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

Validation of complex radiotherapy techniques using polymer gel dosimetry

Modern radiotherapy delivers highly conformal dose distributions to irregularly shaped target volumes while sparing the surrounding normal tissue. Due to the complex planning and delivery techniques, dose verification and validation of the whole treatment workflow by end-to-end tests became much more important and polymer gel dosimeters are one of the few possibilities to capture the delivered dose distribution in 3D. The basic principles and formulations of gel dosimetry and its evaluation methods are described and the available studies validating device-specific geometrical parameters as well as the dose delivery by advanced radiotherapy techniques, such as 3D-CRT/IMRT and stereotactic radiosurgery treatments, the treatment of moving targets, online-adaptive magnetic resonance-guided radiotherapy as well as proton and ion beam treatments, are reviewed. The present status and limitations as well as future challenges of polymer gel dosimetry for the validation of complex radiotherapy techniques are discussed.

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

Background

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

Materials and methods

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

Results

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

Conclusions

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

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

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

A comparison of three-film analysis software for stereotactic radiotherapy patient-specific quality assurance

AIM

The aim of this study was to investigate the suitability of three radiochromic film analysis software for stereotactic radiotherapy patient-specific quality assurance (PSQA): FilmQA Pro v5.0, SNC Patient v6.2, and eFilmQA v5.0.

METHODS

Film calibration was conducted for each software followed by three sets of measurements. The first set assessed calibration accuracy by comparing measured and delivered doses at increments different from those used for calibration. The second set used each software to conduct PSQA through gamma analysis on 10 stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) patients. The third set utilized SNC Patient and eFilmQA to carry out gamma analysis on a collection of four digital test images, eliminating delivery and scanning uncertainties from impacting the analysis. Key supporting features within each software for conducting gamma analysis were identified.

RESULTS

Overall, FilmQA Pro and eFilmQA were deemed comparable and favoured over SNC Patient due to the presence of key features such as triple-channel dosimetry, auto-optimization, and dose scaling. FilmQA Pro has a substantial user base and established reputation. eFilmQA, having been introduced more recently, serves as a viable alternative to FilmQA Pro, having been further refined for stereotactic radiotherapy PSQA.

CONCLUSION

This study investigated the suitability of three film analysis software (FilmQA Pro, eFilmQA, and SNC Patient) for stereotactic radiotherapy PSQA. Results from the investigation indicated that both FilmQA Pro and eFilmQA are comparably suitable and are preferred over SNC Patient. Both FilmQA Pro and eFilmQA are recommended for radiotherapy clinics.

Dosimetric comparison of four-dimensional computed tomography based internal target volume against variations in respiratory motion during treatment between volumetric modulated arc therapy and three-dimensional conformal radiotherapy in lung stereotactic body radiotherapy

This study focused on the dosimetric impact of variations in respiratory motion during lung stereotactic body radiotherapy (SBRT). Dosimetric comparisons between volumetric modulated arc therapy (VMAT) and three-dimensional conformal radiotherapy (3DCRT) were performed using four-dimensional computed tomography (4DCT)-based internal target volumes (ITV). We created retrospective plans for ten patients with lung cancer who underwent SBRT using 3DCRT and VMAT techniques. A Delta4 Phantom + (ScandiDos, Uppsala, Sweden) was used to evaluate the dosimetric robustness of 4DCT-based ITV against variations in respiratory motion during treatment. We analyzed respiratory motion during treatment. Dose-volume histogram parameters were evaluated for the 95% dose (D95%) to the planning target volume (PTV) contoured on CT images obtained under free breathing. The correlations between patient respiratory parameters and dosimetric errors were also evaluated. In the phantom study, the average PTV D95% dose differences for all fractions were - 2.9 ± 4.4% (- 16.0 - 1.2%) and - 2.0 ± 2.8% (- 11.2 - 0.7%) for 3DCRT and VMAT, respectively. The average dose difference was < 3% for both 3DCRT and VMAT; however, in 5 out of 42 fractions in 3DCRT, the difference in PTV D95% was > 10%. Dosimetric errors were correlated with respiratory amplitude and velocity, and differences in respiratory amplitude between 4DCT and treatment days were the main factors causing dosimetric errors. The overall average dose error of the PTV D95% was small; however, both 3DCRT and VMAT cases exceeding 10% error were observed. Larger errors occurred with amplitude variation or baseline drift, indicating limited robustness of 4DCT-based ITV.

Dosimetric Evaluation of Target Motion Effects in Spot-Scanning Proton Therapy: A Phantom Study

Purpose

To evaluate intrafractional motion effects as a function of peak-to-peak motion and period during single-field, single-fraction and single-field, multifraction irradiation of the moving target in spot-scanning proton therapy.

Materials and Methods

An in-house dynamic phantom was used to simulate peak-to-peak motion of 5, 10, and 20 mm with periods of 2, 4, and 8 seconds. The dose distribution in the moving target was measured using radiochromic films. During the perpendicular motion, the film was fixed and moved perpendicular to the beam direction without changing the water equivalent thickness (WET). During longitudinal motion, the film was fixed and moved along the beam direction, causing a change in WET. Gamma index analysis was used with criteria of 3%/3 mm and 3%/2 mm to analyze the dose distributions.

Results

For single-fraction irradiation, varying the period did not result in a significant difference in any of the metrics used (P > .05), except for the local dose within the planning target volume (P < .001). In contrast, varying peak-to-peak motion was significant (P < .001) for all metrics except for the mean planning target volume dose (P ≈ .88) and the local dose (P ≈ .47). The perpendicular motion caused a greater decrease in gamma passing rate (3%/3 mm) than WET variations (65% ± 5% vs 85% ± 4%) at 20 mm peak-to-peak motion.

Conclusion

The implementation of multifraction irradiation allowed to reduce hot and cold spots but did not reduce dose blurring. The motion threshold varied from 7 to 11 mm and depended on the number of fractions, the type of motion, the acceptance criteria, and the calculation method used.

Verifying institutionally developed hybrid 3D-printed coaxial cylindrical phantom for patient-specific quality assurance in stereotactic body radiation therapy of hepatocellular carcinoma

An accurate and reliable patient-specific quality assurance (PSQA) is crucial to ensure the safety and precision of Stereotactic body radiation therapy (SBRT) in treating Hepatocellular carcinoma (HCC). This study examines the effectiveness of a novel hybrid 3D-printed hybrid coaxial cylindrical phantom for PSQA in the SBRT of HCC. The study compared three different point dose verification techniques for PSQA: a traditional solid water phantom, two dimensional detector array I'MatriXX, and a newly developed hybrid 3D-printed phantom. Thirty SBRT HCC liver cases were examined using these techniques, and point doses were measured and compared to planned doses using the perpendicular composite method with solid water and I'MatriXX phantoms. Unlike the other two methods, the point dose was compared in true composite geometry using the hybrid 3D-printed phantom, which enhanced the accuracy and consistency of PSQA. The study aims to assess the statistical significance and accuracy of the hybrid 3D-printed phantom compared to other methods. The results showed all techniques complied with the institutional threshold criteria of within ± 3% for point-dose measurement discrepancies. The hybrid 3D-printed phantom was found to have better consistency with a lower standard deviation than traditional methods. Statistical analysis using Student's t-test revealed the statistical significance of the hybrid 3D-printed phantom technique in patient-specific point-dose assessments with a p-value < 0.01. The hybrid 3D-printed phantom developed institutionally is cost-effective and easy to handle. It has been proven to be a valuable tool for PSQA in SBRT for the treatment of HCC and has demonstrated its practicality and reliability.

Comprehensive characterisation of the IBA myQA SRS for SRS and SBRT patient specific quality assurance

The myQA SRS (IBA) is a new to market 2D complementary metal oxide semiconductor detector array with an active area 140 × 120 mm2 and 0.4 mm resolution, making it a potential real-time dosimetry alternative to radiochromic film for stereotactic plan verification. Characterisation of the device was completed to assess performance. The dosimetric properties of the device were assessed for 6FF and 6FFF beams from a Varian TrueBeam STx with high definition multileaf collimator. Clinical suitability of the device for Patient Specific Quality Assurance was verified using ten SRS/SBRT plans, compared against other detectors, as well as multi leaf collimator (MLC) tests including picket fence and chair. Gamma analysis was performed using myQA software with criteria of 4%/1 mm. The device demonstrated compliance with recommended specifications for basic tests. After the required warm-up period, the maximum deviation in detector signal from initial readings was 0.2%. Short-term and long-term reproducibility was 0.1% (6FF) and 1.0% (6FFF), respectively. Dose linearity was within 0.3% (6FF) and 0.7% (6FFF) and dose-rate dependence within 1.7% (6FF) and 2.9% (6FFF) and were verified with a Farmer type ionization chamber (PTW 30013). Angular dependence was quantified for coplanar and non-coplanar situations. Output factors and beam profiles measured on the device showed agreement within 1% of baseline RAZOR diode (IBA) and CC04 ionisation chamber (IBA) measurements for field sizes 1 × 1 to 10 × 10 cm2. The minimum gamma (4%/1 mm) pass rates for MLC-pattern tests were 96.5% and 98.1% for the myQA SRS and film, respectively. The average gamma (4%/1 mm) pass rates for SBRT and SRS plans were 98.8% and 99.8% respectively. This work represents one of the first studies performed on the commissioning and performance characterisation of this novel device, demonstrating its accuracy and reliability, making it highly useful as a film alternative in stereotactic treatment plan verification.

Evaluation of a novel patient-specific quality assurance phantom for robotic single-isocentre, multiple-target stereotactic radiosurgery, and stereotactic radiotherapy

OBJECTIVES

To evaluate patient-specific quality assurance (PSQA) of 3 targets in a single delivery using a novel film-based phantom.

METHODS

The phantom was designed to rotate freely as a sphere and could measure 3 targets with film in a single delivery. After identifying the coordinates of 3 targets in the skull, the rotation angles about the equator and meridian were computed for optimal phantom setup, ensuring the film plane intersected the 3 targets. The plans were delivered on the CyberKnife system using fiducial tracking. The irradiated films were scanned and processed. All films were analysed using 3 gamma criteria.

