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.

A transit portal dosimetry method for respiratory gating quality assurance with a dynamic 3D printed tumor phantom.

BACKGROUNDS: Respiratory gating is one of the motion management techniques that is used to deliver radiation dose to a tumor at a specific position under free breathing. However, due to the dynamic feedback process of this approach, regular equipment quality assurance (QA) and patient-specific QA checks need to be performed. This work proposes a new QA methodology using electronic portal imaging detector (EPID) to determine the target localization accuracy of phase gating. METHODS: QA tools comprising 3D printed spherical tumor phantoms, programmable stages, and an EPID detector are characterized and assembled. Algorithms for predicting portal dose (PD) through moving phantoms are developed and verified using gamma analysis for two spherical tumor phantoms (2 cm and 4 cm), two different 6 MV volumetric modulated arc therapy plans, and two different gating windows (30%-70% and 40%-60%). Comparison between the two gating windows is then performed using the Wilcoxon signed-rank test. An optimizer routine, which is used to determine the optimal window, based on maximal gamma passing rate (GPR), was applied to an actual breathing curve and breathing plan. This was done to ascertain if our method yielded a similar result with the actual gating window. RESULTS: High GPRs of more than 97% and 91% were observed when comparing the predicted PD with the measured PD in moving phantom at 2 mm/2% and 1 mm/1% levels, respectively. Analysis of gamma heatmaps shows an excellent agreement with the tumor phantom. The GPR of 40%-60% PD was significantly lower than that of the 30%-70% PD at the 1 mm/1% level (p = 0.0064). At the 2 mm/2% level, no significant differences were observed. The optimizer routine could accurately predict the center of the gating window to within a 10% range. CONCLUSION: We have successfully performed and verified a new method for QA with the use of a moving phantom with EPID for phase gating with real-time position management.

A measurement validation of improved plan deliverability with monitor unit objective tool for spine stereotactic ablative radiotherapy.

Spine stereotactic body radiation therapy (SBRT) uses high dose per fraction for palliative pain control. The treatment plans are often heavily modulated due to close proximity to spinal cord and this can lead to poor plan quality which are susceptible to dose delivery discrepancy. Therefore, we aim to assess the effectiveness of the monitor unit (MU) objective tool in Eclipse treatment planning systems in modulating the plan complexity to improve the plan quality in spine SBRT. Seven retrospective spine SBRT plans are re-optimized using the MU objective tool in Eclipse TPS v13.6 and were compared with the original plans. The dose metrics of the tumor PTV were compared using D1cc. D99%, D95%, D0.03cc, D0.1cc, D0.35cc and D1cc, and that of cord PRV were compared using D0.03cc, D0.1cc, D0.35cc. Four different plan complexities were also calculated for the original and re-optimized plans to quantify the impact of the tool on the modulation. Patient specific quality assurance measurements were performed with Stereophan and SRS MapCheck, and analyzed using the 1%/1-mm and 2%/2-mm criteria with gamma analysis. The dose metrics of the PTV and cord PRV of the re-optimized and original plans are similar and still meet the planning dose constraints. In particular, the PTV dose coverage has a small percentage difference of (0.15 ± 1.33)% and (0.01 ± 1.04)% for D99% and D95%, respectively. The 4 calculated plan complexity metrics consistently show that the re-optimized plans are quantitatively less complex than the original plan. The gamma passing rate of the re-optimized plans improved from (92.2 ± 2.0)% to (94.2 ± 1.6)% with the 1%/1-mm criterion, and (98.7 ± 1.0)% to (99.5 ± 0.3)% with the 2%/2-mm criterion. Overall, the re-optimized plans achieve at least a 10% MU reduction (11.7% to 24.6%). Our study shows that optimization with the MU objective tool can reduce plan complexity and improves dose delivery accuracy, while not compromising the dose distribution.

Quantifying Systematic RBE-Weighted Dose Uncertainty Arising from Multiple Variable RBE Models in Organ at Risk.

