Tolerance limits and methodologies for IMRT measurement-based verification QA: Recommendations of AAPM Task Group No. 218

Impact of the Acuros XB spatial discretization error on ArcCHECK VMAT QA for small-field SBRT

PURPOSE

To evaluate the impact of the Acuros XB spatial discretization errors on ArcCHECK volumetric modulated arc therapy (VMAT) QA for small-field SBRT plans.

METHODS

Eighteen SBRT VMAT arcs that failed the ArcCHECK VMAT QA were retrospectively analyzed. Plan verification doses were calculated using Eclipse Acuros XB, and absolute 3%/2 mm gamma passing rates were calculated to compare ArcCHECK and MapCHECK2 with MapPHAN. Verification doses were recalculated using AAA in Eclipse and with the EGSnrc Monte Carlo package. In addition, error-reduced Acuros XB doses were calculated by subdividing the entire arc into several sub-arcs ("split-arc" method), with the angular ranges of the sub-arcs optimized to balance accuracy and efficiency. Relative gamma passing rates were calculated and compared for the four methods: (1) Acuros XB; (2) AAA; (3) EGSnrc Monte Carlo; and (4) the split-arc method.

RESULTS

The absolute gamma passing rates were below 90% for ArcCHECK and above 95% for MapCHECK2. The averaged relative gamma passing rates were (1) 84.7% for clinical Acuros XB; (2) 96.8% for AAA; (3) 98.8% for EGSnrc Monte Carlo; and (4) 96.8% for the split-arc method with 60° sub-arc angle. Compared to the clinical Acuros XB, the split-arc method improved the relative gamma passing rate by 12.1% on average. No significant difference was found between AAA and the split-arc method (p > 0.05).

CONCLUSION

The Acuros XB spatial discretization errors can significantly impact the ArcCHECK VMAT QA results for small-field SBRT plans. The split-arc method may be used to improve the VMAT QA results.

End-to-end quality assurance for stereotactic radiotherapy with Fricke-Xylenol orange-Gelatin gel dosimeter and dual-wavelength cone-beam optical CT readout

PURPOSE

The end-to-end (E2E) quality assurance (QA) test is a unique tool for validating the treatment chain undergone by patients in external radiotherapy. It should be conducted in three dimensions (3D) to get accurate results. This study aims to implement these tests with Fricke-Xylenol orange-Gelatin (FXG) gel dosimeter and a newly developed dual-wavelength reading method on the Vista16™ optical Computed Tomography (CT) scanner (ModusQA) for three treatment techniques in stereotactic radiotherapy, on Novalis (Varian) and CyberKnife (Accuray) linear accelerators.

METHODS

The tests were performed in head phantoms. Gel measurements were compared with planned dose distributions and measured by film and ion chamber measurements by plotting isodose curves and dose profiles, and by conducting a 3D local gamma-index analysis (2%/2mm criteria).

RESULTS

Gamma passing rates were higher than 95 %. Point dose differences between treatment planning and gel and ion chamber measurements at the isocenter were < 2.3 % for both treatments delivered on the Novalis accelerator, while this difference was higher than 4 % for the treatment delivered on the CyberKnife, highlighting a small overdosing of the tumor volume. A good agreement was observed between gel and film dose profiles.

CONCLUSIONS

This study presents the successful implementation of 3D E2E QA tests for stereotactic radiotherapy with FXG gel dosimetry and a dual-wavelength reading method on an optical CT scanner. This dosimetric method provides 3D absolute dose distributions in the 0.25 - 10 Gy dose range with a high spatial resolution and a dose uncertainty of around 2 % (k=1).

PRIMO Monte Carlo software as a tool for commissioning of an external beam radiotherapy treatment planning system

Background

The purpose was to validate the PRIMO Monte Carlo software to be used during the commissioning of a treatment planning system (TPS).

Materials and methods

The Acuros XB v. 16.1 algorithm of the Eclipse was configured for 6 MV and 6 MV flattening-filter-free (FFF) photon beams, from a TrueBeam linac equipped with a high-definition 120-leaf multileaf collimator (MLC). PRIMO v. 0.3.64.1814 software was used with the phase space files provided by Varian and benchmarked against the reference dosimetry dataset published by the Imaging and Radiation Oncology Core-Houston (IROC-H). Thirty Eclipse clinical intensity-modulated radiation therapy (IMRT)/volumetric modulated arc therapy (VMAT) plans were verified in three ways: 1) using the PTW Octavius 4D (O4D) system; 2) the Varian Portal Dosimetry system and 3) the PRIMO software. Clinical validation of PRIMO was completed by comparing the simulated dose distributions on the O4D phantom against dose measurements for these 30 clinical plans. Agreement evaluations were performed using a 3% global/2 mm gamma index analysis.

Results

PRIMO simulations agreed with the benchmark IROC-H data within 2.0% for both energies. Gamma passing rates (GPRs) from the 30 clinical plan verifications were (6 MV/6MV FFF): 99.4% ± 0.5%/99.9% ± 0.1%, 99.8% ± 0.4%/98.9% ± 1.4%, 99.7% ± 0.4%/99.7% ± 0.4%, for the 1), 2) and 3) verification methods, respectively. Agreement between PRIMO simulations on the O4D phantom and 3D dose measurements resulted in GPRs of 97.9% ± 2.4%/99.7% ± 0.4%.

Conclusion

The PRIMO software is a valuable tool for dosimetric verification of clinical plans during the commissioning of the primary TPS.

Feasibility study of a scintillation sheet-based detector for fluence monitoring during external photon beam radiotherapy

PURPOSE

This study evaluated the properties of a scintillation sheet-based dosimetry system for beam monitoring with high spatial resolution, including the effects of this system on the treatment beam. The dosimetric characteristics and feasibility of this system for clinical use were also evaluated.

METHODS

The effects of the dosimetry system on the beam were evaluated by measuring the percentage depth doses, dose profiles, and transmission factors. Fifteen treatment plans were created, and the influence of the dosimetry system on these clinical treatment plans was evaluated. The performance of the system was assessed by determining signal linearity, dose rate dependence, and reproducibility. The feasibility of the system for clinical use was evaluated by comparing intensity distributions with reference intensity distributions verified by quality assurance.

RESULTS

The spatial resolution of the dosimetry system was found to be 0.43 mm/pixel when projected to the isocenter plane. The dosimetry system attenuated the intensity of 6 MV beams by about 1.1%, without affecting the percentage depth doses and dose profiles. The response of the dosimetry system was linear, independent of the dose rate used in the clinic, and reproducible. Comparison of intensity distributions of evaluation treatment fields with reference intensity distributions showed that the 1%/1 mm average gamma passing rate was 99.6%.

CONCLUSIONS

The dosimetry system did not significantly alter the beam characteristics, indicating that the system could be implemented by using only a transmission factor. The dosimetry system is clinically suitable for monitoring treatment beam delivery with higher spatial resolution than other transmission detectors.

Sensitivity and specificity of Varian Halcyon's portal dosimetry for plan-specific pre-treatment QA

PURPOSE

Developed as a plan-specific pre-treatment QA tool, Varian portal dosimetry promises a fast, high-resolution, and integrated QA solution. In this study, the agreement between predicted fluence and measured cumulative portal dose was determined for the first 140 patient plans at our Halcyon linear accelerator. Furthermore, the capability of portal dosimetry to detect incorrect plan delivery was compared to that of a common QA phantom. Finally, tolerance criteria for verification of VMAT plan delivery with Varian portal dosimetry were derived.

METHODS

All patient plans and the corresponding verification plans were generated within the Eclipse treatment planning system. Four representative plans of different treatment sites (prostate, prostate with lymphatic drainage, rectum, and head & neck) were intentionally altered to model incorrect plan delivery. Investigated errors included both systematic and random errors. Gamma analysis was conducted on both portal dose (criteria γ2%/2 mm , γ2%/1 mm , and γ1%/1 mm ) and ArcCHECK measurements (criteria γ3%/3 mm , γ3%/2 mm , and γ2%/2 mm ) with a 10% low-dose threshold. Performance assessment of various acceptance criteria for plan-specific treatment QA utilized receiver operating characteristic (ROC) analysis.

RESULTS

Predicted and acquired portal dosimetry fluences demonstrated a high agreement evident by average gamma passing rates for the clinical patient plans of 99.90%, 96.64%, and 91.87% for γ2%/2 mm , γ2%/1 mm , and γ1%/1 mm , respectively. The ROC analysis demonstrated a very high capability of detecting erroneous plan delivery for portal dosimetry (area under curve (AUC) > 0.98) and in this regard outperforms QA with the ArcCHECK phantom (AUC ≈ 0.82). With the suggested optimum decision thresholds excellent sensitivity and specificity is simultaneously possible.

CONCLUSIONS

Owing to the high achievable spatial resolution, portal dosimetry at the Halcyon can reliably be deployed as plan-specific pre-treatment QA tool to screen for errors. It is recommended to support the fluence integrated portal dosimetry QA by independent phantom-based measurements of a random sample survey of treatment plans.