RESULTS

Fifteen CyberKnife test plans with 3 different modalities were delivered on the phantom. Both automatic and marker-based registration methods were applied when registering the irradiated film and dose plane. Gamma analysis was performed using a 3%/1 mm, 2%/1 mm, and 1%/1 mm criteria with a 10% threshold. For the automatic registration method, the passing rates were 98.2% ± 1.9%, 94.2% ± 3.7%, and 80.9% ± 6.3%, respectively. For the marker-based registration approach, the passing rates were 96.4% ± 2.7%, 91.7% ± 4.3%, and 78.4% ± 6.2%, respectively.

CONCLUSIONS

A novel spherical phantom was evaluated for the CyberKnife system and achieved acceptable PSQA passing rates using TG218 recommendations. The phantom can measure true-composite dose and offers high-resolution results for PSQA, making it a valuable device for robotic radiosurgery.

ADVANCES IN KNOWLEDGE

This is the first study on PSQA of 3 targets concurrently on the CyberKnife system.

Plan complexity metrics for head and neck VMAT competition plans

Previous plan competitions have largely focused on dose metric assessments. However, whether the submitted plans were realistic and reasonable from a quality assurance (QA) perspective remains unclear. This study aimed to investigate the relationship between aperture-based plan complexity metrics (PCM) in volumetric modulated arc therapy (VMAT) competition plans and clinical treatment plans verified through patient-specific QA (PSQA). In addition, the association of PCMs with plan quality was examined. A head and neck (HN) plan competition was held for Japanese institutions from June 2019 to July 2019, in which 210 competition plans were submitted. Dose distribution quality was quantified based on dose-volume histogram (DVH) metrics by calculating the dose distribution plan score (DDPS). Differences in PCMs between the two VMAT treatment plan groups (HN plan competitions held in Japan and clinically accepted HN VMAT plans through PSQA) were investigated. The mean (± standard deviation) DDPS for the 98 HN competition plans was 158.5 ± 20.6 (maximum DDPS: 200). DDPS showed a weak correlation with PCMs with a maximum r of 0.45 for monitor unit (MU); its correlation with some PCMs was "very weak." Significant differences were found in some PCMs between plans with the highest 20% DDPSs and the remaining plans. The clinical VMAT and competition plans revealed similar distributions for some PCMs. Deviations in PCMs for the two groups were comparable, indicating considerable variability among planners regarding planning skills. The plan complexity for HN VMAT competition plans increased for high-quality plans, as shown by the dose distribution. Direct comparison of PCMs between competition plans and clinically accepted plans showed that the submitted HN VMAT competition plans were realistic and reasonable from the QA perspective. This evaluation may provide a set of criteria for evaluating plan quality in plan competitions.

Efficacy of flattening filter-free beams with the acuros XB algorithm in thoracic spine stereotactic body radiation therapy

This study aimed to determine the dosimetric value of flattening filter-free (FFF) beams compared to flattening filter (FF) beams using different algorithms in the treatment planning of thoracic spine stereotactic body radiation therapy (SBRT). A total of 120 plans were created for 15 patients using the Anisotropic Analytical Algorithm (AAA) and the Acuros External Beam (AXB) algorithm with FF and FFF beams at 6 MV and 10 MV energies. Various dosimetric parameters were evaluated, including target coverage, dose spillage, and organs-at-risk sparing of the spinal cord and esophagus. Treatment delivery parameters, such as the monitor units (MUs), modulation factors (MFs), beam-on time (BOT), and dose calculation time (DCT), were also collected. Significant differences were observed in the dosimetric parameters when AXB was used for all energies (P < 0.05). 6 XFFF energy was the best option for target coverage, dose spillage, and organs-at-risk sparing. In contrast, dosimetric parameters had no significant difference when using the AAA. The AAA and AXB calculations showed that the 6 XFFF beam had the shortest DCT. The treatment delivery parameters indicated that 10 XFF beam required the fewest MUs and MFs. In addition, the 10 XFFF beam demonstrated the shortest BOT. For effective treatment of the thoracic spine using SBRT, it is recommended to use the 10 XFFF beam because of the short BOT. Moreover, the AXB algorithm should be used because of its accurate dose calculation in regions with tissue heterogeneity.

Commissioning of Mobius3D/FX for patient-specific quality assurance: The CUIMC-NewYork Presbyterian Hospital experience

PURPOSE

To present the process undertaken by our institute in commissioning Mobius3D (M3D) for patient-specific quality assurance.

METHOD

168 plans were randomly selected to compare dose distribution measured with ArcCheck and dose calculated from M3D, both compared against the treatment planning system (TPS). The gamma criteria for measurement and M3D are 3%/2 mm with 10% and 50% dose thresholds, respectively. The effect of tissue inhomogeneity was investigated on 11 plans by recalculating the dose in M3D on a homogeneous phantom. Tolerance and action limits were established following the AAPM Task Group 218 recommendations.

RESULTS

The M3D showed high variability in gamma passing rate compared to the measurement. Twenty-three out of 168 plans had false negative dose comparisons. These plans fall under high tissue inhomogeneity like lung and metal implants, small field targets, and breast plans planned with high energy. One false negative case (0.6%) was observed. A single tolerance limit of 91% and 92% gamma passing rate for the M3D and measurement-based PSQA were established, respectively. Against the expectation, recalculating plans on the homogeneous phantom in M3D did not necessarily increase the gamma passing rate. These plans have a duty cycle >4.2, and the small field sizes combined with differences in slice thickness contributed to observed dose differences in the homogeneous phantom comparisons.

CONCLUSION

Following the commissioning, M3D is adopted in our institute. Currently, the gamma criteria used for measurement and M3D are 3%/2 mm, 40% dose threshold, with gamma passing rates of 92% and 95%, respectively. A higher passing rate for M3D is adopted until more data is available. The combined effect of plan modulation, the field sizes, the tissue inhomogeneity, the dose algorithm, and the volume averaging effect from differences in slice thickness can contribute to the differences in dose in M3D and TPS.

Detecting outliers beyond tolerance limits derived from statistical process control in patient-specific quality assurance

BACKGROUND

Tolerance limit is defined on pre-treatment patient specific quality assurance results to identify "out of the norm" dose discrepancy in plan. An out-of-tolerance plan during measurement can often cause treatment delays especially if replanning is required. In this study, we aim to develop an outlier detection model to identify out-of-tolerance plan early during treatment planning phase to mitigate the above-mentioned risks.

METHODS

Patient-specific quality assurance results with portal dosimetry for stereotactic body radiotherapy measured between January 2020 and December 2021 were used in this study. Data were divided into thorax and pelvis sites and gamma passing rates were recorded using 2%/2 mm, 2%/1 mm, and 1%/1 mm gamma criteria. Statistical process control method was used to determine six different site and criterion-specific tolerance and action limits. Using only the inliers identified with our determined tolerance limits, we trained three different outlier detection models using the plan complexity metrics extracted from each treatment field-robust covariance, isolation forest, and one class support vector machine. The hyperparameters were optimized using the F1-score calculated from both the inliers and validation outliers' data.

RESULTS

308 pelvis and 200 thorax fields were used in this study. The tolerance (action) limits for 2%/2 mm, 2%/1 mm, and 1%/1 mm gamma criteria in the pelvis site are 99.1% (98.1%), 95.8% (91.1%), and 91.7% (86.1%), respectively. The tolerance (action) limits in the thorax site are 99.0% (98.7%), 97.0% (96.2%), and 91.5% (87.2%). One class support vector machine performs the best among all the algorithms. The best performing model in the thorax (pelvis) site achieves a precision of 0.56 (0.54), recall of 1.0 (1.0), and F1-score of 0.72 (0.70) when using the 2%/2 mm (2%/1 mm) criterion.

CONCLUSION

The model will help the planner to identify an out-of-tolerance plan early so that they can refine the plan further during the planning stage without risking late discovery during measurement.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy

BACKGROUND

Accurate and efficient dose calculation is essential for on-line adaptive planning in proton therapy. Deep learning (DL) has shown promising dose prediction results in photon therapy. However, there is a scarcity of DL-based dose prediction methods specifically designed for proton therapy. Successful dose prediction method for proton therapy should account for more challenging dose prediction problems in pencil beam scanning proton therapy (PBSPT) due to its sensitivity to heterogeneities.

PURPOSE

To develop a DL-based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on-line adaptive proton therapy clinical decision and subsequent replanning.

METHODS

PBSPT plans of 103 prostate cancer patients (93 for training and the other 10 for independent testing) and 83 lung cancer patients (73 for training and the other 10 for independent testing) previously treated at our institution were included in the study, each with computed tomography scans (CTs), structure sets, and plan doses calculated by the in-house developed Monte-Carlo dose engine (considered as the ground truth in the model training and testing). For the ablation study, we designed three experiments corresponding to the following three methods: (1) Experiment 1, the conventional region of interest (ROI) (composed of targets and organs-at-risk [OARs]) method. (2) Experiment 2, the beam mask (generated by raytracing of proton beams) method to improve proton dose prediction. (3) Experiment 3, the sliding window method for the model to focus on local details to further improve proton dose prediction. A fully connected 3D-Unet was adopted as the backbone. Dose volume histogram (DVH) indices, 3D Gamma passing rates with a criterion of 3%/3 mm/10%, and dice coefficients for the structures enclosed by the iso-dose lines between the predicted and the ground truth doses were used as the evaluation metrics. The calculation time for each proton dose prediction was recorded to evaluate the method's efficiency.

RESULTS

Compared to the conventional ROI method, the beam mask method improved the agreement of DVH indices for both targets and OARs and the sliding window method further improved the agreement of the DVH indices (for lung cancer, CTV D98 absolute deviation: 0.74 ± 0.18 vs. 0.57 ± 0.21 vs. 0.54 ± 0.15 Gy[RBE], ROI vs. beam mask vs. sliding window methods, respectively). For the 3D Gamma passing rates in the target, OARs, and BODY (outside target and OARs), the beam mask method improved the passing rates in these regions and the sliding window method further improved them (for prostate cancer, targets: 96.93% ± 0.53% vs. 98.88% ± 0.49% vs. 99.97% ± 0.07%, BODY: 86.88% ± 0.74% vs. 93.21% ± 0.56% vs. 95.17% ± 0.59%). A similar trend was also observed for the dice coefficients. This trend was especially remarkable for relatively low prescription isodose lines (for lung cancer, 10% isodose line dice: 0.871 ± 0.027 vs. 0.911 ± 0.023 vs. 0.927 ± 0.017). The dose predictions for all the testing cases were completed within 0.25 s.

