MU variability in CBCT-guided online adaptive radiation therapy.

PURPOSE: CBCT-guided online-adaptive radiotherapy (oART) systems have been made possible by using artificial intelligence and automation to substantially reduce treatment planning time during on-couch adaptive sessions. Evaluating plans generated during an adaptive session presents significant challenges to the clinical team as the planning process gets compressed into a shorter window than offline planning. We identified MU variations up to 30% difference between the adaptive plan and the reference plan in several oART sessions that caused the clinical team to question the accuracy of the oART dose calculation. We investigated the cause of MU variation and the overall accuracy of the dose delivered when MU variations appear unnecessarily large. METHODS: Dosimetric and adaptive plan data from 604 adaptive sessions of 19 patients undergoing CBCT-guided oART were collected. The analysis included total MU per fraction, planning target volume (PTV) and organs at risk (OAR) volumes, changes in PTV-OAR overlap, and DVH curves. Sessions with MU greater than two standard deviations from the mean were reoptimized offline, verified by an independent calculation system, and measured using a detector array. RESULTS: MU variations relative to the reference plan were normally distributed with a mean of -1.0% and a standard deviation of 11.0%. No significant correlation was found between MU variation and anatomic changes. Offline reoptimization did not reliably reproduce either reference or on-couch total MUs, suggesting that stochastic effects within the oART optimizer are likely causing the variations. Independent dose calculation and detector array measurements resulted in acceptable agreement with the planned dose. CONCLUSIONS: MU variations observed between oART plans were not caused by any errors within the oART workflow. Providers should refrain from using MU variability as a way to express their confidence in the treatment planning accuracy. Clinical decisions during on-couch adaptive sessions should rely on validated secondary dose calculations to ensure optimal plan selection.

Using machine learning to predict gamma passing rate in volumetric-modulated arc therapy treatment plans.

PURPOSE: This study aims to develop an algorithm to predict gamma passing rate (GPR) in the volumetric-modulated arc therapy (VMAT) technique. MATERIALS AND METHODS: A total of 118 clinical VMAT plans, including 28 mediastina, 25 head and neck, 40 brains intensity-modulated radiosurgery, and 25 prostate cases, were created in RayStation treatment planning system for Edge and TrueBeam linacs. In-house scripts were developed to compute Modulation indices such as plan-averaged beam area (PA), plan-averaged beam irregularity (PI), total monitor unit (MU), leaf travel/arc length, mean dose rate variation, and mean gantry speed variation. Pretreatment verifications were performed on ArcCHECK phantom with SNC software. GPR was calculated with 3%/2 mm and 10% threshold. The dataset was randomly split into a training (70%) and a test (30%) dataset. A random forest regression (RFR) model and support vector regression (SVR) with linear kernel were trained to predict GPR using the complexity metrics as input. The prediction performance was evaluated by calculating the mean absolute error (MAE), R2 , and root mean square error (RMSE). RESULTS: RMSEs at γ 3%/2 mm for RFR and SVR were 1.407 ± 0.103 and 1.447 ± 0.121, respectively. MAE was 1.14 ± 0.084 for RFR and 1.101 ± 0.09 for SVR. R2 was equal to 0.703 ± 0.027 and 0.689 ± 0.053 for RFR and SVR, respectively. GPR of 3%/2 mm with a 10% threshold can be predicted with an error smaller than 3% for 94% of plans using RFR and SVR models. The most important metrics that had the greatest impact on how accurately GPR can be predicted were determined to be the PA, PI, and total MU. CONCLUSION: In terms of its prediction values and errors, SVR (linear) appeared to be comparable with RFR for this dataset. Based on our results, the PA, PI, and total MU calculations may be useful in guiding VMAT plan evaluation and ultimately reducing uncertainties in planning and radiation delivery.

Evaluation of parameters affecting gamma passing rate in patient-specific QAs for multiple brain lesions IMRS treatments using ray-station treatment planning system.