PURPOSE: Relative biological effectiveness (RBE) uncertainties have been a concern for treatment planning in proton therapy, particularly for treatment sites that are near organs at risk (OARs). In such a clinical situation, the utilization of variable RBE models is preferred over constant RBE model of 1.1. The problem, however, lies in the exact choice of RBE model, especially when current RBE models are plagued with a host of uncertainties. This paper aims to determine the influence of RBE models on treatment planning, specifically to improve the understanding of the influence of the RBE models with regard to the passing and failing of treatment plans. This can be achieved by studying the RBE-weighted dose uncertainties across RBE models for OARs in cases where the target volume overlaps the OARs. Multi-field optimization (MFO) and single-field optimization (SFO) plans were compared in order to recommend which technique was more effective in eliminating the variations between RBE models. METHODS: Fifteen brain tumor patients were selected based on their profile where their target volume overlaps with both the brain stem and the optic chiasm. In this study, 6 RBE models were analyzed to determine the RBE-weighted dose uncertainties. Both MFO and SFO planning techniques were adopted for the treatment planning of each patient. RBE-weighted dose uncertainties in the OARs are calculated assuming ( α ß ) x of 3 Gy and 8 Gy. Statistical analysis was used to ascertain the differences in RBE-weighted dose uncertainties between MFO and SFO planning. Additionally, further investigation of the linear energy transfer (LET) distribution was conducted to determine the relationship between LET distribution and RBE-weighted dose uncertainties. RESULTS: The results showed no strong indication on which planning technique would be the best for achieving treatment planning constraints. MFO and SFO showed significant differences (P <.05) in the RBE-weighted dose uncertainties in the OAR. In both clinical target volume (CTV)-brain stem and CTV-chiasm overlap region, 10 of 15 patients showed a lower median RBE-weighted dose uncertainty in MFO planning compared with SFO planning. In the LET analysis, 8 patients (optic chiasm) and 13 patients (brain stem) showed a lower mean LET in MFO planning compared with SFO planning. It was also observed that lesser RBE-weighted dose uncertainties were present with MFO planning compared with SFO planning technique. CONCLUSIONS: Calculations of the RBE-weighted dose uncertainties based on 6 RBE models and 2 different ( α ß ) x revealed that MFO planning is a better option as opposed to SFO planning for cases of overlapping brain tumor with OARs in eliminating RBE-weighted dose uncertainties. Incorporation of RBE models failed to dictate the passing or failing of a treatment plan. To eliminate RBE-weighted dose uncertainties in OARs, the MFO planning technique is recommended for brain tumor when CTV and OARs overlap.

Standardizing Monte Carlo simulation parameters for a reproducible dose-averaged linear energy transfer.

OBJECTIVE: Dose-averaged linear energy transfer (LETD) is one of the factors which determines relative biological effectiveness (RBE) for treatment planning in proton therapy. It is usually determined from Monte Carlo (MC) simulation. However, no standard simulation protocols were established for sampling of LETD. Simulation parameters like maximum step length and range cut will affect secondary electrons production and have an impact on the accuracy of dose distribution and LETD. We aim to show how different combinations of step length and range cut in GEANT4 will affect the result in sampling of LETD using different MC scoring methods. METHODS: In this work, different step length and range cut value in a clinically relevant voxel geometry were used for comparison. Different LETD scoring methods were established and the concept of covariance between energy deposition per step and step length is used to explain the differences between them. RESULTS: We recommend a maximum step length of 0.05 mm and a range cut of 0.01 mm in MC simulation as this yields the most consistent LETD value across different scoring methods. Different LETD scoring methods are also compared and variation up to 200% can be observed at the plateau of 80 MeV proton beam. Scoring Method one has one of the lowest percentage differences compared across all simulation parameters. CONCLUSION: We have determined a set of maximum step length and range cut parameters to be used for LETD scoring in a 1 mm voxelized geometry. LETD scoring method should also be clearly defined and standardized to facilitate cross-institutional studies. ADVANCES IN KNOWLEDGE: Establishing a standard simulation protocol for sampling LETD would reduce the discrepancy when comparing data across different centres, and this can improve the calculation for RBE.

Dosimetric uncertainties impact on cell survival curve with low energy proton.

There is an increasing number of radiobiological experiments being conducted with low energy protons (less than 5 MeV) for radiobiological studies due to availability of sub-millimetre focused beam. However, low energy proton has broad microdosimetric spectra which can introduce dosimetric uncertainty. In this work, we quantify the impact of this dosimetric uncertainties on the cell survival curve and how it affects the estimation of the alpha and beta parameters in the LQ formalism. Monte Carlo simulation is used to generate the microdosimetric spectra in a micrometer-sized water sphere under proton irradiation. This is modelled using radiobiological experiment set-up at the Centre of Ion Beam Application (CIBA) in National University of Singapore. Our results show that the microdosimetric spectra can introduce both systematic and random shifts in dose and cell survival; this effect is most pronounced with low energy protons. The alpha and beta uncertainties can be up to 10% and above 30%, respectively for low energy protons passing through thin cell target (about 10 microns). These uncertainties are non-negligible and show that care must be taken in using the cell survival curve and its derived parameters for radiobiological models.