CONCLUSIONS

An accurate and efficient deep learning-augmented proton dose prediction framework has been developed for PBSPT, which can predict accurate dose distributions not only inside but also outside ROI efficiently. The framework can potentially further reduce the initial planning and adaptive replanning workload in PBSPT.

Dosimetrically motivated beam-angle optimization for non-coplanar arc radiotherapy with and without dynamic collimator rotation

BACKGROUND

Non-coplanar techniques have shown to improve the achievable dose distribution compared to standard coplanar techniques for multiple treatment sites but finding optimal beam directions is challenging. Dynamic collimator trajectory radiotherapy (colli-DTRT) is a new intensity modulated radiotherapy technique that uses non-coplanar partial arcs and dynamic collimator rotation.

PURPOSE

To solve the beam angle optimization (BAO) problem for colli-DTRT and non-coplanar VMAT (NC-VMAT) by determining the table-angle and the gantry-angle ranges of the partial arcs through iterative 4π fluence map optimization (FMO) and beam direction elimination.

METHODS

BAO considers all available beam directions sampled on a gantry-table map with the collimator angle aligned to the superior-inferior axis (colli-DTRT) or static (NC-VMAT). First, FMO is performed, and beam directions are scored based on their contributions to the objective function. The map is thresholded to remove the least contributing beam directions, and arc candidates are formed by adjacent beam directions with the same table angle. Next, FMO and arc candidate trimming, based on objective function penalty score, is performed iteratively until a desired total gantry angle range is reached. Direct aperture optimization on the final set of colli-DTRT or NC-VMAT arcs generates deliverable plans. colli-DTRT and NC-VMAT plans were created for seven clinically-motivated cases with targets in the head and neck (two cases), brain, esophagus, lung, breast, and prostate. colli-DTRT and NC-VMAT were compared to coplanar VMAT plans as well as to class-solution non-coplanar VMAT plans for the brain and head and neck cases. Dosimetric validation was performed for one colli-DTRT (head and neck) and one NC-VMAT (breast) plan using film measurements.

RESULTS

Target coverage and conformity was similar for all techniques. colli-DTRT and NC-VMAT plans had improved dosimetric performance compared to coplanar VMAT for all treatment sites except prostate where all techniques were equivalent. For the head and neck and brain cases, mean dose reduction-in percentage of the prescription dose-to parallel organs was on average 0.7% (colli-DTRT), 0.8% (NC-VMAT) and 0.4% (class-solution) compared to VMAT. The reduction in D2% for the serial organs was on average 1.7% (colli-DTRT), 2.0% (NC-VMAT) and 0.9% (class-solution). For the esophagus, lung, and breast cases, mean dose reduction to parallel organs was on average 0.2% (colli-DTRT) and 0.3% (NC-VMAT) compared to VMAT. The reduction in D2% for the serial organs was on average 1.3% (colli-DTRT) and 0.9% (NC-VMAT). Estimated delivery times for colli-DTRT and NC-VMAT were below 4 min for a full gantry angle range of 720°, including transitions between arcs, except for the brain case where multiple arcs covered the whole table angle range. These times are in the same order as the class-solution for the head and neck and brain cases. Total optimization times were 25%-107% longer for colli-DTRT, including BAO, compared to VMAT.

CONCLUSIONS

We successfully developed dosimetrically motivated BAO for colli-DTRT and NC-VMAT treatment planning. colli-DTRT and NC-VMAT are applicable to multiple treatment sites, including body sites, with beneficial or equivalent dosimetric performances compared to coplanar VMAT and reasonable delivery times.

A TPS integrated machine learning tool for predicting patient-specific quality assurance outcomes in volumetric-modulated arc therapy

PURPOSE

Machine learning (ML) models have been demonstrated to be beneficial for optimizing the workload of patient-specific quality assurance (PSQA). Implementing them in clinical routine frequently requires third-party applications beyond the treatment planning system (TPS), slowing down the workflow. To address this issue, a PSQA outcomes predictive model was carefully selected and validated before being fully integrated into the TPS.

MATERIALS AND METHODS

Nine ML algorithms were evaluated using cross-validation. The learning database was built by calculating complexity metrics (CM) and binarizing PSQA results into "pass"/"fail" classes for 1767 VMAT arcs. The predictive performance was evaluated using area under the ROC curve (AUROC), sensitivity, and specificity. The ML model was integrated into the TPS via a C# script. Script-guided reoptimization impact on PSQA and dosimetric results was evaluated on ten VMAT plans with "fail"-predicted arcs. Workload reduction potential was also assessed.

RESULTS

The selected model exhibited an AUROC of 0.88, with a sensitivity and specificity exceeding 50 % and 90 %, respectively. The script-guided reoptimization of the ten evaluated plans led to an average improvement of 1.4 ± 0.9 percentage points in PSQA results, while preserving the quality of the dose distribution. A yearly savings of about 140 h with the use of the script was estimated.

CONCLUSIONS

The proposed script is a valuable complementary tool for PSQA measurement. It was efficiently integrated into the clinical workflow to enhance PSQA outcomes and reduce PSQA workload by decreasing the risk of failing QA and thereby, the need for repeated replanning and measurements.

Is it still necessary to perform measured based pre-treatment patient-specific QA for SRS HyperArc treatments?

PURPOSE

The Mobius3D system was validated as a modern secondary check dosimetry system. In particular, our objective has been to assess the suitability of the M3D as pre-treatment patient-specific Quality Assurance (QA) tool for Stereotactic Radiosurgery (SRS) HyperArc (HA) treatments. We aimed to determine whether Mobius3D could safely replace the measurements-based patient-specific QA for this type of treatment.

METHODS

30 SRS HA treatment plans for brain were selected. The dose distributions, calculated by Mobius and our routinely used algorithm (AcurosXB v.15.6), were compared using gamma analysis index and DVH parameters based on the patient's CT dataset. All 30 plans were then delivered across the ionization chamber in a homogeneous phantom and the measured dose was compared with both M3D and TPS calculated one. The plans were delivered and verified in terms of PSQA using the electronic portal imaging device (EPID) with Portal Dosimetry (PD) and myQA SRS (IBA Dosimetry) detector. Plans that achieved a global gamma passing rate (GPR) ≥ 97% based on 2%/2 mm criteria, with both Mobius3D and the conventional methods were evaluated acceptable. Finally, we assessed the capability of the M3D system to detect errors related to the position of the Multi-Leaf Collimator (MLC) in comparison to the analyzed measurement-based systems.

RESULTS

No relevant differences were observed in the comparison between the dose calculated on the CT-dataset by M3D and the TPS. Observed discrepancies are imputable to different used algorithms, but no discrepancies related to goodness of plans have been found. Average differences between calculated (M3D and TPS) vs measured dose with ionization chamber were 2.5% (from 0.41% to 3.2%) and 1.81% (from 0.66% to 2.65%), for M3D and TPS, respectively. All plans passed with a gamma passing rate > 97% using conventional PSQA methods with a gamma criterion of 2% dose difference and 2 mm distance-to-agreement. The average gamma passing rate for the M3D system was determined to be 99.4% (from 97.3% to 100%). Results from this study also demonstrated Mobius has better error detectability than conventional measurement-based systems.

CONCLUSION

Our study shows Mobius3D could be a suitable alternative to conventional measured based QA methods for SRS HyperArc treatments.

Is it necessary to perform measurement-based patient-specific quality assurance for online adaptive radiotherapy with Elekta Unity MR-Linac?

This study aimed to investigate the necessity of measurement-based patient-specific quality assurance (PSQA) for online adaptive radiotherapy by analyzing measurement-based PSQA results and calculation-based 3D independent dose verification results with Elekta Unity MR-Linac. There are two workflows for Elekta Unity enabled in the treatment planning system: adapt to position (ATP) and adapt to shape (ATS). ATP plans are those which have relatively slighter shifts from reference plans by adjusting beam shapes or weights, whereas ATS plans are the new plans optimized from the beginning with probable re-contouring targets and organs-at-risk. PSQA gamma passing rates were measured using an MR-compatible ArcCHECK diode array for 78 reference plans and corresponding 208 adaptive plans (129 ATP plans and 79 ATS plans) of Elekta Unity. Subsequently, the relationships between ATP, or ATS plans and reference plans were evaluated separately. The Pearson's r correlation coefficients between ATP or ATS adaptive plans and corresponding reference plans were also characterized using regression analysis. Moreover, the Bland-Altman plot method was used to describe the agreement of PSQA results between ATP or ATS adaptive plans and reference plans. Additionally, Monte Carlo-based independent dose verification software ArcherQA was used to perform secondary dose check for adaptive plans. For ArcCHECK measurements, the average gamma passing rates (ArcCHECK vs. TPS) of PSQA (3%/2 mm criterion) were 99.51% ± 0.88% and 99.43% ± 0.54% for ATP and ATS plans, respectively, which were higher than the corresponding reference plans 99.34% ± 1.04% (p < 0.05) and 99.20% ± 0.71% (p < 0.05), respectively. The Pearson's r correlation coefficients were 0.720 between ATP and reference plans and 0.300 between ATS and reference plans with ArcCHECK, respectively. Furthermore, >95% of data points of differences between both ATP and ATS plans and reference plans were within ±2σ (standard deviation) of the mean difference between adaptive and reference plans with ArcCHECK measurements. With ArcherQA calculation, the average gamma passing rates (ArcherQA vs. TPS) were 98.23% ± 1.64% and 98.15% ± 1.07% for ATP and ATS adaptive plans, separately. It might be unnecessary to perform measurement-based PSQA for both ATP and ATS adaptive plans for Unity if the gamma passing rates of both measurements of corresponding reference plans and independent dose verification of adaptive plans have high gamma passing rates. Periodic machine QA and verification of adaptive plans were recommended to ensure treatment safety.