PURPOSE: Using intensity-modulated radiosurgery (IMRS) with single isocenter for the treatment of multiple brain lesions has gained acceptance in recent years. One of the challenges of this technique is conducting a patient-specific quality assurance (QA), involving accurate gamma passing rate (GPR) calculations for small and wide spread-out targets. We evaluated effects of parameters such as dose grid and energy on GPR using our clinical IMRS plans. METHODS: Ten patients with total of 40 volumetric modulated arc therapy (VMAT) plans were created in Raystation (V.8A) treatment planning system (TPS) for the Varian Edge Linac using 6 and 10 flattening filter-free (FFF) beams and planned dose grids of 1 mm and 2 mm resulting in four plans with 6-10 targets per patient. All parameters and objectives except dose grid and energy were kept the same in all plans. Next, patient-specific QAs were measured evaluating GPR with 10% threshold, 3%/3 mm objective, and an acceptance criterion of 95%. Modulation factors (MF) and confidence intervals were calculated. Two modes of measurements, standard density (SD) and high density (HD), were used. RESULTS: Generally, plans computed with 1 mm dose grid have higher GPRs than those with 2 mm dose grid for both energies used. The GPRs of 6 FFF plans were higher than those of 10 FFF plans. GPR showed no noticeable difference between HD and SD measurements. Negative correlation between MF and GPR was observed. The HD pass rates fall within the confidence interval of SD. CONCLUSION: Calculated dose grid should be less than or equal to one-third of distance to agreement, thus 1 mm planned dose grid is recommended to reduce artifacts in gamma calculation. GPR of SD and HD measurement modes is almost the same, which indicates that SD mode is clinically preferable for performing patient-specific QAs. According to our results, using 6 FFF beams with 1 mm planned dose grid is more accurate and reliable for dose calculation of IMRS plans.

Technical Note: Influence of Compton currents on profile measurements in small-volume ion chambers.

PURPOSE: This work is to evaluate the effects of Compton current generation in three small-volume ionization chambers on measured beam characteristics for electron fields. METHODS: Beam scans were performed using Exradin A16, A26, and PTW 31014 microchambers. Scans with varying chamber components shielded were performed. Static point measurements, output factors, and cable only irradiations were performed to determine the contribution of Compton currents to various components of the chamber. Monte Carlo simulations were performed to evaluate why one microchamber showed a significant reduction in Compton current generation. RESULTS: Beam profiles demonstrated significant distortion for two of the three chambers when scanned parallel to the chamber axis, produced by electron deposition within the wire. Measurements of ionization produced within the cable identified Compton current generation as the cause of these distortions. The size of the central collecting wire was found to have the greatest influence on the magnitude of Compton current generation. CONCLUSIONS: Microchambers can demonstrate significant (>5%) deviations from properties as measured with larger volume chambers (0.125 cm(3) and above). These deviations can be substantially reduced by averaging measurements conducted at opposite polarities.

Correction factor measurements for multiple detectors used in small field dosimetry on the Varian Edge radiosurgery system.

PURPOSE: Accurate dosimetry of small fields remains a challenge to the clinical physicist. Choosing the appropriate detector and determination of kQclin,Qmsr (fclin,fmsr) factors continue to be an area of active research. The purpose of this study is to evaluate the output factors for a dedicated stereotactic accelerator using multiple dosimeters designed for use in small fields and evaluate published kQclin,Qmsr (fclin,fmsr) factors relative to measured values using a commercial scintillating fiber. METHODS: Four microionization chambers, a commercial plastic scintillation detector, and a semiconducting diode were used to measure output factors for a linear accelerator. Field sizes ranging from 6 × 6 to 0.6 × 0.6 cm(2) were measured in a water phantom at 10 cm depth for 100 cm SSD. All microionization chambers were mounted in both vertical and horizontal configurations. Fields were normalized to the output at 5 × 5 cm(2). Output correction factors, kQclin,Qmsr (fclin,fmsr), were calculated as the ratio of a detector response relative to the scintillating fiber response for a given clinical field size, fclin. RESULTS: Ionization chambers consistently under-responded for small fields relative to the scintillating fiber. Variations in response between horizontal and vertical mounting were most notable for the microchambers, with the vertical mounting which reduced the magnitude of the necessary correction factor, kQclin,Qmsr (fclin,fmsr), for the microionization chambers ranging from 1.1 to 1.2 for the smallest field size at all energies. The semiconducting diode over-responded by 7% for the smallest field size across all energies, resulting in a kQclin,Qmsr (fclin,fmsr) of ∼ 0.93. CONCLUSIONS: The commercial scintillating fiber, which produces accurate and consistent ratios of dose to water for nonstandard fields, can be used to measure correction factors for various detectors used in a clinical setting. This can allow for comparison of measured correction factors to previously published values.