneity validation, the transit dose of these fields was studied using three phantoms: 10 , 30 , and a 3 cm cork slab placed between 10 cm of solid water. The PerFRACTION expected doses were compared with PRIMO Monte Carlo simulation results and ionization chamber measurements.

RESULTS

Using the 10 cm solid water phantom, for the basic validation fields, the root mean square (RMS) of the difference between PerFRACTION and PRIMO simulations was 0.6%. In the IMRT fields, the RMS of the difference was 1.2%. When comparing respect ionization chamber measurements, the RMS of the difference was 1.0% both for the basic and the IMRT validation. The average passing rate with a γ(2%/2 mm, TH = 20%) criterion between PRIMO dose distribution and PerFRACTION expected dose was 96.0% ± 5.8%.

CONCLUSION

We validated PerFRACTION calculated transit dose with PRIMO Monte Carlo and ionization chamber measurements adapting the methodology of the MMPG5a report. The methodology presented can be applied to validate other forward-projection transit dosimetry software.

A phantom based evaluation of the clinical imaging performance of electronic portal imaging devices

Purpose

In this study an evaluation of the imaging performance of an electronic portal imaging device (EPID) is presented. The evaluation performed employing the QC-3V image quality phantom.

Methods

An EPID system of a 6 MV LINAC, was used to obtain images of a QC-3V EPID phantom. The X-ray source to phantom distance was 100 cm and the field size was 15x15 cm2. The irradiation conditions comprised Dose Rates (DR) of 200, 400 and 600 for a 2 MU-100 MU range. The Contrast Transfer Function (CTF), the Noise Power Spectrum (NPS), the Normalized Noise Power Spectrum (NNPS) and the Contrast-to-Noise Ratio (CNR) were studied. In addition, an alternative factor showing a frequency related output signal-to-noise ratio (SNR), the Signal-to-Noise-Frequency Response (SNFR), has been introduced. SNFR is a comprehensive quality index, easily determined in clinical environment.

Results

The CTF curves were found comparable to each other. The lowest values were measured at 2 MU and 200 MU/min. Concerning the NPS and NNPS graphs it was found that the values decrease up to approximately 0.3 lp/mm and demonstrate a white noise shape afterwards. SNFR values were found reducing with spatial frequency. Highest CNR were found between the region 7 and 11 of the phantom.

Conclusions

The influence of MU and DR on EPID performance were investigated. Image quality was assessed using the QC-3V phantom. The presented results can lead to image quality amelioration and act supportively to current image quality control routine protocols.