Systematic evaluation of spatial resolution and gamma criteria for quality assurance with detector arrays in stereotactic radiosurgery

PURPOSE

To characterize detector array spacing and gamma index for quality assurance (QA) of stereotactic radiosurgery (SRS) deliveries. Use the Nyquist theorem to determine the required detector spacing in SRS fields, and find optimal gamma indices to detect MLC errors using the SRS MapCHECK, ArcCHECK, and a portal imaging device (EPID).

METHODS

The required detector spacing was determined via Fourier analysis of small radiation fields and profiles of typical SRS treatment plans. The clinical impact of MLC errors of 0.5, 1, and 2 mm was evaluated. Global gamma (low-dose threshold 10%) was evaluated for the three detector systems using various combinations of the distance to agreement and the dose difference.

RESULTS

While MLC errors only slightly affected mean dose to PTV and a 2 mm thick surrounding structure (PTV_2 mm), significant PTV underdose incurred with increase in maximum dose to PTV_2 mm. Gamma indices with highest sensitivity to the introduced errors at 95% tolerance level for plans on target volumes of 3.2 cm3 (plan 3 cc) and 35.02 cm3 (plan 35 cc) were 2%/1 mm for the SRS MapCHECK and 2%/3 mm for the ArcCHECK, with 3%/1 mm (plan 3cc) and 2%/1 mm (plan 35cc) for the EPID. Drops in passing rates for a 2 mm MLC error were (46.2%, 41.6%) for the SRS MapCHECK and (12.2%, 4.2%) for the ArcCHECK for plan 3cc and plan 35cc, respectively. For Portal Dose, values were 4.5% (plan 3cc) and 7% (plan 35cc). The Nyquist frequency of two SRS dose distributions lie between 0.26  and 0.1 mm-1 , corresponding to detector spacings of 1.9 and 5 mm. Evaluation of SRS MapCHECK data with doubled detector density indicates that increased detector density may reduce the system's sensitivity to errors, necessitating a tighter gamma index.

CONCLUSIONS

The present results give insight on the performance of detector arrays and gamma indices for the investigated detectors during SRS QA.

Radiation Therapy Physics Quality Assurance and Management Practices in Low- and Middle-Income Countries: An Initial Pilot Survey in Six Countries and Validation Through a Site Visit

Purpose

Our purpose was to assess physics quality assurance (QA) practices in less resourced radiation therapy (RT) centers to improve quality of care.

Methods and Materials

A preliminary study was conducted in 2020 of 13 select RT centers in 6 countries, and in 2021, our team conducted onsite visits to all the RT centers in Ghana, one of the countries from the initial survey. The RT centers included 1 private and 2 public institutions (denoted as Public-1 and Public-2). Follow-up surveys were sent to 17 medical physicists from the site visit. Questions centered on the topics of equipment, institutional practice, physics quality assurance, management, and safety practices. Qualitative and descriptive methods were used for data analysis. Questions regarding operational challenges (machine downtime, patient-related issues, power outages, and staffing) were asked on a 5-point Likert scale.

Results

The preliminary survey from 2020 had a 92% response rate. One key result showed that for RT centers in lower gross national income per capita countries there was a direct correlation between QA needs and the gross national income per capita of the country. The needs identified included film/array detectors, independent dose calculation software, calibration of ion chambers, diodes, thermoluminiscence diodes (TLDs), phantoms for verification, Treatment Planning System (TPS) test phantoms, imaging test phantoms and film dosimeters, education, and training. For the post survey after the site visit in 2021, we received a 100% response rate. The private and the Public-1 institutions each have computed tomography simulators located in their RT center. The average daily patient external beam workload for each clinic on a linear accelerator was: private = 25, Public-1 = 55, Public-2 = 40. The Co-60 workload was: Public-1 = 45, Public-2 = 25 (there was no Co-60 at the private hospital). Public-1 and -2 lacked the equipment necessary to conform to best practices in Task Group reports (TG) 142 and 198. Public-2 reported significant operational challenges. Notably, Public-1 and -2 have peer review chart rounds, which are attended by clinical oncologists, medical physicists, physicians, and physics trainees. All 17 physicists who responded to the post site visit survey indicated they had a system of documenting, tracking, and trending patient-related safety incidents, but only 1 physicist reported using International Atomic Energy Agency Safety in Radiation Oncology.

Conclusions

The preliminary study showed a direct correlation between QA needs and the development index of a country, and the follow-up survey examines operational and physics QA practices in the RT clinics in Ghana, one of the initial countries surveyed. This will form the basis of a planned continent-wide survey in Africa intended to spotlight QA practices in low- and middle-income countries, the challenges faced, and lessons learned to help understand the gaps and needs to support local physics QA and management programs. Audits during the site visit show education and training remain the most important needs in operating successful QA programs.

Application and Challenges of Statistical Process Control in Radiation Therapy Quality Assurance

Quality assurance (QA) is important for ensuring precision in radiation therapy. The complexity and resource-intensive nature of QA has increased with the continual evolution of equipment and techniques. An effective approach is to improve the process control technology and resource optimization. Statistical process control is an economical and efficient tool that has been widely used to monitor, control, and improve quality management processes and is now being increasingly used for radiation therapy QA. This article reviews the development and methodology of statistical process control technology, evaluates its suitability in radiation therapy QA practices, and assesses its importance and challenges in optimizing radiation therapy QA processes.

A feasibility study to predict 3D dose delivery accuracy for IMRT using DenseNet with log files

OBJECTIVE

This study aims to explore the feasibility of DenseNet in the establishment of a three-dimensional (3D) gamma prediction model of IMRT based on the actual parameters recorded in the log files during delivery.

METHODS

A total of 55 IMRT plans (including 367 fields) were randomly selected. The gamma analysis was performed using gamma criteria of 3% /3 mm (Dose Difference/Distance to Agreement), 3% /2 mm, 2% /3 mm, and 2% /2 mm with a 10% dose threshold. In addition, the log files that recorded the gantry angle, monitor units (MU), multi-leaf collimator (MLC), and jaws position during delivery were collected. These log files were then converted to MU-weighted fluence maps as the input of DenseNet, gamma passing rates (GPRs) under four different gamma criteria as the output, and mean square errors (MSEs) as the loss function of this model.

RESULTS

Under different gamma criteria, the accuracy of a 3D GPR prediction model decreased with the implementation of stricter gamma criteria. In the test set, the mean absolute error (MAE) of the prediction model under the gamma criteria of 3% /3 mm, 2% /3 mm, 3% /2 mm, and 2% /2 mm was 1.41, 1.44, 3.29, and 3.54, respectively; the root mean square error (RMSE) was 1.91, 1.85, 4.27, and 4.40, respectively; the Sr was 0.487, 0.554, 0.573, and 0.506, respectively. There was a correlation between predicted and measured GPRs (P < 0.01). Additionally, there was no significant difference in the accuracy between the validation set and the test set. The accuracy in the high GPR group was high, and the MAE in the high GPR group was smaller than that in the low GPR group under four different gamma criteria.

CONCLUSIONS

In this study, a 3D GPR prediction model of patient-specific QA using DenseNet was established based on log files. As an auxiliary tool for 3D dose verification in IMRT, this model is expected to improve the accuracy and efficiency of dose validation.

Impact of 1.5 T Magnetic Field on Treatment Plan Quality in MR-Guided Radiotherapy: Typical Phantom Test Cases

PURPOSE

This study aims to investigate the influence of the magnetic field on treatment plan quality using typical phantom test cases, which encompass a circle target test case, AAPM TG119 test cases (prostate, head-and-neck, C-shape, multi-target test cases), and a lung test case.

MATERIALS AND METHODS

For the typical phantom test cases, two plans were formulated. The first plan underwent optimization in the presence of a 1.5 Tesla magnetic field (1.5 T plan). The second plan was re-optimized without a magnetic field (0 T plan), utilizing the same optimization conditions as the first plan. The two plans were compared based on various parameters, including con-formity index (CI), homogeneity index (HI), fit index (FI) and dose coverage of the planning target volume (PTV), dose delivered to organs at risk (OARs) and normal tissue (NT), monitor unit (MU). A plan-quality metric (PQM) scoring procedure was employed. For the 1.5 T plans, dose verifications were performed using an MR-compatible ArcCHECK phantom.

RESULTS

A smaller dose influence of the magnetic field was found for the circle target, prostate, head-and-neck, and C-shape test cases, compared with the multi-target and lung test cases. In the multi-target test case, the significant dose influence was on the inferior PTV, followed by the superior PTV. There was a relatively large dose influence on the PTV and OARs for lung test case. No statistically significant differences in PQM and MUs were observed. For the 1.5 T plans, gamma passing rates were all higher than 95% with criteria of 2 mm/3% and 2 mm/2%.

CONCLUSION

The presence of a 1.5 T magnetic field had a relatively large impact on dose parameters in the multi-target and lung test cases compared with other test cases. However, there were no significant influences on the plan-quality metric, MU and dose accuracy for all test cases.

Unbiased evaluation of predicted gamma passing rate by an event-mixing technique

BACKGROUND

Predicting models of the gamma passing rate (GPR) have been studied to substitute the measurement-based gamma analysis. Since these studies used data from different radiotherapy systems comprising TPS, linear accelerator, and detector array, it has been difficult to compare the performances of the predicting models among institutions with different radiotherapy systems.

PURPOSE

We aimed to develop unbiased scoring methods to evaluate the performance of the models predicting the GPR, by introducing both best and worst limits for the performance of the GPR prediction.