Framework for Quality Assurance of Ultrahigh Dose Rate Clinical Trials Investigating FLASH Effects and Current Technology Gaps

FLASH radiation therapy (FLASH-RT), delivered with ultrahigh dose rate (UHDR), may allow patients to be treated with less normal tissue toxicity for a given tumor dose compared with currently used conventional dose rate. Clinical trials are being carried out and are needed to test whether this improved therapeutic ratio can be achieved clinically. During the clinical trials, quality assurance and credentialing of equipment and participating sites, particularly pertaining to UHDR-specific aspects, will be crucial for the validity of the outcomes of such trials. This report represents an initial framework proposed by the NRG Oncology Center for Innovation in Radiation Oncology FLASH working group on quality assurance of potential UHDR clinical trials and reviews current technology gaps to overcome. An important but separate consideration is the appropriate design of trials to most effectively answer clinical and scientific questions about FLASH. This paper begins with an overview of UHDR RT delivery methods. UHDR beam delivery parameters are then covered, with a focus on electron and proton modalities. The definition and control of safe UHDR beam delivery and current and needed dosimetry technologies are reviewed and discussed. System and site credentialing for large, multi-institution trials are reviewed. Quality assurance is then discussed, and new requirements are presented for treatment system standard analysis, patient positioning, and treatment planning. The tables and figures in this paper are meant to serve as reference points as we move toward FLASH-RT clinical trial performance. Some major questions regarding FLASH-RT are discussed, and next steps in this field are proposed. FLASH-RT has potential but is associated with significant risks and complexities. We need to redefine optimization to focus not only on the dose but also on the dose rate in a manner that is robust and understandable and that can be prescribed, validated, and confirmed in real time. Robust patient safety systems and access to treatment data will be critical as FLASH-RT moves into the clinical trials.

Experimental validation of a novel method of dose accumulation for the rectum

BACKGROUND

Dose-surface maps (DSMs) are an increasingly popular tool to evaluate spatial dose-outcome relationships for the rectum. Recently, DSM addition has been proposed as an alternative method of dose accumulation from deformable registration-based techniques. In this study, we performed the first experimental investigation of the accuracy at which DSM accumulation can capture the total dose delivered to a rectum's surface in the presence of inter-fraction motion.

MATERIAL AND METHODS

A custom PVC rectum phantom capable of representing typical rectum inter-fraction motion and filling variations was constructed for this project. The phantom allowed for the placement of EBT3 film sheets on the representative rectum surface to measure rectum surface dose. A multi-fraction prostate VMAT treatment was designed and delivered to the phantom in a water tank for a variety of inter-fraction motion scenarios. DSMs for each fraction were calculated in two ways using CBCT images acquired during delivery and summed to produce accumulated DSMs. Accumulated DSMs were then compared to film measurements using gamma analysis (3%/2 mm criteria). Similarity of isodose clusters between films and DSMs was also investigated.

RESULTS

Baseline agreement between film measurements and accumulated DSMs for a stationary rectum was 95.6%. Agreement between film and accumulated DSMs in the presence of different types of inter.-fraction motion was ≥92%, and isodose cluster mean distance to agreement was within 1.5 mm for most scenarios. Overall, DSM accumulation performed the best when using DSMs that accounted for changes in rectum path orientation.

CONCLUSION

Dose accumulation performed with DSMs was found to accurately replicate total delivered dose to a rectum phantom in the presence of inter-fraction motion.

Moving towards process-based radiotherapy quality assurance using statistical process control

Monitoring Radiotherapy Quality Assurance (QA) using Statistical Process Control (SPC) methods has gained wide acceptance. The significance of understanding the SPC methodologies has increased among the medical physics community with the release of Task Group (TG) reports from the American Association of Physicists in Medicine (AAPM) on patient-specific QA (PSQA) (TG-218) and Proton therapy QA (TG-224). Even though these reports recommend using SPC for QA analysis, physicists have ambiguities and doubts in choosing proper SPC tools and methodologies. This review article summarises the utilisation of SPC methods for different Radiotherapy QAs published in the literature, such as PSQA, routine Linac QA and patient positional verification. QA analysis using SPC could assist the user in distinguishing between 'special' and 'routine' sources of variations in the QA, which can aid in reducing actions on false positive QA results. For improved PSQA monitoring, machine-specific, site-specific, and technique-specific Tolerance Limits and Action Limits derived from a two-stage SPC-based approach can be used. Adopting a combination of Shewhart's control charts and time-weighted control charts for routine Linac QA monitoring could add more insights to the QA process. Incorporating SPC tools into existing image review modules or introducing new SPC software packages specifically designed for clinical use can significantly enhance the image review process. Proper selection and having adequate knowledge of SPC tools are essential for efficient QA monitoring, which is a function of the type of QA data available, and the magnitude of process drift to be monitored.

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

PURPOSE

Electronic portal imaging devices (EPIDs) have been widely utilized for patient-specific quality assurance (PSQA) and their use for transit dosimetry applications is emerging. Yet there are no specific guidelines on the potential uses, limitations, and correct utilization of EPIDs for these purposes. The American Association of Physicists in Medicine (AAPM) Task Group 307 (TG-307) provides a comprehensive review of the physics, modeling, algorithms and clinical experience with EPID-based pre-treatment and transit dosimetry techniques. This review also includes the limitations and challenges in the clinical implementation of EPIDs, including recommendations for commissioning, calibration and validation, routine QA, tolerance levels for gamma analysis and risk-based analysis.

METHODS

Characteristics of the currently available EPID systems and EPID-based PSQA techniques are reviewed. The details of the physics, modeling, and algorithms for both pre-treatment and transit dosimetry methods are discussed, including clinical experience with different EPID dosimetry systems. Commissioning, calibration, and validation, tolerance levels and recommended tests, are reviewed, and analyzed. Risk-based analysis for EPID dosimetry is also addressed.

RESULTS

Clinical experience, commissioning methods and tolerances for EPID-based PSQA system are described for pre-treatment and transit dosimetry applications. The sensitivity, specificity, and clinical results for EPID dosimetry techniques are presented as well as examples of patient-related and machine-related error detection by these dosimetry solutions. Limitations and challenges in clinical implementation of EPIDs for dosimetric purposes are discussed and acceptance and rejection criteria are outlined. Potential causes of and evaluations of pre-treatment and transit dosimetry failures are discussed. Guidelines and recommendations developed in this report are based on the extensive published data on EPID QA along with the clinical experience of the TG-307 members.

CONCLUSION

TG-307 focused on the commercially available EPID-based dosimetric tools and provides guidance for medical physicists in the clinical implementation of EPID-based patient-specific pre-treatment and transit dosimetry QA solutions including intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) treatments.

Dosimetric characteristics of 6MV flattening filter free and flattened beams among beam-matched linacs: a three-institutional study

BACKGROUND

Beam matching is a concept in radiotherapy applied to clinics where more than one linac is employed to harmonise beam characteristics across linacs for allowing patients interchange without replanning. In view of this, the current study analyzes and compares dosimetric characteristics of 6MV flattening filter free and flattened beams of three beam-matched linear accelerators (linacs) from three different clinics with the aim to evaluate the matching under tight criteria for gamma analysis.

METHODS

Three Elekta linacs from three different clinics were included. The linacs have the same collimator assembly, Elekta Agility. Beam data were collected during commissioning process using PTW dosimetry systems. Dose profiles and percentage depth doses (PDD) were analyzed using 1D gamma analysis (1 mm/1%) as well as the following parameters: depth of maximum dose, PDD10, flatness, unflattnes, symmetry, penumbra, output factors. Additionally, five stereotactic treatment plans were optimized in one clinic and calculated by all three planning systems (Monaco) for a dosimetric comparison.

RESULTS

Gamma analysis of dose profiles and PDDs showed clinically acceptable results of 96.3% passing rate for profiles and 100% passing rate for PDDs. All dosimetric parameters were in good agreement with the reference data. Furthermore, dosimetric comparisons between stereotactic treatment plans showed a maximum standard deviation of 0.48 Gy for the maximum dose to PTV, and a maximum standard deviation of 0.1 Gy for the dose to the organs at risk.

CONCLUSIONS

All three linacs showed a strong agreement between parameters and passed the gamma analysis using 1% DD/1mm DTA criteria. This study confirmed the matching between linacs, offering the possibility to interchange patients with no replanning.

Study of the prediction of gamma passing rate in dosimetric verification of intensity-modulated radiotherapy using machine learning models based on plan complexity

Objective

To predict the gamma passing rate (GPR) in dosimetric verification of intensity-modulated radiotherapy (IMRT) using three machine learning models based on plan complexity and find the best prediction model by comparing and evaluating the prediction ability of the regression and classification models of three classical algorithms: artificial neural network (ANN), support vector machine (SVM) and random forest (RF).

Materials and methods

269 clinical IMRT plans were chosen retrospectively and the GPRs of a total of 2340 fields by the 2%/2mm standard at the threshold of 10% were collected for dosimetric verification using electronic portal imaging device (EPID). Subsequently, the plan complexity feature values of each field were extracted and calculated, and a total of 6 machine learning models (classification and regression models for three algorithms) were trained to learn the relation between 21 plan complexity features and GPRs. Each model was optimized by tuning the hyperparameters and ten-fold cross validation. Finally, the GPRs predicted by the model were compared with measured values to verify the accuracy of the model, and the evaluation indicators were applied to evaluate each model to find the algorithm with the best prediction performance.