Analysis of intra-fraction prostate motion and derivation of duration-dependent margins for radiotherapy using real-time 4D ultrasound.

BACKGROUND AND PURPOSE: During radiotherapy, prostate motion changes over time. Quantifying and accounting for this motion is essential. This study aimed to assess intra-fraction prostate motion and derive duration-dependent planning margins for two treatment techniques. MATERIAL AND METHODS: A four-dimension (4D) transperineal ultrasound Clarity® system was used to track prostate motion. We analysed 1913 fractions from 60 patients undergoing volumetric-modulated arc therapy (VMAT) to the prostate. The mean VMAT treatment duration was 3.4 min. Extended monitoring was conducted weekly to simulate motion during intensity-modulated radiation therapy (IMRT) treatment (an additional seven minutes). A motion-time trend analysis was conducted and the mean intra-fraction motion between VMAT and IMRT treatments compared. Duration-dependent margins were calculated and anisotropic margins for VMAT and IMRT treatments were derived. RESULTS: There were statistically significant differences in the mean intra-fraction motion between VMAT and the simulated IMRT duration in the inferior (0.1 mm versus 0.3 mm) and posterior (-0.2 versus -0.4 mm) directions respectively (p ≪ 0.01). An intra-fraction motion trend inferiorly and posteriorly was observed. The recommended minimum anisotropic margins are 1.7 mm/2.7 mm (superior/inferior); 0.8 mm (left/right), 1.7 mm/2.9 mm (anterior/posterior) for VMAT treatments and 2.9 mm/4.3 mm (superior/inferior), 1.5 mm (left/right), 2.8 mm/4.8 mm (anterior/posterior) for IMRT treatments. Smaller anisotropic margins were required for VMAT compared to IMRT (differences ranging from 1.2 to 1.6 mm superiorly/inferiorly, 0.7 mm laterally and 1.1-1.9 mm anteriorly/posteriorly). CONCLUSIONS: VMAT treatment is preferred over IMRT as prostate motion increases with time. Larger margins should be employed in the inferior and posterior directions for both treatment durations. Duration-dependent margins should be applied in the presence of prolonged imaging and verification time.

Dosimetric comparison of peripheral NSCLC SBRT using Acuros XB and AAA calculation algorithms.

There is a concern for dose calculation in highly heterogenous environments such as the thorax region. This study compares the quality of treatment plans of peripheral non-small cell lung cancer (NSCLC) stereotactic body radiation therapy (SBRT) using 2 calculation algorithms, namely, Eclipse Anisotropic Analytical Algorithm (AAA) and Acuros External Beam (AXB), for 3-dimensional conformal radiation therapy (3DCRT) and volumetric-modulated arc therapy (VMAT). Four-dimensional computed tomography (4DCT) data from 20 anonymized patients were studied using Varian Eclipse planning system, AXB, and AAA version 10.0.28. A 3DCRT plan and a VMAT plan were generated using AAA and AXB with constant plan parameters for each patient. The prescription and dose constraints were benchmarked against Radiation Therapy Oncology Group (RTOG) 0915 protocol. Planning parameters of the plan were compared statistically using Mann-Whitney U tests. Results showed that 3DCRT and VMAT plans have a lower target coverage up to 8% when calculated using AXB as compared with AAA. The conformity index (CI) for AXB plans was 4.7% lower than AAA plans, but was closer to unity, which indicated better target conformity. AXB produced plans with global maximum doses which were, on average, 2% hotter than AAA plans. Both 3DCRT and VMAT plans were able to achieve D95%. VMAT plans were shown to be more conformal (CI = 1.01) and were at least 3.2% and 1.5% lower in terms of PTV maximum and mean dose, respectively. There was no statistically significant difference for doses received by organs at risk (OARs) regardless of calculation algorithms and treatment techniques. In general, the difference in tissue modeling for AXB and AAA algorithm is responsible for the dose distribution between the AXB and the AAA algorithms. The AXB VMAT plans could be used to benefit patients receiving peripheral NSCLC SBRT.