METHODS

Two hundred head-and-neck VMAT plans were used to develop a framework. The GPRs were measured using the ArcCHECK device. The predicted GPR [p] was generated using a deep learning-based model [pDL ]. The predicting model was evaluated using four metrics: standard deviation (SD) [σ], Pearson's correlation coefficient (CC) [r], mean squared error (MSE) [s], and mean absolute error (MAE) [a]. The best limit [σ m ${\sigma _m}$ ,r m ${r_m}$ ,s m ${s_m}$ , anda m ${a_m}$ ] was estimated by measuring the SD of measured GPR [m] by shifting the device along the longitudinal direction to measure different sampling points. Mimicked best and worst p's [pbest and pworst ] were generated from pDL . The worst limit was defined such that m and p have no correlation [CC ∼ 0]. The worst limit [σMix , rMix , sMix , and aMix ] was generated using the event-mixing (EM) technique originally introduced in high-energy physics experiments. The range of σ, r, s, and a was defined to be[ σ m , σ Mix ] $[ {{\sigma _m},{\sigma _{{\mathrm{Mix}}}}} ]$ ,[ 0 , r m ] $[ {0,{r_m}} ]$ ,[ s m , s Mix ] $[ {{s_m},{s_{{\mathrm{Mix}}}}} ]$ , and[ a m , a Mix ] $[ {{a_m},{a_{{\mathrm{Mix}}}}} ]$ . The achievement score (AS) independently based on σ, r, s, and a were calculated for pDL , pbest and pworst . The probability that p fails the gamma analysis (alert frequency; AF) was estimated as a function ofσ d ${\sigma _d}$ values within the [σ m ${\sigma _m}$ , σMix ] range for the 3%/2 mm data with a 95% criterion.

RESULTS

SDs of the best limit were well reproduced byσ m = 0.531 100 - m ${\sigma _m} = \;0.531\sqrt {100 - m} $ . The EM technique successfully generated the( m , p ) $( {m,p} )$ pairs with no correlation. The AS using four metrics showed good agreement. This agreement indicates successful definitions of both best and worst limits, consistent definitions of the AS, and successful generations of mixed events. The AF for the DL-based model with the 3%/2 mm tolerance was 31.5% and 63.0% with CL's 99% and 99.9%, respectively.

CONCLUSION

We developed the AS to evaluate the predicting model of the GPR in an unbiased manner by excluding the effects of the precision of the radiotherapy system and the spreading of the GPR. The best and worst limits of the GPR prediction were successfully generated using the measured precision of the GPR and the EM technique, respectively. The AS andσ p ${\sigma _p}$ are expected to enable objective evaluation of the predicting model and setting exact achievement goal of precision for the predicted GPR.

Machine learning-based ensemble prediction model for the gamma passing rate of VMAT-SBRT plan

PURPOSE

The purpose of this study was to accurately predict or classify the beam GPR with an ensemble model by using machine learning for SBRT(VMAT) plans.

METHODS

A total of 128 SBRT VMAT plans with 330 arc beams were retrospectively selected, and 216 radiomics and 34 plan complexity features were calculated for each arc beam. Three models for GPR prediction and classification using support vector machine algorithm were as follows: (1) plan complexity feature-based model (plan model); (2) radiomics feature-based model (radiomics model); and (3) an ensemble model combining the two models (ensemble model). The prediction performance was evaluated by calculating the mean absolute error (MAE), root mean square error (RMSE), and Spearman's correlation coefficient (SC), and the classification performance was measured by calculating the area under the receiver operating characteristic curve (AUC), accuracy, specificity, and sensitivity.

RESULTS

The MAE, RMSE and SC at the 2 %/2 mm gamma criterion in the test dataset were 1.4 %, 2.57 %, and 0.563, respectively, for the plan model; 1.42 %, and 2.51 %, and 0.508, respectively, for the radiomics model; and 1.33 %, 2.49 %, and 0.611, respectively, for the ensemble model. The accuracy, specificity, sensitivity, and AUC at the 2 %/2 mm gamma criterion in the test dataset were 0.807, 0.824, 0.681, and 0.854, respectively, for the plan model; 0.860, 0.893, 0.624, and 0.877, respectively, for the radiomics model; and 0.852, 0.871, 0.710, and 0.896, respectively, for the ensemble model.

CONCLUSIONS

The ensemble model can improve the prediction and classification performance for the GPR of SBRT (VMAT).

Predicting the error magnitude in patient-specific QA during radiotherapy based on ResNet

BACKGROUND

The error magnitude is closely related to patient-specific dosimetry and plays an important role in evaluating the delivery of the radiotherapy plan in QA. No previous study has investigated the feasibility of deep learning to predict error magnitude.

OBJECTIVE

The purpose of this study was to predict the error magnitude of different delivery error types in radiotherapy based on ResNet.

METHODS

A total of 34 chest cancer plans (172 fields) of intensity-modulated radiation therapy (IMRT) from Eclipse were selected, of which 30 plans (151 fields) were used for model training and validation, and 4 plans including 21 fields were used for external testing. The collimator misalignment (COLL), monitor unit variation (MU), random multi-leaf collimator shift (MLCR), and systematic MLC shift (MLCS) were introduced. These dose distributions of portal dose predictions for the original plans were defined as the reference dose distribution (RDD), while those for the error-introduced plans were defined as the error-introduced dose distribution (EDD). Different inputs were used in the ResNet for predicting the error magnitude.

RESULTS

In the test set, the accuracy of error type prediction based on the dose difference, gamma distribution, and RDD + EDD was 98.36%, 98.91%, and 100%, respectively; the root mean squared error (RMSE) was 1.45-1.54, 0.58-0.90, 0.32-0.36, and 0.15-0.24; the mean absolute error (MAE) was 1.06-1.18, 0.32-0.78, 0.25-0.27, and 0.11-0.18, respectively, for COLL, MU, MLCR and MLCS.

CONCLUSIONS

In this study, error magnitude prediction models with dose difference, gamma distribution, and RDD + EDD are established based on ResNet. The accurate prediction of the error magnitude under different error types can provide reference for error analysis in patient-specific QA.

Multileaf Collimator Modeling and Commissioning for Complex Radiation Treatment Plans Using 2-Dimensional (2D) Diode Array MapCHECK2

Purpose: This study aims to develop a data-collecting package ExpressMLC and investigate the applicability of MapCHECK2 for multileaf collimator (MLC) modeling and commissioning for complex radiation treatment plans. Materials and methods: The MLC model incorporates realistic parameters to account for sophisticated MLC features. A set of 8 single-beam plans, denoted by ExpressMLC, is created for the determination of parameters. For the commissioning of the MLC model, 4 intensity modulated radiation therapy (IMRT) plans specified by the AAPM TG 119 report were transferred to a computed tomography study of MapCHECK2, recalculated, and compared to measurements on a Varian accelerator. Both per-beam and composite-beam dose verification were conducted. Results: Through sufficient characterization of the MLC model, under 3%/2 mm and 2%/2 mm criteria, MapCHECK2 can be used to accurately verify per beam dose with gamma passing rate better than 90.9% and 89.3%, respectively, while the Gafchromic EBT3 films can achieve gamma passing rate better than 89.3% and 85.7%, respectively. Under the same criteria, MapCHECK2 can achieve composite beam dose verification with a gamma passing rate better than 95.9% and 90.3%, while the Gafchromic EBT3 films can achieve a gamma passing rate better than 96.1% and 91.8%; the p-value from the Mann Whitney test between gamma passing rates of the per beam dose verification using full MapCHECK2 package calibrated MLC model and film calibrated MLC model is .44 and .47, respectively; the p-value between those of the true composite beam dose verification is .62 and .36, respectively. Conclusion: It is confirmed that the 2-dimensional (2D) diode array MapCHECK2 can be used for data collection for MLC modeling with the combination of the ExpressMLC package of plans, whose doses are sufficient for the determination of MLC parameters. It could be a fitting alternative to films to boost the efficiency of MLC modeling and commissioning without sacrificing accuracy.

Early results of a remote dosimetry audit program for lung stereotactic body radiation therapy

Background and purpose

A dosimetry audit program based on alanine electron paramagnetic resonance (EPR) and radiochromic film dosimetry, may be a valuable tool for monitoring and improving the quality of lung stereotactic body radiotherapy (SBRT). The aim of this study was to report the initial, independent assessment of the dosimetric accuracy for lung SBRT practice using these dosimeters in combination with a novel phantom design.

Materials and Methods

The audit service was a remote audit program performed on a commercial lung phantom preloaded with film and alanine detectors. An alanine pellet was placed in the centre of the target simulated using silicone in a 3D-printed mould. Large film detectors were placed coronally through the target and the lung/tissue interface and analysed using gamma analysis. The beam output was always checked on the same day with alanine dosimetry in water. We audited 29 plans from 14 centres up to now.

Results

For the alanine results 28/29 plans were within 5 % with 19/29 plans being within 3 %. The passing rates were > 95 % for the film through the target for 27/29 plans and 17/29 plans for the film at the lung/tissue interface. For three plans the passing rate was < 90 % for the film on top of the lungs.

Conclusions

The preliminary results were very satisfactory for both detectors. The high passing rates for the film in the interface region indicate good performance of the treatment planning systems. The phantom design was robust and performed well on several treatment systems.

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

PURPOSE

We sought to develop machine learning models to predict the results of patient-specific quality assurance (QA) for volumetric modulated arc therapy (VMAT), which were represented by several dose-evaluation metrics-including the gamma passing rates (GPRs)-and criteria based on the radiomic features of 3D dose distribution in a phantom.

METHODS

A total of 4,250 radiomic features of 3D dose distribution in a cylindrical dummy phantom for 140 arcs from 106 clinical VMAT plans were extracted. We obtained the following dose-evaluation metrics: GPRs with global and local normalization, the dose difference (DD) in 1% and 2% passing rates (DD1% and DD2%) for 10% and 50% dose threshold, and the distance-to-agreement in 1-mm and 2-mm passing rates (DTA1 mm and DTA2 mm) for 0.5%/mm and 1.0%.mm dose gradient threshold determined by measurement using a diode array in patient-specific QA. The machine learning regression models for predicting the values of the dose-evaluation metrics using the radiomic features were developed based on the elastic net (EN) and extra trees (ET) models. The feature selection and tuning of hyperparameters were performed with nested cross-validation in which four-fold cross-validation is used within the inner loop, and the performance of each model was evaluated in terms of the root mean square error (RMSE), the mean absolute error (MAE), and Spearman's rank correlation coefficient.

RESULTS

The RMSE and MAE for the developed machine learning models ranged from <1% to nearly <10% depending on the dose-evaluation metric, the criteria, and dose and dose gradient thresholds used for both machine learning models. It was advantageous to focus on high dose region for predicating global GPR, DDs, and DTAs. For certain metrics and criteria, it was possible to create models applicable for patients' heterogeneity by training only with dose distributions in phantom.