Results

The RF algorithm had the optimal prediction effect on GPR, and its mean absolute error (MAE) on the test set was 1.81%, root mean squared error (RMSE) was 2.14%, and correlation coefficient (CC) was 0.72; SVM was the second and ANN was the worst. Among the classification models, the RF algorithm also had the optimal prediction performance with the highest area under the curve (AUC) value of 0.80, specificity and sensitivity of 0.80 and 0.68 respectively, followed by SVM and the worst ANN.

Conclusion

All the three classic algorithms, ANN, SVM, and RF, could realize the prediction and classification of GPR. The RF model based on plan complexity had the optimal prediction performance which could save valuable time for quality control workers to improve quality control efficiency.

Integrating plan complexity and dosiomics features with deep learning in patient-specific quality assurance for volumetric modulated arc therapy

PURPOSE

To investigate the feasibility and performance of deep learning (DL) models combined with plan complexity (PC) and dosiomics features in the patient-specific quality assurance (PSQA) for patients underwent volumetric modulated arc therapy (VMAT).

METHODS

Total of 201 VMAT plans with measured PSQA results were retrospectively enrolled and divided into training and testing sets randomly at 7:3. PC metrics were calculated using house-built algorithm based on Matlab. Dosiomics features were extracted and selected using Random Forest (RF) from planning target volume (PTV) and overlap regions with 3D dose distributions. The top 50 dosiomics and 5 PC features were selected based on feature importance screening. A DL DenseNet was adapted and trained for the PSQA prediction.

RESULTS

The measured average gamma passing rate (GPR) of these VMAT plans was 97.94% ± 1.87%, 94.33% ± 3.22%, and 87.27% ± 4.81% at the criteria of 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. Models with PC features alone demonstrated the lowest area under curve (AUC). The AUC and sensitivity of PC and dosiomics (D) combined model at 2%/2 mm were 0.915 and 0.833, respectively. The AUCs of DL models were improved from 0.943, 0.849, 0.841 to 0.948, 0.890, 0.942 in the combined models (PC + D + DL) at 3%/3 mm, 3%/2 mm and 2%/2 mm, respectively. A best AUC of 0.942 with a sensitivity, specificity and accuracy of 100%, 81.8%, and 83.6% was achieved with combined model (PC + D + DL) at 2%/2 mm.

CONCLUSIONS

Integrating DL with dosiomics and PC metrics is promising in the prediction of GPRs in PSQA for patients underwent VMAT.

Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors

This study aims to evaluate the specific characteristics of various multileaf collimator (MLC) position errors that are correlated with the indices using dose distribution. The dose distribution was investigated using the gamma, structural similarity, and dosiomics indices. Cases from the American Association of Physicists in Medicine Task Group 119 were planned, and systematic and random MLC position errors were simulated. The indices were obtained from distribution maps and statistically significant indices were selected. The final model was determined when all values of the area under the curve, accuracy, precision, sensitivity, and specificity were higher than 0.8 (p < 0.05). The dose-volume histogram (DVH) relative percentage difference between the error-free and error datasets was examined to investigate clinical relations. Seven multivariate predictive models were finalized. The common significant dosiomics indices (GLCM Energy and GLRLM_LRHGE) can characterize the MLC position error. In addition, the finalized logistic regression model for MLC position error prediction showed excellent performance with AUC > 0.9. Furthermore, the results of the DVH were related to dosiomics analysis in that it reflects the characteristics of the MLC position error. It was also shown that dosiomics analysis could provide important information on localized dose-distribution differences in addition to DVH information.

Evaluation of the dataset quality in gamma passing rate predictions using machine learning methods

OBJECTIVE

Gamma passing rate (GPR) predictions using machine learning methods have been explored for treatment verification of radiotherapy plans. However, these methods presented datasets with unbalanced number of plans having different treatment conditions (heterogeneous datasets), such as anatomical sites or dose per fractions, leading to lower model interpretability and prediction performance.

METHODS

We investigated the impact of the dataset composition on GPR binary classification (pass/fail) using random forest (RF), XG-boost, and neural network (NN) models. 945 plans were used to create one reference dataset (randomly assembled) and 24 customized datasets that considered four heterogeneity factors independently (anatomical region, number of arcs, dose per fraction, and treatment unit). 309 predictor features were extracted and calculated from plan parameters, modulation complexity metrics, and radiomic analysis (leave-trajectory maps, 3D dose distributions, and portal dosimetry images). The models' performances were measured using the area under the curve from the receiver operating characteristic (ROC-AUC).

RESULTS

Radiomics features for reference models increased ROC-AUC values up to 13%, 15%, and 5% for RF, XG-Boost, and NN, respectively. The datasets with higher heterogeneous conditions presented the lower ROC-AUC values (RF: 0.72 ± 0.11, XG-Boost: 0.67 ± 0.1, NN: 0.89 ± 0.05) compared to models with less heterogeneous treatment conditions (RF: 0.88 ± 0.06, XG-Boost: 0.89 ± 0.07, NN: 0.98 ± 0.01). The ten most important features for each heterogeneity dataset group demonstrated their correlation with the treatments' physical aspects and GPR prediction.

CONCLUSION

Improvements in data generalization and model performances can be associated with datasets having similar treatment conditions. This analysis might be implemented to evaluate the dataset quality and model consistency of further ML applications in radiotherapy.

ADVANCES IN KNOWLEDGE

Dataset heterogeneities decrease ML model performance and reliability.

Impact of log file source and data frequency on accuracy of log file-based patient specific quality assurance

Performing phantom measurements for patient-specific quality assurance (PSQA) adds a significant amount of time to the adaptive radiotherapy procedure. Log file based PSQA can be used to increase the efficiency of this process. This study compared the dosimetric accuracy of high-frequency linear accelerator (Linac) log files and low-frequency log data stored in the oncology information system (OIS). Thirty patients were included, that were recently treated in the head and neck (HN), brain, and prostate region with volumetric modulated arc therapy (VMAT) and an additional ten patients treated using stereotactic body radiation therapy (SBRT) with 3D-conformal radiotherapy (3D-CRT) technique. Log data containing a single fraction were used to calculate the dose distributions. The dosimetric differences between Linac log files and OIS logs were evaluated with a gamma analysis with 2%/2 mm criterion and dose threshold of 30%. The original treatment plan was used as a reference. Moreover, DVH parameters of D_98%, D_50%, and D_2% of the planning-target volume (PTV) and dose to several organs at risk (OARs) were reported. Significant differences in dose distributions between the two log types and the original dose were observed for PTV D_98% and D_2% (r < 0.001) for HN cases, PTV D_98% (r = 0.005) for brain cases, and PTV D_50% (r = 0.015) for prostate cases. No significant differences were found between the two log types with respect to D_50%. The root mean square (RMS) error of the leaf positions of the OIS log was approximately twice the RMS error of the Linac log file for VMAT plans, but identical for 3D-CRT plans. The relationship between the gamma pass rate and the RMS error showed a moderate correlation for the Linac log files (r = -0.58, p < 0.001) and strong correlation for OIS logs (r = -0.71, p < 0.001). Furthermore, all doses calculated using Linac log files and OIS log data had a GPR >90% for an RMS error < 3.3 mm. Based on these findings, a tolerance limit of RMS error of 3.3 mm for considering OIS log based PSQA was established. Nevertheless, the OIS log data quality should be improved to achieve adequate PSQA.

A method for selecting reference beam model of VMAT plans with three 6MV beam-matched linear accelerators during radiation oncology

Our objective was to provide a method for selecting reference beam model and evaluating the dosimetric accuracy of volumetric modulated arc therapy (VMAT) plans delivered on three Elekta beam-matched linacs during radiation oncology. Beam data was measured on three beam-matched linacs including Synergy1, Synergy2 and VersaHD. For eighteen lung and esophagus cases, fifty-four plans were generated using VMAT technique with three linac beam models respectively for point dose measurement and three-dimensional dose measurement. Each VMAT plan was executed sequentially on three linacs respectively. Measurement results were compared with treatment planning system (TPS) calculation results for all VMAT plans. Among three beam-matched linacs, discrepancy in beam output factor, percentage depth dose at 5 cm, 10 cm, 20 cm depth and MLC leaf offset are all within 1% except 20 × 20 cm2 and 30 × 30 cm2 field sizes, and discrepancy in beam profile is all within 2%. With comparison between measurement result and TPS calculation result, the absolute dose deviations are within the range of ± 3%, and the gamma passing rates are all over 95% for all VMAT plans, which are within the tolerance of clinical acceptability. Compared with all plans delivered on Synegy1 and VersaHD, the point dose discrepancy between measured results and TPS calculated results for plans delivered on Synergy2 is smallest, and the gamma passing rate between measured results and TPS calculated results for plans delivered on Synergy2 is highest. The beam-matched linacs demonstrate good agreement between measurement result and TPS calculation result for VMAT plans. The method can be used for selecting reference beam model for VMAT plans.

Investigation of total skin helical tomotherapy using a 3D-printed total skin bolus

OBJECTIVE

To investigate the effectiveness of using a 3D-printed total skin bolus in total skin helical tomotherapy for the treatment of mycosis fungoides.