CONCLUSIONS

The developed machine learning models showed high performance for predicting dose-evaluation metrics especially for high dose region depending on the metric and criteria. Our results demonstrate that the radiomic features of dose distribution can be considered good indicators of the plan complexity and useful in predicting measured dose evaluation metrics.

The Quality Assurance of a 1.5 T MR-Linac

The recent introduction of a commercial 1.5 T MR-linac system has considerably improved the image quality of the patient acquired in the treatment unit as well as enabling online adaptive radiation therapy (oART) treatment strategies. Quality Assurance (QA) of this new technology requires new methodology that allows for the high field MR in a linac environment. The presence of the magnetic field requires special attention to the phantoms, detectors, and tools to perform QA. Due to the design of the system, the integrated megavoltage imager (MVI) is essential for radiation beam calibrations and QA. Additionally, the alignment between the MR image system and the radiation isocenter must be checked. The MR-linac system has vendor-supplied phantoms for calibration and QA tests. However, users have developed their own routine QA systems to independently check that the machine is performing as required, as to ensure we are able to deliver the intended dose with sufficient certainty. The aim of this work is therefore to review the MR-linac specific QA procedures reported in the literature.

Efficacy of the collapsed cone algorithm calculated radiotherapy plans in intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT): A comparative dosimetric study in tumors of thorax

AIM

In this study, efficacy of collapsed cone algorithm-generated intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) were evaluated for treatment of thoracic esophageal cancer.

MATERIALS AND METHODS

Ten previously treated patients with VMAT were considered for evaluation. The planning parameters were evaluated in terms of max dose, mean dose, Homogeneity Index, Conformity Index for planning target volume, and organ at risk doses. Total monitor unit, treatment time, and gamma passing index were also reported.

RESULTS

The target dose coverage of the VMAT and IMRT plans achieved the clinical dosimetric criteria for all ten patients in the evaluation. Under the condition of equivalent target dose distribution, the VMAT plan's Conformity Index, monitor unit, treatment time, and gamma passing index rate were superior than in the IMRT plan, and the result was statistically significant.

CONCLUSION

Collapsed cone algorithm-based VMAT can have a more effective and better approach for esophageal cancer than IMRT.

Impact of ovary-sparing treatment planning on plan quality, treatment time and gamma passing rates in intensity-modulated radiotherapy for stage I/II cervical cancer

BACKGROUND

This study aimed to investigate the impact of ovary-sparing intensity-modulated radiotherapy (IMRT) on plan quality, treatment time, and gamma passing rates for stage I/II cervical cancer patients.

METHODS

Fifteen stage I/II cervical cancer patients were retrospectively enrolled, and a pair of clinically suitable IMRT plans were designed for each patient, with (Group A) and without (Group B) ovary-sparing. Plan factors affecting plan quality, treatment time, and gamma passing rates, including the number of segments, monitor units, percentage of small-area segments (field area < 20 cm2), and percentage of small-MU segments (MU < 10), were compared and statistically analyzed. Key plan quality indicators, including ovarian dose, target dose coverage (D98%, D95%, D50%, D2%), conformity index, and homogeneity index, were evaluated and statistically assessed. Treatment time and gamma passing rates collected by IBA MatriXX were also compared.

RESULTS

The median ovarian dose in Group A and Group B was 7.61 Gy (range 6.71-8.51 Gy) and 38.52 Gy (range 29.84-43.82 Gy), respectively. Except for monitor units, all other plan factors were significantly lower in Group A than in Group B (all P < .05). Correlation coefficients between plan factors, treatment time, and gamma passing rates that were statistically different were all negative. Both Groups of plans met the prescription requirement (D95% ≥ 45.00 Gy) for clinical treatment. D98% was smaller for Group A than for Group B (P < .05); D50% and D2% were larger for Group A than for Group B (P < .05, P < .05). Group A plans had worse conformity index and homogeneity index than Group B plans (P < .05, P < .05). Treatment time did not differ significantly (P > .05). Gamma passing rates in Group A were higher than in Group B with the criteria of 2%/3 mm (P < .05) and 3%/2 mm (P < .05).

CONCLUSION

Despite the slightly decreased quality of the treatment plans, the ovary-sparing IMRT plans exhibited several advantages including lower ovarian dose and plan complexity, improved gamma passing rates, and a negligible impact on treatment time.

Analysis of dose distribution reproducibility based on a fluence map of in vivo transit dose using an electronic portal imaging device

Morphological changes can affect distribution of dose in patients. Determination of the dose distribution changes for each fraction radiotherapy can be done by relativein vivodosimetry (IVD). This study analysed the distribution of doses per fraction based on the fluence map recorded by the electronic portal imaging device (EPID) of the patient's transit dose. This research examined cases involving the cervix, breast, and nasopharynx. Transit dose analysis was performed by calculating the gamma index (GI) with composite and field-by-field methods. The gamma passing rate (GPR) value was assessed for its correlation with the subject's body weight. In the case of the nasopharynx, breast, and cervix, the GPR value decreased as the fraction increased. In the case of the nasopharynx, the correlation between the GPR and fraction radiotherapy showed no difference when using either composite or field-by-field methods. However, in cases involving the cervix and breast, there was a difference in the correlation values between the composite and field-by-field methods, where the subject had a significant correlation (p< 0.05) when it was done using a field-by-field method. In addition, the nasopharynx had the highest number of subjects with significant correlation (p< 0.05) between GPR and body weight, followed by the cervix and breast. In the nasopharynx, breast, and cervix, the reproducibility of the dose distribution decreased. This decreased reproducibility was associated with changes in body weight.

Patient specific quality assurance of volumetric modulated arc therapy of synchronous bilateral breast cancer

Synchronous bilateral breast cancers (SBBC) present a considerable issue in external beam radiotherapy because of large fields size and large target volumes. Mono-isocentric volumetric modulated arc therapy (VMAT) appears as an appropriate irradiation technique for these types of tumors. The aim of this study was to demonstrate the utility of a 3D DVH pretreatment quality assurance program in VMAT of SBBC cases. Twenty SBBC patients who underwent radiation therapy in our department were retrospectively enrolled in this study. Fifteen patients were treated exclusively to the mammary glands. Five patients benefited from a dose boost on the tumor bed (60Gy). Nine patients were irradiated on the supraclavicular nodes (50Gy). This dose was delivered in 25 fractions and integrated boost was used when appropriate. Depending on the complexity of the treatment plans; 2 or 4 arcs VMAT plans were used in a mono-isocentric technique. The patient specific quality assurance (PSQA) was evaluated using COMPASS measured data, COMPASS reconstructed (CR) and COMPASS computed (CC) dose compared to treatment planning system (TPS) dose. Clinical evaluation was based on DVH metrics for target volumes and organ at risks. The maximum average dose deviation between TPS, CC, and CR was below 3%. The paired t-test between TPS, CC, and CR shows a strong agreement (p < 0.001). The 3DVH dose distribution comparison between TPS and COMPASS were also performed with good gamma score for global analysis. COMPASS was successfully evaluated as a 3DVH pretreatment system for SBBC despite the large fields size and complex target volumes. It allows the verification of the plan in 3D patient anatomy and the evaluation of dose discrepancies.

Evaluation of complexity and deliverability of IMRT treatment plans for breast cancer

This study aimed to predict the outcome of patient specific quality assurance (PSQA) in IMRT for breast cancer using complexity metrics, such as MU factor, MAD, CAS, MCS. Several breast cancer plans were considered, including LBCS, RBCS, LBCM, RBCM, left breast, right breast and the whole breast for both Edge and TrueBeam LINACS. Dose verification was completed by Portal Dosimetry (PD). The receiver operating characteristic (ROC) curve was employed to determine whether the treatment plans pass or failed. The area under the curve (AUC) was used to assess the classification performance. The correlation of PSQA and complexity metrics was examined using Spearman's rank correlation coefficient (Rs). For LINACS, the most suitable complexity metric was found to be the MU factor (Edge Rs = - 0.608, p < 0.01; TrueBeam Rs = - 0.739, p < 0.01). Regarding the specific breast cancer categories, the optimal complexity metrics were as follows: MAD (AUC = 0.917) for LBCS, MCS (AUC = 0.681) for RBCS, MU factor (AUC = 0.854) for LBCM and MAD (AUC = 0.731) for RBCM. On the Edge LINAC, the preferable method for breast cancers was MCS (left breast, AUC = 0.938; right breast, AUC = 0.813), while on the TrueBeam LINAC, it became MU factor (left breast, AUC = 0.950) and MCS (right breast, AUC = 0.806), respectively. Overall, there was no universally suitable complexity metric for all types of breast cancers. The choice of complexity metric depended on different cancer types, locations and treatment LINACs. Therefore, when utilizing complexity metrics to predict PSQA outcomes in IMRT for breast cancer, it was essential to select the appropriate metric based on the specific circumstances and characteristics of the treatment.

Sensitivity and specificity of secondary dose calculation for head and neck treatment plans

PURPOSE

Secondary dose calculation (SDC) with an independent algorithm is one option to perform plan-specific quality assurance (QA). While measurement-based QA can potentially detect errors in plan delivery, the dose values are typically only compared to calculations on homogeneous phantom geometries instead of patient CT data. We analyzed the sensitivity and specificity of an SDC software by purposely introducing different errors and determined thresholds for optimal decisions.

METHODS

Thirty head and neck VMAT plans and 30 modifications of those plans, including errors related to density and beam modelling, were recalculated using RadCalc with a Monte Carlo algorithm. Decision thresholds were obtained by receiver operating characteristics (ROC) analysis. For comparison, measurement-based QA using the ArcCHECK phantom was carried out and evaluated in the same way.

RESULTS

Despite optimized decision thresholds, none of the systems was able to reliably detect all errors. ArcCHECK analysis using a 2%/2 mm criterion with a threshold of 91.1% had an area under the curve (AUC) of 0.80. Evaluating differences in recalculated and planned DVH parameter of the target structures in RadCalc with a 2% threshold an AUC of 0.86 was achieved. Out-of-field deviations could be attributed to weaknesses in the beam model.

CONCLUSIONS

Secondary dose calculation with RadCalc is an alternative to established measurement-based phantom QA. Different tools catch different errors; therefore, a combination of approaches should be preferred.