MATERIALS AND METHODS

A 65-year-old female patient with a 3-year history of mycosis fungoides underwent treatment using an in-house desktop fused deposition modelling printer to create a total skin bolus made of a 5-mm-thick flexible material, which increased the skin dose through dose building. The patient's scan was segmented into upper and lower sections, with the division line placed 10 cm above the patella. The prescription was to deliver 24 Gy over 24 fractions, given 5 times per week. The plan parameters consisted of a field width of 5 cm, pitch of 0.287 and modulation factor of 3. The complete block was placed 4 cm away from the planned target region to reduce the area of the internal organs at risk, especially the bone marrow. Dose delivery accuracy was verified using point dose verification with a "Cheese" phantom (Gammex RMI, Middleton, WI), 3D plane dose verification with ArcCHECK (Model 1220, Sun Nuclear, Melbourne, FL), and multipoint film dose verification. Megavoltage computed tomography guidance was also utilized to ensure the accuracy of the setup and treatment.

RESULTS

A 5-mm-thick 3D-printed suit was used as a bolus to achieve a target volume coverage of 95% of the prescribed dose. The conformity index and homogeneity index of the lower segment were slightly better than those of the upper segment. As the distance from the skin increased, the dose to the bone marrow gradually decreased, and the dose to other organs at risk remained within clinical requirements. The point dose verification deviation was less than 1%, the 3D plane dose verification was greater than 90%, and the multipoint film dose verification was less than 3%, all of which confirmed the accuracy of the delivered dose. The total treatment time was approximately 1.5 h, which included 0.5 h of wearing the 3D-printed suit and 1 h with the beam on. Patients only experienced mild fatigue, nausea or vomiting, low-grade fever, and grade III bone marrow suppression.

CONCLUSION

The use of a 3D-printed suit for total skin helical tomotherapy can result in a uniform dose distribution, short treatment time, simple implementation process, good clinical outcomes, and low toxicity. This study presents an alternative treatment approach that can potentially yield improved clinical outcomes for mycosis fungoides.

A virtual audit system for intensity-modulated radiation therapy credentialing in Japan Clinical Oncology Group clinical trials: A pilot study

PURPOSE

The Medical Physics Working Group of the Radiation Therapy Study Group at the Japan Clinical Oncology Group is currently developing a virtual audit system for intensity-modulated radiation therapy dosimetry credentialing. The target dosimeters include films and array detectors, such as ArcCHECK (Sun Nuclear Corporation, Melbourne, Florida, USA) and Delta4 (ScandiDos, Uppsala, Sweden). This pilot study investigated the feasibility of our virtual audit system using previously acquired data.

METHODS

We analyzed 46 films (32 and 14 in the axial and coronal planes, respectively) from 29 institutions. Global gamma analysis between measured and planned dose distributions used the following settings: 3%/3 mm criteria (the dose denominator was 2 Gy), 30% threshold dose, no scaling of the datasets, and 90% tolerance level. In addition, 21 datasets from nine institutions were obtained for array evaluation. Five institutions used ArcCHECK, while the others used Delta4. Global gamma analysis was performed with 3%/2 mm criteria (the dose denominator was the maximum calculated dose), 10% threshold dose, and 95% tolerance level. The film calibration and gamma analysis were conducted with in-house software developed using Python (version 3.9.2).

RESULTS

The means ± standard deviations of the gamma passing rates were 99.4 ± 1.5% (range, 92.8%-100%) and 99.2 ± 1.0% (range, 97.0%-100%) in the film and array evaluations, respectively.

CONCLUSION

This pilot study demonstrated the feasibility of virtual audits. The proposed virtual audit system will contribute to more efficient, cheaper, and more rapid trial credentialing than on-site and postal audits; however, the limitations should be considered when operating our virtual audit system.

Development of a deep learning-based error detection system without error dose maps in the patient-specific quality assurance of volumetric modulated arc therapy

To detect errors in patient-specific quality assurance (QA) for volumetric modulated arc therapy (VMAT), we proposed an error detection method based on dose distribution analysis using unsupervised deep learning approach and analyzed 161 prostate VMAT beams measured with a cylindrical detector. For performing error simulation, in addition to error-free dose distribution, dose distributions containing nine types of error, including multileaf collimator (MLC) positional errors, gantry rotation errors, radiation output errors and phantom setup errors, were generated. Only error-free data were employed for the model training, and error-free and error data were employed for the tests. As a deep learning model, the variational autoencoder (VAE) was adopted. The anomaly of test data was quantified by calculating Mahalanobis distance based on the feature vectors acquired from a trained encoder. Based on this anomaly, test data were classified as 'error-free' or 'any-error.' For comparison with conventional approaches, gamma (γ)-analysis was performed, and supervised learning convolutional neural network (S-CNN) was constructed. Receiver operating characteristic curves were obtained to evaluate their performance with the area under the curve (AUC). For all error types, except systematic MLC positional and radiation output errors, the performance of the methods was in the order of S-CNN ˃ VAE-based ˃ γ-analysis (only S-CNN required error data for model training). For example, in random MLC positional error simulation, the AUC of our method, S-CNN and γ-analysis were 0.699, 0.921 and 0.669, respectively. Our results showed that the VAE-based method has the potential to detect errors in patient-specific VMAT QA.

Practical and technical key challenges in head and neck adaptive radiotherapy: The GORTEC point of view

Anatomical variations occur during head and neck (H&N) radiotherapy (RT) treatment. These variations may result in underdosage to the target volume or overdosage to the organ at risk. Replanning during the treatment course can be triggered to overcome this issue. Due to technological, methodological and clinical evolutions, tools for adaptive RT (ART) are becoming increasingly sophisticated. The aim of this paper is to give an overview of the key steps of an H&N ART workflow and tools from the point of view of a group of French-speaking medical physicists and physicians (from GORTEC). Focuses are made on image registration, segmentation, estimation of the delivered dose of the day, workflow and quality assurance for an implementation of H&N offline and online ART. Practical recommendations are given to assist physicians and medical physicists in a clinical workflow.

Multicentric evaluation of a machine learning model to streamline the radiotherapy patient specific quality assurance process

PURPOSE

Patient-specific quality assurance (PSQA) is performed to ensure that modulated treatment plans can be delivered as intended, but constitutes a substantial workload that could slow down the radiotherapy process and delay the start of clinical treatments. In this study, we investigated a machine learning (ML) tree-based ensemble model to predict the gamma passing rate (GPR) for volumetric modulated arc therapy (VMAT) plans.

MATERIALS AND METHODS

5622 VMAT plans from multiple treatment sites were selected from a database of Institution 1 and the ML model trained using 19 metrics. PSQA analyses were performed automatically using criteria 3%/1 mm (global normalization, absolute dose, 10% threshold) and 95% action limit. Model's performance was evaluated on an out-of-sample test set of Institution 1 and on two independent sets of measurements collected at Institution 2 and Institution 3. Mean absolute error (MAE), as well as the model's sensitivity and specificity, were computed.

RESULTS

The model obtained a MAE of 2.33%, 2.54% and 3.91% for the three Institutions, with a specificity of 0.90, 0.90 and 0.68, and a sensitivity of 0.61, 0.25, and 0.55, respectively. Small positive median values of the residuals (i.e., the difference between measurements and predictions) were observed for each Institution (0.95%, 1.66%, and 3.42%). Thus, the model's predictions were, on average, close to the real values and provided a conservative estimation of the GPR.

CONCLUSIONS

ML models can be integrated into clinical practice to streamline the radiotherapy workflow, but they should be center-specific or thoroughly verified within centers before clinical use.

Online adaptive radiotherapy and dose delivery accuracy: A retrospective analysis

PURPOSE

With online adaptive radiotherapy (ART), patient-specific quality assurance (PSQA) testing cannot be performed prior to delivery of the adapted treatment plan. Consequently, the dose delivery accuracy of adapted plans (i.e., the ability of the system to interpret and deliver the treatment as planned) are not initially verified. We investigated the variation in dose delivery accuracy of ART on the MRIdian 0.35 T MR-linac (Viewray Inc., Oakwood, USA) between initial plans and their respective adapted plans, by analyzing PSQA results.

METHODS

We considered the two main digestive localizations treated with ART (liver and pancreas). A total of 124 PSQA results acquired with the ArcCHECK (Sun Nuclear Corporation, Melbourne, USA) multidetector system were analyzed. PSQA result variations between the initial plans and their respective adapted plans were statistically investigated and compared with the variation in MU number.

RESULTS

For the liver, limited deterioration in PSQA results was observed, and was within the limits of clinical tolerance (Initial = 98.2%, Adapted = 98.2%, p = 0.4503). For pancreas plans, only a few significant deteriorations extending beyond the limits of clinical tolerance were observed and were due to specific, complex anatomical configurations (Initial = 97.3%, Adapted = 96.5%, p = 0.0721). In parallel, we observed an influence of the increase in MU number on the PSQA results.

CONCLUSION

We show that the dose delivery accuracy of adapted plans, in terms of PSQA results, is preserved in ART processes on the 0.35 T MR-linac. Respecting good practices, and minimizing the increase in MU number can help to preserve the accuracy of delivery of adapted plans as compared to their respective initial plans.

Helical tomotherapy and two types of volumetric modulated arc therapy: dosimetric and clinical comparison for several cancer sites

Radiotherapy accelerators have undergone continuous technological developments. We investigated the differences between Radixact™ and VMAT treatment plans. Sixty patients were included in this study. Dosimetric comparison between the Radixact™ and VMAT plans was performed for six cancer sites: whole-brain, head and neck, lymphoma, lung, prostate, and rectum. The VMAT plans were generated with two Elekta linear accelerators (Synergy^® and Versa HD™). The planning target volume (PTV) coverage, organs-at-risk dose constraints, and four dosimetric indexes were considered. The deliverability of the plans was assessed using quality assurance (gamma index evaluation) measurements; clinical judgment was included in the assessment. The mean AAPM TG218 (3%-2 mm, global normalization) gamma index values were 99.4%, 97.8%, and 96.6% for Radixact™, Versa HD™, and Synergy®, respectively. Radixact™ performed better than Versa HD™ in terms of dosimetric indexes, hippocampi D_100%, spinal cord D_max, rectum V_{38.4  Gy}, bladder V_{30 Gy}, and V_{40 Gy}. Versa HD™ saved more of the (lungs-PTV) V_{5 Gy} and (lungs-PTV) D_mean, heart D_mean, breasts V_{4 Gy}, and bowel V_{45 Gy}. Regarding Synergy^®, the head and neck Radixact™ plan saved more of the parotid gland, oral cavity, and supraglottic larynx. From a clinical point of view, for the head and neck, prostate, and rectal sites, the Radixact™ and Versa HD™ plans were similar; Radixact™ plans were preferable for the head and neck and rectum to Synergy^® plans. The quality of linac plans has improved, and differences with tomotherapy have decreased. However, tomotherapy continues to be an essential add-on in multi-machine departments.

Guaranteed performance of individual control chart used in gamma passing rate-based patient-specific quality assurance

PURPOSE

To assess the effect of sampling variability on the performance of individual charts (I-charts) for PSQA and provide a robust and reliable method for unknown PSQA processes.

MATERIALS AND METHODS

A total of 1327 pretreatment PSQAs were analyzed. Different datasets with samples in the range of 20-1000 were used to estimate the lower control limit (LCL). Based on the iterative "Identify-Eliminate-Recalculate" and direct calculation without any outlier filtering procedures, five I-charts methods, namely the Shewhart, quantile, scaled weighted variance (SWV), weighted standard deviation (WSD), and skewness correction (SC) method, were used to compute the LCL. The average run length (ARL₀) and false alarm rate (FAR₀) were calculated to evaluate the performance of LCL.

RESULTS

The ground truth of the values of LCL, FAR₀, and ARL₀ obtained via in-control PSQAs were 92.31%, 0.135%, and 740.7, respectively. Further, for in-control PSQAs, the width of the 95% confidence interval of LCL values for all methods tended to decrease with the increase in sample size. In all sample ranges of in-control PSQAs, only the median LCL and ARL₀ values obtained via WSD and SWV methods were close to the ground truth. For the actual unknown PSQAs, based on the "Identify-Eliminate-Recalculate" procedure, only the median LCL values obtained by the WSD method were closest to the ground truth.

CONCLUSIONS

Sampling variability seriously affected the I-chart performance in PSQA processes, particularly for small samples. For unknown PSQAs, the WSD method based on the implementation of the iterative "Identify-Eliminate-Recalculate" procedure exhibited sufficient robustness and reliability.

Optimization of the Dose Rate Effect in Tetrazolium Gellan Gel Dosimeters

Tetrazolium salts provide an appealing candidate for 3D gel dosimeters as they exhibit a low intrinsic color, no signal diffusion and excellent chemical stability. However, a previously developed commercial product (the ClearView 3D Dosimeter) based on a tetrazolium salt dispersed within a gellan gum matrix presented a noticeable dose rate effect. The goal of this study was to find out whether ClearView could be reformulated in order to minimize the dose rate effect by optimizing of the tetrazolium salt and gellan gum concentrations and by the addition a thickening agent, ionic crosslinkers, and radical scavengers. To that goal, a multifactorial design of experiments (DOE) was conducted in small-volume samples (4-mL cuvettes). It showed that the dose rate could be effectively minimized without sacrificing the integrity, chemical stability, or dose sensitivity of the dosimeter. The results from the DOE were used to prepare candidate formulations for larger-scale testing in 1-L samples to allow for fine-tuning the dosimeter formulation and conducting more detailed studies. Finally, an optimized formulation was scaled-up to a clinically relevant volume of 2.7 L and tested against a simulated arc treatment delivery with three spherical targets (diameter 3.0 cm), requiring different doses and dose rates. The results showed excellent geometric and dosimetric registration, with a gamma passing rate (at 10% minimum dose threshold) of 99.3% for dose difference and distance to agreement criteria of 3%/2 mm, compared to 95.7% in the previous formulation. This difference may be of clinical importance, as the new formulation may allow the quality assurance of complex treatment plans, relying on a variety of doses and dose rates; thus, expanding the potential practical application of the dosimeter.

A novel automated planning approach for multi-anatomical sites cancer in Raystation treatment planning system

PURPOSE

To develop an automated planning approach in Raystation and evaluate its feasibility in multiple clinical application scenarios.

METHODS

An automated planning approach (Ruiplan) was developed by using the scripting platform of Raystation. Radiotherapy plans were re-generated both automatically by using Ruiplan and manually. 60 patients, including 20 patients with nasopharyngeal carcinoma (NPC), 20 patients with esophageal carcinoma (ESCA), and 20 patients with rectal cancer (RECA) were retrospectively enrolled in this study. Dosimetric and planning efficiency parameters of the automated plans (APs) and manual plans (MPs) were statistically compared.

RESULTS

For target coverage, APs yielded superior dose homogeneity in NPC and RECA, while maintaining similar dose conformity for all studied anatomical sites. For OARs sparing, APs led to significant improvement in most OARs sparing. The average planning time required for APs was reduced by more than 43% compared with MPs. Despite the increased monitor units (MUs) for NPC and RECA in APs, the beam-on time of APs and MPs had no statistical difference. Both the MUs and beam-on time of APs were significantly lower than that of MPs in ESCA.

CONCLUSIONS

This study developed a new automated planning approach, Ruiplan, it is feasible for multi-treatment techniques and multi-anatomical sites cancer treatment planning. The dose distributions of targets and OARs in the APs were similar or better than those in the MPs, and the planning time of APs showed a sharp reduction compared with the MPs. Thus, Ruiplan provides a promising approach for realizing automated treatment planning in the future.

A method for adjusting MLC leaf positions outside a reference region for VMAT plans in a commercial treatment planning system

Multileaf collimators (MLC) leaf positions in a volumetric modulated arc therapy (VMAT) plan is determined from inverse treatment planning process. On the isocenter plane, leaf projections should not be set too far out of projected PTV boundary. In this study we developed an automatic method of adjusting leaf positions outside a reference region of interest (ROI) for VMAT plans generated in Pinnacle treatment planning system (TPS). The proposed method consisted of a Pinnacle script and a Python program. It checked each MLC leaf position for all control points in a VMAT arc relative to a reference ROI created by adding a small margin to PTV. For leaves opened outside the reference ROI, the method adjusted their positions to reduce dose to normal tissue while maintaining PTV coverage and satisfying leaf position constraints. The deliverability and dose accuracy of the method was verified by applying it to 15 VMAT plans which were delivered in five different linacs in our department. Dosimetric improvement of the proposed method was analyzed for another group of 16 randomly selected VMAT plans. The average gamma passing rate using a 3%/3 mm criteria for the verification group of VMAT plans was 98.3% and all passing rates were above our internal passing threshold. Dosimetric improvement was observed for the evaluation group of VMAT plans. The method can improve normal tissue protection for VMAT plans. It can be safely applied in routine clinic work.

Correction factors for commissioning and patient specific quality assurance of stereotactic fields in a Monte Carlo based treatment planning system : TPS correction factors

Validation of small field dosimetry is crucial for stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT). Accurate and considered measurement of linear accelerator dose must be compared to precise and accurate calculation by the treatment planning system (TPS). Monte Carlo calculated distributions contain statistical noise, reducing the reliance that should be given to single voxel doses. The average dose to a small volume of interest (VOI) can minimise the influence of noise, but for small fields introduces significant volume averaging. Similar challenges present during measurement of composite dose from clinical plans when a small volume ionisation chamber is used. This study derived correction factors for VOI averaged TPS doses calculated for small fields, allowing correction to an isocentre dose following account for statistical noise. These factors were used to determine an optimal VOI to represent small volume ionisation chambers during patient specific quality assurance (PSQA). A retrospective comparison of 82 SRS and 28 SBRT PSQA measurements to TPS calculated doses from varying VOI was completed to evaluate the determined volumes. Small field commissioning correction factors of under 5% were obtained for field sizes of 8 mm and larger. Optimal spherical VOI with radius between 1.5 and 1.8 mm and 2.5 to 2.9 mm were determined for IBA CC01 and CC04 ionisation chambers respectively. Review of PSQA confirmed an optimal agreement between CC01 measured doses and a volume of 1.5 to 1.8 mm while CC04 measured doses showed no variation with VOI.