Quality assurance for mixed electron-photon beam radiation therapy using treatment log files and MapCHECK

BACKGROUND

Mixed photon-electron beam radiotherapy (MBRT) is a technique that combines the use of both photons and electrons in one single treatment plan to exploit their advantageous and complimentary characteristics. Compared to other photon treatment modalities, it has been shown that the MBRT technique contributes to better target coverage and organ-at-risk (OAR) sparing. However, the use of combined photons and electrons in one delivery makes the technique more complex and a well-established quality assurance (QA) protocol for MBRT is essential.

PURPOSE

To investigate the feasibility of using MapCHECK and log file-dose reconstruction for MBRT plan verification and to recommend a patient-specific quality assurance (PSQA) protocol for MBRT.

METHODS

MBRT plans were robustly optimized for five soft-tissue sarcoma (STS) patients. Each plan comprised step-and-shoot deliveries of a six MV photon beam and a combination of five electron beam energies at an SAD of 100 cm. The plans were delivered to the MapCHECK device with collapsed gantry angle and the 2D dose distributions at the detector depth were measured. To simulate the expected dose distribution delivered to the MapCHECK, a MapCHECK computational phantom was modeled in EGSnrc based on vendor-supplied blueprint information. The dose to the detectors in the model was scored using the DOSXYZnrc user code. The agreement between the measured and the simulated dose distribution was evaluated using 2D gamma analysis with a gamma criterion of 3%/2 mm and a low dose threshold of 10%. One of the plans was selected and delivered with a rotating gantry angle for trajectory log file collection. To evaluate the potential interlinac and intralinac differences, the plan was delivered repeatedly on three linacs. From the collected log files, delivery parameters were retrieved to recalculate the 3D dose distributions in the patient's anatomy with DOSXYZnrc. The recalculated mean dose to the clinical target volume (CTV) and OARs from all deliveries were computed and compared with the planned dose in terms of percentage difference. To validate the accuracy of log file-based QA, the log file-recalculated dose was also compared with film measurement.

RESULTS

The agreement of the total dose distribution between the MapCHECK measurement and simulation showed gamma passing rates of above 97% for all five MBRT plans. In the log file-dose recalculation, the difference between the recalculated and the planned dose to the CTV and OARs was below 1% for all deliveries. No significant inter- or intralinac differences were observed. The log file-dose had a gamma passing rate of 98.6% compared to film measurement.

CONCLUSION

Both the MapCHECK measurements and log file-dose recalculations showed excellent agreement with the expected dose distribution. This study demonstrates the potential of using MapCHECK and log files as MBRT QA tools.

Particular issues to be considered in small field dosimetry for TrueBeam STx commissioning

This study aims to report the relevant issues concerning small fields in the commissioning of a TrueBeam STx for photon energies of 6MV, 10MV, 6FFF, and 10FFF. Percent depth doses, profiles, and field output factors were measured according to the beam model configuration of the treatment planning system. Multiple detectors were used based on the IAEA TRS-483 protocol as well as EBT3 radiochromic film. Analytical Anisotropic and Acuros XB algorithms, were configured and validated through basic dosimetry comparisons and end-to-end clinical tests.

Viability of the virtual cone technique using a fixed small multi-leaf collimator field for stereotactic radiosurgery of trigeminal neuralgia

Dosimetric uncertainties in very small (≤1.5 × 1.5 cm2 ) photon fields are remarkably higher, which undermines the validity of the virtual cone (VC) technique with a diminutive and variable MLC fields. We evaluate the accuracy and reproducibility of the VC method with a very small, fixed MLC field setting, called a fixed virtual cone (fVC), for small target radiosurgery such as trigeminal neuralgia (TGN). The fVC is characterized by 0.5 cm x 0.5 cm high-definition (HD) MLC field of 10MV FFF beam defined at 100 cm SAD, while backup jaws are positioned at 1.5 cm x 1.5 cm. A spherical dose distribution equivalent to 5 mm (diameter) physical cone was generated using 10-14 non-coplanar, partial arcs. Dosimetric accuracy was validated using SRS diode (PTW 60018), SRS MapCHECK (SNC) measurements. As a quality assurance measure, 10 treatment plans (SRS) for TGN, consisting of various arc ranges at different collimator angles were analyzed using 6 MV FFF and 10 MV FFF beams, including a field-by-field study (n = 130 fields). Dose outputs were compared between the Eclipse TPS and measurements (SRS MapCHECK). Moreover, dosimetric changes in the field defining fVC, prompted by a minute (± 0.5-1.0 mm) leaf shift, was examined among TPS, diode measurements, and Monte Carlo (MC) simulations. The beam model for fVC was validated (≤3% difference) using SRS MapCHECK based absolute dose measurements. The equivalent diameters of the 50% isodose distribution were found comparable to that of a 5 mm cone. Additionally, the comparison of field output factors, dose per MU between the TPS and SRS diode measurements using the fVC field, including ± 1 mm leaf shift, yielded average discrepancies within 5.5% and 3.5% for 6 MV FFF and 10 MV FFF beams, respectively. Overall, the fVC method is a credible alternative to the physical cone (5 mm) that can be applied in routine radiosurgical treatment of TGN.

Simulation of consequences of using nonideal detectors during beam data commissioning measurements

BACKGROUND

Beam data commissioning is a core task of radiotherapy physicists. Despite multiple detectors available, a feasible measurement program compromises between detector properties and time constraints. Therefore, it is important to understand how nonideal measurement data propagates into patient dose calculation.

PURPOSE

We simulated the effects of realistic errors, due to beam commissioning with presumably nonoptimal detectors, on the resulting patient dose distributions. Additionally, the detectability of such beam commissioning errors during patient plan quality assurance (QA) was evaluated.

METHODS

A clinically used beam model was re-commissioned introducing changes to depth dose curves, output factors, profiles or combinations of those. Seventeen altered beam models with incremental changes of the modelling parameters were created to analyze dose changes on simplified anatomical phantoms. Additionally, fourteen altered models incorporate changes in the order of signal differences reported for typically used detectors. Eighteen treatment plans of different types were recalculated on patient CT data sets using the altered beam models.

RESULTS

For the majority of clinical plans, dose distributions in the target volume recalculated on the patient computed tomography data were similar between the original and the modified beam models, yielding global 2%/2 mm gamma pass rates above 98.9%. Larger changes were observed for certain combinations of beam modelling errors and anatomical sites, most extreme for output factor changes in a small target volume plan with a pass rate of 80.6%. Modelling an enlarged penumbra as if measured with a 0.125 cm3 ion chamber had the largest effect on the dose distribution (average pass rate of 96.5%, lowest 85.4%). On different QA phantom geometries, dose distributions between calculations with modified and unmodified models typically changed too little to be detected in actual measurements.

CONCLUSION

While the simulated errors during beam modelling had little effect on most plans, in some cases changes were considerable. High-quality penumbra and small field output factor should be a main focus of commissioning measurements. Detecting modelling issues using standard patient QA phantoms is unlikely. Verification of a beam model should be performed especially for plans with high modulation and in different depths or geometries representing the variety of situations expected clinically.

Results of the IAEA supported national end-to-end audit of the IMRT technique in Poland

The dosimetry audit services were established in Poland in 1991, since then new audits have been introduced. The recently developed IAEA audit methodology for IMRT H&N treatments was tested nationally. Anthropomorphic SHANE phantom (CIRS) was used to perform measurements in 8 hospitals which voluntarily participated in the study. Each participant had to complete successfully pre-visit activities to take part in an onsite visit. During the visit, auditors together with the local staff, did a CT scan using local protocol, recalculated the plan and verified all the relevant parameters and performed measurements with an ionization chamber and films in SHANE. The adoption of IAEA methodology to the national circumstances was done with no major issues. Participants plans were verified and the results of ionization chamber were all within the 5 % tolerance limit for PTV (max 4,5%) and 7 % for OAR (max 5,3%). Film global gamma results (3 %, 3 mm, 90 % acceptance limit) were within 91,5-99,7% range. The IAEA established acceptance criteria which were achievable for most tests except for CTtoRED conversion curve. The locally performed study allowed establishing new limits. The audit gave interesting results and showed that the procedure is very thorough and capable to identify issues related with suboptimal treatment preparation and delivery. The new limits for CTtoRED conversion curve were adopted for national study. Such an audit gives an opportunity to verify the quality of locally implemented procedures and should be available for Polish hospitals on a daily basis.

Pretreatment patient-specific quality assurance prediction based on 1D complexity metrics and 3D planning dose: classification, gamma passing rates, and DVH metrics

PURPOSE

Highly modulated radiotherapy plans aim to achieve target conformality and spare organs at risk, but the high complexity of the plan may increase the uncertainty of treatment. Thus, patient-specific quality assurance (PSQA) plays a crucial role in ensuring treatment accuracy and providing clinical guidance. This study aims to propose a prediction model based on complexity metrics and patient planning dose for PSQA results.

MATERIALS AND METHODS

Planning dose, measurement-based reconstructed dose and plan complexity metrics of the 687 radiotherapy plans of patients treated in our institution were collected for model establishing. Global gamma passing rate (GPR, 3%/2mm,10% threshold) of 90% was used as QA criterion. Neural architecture models based on Swin-transformer were adapted to process 3D dose and incorporate 1D metrics to predict QA results. The dataset was divided into training (447), validation (90), and testing (150) sets. Evaluation of predictions was performed using mean absolute error (MAE) for GPR, planning target volume (PTV) HI and PTV CI, mean absolute percentage error (MAPE) for PTV D95, PTV D2 and PTV Dmean, and the area under the receiver operating characteristic (ROC) curve (AUC) for classification. Furthermore, we also compare the prediction results with other models based on either only 1D or 3D inputs.