Impact of the Extremities Positioning on the Set-Up Reproducibility for the Total Marrow Irradiation Treatment

Total marrow (lymph node) irradiation (TMI/TMLI) delivery requires more time than standard radiotherapy treatments. The patient's extremities, through the joints, can experience large movements. The reproducibility of TMI/TMLI patients' extremities was evaluated to find the best positioning and reduce unwanted movements. Eighty TMI/TMLI patients were selected (2013-2022). During treatment, a cone-beam computed tomography (CBCT) was performed for each isocenter to reposition the patient. CBCT-CT pairs were evaluated considering: (i) online vector shift (OVS) that matched the two series; (ii) residual vector shift (RVS) to reposition the patient's extremities; (iii) qualitative agreement (range 1-5). Patients were subdivided into (i) arms either leaning on the frame or above the body; (ii) with or without a personal cushion for foot positioning. The Mann-Whitney test was considered (p < 0.05 significant). Six-hundred-twenty-nine CBCTs were analyzed. The median OVS was 4.0 mm, with only 1.6% of cases ranked < 3, and 24% of RVS > 10 mm. Arms leaning on the frame had significantly smaller RVS than above the body (median: 8.0 mm/6.0 mm, p < 0.05). Using a personal cushion for the feet significantly improved the RVS than without cushions (median: 8.5 mm/1.8 mm, p < 0.01). The role and experience of the radiotherapy team are fundamental to optimizing the TMI/TMLI patient setup.

Predicted Inferior Outcomes for Lung SBRT With Treatment Planning Systems That Fail Independent Phantom-Based Audits

PURPOSE

More than 15% of radiation therapy clinics fail external audits with anthropomorphic phantoms conducted by Imaging and Radiation Oncology Core-Houston (IROC-H) while passing other industry-standard quality assurance (QA) tests. We seek to evaluate the predicted effect of such failed plans on outcomes for patients treated with stereotactic body radiation therapy (SBRT) for lung tumors.

METHODS AND MATERIALS

We conducted a retrospective study of 55 patients treated with SBRT for lung tumors with a prescription biologically equivalent dose (BED)₁₀ ≥100 Gy using a treatment planning system (TPS) that passed IROC-H phantom audits. Sample linear accelerator beam models with introduced errors were commissioned by varying the multileaf collimator leaf-tip offset parameter (ie, dosimetric leaf gap) over the range ±1.0 mm relative to the validated model. These models mimic TPS that pass internal QA measures but fail IROC-H tests. Patient plans were recalculated on sample beam models. The predicted tumor control probability (TCP) and normal tissue complication probability (NTCP) were calculated based on published dose-response models.

RESULTS

A leaf-tip offset value of -1.0 mm decreased the fraction of plans receiving a planning treatment volume of BED₁₀ ≥100 Gy from 95% to 27%. This translated to a significant decrease in 2-year TCP of 4.8% (95% CI: 2.0%-5.5%) with a decrease in TCP up to 21%. Conversely, a leaf-tip offset of +1.0 mm resulted in 36% of patients exceeding previously met organs at risk (OAR) constraints, including 2 instances of spinal cord and brachial plexus overdoses and a small increase in chest wall NTCP of 0.7%, (95% CI: 0.5%-0.8%).

CONCLUSIONS

Simulated treatment plans with modest MLC leaf offsets result in lung SBRT plans that significantly underdose tumor or exceed OAR constraints. These dosimetric endpoints translate to significant detriments in TCP. These simulated plans mimic planning systems that pass internal QA measures but fail independent phantom-based tests, underscoring the need for enhanced quality assurance including external audits of TPS.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

Implementation, Dosimetric Assessment, and Treatment Validation of Knowledge-Based Planning (KBP) Models in VMAT Head and Neck Radiation Oncology

The aim of this study was to evaluate knowledge-based treatment planning (KBP) models in terms of their dosimetry and deliverability and to investigate their clinical benefits. Three H&N KBP models were built utilizing RapidPlan™, based on the dose prescription, which is given according to the planning target volume (PTV). The training set for each model consisted of 43 clinically acceptable volumetric modulated arc therapy (VMAT) plans. Model quality was assessed and compared to the delivered treatment plans using the homogeneity index (HI), conformity index (CI), structure dose difference (PTV, organ at risk—OAR), monitor units, MU factor, and complexity index. Model deliverability was assessed through a patient-specific quality assurance (PSQA) gamma index-based analysis. The dosimetric assessment showed better OAR sparing for the RapidPlan™ plans and for the low- and high-risk PTV, and the HI, and CI were comparable between the clinical and RapidPlan™ plans, while for the intermediate-risk PTV, CI was better for clinical plans. The 2D gamma passing rates for RapidPlan™ plans were similar or better than the clinical ones using the 3%/3 mm gamma-index criterion. Monitor units, the MU factors, and complexity indices were found to be comparable between RapidPlan™ and the clinical plans. Knowledge-based treatment plans can be safely adapted into clinical routines, providing improved plan quality in a time efficient way while minimizing user variability.

A convolutional neural network model for EPID-based non-transit dosimetry

PURPOSE

To develop an alternative computational approach for EPID-based non-transit dosimetry using a convolutional neural network model.

METHOD

A U-net followed by a non-trainable layer named True Dose Modulation recovering the spatialized information was developed. The model was trained on 186 Intensity-Modulated Radiation Therapy Step & Shot beams from 36 treatment plans of different tumor locations to convert grayscale portal images into planar absolute dose distributions. Input data were acquired from an amorphous-Silicon Electronic Portal Image Device and a 6 MV X-ray beam. Ground truths were computed from a conventional kernel-based dose algorithm. The model was trained by a two-step learning process and validated through a five-fold cross-validation procedure with sets of training and validation of 80% and 20%, respectively. A study regarding the dependance of the amount of training data was conducted. The performance of the model was evaluated from a quantitative analysis based the ϒ-index, absolute and relative errors computed between the inferred dose distributions and ground truths for six square and 29 clinical beams from seven treatment plans. These results were also compared to those of an existing portal image-to-dose conversion algorithm.

RESULTS

For the clinical beams, averages of ϒ-index and ϒ-passing rate (2%-2mm > 10% D_max ) of 0.24 (±0.04) and 99.29 (±0.70)% were obtained. For the same metrics and criteria, averages of 0.31 (±0.16) and 98.83 (±2.40)% were obtained with the six square beams. Overall, the developed model performed better than the existing analytical method. The study also showed that sufficient model accuracy can be achieved with the amount of training samples used.

CONCLUSION

A deep learning-based model was developed to convert portal images into absolute dose distributions. The accuracy obtained shows that this method has great potential for EPID-based non-transit dosimetry.

Deep Hybrid Learning Prediction of Patient-Specific Quality Assurance in Radiotherapy: Implementation in Clinical Routine

BACKGROUND

Arc therapy allows for better dose deposition conformation, but the radiotherapy plans (RT plans) are more complex, requiring patient-specific pre-treatment quality assurance (QA). In turn, pre-treatment QA adds to the workload. The objective of this study was to develop a predictive model of Delta4-QA results based on RT-plan complexity indices to reduce QA workload.

METHODS

Six complexity indices were extracted from 1632 RT VMAT plans. A machine learning (ML) model was developed for classification purpose (two classes: compliance with the QA plan or not). For more complex locations (breast, pelvis and head and neck), innovative deep hybrid learning (DHL) was trained to achieve better performance.

RESULTS

For not complex RT plans (with brain and thorax tumor locations), the ML model achieved 100% specificity and 98.9% sensitivity. However, for more complex RT plans, specificity falls to 87%. For these complex RT plans, an innovative QA classification method using DHL was developed and achieved a sensitivity of 100% and a specificity of 97.72%.

CONCLUSIONS

The ML and DHL models predicted QA results with a high degree of accuracy. Our predictive QA online platform is offering substantial time savings in terms of accelerator occupancy and working time.

Optimised conformal total body irradiation: a heterogeneous practice, so where next?

The use of volumetric arc therapy and inverse planning has been in routine use in radiotherapy for two decades. However, use in total body irradiation (TBI) has been more recent and few guidelines exist as to how to plan or verify. This has led to heterogeneous approaches. The goal of this review is to provide an overview of current advanced planning and dosimetry verification protocols used in optimised conformal TBI as a basis for investigating the need for greater standardisation in TBI.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

An effective and optimized patient-specific QA workload reduction for VMAT plans after MLC-modelling optimization

INTRODUCTION

Many complexity metrics characterize modulated plans. First, this study aimed at identify the optimal complexity metrics to reduce workload associated to patient-specific quality assurance (PSQA) for our equipment and processes. Second, it intended to optimize our MLC modelling to improve measurement and calculation agreement with expectation of further reducing PSQA workload.

METHODS

Correlation and sensitivity at specificity equals to 1 were evaluated for PSQA results and different complexity metrics. Thresholds to stop PSQA were determined. After validation of the optimal complexity metric and threshold for our equipment and process, the MLC modelling was reviewed with a recently published methodology. This method is based on measurements with a Farmer-type ionization chamber of synchronous and asynchronous sweeping gap plans. Effect on the PSQA results and the identified threshold was investigated.

RESULTS

In our center, the most appropriate complexity metric for reducing our PSQA workload was the Modulation Complexity Score for VMAT (MCSv). The optimization of the MLC modelling significantly reduced the number of controlled plans, specifically for one of our two Varian Clinac. Any plan with a MCSv >= 0.34 is treated without PSQA.

CONCLUSION

This study rationalized and reduced our PSQA workload by approximately 30%. It is a continuing work with new TPS, machine or PSQA equipment. It encourages centers to re-evaluate their MLC modelling as well as assess the benefit of complexity metrics to streamline their PSQA workflow. An easier access, at least for reporting, at best for optimizing plans, into the TPS would be beneficial for the community.

Effects of reconstruction methods on dose distribution for lung stereotactic body radiotherapy treatment plans

The aim of the present study was to investigate the effect of tumour motion on various imaging strategies as well as on treatment plan accuracy for lung stereotactic body radiotherapy treatment (SBRT) cases. The ExacTrac gating phantom and paraffin were used to investigate respiratory motion and represent a lung tumour, respectively. Four-dimensional computed tomography (4DCT) imaging was performed, while the phantom was moving sinusoidally with 4 s cycling time with three different amplitudes of 8, 16, and 24 mm. Reconstructions were done with maximum (MIP) and average intensity projection (AIP) methods. Comparisons of target density and volume were performed using two reconstruction techniques and references values. Volumetric modulated arc therapy (VMAT) and intensity modulated radiation therapy (IMRT) were planned based on reconstructed computed tomography (CT) sets, and it was examined how density variations affect the dose-volume histogram (DVH) parameters. 4D cone beam computed tomography (CBCT) was performed with the Elekta Versa HD linac imaging system before irradiation and compared with 3D CBCT. Thus, various combinations of 4DCT reconstruction methods and treatment alignment methods have been investigated. Point measurements as well as 2 and 3D dose measurements were done by optically stimulated luminescence (OSL), gafchromic films, and electronic portal imaging devices (EPIDs), respectively. The mean volume reduction was 7.8% for the AIP and 2.6% for the MIP method. The obtained Hounsfield Unit (HU) values were lower for AIP and higher for MIP when compared with the reference volume density. In DVH analysis, there were no statistical differences for D_95%, D_98%, and D_mean (p > 0.05). However, D_2% was significantly affected by HU changes (p < 0.01). A positional variation was obtained up to 2 mm in moving direction when 4D CBCT was applied after 3D CBCT. Dosimetric measurements showed that the main part of the observed dose deviation was due to movement. In lung SBRT treatment plans, D_2% doses differ significantly according to the reconstruction method. Additionally, it has been observed that setups based on 3D imaging can cause a positional error of up to 2 mm compared to setups based on 4D imaging. It is concluded that MIP has advantages over AIP in defining internal target volume (ITV) in lung SBRT applications. In addition, 4D CBCT and 3D EPID dosimetry are recommended for lung SBRT treatments.

AAPM Task Group Report 306: Quality control and assurance for tomotherapy: An update to Task Group Report 148

Since the publication of AAPM Task Group (TG) 148 on quality assurance (QA) for helical tomotherapy, there have been many new developments on the tomotherapy platform involving treatment delivery, on-board imaging options, motion management, and treatment planning systems (TPSs). In response to a need for guidance on quality control (QC) and QA for these technologies, the AAPM Therapy Physics Committee commissioned TG 306 to review these changes and make recommendations related to these technology updates. The specific objectives of this TG were (1) to update, as needed, recommendations on tolerance limits, frequencies and QC/QA testing methodology in TG 148, (2) address the commissioning and necessary QA checks, as a supplement to Medical Physics Practice Guidelines (MPPG) with respect to tomotherapy TPS and (3) to provide risk-based recommendations on the new technology implemented clinically and treatment delivery workflow. Detailed recommendations on QA tests and their tolerance levels are provided for dynamic jaws, binary multileaf collimators, and Synchrony motion management. A subset of TPS commissioning and QA checks in MPPG 5.a. applicable to tomotherapy are recommended. In addition, failure mode and effects analysis has been conducted among TG members to obtain multi-institutional analysis on tomotherapy-related failure modes and their effect ranking.

Study of dose dependence on density in planar 3D-printed applicators for HDR Ir192 surface brachytherapy

PURPOSE

This paper describes a method to evaluate the influence of 3D printed plesiotherapy applicators densities in the most clinically relevant dosimetric planes of these brachytherapy treatments. Studied densities range goes from that of water to that of air including the intermediate applicators densities made of acrylonitrile butadiene styrene and polylactic acid, materials used as Fused Deposition Modelling (FDM) filaments.

METHODS AND MATERIALS

All applicators were manufactured by means of FDM 3D printing and a special empty applicator of ABS walls was designed to be filled with water or air. In each of these applicators, the values of the dose and gamma index at the surface and at the prescription depth were measured in clinical conditions, using EBT films.

RESULTS

Analysis of results allow us to conclude that the influence of the applicators density on the dose value in the studied materials depends on the distance at which the dose is measured. Thus, at the prescription depth no influence is observed, however this influence becomes noticeable near the surface of the applicators with dose differences of more than 10% for densities close to 0.4 g/cm³.

CONCLUSION

Therefore, the density of FDM manufactured applicators should be taken into account when calculating surface dose for low density applicators, as variations caused by density can have clinical implications because is the surface dose that is associated with the toxicity of brachytherapy skin treatments.

Evaluation of HyperArc™ using film and portal dosimetry quality assurance

HyperArc™ is a stereotactic radiotherapy modality designed for targeting multiple brain metastases using a single isocenter with multiple non-coplanar arcs. This study aimed to assess the efficacy of two patient-specific quality assurance methods, film and the Varian Portal Dosimetry System with Varian's HyperArc™ technique and raise important considerations in the customisation of patient-specific quality assurance to accommodate HyperArc™ delivery. Assessment criteria included gamma analysis and mean dose at full width half maximum. The minimum metastasis size, maximum off-axis distance and suitable energy were identified and validated. Patient-specific quality assurance procedures were applied to a range of clinically relevant brain metastasis plans. Initial investigation into energy selection showed no significant differences in gamma pass rates using 6MV, 6MV FFF, or 10MV FFF for metastasis sizes greater than 15 mm diameter at the isocenter. Gamma pass rates (2%/2mm) for 15 mm metastases at the isocenter for all energies were greater than 96.0% for portal dosimetry and greater than 98.7% for film. Fields of size 15 mm placed at various distances (10-70 mm) from the isocenter resulted in a maximum mean dose difference of 1.5% between film and planned. Clinically relevant plans resulted in a maximum mean dose difference for selected metastases of 1.0% between film and plan and a maximum point dose difference of 2.9% between portal dose and plan. Portal dose image prediction was a quick and convenient quality assurance tool for metastases larger than 15 mm near the isocenter but provided diminished geometrical relevance for off-axis metastases. Film QA required exacting procedures but offered the ability to assess the accuracy of geometrical targeting for off-axis metastases and provided dosimetric accuracy for metastases to well below 15 mm diameter.

Clinical Feasibility of Using Single-isocentre Non-coplanar Volumetric Modulated Arc Therapy Combined with Non-coplanar Cone Beam Computed Tomography in Hypofractionated Stereotactic Radiotherapy for Five or Fewer Multiple Intracranial Metastases

AIMS

To evaluate the clinical feasibility of single-isocentre non-coplanar volumetric modulated arc therapy (NC-VMAT) with non-coplanar cone beam computed tomography (NC-CBCT) in hypofractionated stereotactic radiotherapy (HSRT) for five or fewer multiple brain metastases.

MATERIALS AND METHODS

Ten patients with multiple brain metastases who underwent single-isocentre NC-VMAT HSRT with limited couch rotations (within ±45°) and NC-CBCT with a limited scanning range (150-200°) were included in the current analysis. Conventional single-isocentre coplanar VMAT (C-VMAT) plans were generated and compared with NC-VMAT plans. The intracranial response and toxicities of single-isocentre NC-VMAT HSRT were also evaluated.

RESULTS

Compared with C-VMAT, NC-VMAT generated better target conformity (P < 0.05), a lower gradient index (P < 0.05) and better normal brain tissue sparing, especially for volume ≥12 Gy, with a median reduction of 12.65 cm³. For 45° couch rotation, NC-CBCT produced sufficient image quality to differentiate bony anatomy, even with a 150° scanning range, which could be successfully used for patient set-up correction. After NC-CBCT, 57.1% of the measured non-coplanar set-up errors exceeded the threshold value. The median gamma passing rate of NC-VMAT was higher than that of C-VMAT plans (P < 0.05). The non-coplanar beam of NC-VMAT with NC-CBCT corrections exhibited superior gamma passing rate to that without NC-CBCT corrections. The intracranial objective response rate and disease control rate for all patients were 80% (8/10) and 100% (10/10), respectively, and the most common toxicities were headache (20%) and dizziness (20%).

CONCLUSION

NC-VMAT with limited couch rotation (within ±45°) combined with NC-CBCT with a limited scanning range (150-200°) markedly improves the plan quality and set-up accuracy in single-isocentre multiple-target HSRT.