RESULTS

In this dataset, 72.8% (500/687) plans passed the pretreatment QA under the criterion. On the testing set, our model achieves the highest performance, with the 1D model slightly surpassing the 3D model. The performance results are as follows (combine, 1D, and 3D transformer): The AUCs are 0.92, 0.88 and 0.86 for QA classification. The MAEs of prediction are 0.039, 0.046, and 0.040 for 3D GPR, 0.018, 0.021, and 0.019 for PTV HI, and 0.075, 0.078, and 0.084 for PTV CI. Specifically, for cases with 3D GPRs greater than 90%, the MAE could achieve 0.020 (combine). The MAPE of prediction is 1.23%, 1.52%, and 1.66% for PTV D95, 2.36%, 2.67%, and 2.45% for PTV D2, and 1.46%, 1.70%, and 1.71% for PTV Dmean.

CONCLUSION

The model based on 1D complexity metrics and 3D planning dose could predict pretreatment PSQA results with high accuracy and the complexity metrics play a leading role in the model. Furthermore, dose-volume metric deviations of PTV could be predicted and more clinically valuable information could be provided.

Comparison of Progressive Resolution Optimizer and Photon Optimizer algorithms in RapidArc delivery for head and neck SIB treatments

Background

The aim of this study is to analyze and verify characterization of two different algorithms using simultaneous integrated boost (SIB) in head and neck (H&N) plans.

Materials and methods

In our study 15 patients were selected, who received radiation therapy by using Eclipse volumetric modulated arc therapy (VMAT) Progressive Resolution Optimizer (PRO) algorithm 15.1. The same cases were re-optimized using a Photon Optimizer (PO) algorithm 15.6.A total of 30 treatment plans (15 PRO-VMAT plans and 15 PO-VMAT plans) were produced in the present study. All plans were created using double full arcs, keeping the identical constraints, cost functions and optimization time. Plan evaluation was done using planning target volume (PTV) parameters (D98%, D95%, D50%, D2% mean dose and V105%), homogeneity index (HI), conformity index (CI), Monitor unit (MU) per degree with control points (CP), organ at risk (OAR) doses and gamma verification (Portal dosimetry and ArcCHECK) values were evaluated. Treatment was delivered in Varian Truebeam 2.5, energy 6 MV with Millennium 120 multileaf collimator (MLC).

Results

The PTV coverage (D95%) for PRO and PO were 98.7 ± 0.8 Gy, 98.8 ± 0.9 Gy, HI were 0.09 ± 0.02 and 0.09 ± 0.02, CI were 0.98 ± 0.01 and 0.99 ± 0.01. Monitor units (MU) for PRO and PO were 647.5 ± 137.9, 655.2 ± 138.4. The Portal dose results were [3%, 3mm (%) & 1 %, 1 mm (%)] for PO and PRO 100 ± 0.1, 95.1 ± 1.4 and 100 ± 0.1, 95.2 ± 1.3. For ArcCHECK were 99.9 ± 0.1, 94.7 ± 3.0 and 99.9 ± 0.1, 93.5 ± 3.9, respectively.

Conclusion

Results showed that PTV coverage and OAR doses were comparable. For individual patients CI and HI of PO showed slightly higher values than PRO. MUs for PO were slightly increased as compared to PRO. MU per degree with each individual control points generated by PO showed a high degree of modulation compared to PRO. Hence, new PO optimizer can produce a comparable degree of plan while using the same PRO objectives.

Deep learning based MLC aperture and monitor unit prediction as a warm start for breast VMAT optimisation

Objective. Automated treatment planning today is focussed on non-exact, two-step procedures. Firstly, dose-volume histograms (DVHs) or 3D dose distributions are predicted from the patient anatomy. Secondly, these are converted in multi-leaf collimator (MLC) apertures and monitor units (MUs) using a generic optimisation to obtain the final treatment plan. In contrast, we present a method to predict volumetric modulated arc therapy (VMAT) MLC apertures and MUs directly from patient anatomy using deep learning. The predicted plan is then provided as initialisation to the optimiser for fine-tuning.Approach. 148 patients (training: 101; validation: 23; test: 24), treated for right breast cancer, are replanned to obtain a homogeneous database of 3-arc VMAT plans (PTVBreast: 45.57 Gy; PTVBoost: 55.86 Gy) according to the clinical protocol, using RapidPlanTMwith automatic optimisation and extended convergence mode (clinical workflow). Projections of the CT and contours are created along the beam's eye view of all control points and given as input to a U-net type convolutional neural networks (CNN). The output are the MLC aperture and MU for all control points, from which a DICOM RTplan is built. This is imported and further optimised in the treatment planning system using automatic optimisation without convergence mode, with clinical PTV objectives and organs-at-risk (OAR) objectives based on the DVHs calculated from the imported plan (CNN workflow).Main results. Mean dose differences between the clinical and CNN workflow over the test set are 0.2 ± 0.5 Gy atD95%and 0.6 ± 0.4 Gy atD0.035ccof PTVBreastand -0.4 ± 0.3 Gy atD95%and 0.7 ± 0.3 Gy atD0.035ccof PTVBoost. For the OAR, they are -0.2 ± 0.2 Gy forDmean,heartand 0.04 ± 0.8 Gy forDmean,ipsilateral lung. The mean computation time is 60 and 25 min respectively.Significance. VMAT optimisation can be initialised by MLC apertures and MUs, directly predicted from patient anatomy using a CNN, reducing planning time with more than half while maintaining clinically acceptable plans. This procedure puts the planner in a supervising role over an AI-based treatment planning workflow.

Why we should care about gas pockets in online adaptive MRgRT: a dosimetric evaluation

Introduction

Contouring of gas pockets is a time consuming step in the workflow of adaptive radiotherapy. We would like to better understand which gas pockets electronic densitiy should be used and the dosimetric impact on adaptive MRgRT treatment.

Materials and methods

21 CT scans of patients undergoing SBRT were retrospectively evaluated. Anatomical structures were contoured: Gross Tumour Volume (GTV), stomach (ST), small bowel (SB), large bowel (LB), gas pockets (GAS) and gas in each organ respectively STG, SBG, LBG. Average HU in GAS was converted in RED, the obtained value has been named as Gastrointestinal Gas RED (GIGED). Differences of average HU in GAS, STG, SBG and LBG were computed. Three treatment plans were calculated editing the GAS volume RED that was overwritten with: air RED (0.0012), water RED (1.000), GIGED, generating respectively APLAN, WPLAN and the GPLAN. 2-D dose distributions were analyzed by gamma analysis. Parameter called active gas volume (AGV) was calculated as the intersection of GAS with the isodose of 5% of prescription dose.

Results

Average HU value contained in GAS results to be equal to -620. No significative difference was noted between the average HU of gas in different organ at risk. Value of Gamma Passing Rate (GPR) anticorrelates with the AGV for each plan comparison and the threshold value for GPR to fall below 90% is 41, 60 and 139 cc for WPLANvsAPLAN, GPLANvsAPLAN and WPLANvsGPLAN respectively.

Discussions

GIGED is the right RED for Gastrointestinal Gas. Novel AGV is a useful parameter to evaluate the effect of gas pocket on dose distribution.

Isodose surface differences: A novel tool for the comparison of dose distributions

BACKGROUND

Comparing dose distributions is a routine task in radiotherapy, mainly in patient-specific quality assurance (PSQA). Currently, the evaluation of the dose distributions is being performed mainly with statistical methods, which could underestimate the clinical importance of the spotted differences, as per the literature.

PURPOSE

This paper aims to provide proof-of-concept for a novel dose distribution comparison method based on the difference of the isodose surfaces. The new method connects acceptance tolerance to QA limitations (equipment capabilities) and integrates a clinical approach into the analysis procedure.

METHODS

The distance of dose points from the isocenter can be used as a function to define the shape of an isodose surface expressed as a histogram. Isodose surface differences (ISD) are defined as the normalized differences of reference and evaluated surface histograms plotted against their corresponding isodose. Acceptance tolerances originate from actual QA tolerances and are presented clinically intuitively. The ISD method was compared to the gamma index using intentionally erroneous VMAT and IMRT plans.

RESULTS

Results revealed that the ISD method is sensitive to all errors induced in the plans. Discrepancies are presented per isodose, enabling the evaluation of the plan in two regions representing PTV and Normal Tissue. ISD manages to flag errors that would remain undetected under the gamma analysis.

CONCLUSION

The ISD method is a meaningful, QA-related, registration-free, and clinically oriented technique of dose distribution evaluation. This method can be used either as a standalone or an auxiliary tool to the well-established evaluation procedures, overcoming significant limitations reported in the literature.

Comprehensive evaluation and new recommendations in the use of Gafchromic EBT3 film

BACKGROUND

Gafchromic film's unique properties of tissue-equivalence, dose-rate independence, and high spatial resolution make it an attractive choice for many dosimetric applications. However, complicated calibration processes and film handling limits its routine use.

PURPOSE

We evaluated the performance of Gafchromic EBT3 film after irradiation under a variety of measurement conditions to identify aspects of film handling and analysis for simplified but robust film dosimetry.

METHODS

The short- (from 5 min to 100 h) and long-term (months) film response was evaluated for clinically relevant doses of up to 50 Gy for accuracy in dose determination and relative dose distributions. The dependence of film response on film-read delay, film batch, scanner type, and beam energy was determined.

RESULTS

Scanning the film within a 4-h window and using a standard 24-h calibration curve introduced a maximum error of 2% over a dose range of 1-40 Gy, with lower doses showing higher uncertainty in dose determination. Relative dose measurements demonstrated <1 mm difference in electron beam parameters such as depth of 50% of the maximum dose value (R50 ), independent of when the film was scanned after irradiation or the type of calibration curve used (batch-specific or time-specific calibration curve) if the same default scanner was used. Analysis of films exposed over a 5-year period showed that using the red channel led to the lowest variation in the measured net optical density values for different film batches, with doses >10 Gy having the lowest coefficient of variation (<1.7%). Using scanners of similar design produced netOD values within 3% after exposure to doses of 1-40 Gy.

CONCLUSIONS

This is the first comprehensive evaluation of the temporal and batch dependence of Gafchromic EBT3 film evaluated on consolidated data over 8 years. The relative dosimetric measurements were insensitive to the type of calibration applied (batch- or time-specific) and in-depth time-dependent dosimetric signal behaviors can be established for film scanned outside of the recommended 16-24 h post-irradiation window. We generated guidelines based on our findings to simplify film handling and analysis and provide tabulated dose- and time-dependent correction factors to achieve this without reducing the accuracy of dose determination.