Effect of angular dependence for small-field dosimetry using seven different detectors

BACKGROUND

Small-field dosimetry is challenging for radiotherapy dosimetry because of the loss of lateral charged equilibrium, partial occlusion of the primary photon source by the collimating devices, perturbation effects caused by the detector materials and their design, and the detector size relative to the radiation field size, which leads to a volume averaging effect. Therefore, a suitable tool for small-field dosimetry requires high spatial resolution, tissue equivalence, angular independence, and energy and dose rate independence to achieve sufficient accuracy. Recently, with the increasing use of combinations of coplanar and non-coplanar beams for small-field dosimetry, there is a need to clarify angular dependence for dosimetry where the detector is oriented at various angles to the incident beam. However, the effect of angular dependence on small-field dosimetry with coplanar and non-coplanar beams has not been fully clarified.

PURPOSE

This study clarified the effect of angular dependence on small-field dosimetry with coplanar and non-coplanar beams using various detectors.

METHODS

Seven different detectors were used: CC01, RAZOR, RAZOR Nano, Pinpoint 3D, stereotactic field diode (SFD), microSilicon, and microDiamond. All measurements were taken using a TrueBeam STx with 6 MV and 10 MV flattening filter-free (FFF) energies using a water-equivalent spherical phantom with a source-to-axis distance of 100 cm. The detector was inserted in a perpendicular orientation, and the gantry was rotated at 15° increments from the incidence beam angle. A multi-leaf collimator (MLC) with four field sizes of 0.5 × 0.5, 1 × 1, 2 × 2, and 3 × 3 cm² , and four couch angles from 0°, 30°, 60°, and 90° (coplanar and non-coplanar) were adopted. The angular dependence response (AR) was defined as the ratio of the detector response at a given irradiation gantry angle normalized to the detector response at 0°. The maximum AR differences were calculated between the maximum and minimum AR values for each detector, field size, energy, and couch angle.

RESULTS

The maximum AR difference for the coplanar beam was within 3.3% for all conditions, excluding the maximum AR differences in 0.5 × 0.5 cm² field for CC01 and RAZOR. The maximum AR difference for non-coplanar beams was within 2.5% for fields larger than 1 × 1 cm² , excluding the maximum AR differences for RAZOR Nano, SFD, and microSilicon. The Pinpoint 3D demonstrated stable AR tendencies compared to other detectors. The maximum difference was within 2.0%, except for the 0.5 × 0.5 cm² field and couch angle at 90°. The tendencies of AR values for each detector were similar when using different energies.

CONCLUSION

This study clarified the inherent angular dependence of seven detectors that were suitable for small-field dosimetry. The Pinpoint 3D chamber had the smallest angular dependence of all detectors for the coplanar and non-coplanar beams. The findings of this study can contribute to the calculation of the AR correction factor, and it may be possible to adapt detectors with a large angular dependence on coplanar and non-coplanar beams. However, note that the gantry sag and detector-specific uncertainties increase as the field size decreases.

Prediction models as decision-support tools for virtual patient-specific quality assurance of helical tomotherapy plans

Background and purpose

Prediction models may be reliable decision-support tools to reduce the workload associated with the measurement-based patient-specific quality assurance (PSQA) of radiotherapy plans. This study compared the effectiveness of three different models based on delivery parameters, complexity metrics and sinogram radiomics features as tools for virtual-PSQA (vPSQA) of helical tomotherapy (HT) plans.

Materials and methods

A dataset including 881 RT plans created with two different treatment planning systems (TPSs) was collected. Sixty-five indicators including 12 delivery parameters (DP) and 53 complexity metrics (CM) were extracted using a dedicated software library. Additionally, 174 radiomics features (RF) were extracted from the plans' sinograms. Three groups of variables were formed: A (DP), B (DP + CM) and C (DP + CM + RF). Regression models were trained to predict the gamma index passing rate P R γ (3%G, 2mm) and the impact of each group of variables was investigated. ROC-AUC analysis measured the ability of the models to accurately discriminate between 'deliverable' and 'non-deliverable' plans.

Results

The best performance was achieved by model C which allowed detecting around 16% and 63% of the 'deliverable' plans with 100% sensitivity for the two TPSs, respectively. In a real clinical scenario, this would have decreased the whole PSQA workload by approximately 35%.

Conclusions

The combination of delivery parameters, complexity metrics and sinogram radiomics features allows for robust and reliable PSQA gamma passing rate predictions and high-sensitivity detection of a fraction of deliverable plans for one of the two TPSs. Promising yet improvable results were obtained for the other one. The results foster a future adoption of vPSQA programs for HT.

Evaluation of stereotactic VMAT lung treatment plans for small moving targets

PURPOSE

The aim of this study is to perform patient quality controls and end-to-end tests for stereotactic VMAT lung treatment plans and to investigate the influence of various parameters on the results.

METHOD

18 plans were defined by an experimental design methodology to cover a large variety of stereotactic VMAT lung treatments including different doses per fraction, target diameters, target movements and respiratory parameters. Plans were first controlled using portal dosimetry and a homogeneous static cylindrical phantom. End-to-end tests were then performed in a dynamic respiratory thorax phantom. Measurements were conducted with ionization chamber and films. Calculations were performed with the AcurosXB and AAA algorithms in 6 FFF.

RESULTS

Portal dosimetry gave excellent gamma pass rates (greater than 97.1 %) and dose deviations between measurement and calculations in a homogeneous static phantom were smaller than 2 %. The methodology followed for comparing calculated and measured doses in a moving target was validated in static fields (largest deviation smaller than  2 %). End-to-end tests showed mean deviations of 1.9 %, 3.3 % and 6.6 % for the 3, 2 and 1 cm diameter's target respectively. Deviations increased for larger movements for the 1 cm lesion.

CONCLUSION

End-to-end tests revealed that stereotactic VMAT lung treatment plans for moving targets can be delivered within 5 % for 3 and 2 cm diameter targets and amplitudes up to 1.5 cm. The AcurosXB and AAA algorithms however tend to underestimate the dose to the target. Even with satisfactory patient quality controls like portal dosimetry, extra care should be taken for GTV lesions smaller than 2 cm.

Comparing log file to measurement-based patient-specific quality assurance

Recent technological advances have allowed the possibility of performing patient-specific quality assurance (QA) without time-intensive measurements. The objectives of this study are to: (1) compare how well the log file-based Mobius QA system agrees with measurement-based QA methods (ArcCHECK and portal dosimetry, PD) in passing and failing plans, and; (2) evaluate their error sensitivities. To these ends, ten phantom plans and 100 patient plans were measured with ArcCHECK and PD on VitalBeam, while log files were sent to Mobius for dose recalculation. Gamma evaluation was performed using criteria 3%/2 mm, per TG218 recommendations, and non-inferiority of the Mobius recalculation was determined with statistical testing. Ten random plans were edited to include systematic errors, then subjected to QA. Receiver operating characteristic curves were constructed to compare error sensitivities across the QA systems, and clinical significance of the errors was determined by recalculating dose to patients. We found no significant difference between Mobius, ArcCHECK, and PD in passing plans at the TG218 action limit. Mobius showed good sensitivity to collimator and gantry errors but not MLC bank shift errors, but could flag discrepancies in treatment delivery. Systematic errors were clinically significant only at large magnitudes; such unacceptable plans did not pass QA checks at the TG218 tolerance limit. Our results show that Mobius is not inferior to existing measurement-based QA systems, and can supplement existing QA practice by detecting real-time delivery discrepancies. However, it is still important to maintain rigorous routine machine QA to ensure reliability of machine log files.

Dosimetric comparison of two dose expansion methods in intensity modulated radiotherapy for breast cancer

BACKGROUND

To explore the dosimetric difference between IMRT-VB plan based on the establishment of external expansion structure and virtual bolus (VB) and IMRT-SF based on the skin flash (SF) tool of the Eclipse treatment planning system in postoperative chest wall target intensity modulation radiotherapy plan of breast cancer.

METHODS

Twenty patients with breast cancer were randomly selected as subjects to develop IMRT-VB plan based on virtual bolus and IMRT-SF plan based on skin flash tool of Eclipse treatment planning system. The planning target volume, monitor unit (MU) of every single treatment and the dosimetric parameters of organ at risk (OARs) were recorded. Paired t-test was used for normal distribution data while nonparametric paired Wilcoxon rank sum test was used for non-normal distribution data.

RESULTS

Both IMRT-VB and IMRT-SF plan can expand outward to the chest wall skin and meet the dose requirements of clinical prescription. The conformal index, the homogeneity index, D_2%, D_98% and D_50% were significantly better in IMRT-SF plan than those in IMRT-VB plan (P < 0.05). The average MU of the IMRT-SF plan was much higher than that of the IMRT-VB plan (866.0 ± 68.1 MU vs. 760.9 ± 50.4 MU, P < 0.05). In terms of organ at risk protection, IMRT-SF plan had more advantages in the protection of ipsilateral lung and spinal cord than IMRT-VB plan (P < 0.05).

CONCLUSION

Our study indicated that IMRT-SF plan displayed clinical application superiority compared to IMRT-VB plan, and the operation steps of which are simpler and faster. Besides, IMRT-SF plan took advantages in achieve effective external expansion of skin dose intensity and OARs protection.