Penoncello, Gregory P.

Abstract Introduction Linear accelerators require a large amount of data to be collected daily, monthly and annually to verify safe deliveries for patients. Different detectors have been utilized to improve the simplicity, efficiency and accuracy of the various experimental setups required to collect the necessary data resulting in reduced data collection and evaluation time. Plastic scintillators are stable and energy independent radiation detectors with high spatial resolution that emit light proportional to the amount of radiation incident on them. With an appropriate photodetector and technique to measure and analyze the light that is emitted, scintillators can be utilized to measure dosimetric parameters necessary for various monthly quality assurance requirements. Methods A uniform cylindrical plastic scintillator imaged by a complementary metal oxide semiconductor (CMOS) camera is designed to act as a radiation detector to measure 2D projections of linear accelerator beams. Beams were delivered to the detector to evaluate machine quality assurance (QA) parameters, including beam energy, output, profile consistency and reproducibility as described by TG‐198. These measurements were compared to calculations from the Eclipse treatment planning system (TPS). Typical monthly quality assurance (QA) beams were delivered and 2D projections of the scintillation light were measured to validate the accuracy and reproducibility of this detector system for monthly QA. Results The plastic scintillator was able to accurately characterize the radiation beam. Energy and profile measurements were reproducible and within 2%/2mm of calculations in the TPS. Output measurements had maximum variations of up to 1.3% and average differences of 0.5%. Conclusion A simple cylindrical plastic scintillator and CMOS camera radiation detector setup was designed and tested for measuring monthly QA dosimetric parameters specified by TG‐198 with accurate and reproducible output, energy and profiles measurements. This method reduces the number of measurements required, allowing multiple parameters to be evaluated in a single beam delivery.

AbstractBackgroundCone‐beam computed tomography (CBCT) allows for patient setup and positioning, and potentially dose verification or adaptive replanning prior to each treatment delivery. Poor CBCT image quality due to scatter artifacts and patient motion has been a major limiting factor. A new image reconstruction algorithm was recently clinically implemented for improving image quality through iterative reconstruction (iCBCT).PurposeThis study aims to characterize iCBCT image quality, establish image value (HU)‐to‐relative electron density (RED) calibration curves for dose calculation, and assess the dosimetric accuracy for different anatomical sites.Material and methodsBoth conventional CBCT and iCBCT scans were acquired from a Varian TrueBeam On‐Board Imager system. A Catphan 604 phantom was scanned to compare image quality between the traditional Feldkamp–Davis–Kress (FDK) and novel iterative reconstruction techniques. Computerized Imaging Reference Systems (CIRS) electron density phantom was used to construct site‐specific HU‐RED curves corresponding to various scan settings. The CIRS Dynamic Thorax phantom, Rando pelvis phantom, and BrainLab head phantom were used for assessing dosimetric accuracy calculated on iCBCT images, compared to that on traditional FDK‐based CBCT images. All phantoms were scanned on a computed tomography (CT) to obtain baseline HU values for comparison.ResultsTest results obtained from Catphan showed statistically significant improvement with iCBCT, compared to FDK CBCT. Average HU differences from the baseline CT values were improved to within ±30 HU for iCBCT, compared to FDK CBCT for phantom studies. Dose calculated on iCBCT for both phantoms and patient cases directly using baseline HU‐RED calibration from CT showed 0.5%–2.0% accuracy from the baseline dose calculated on CT, which is comparable to doses calculated using site‐specific HU‐RED calibration curves.ConclusioniCBCT provides improved image quality, improved HU accuracy compared to CT baseline, and has potential to provide online dose verification as part of the adaptive radiotherapy workflow directly using the baseline HU‐RED calibration curve from CT.

AbstractPurposeTo investigate the dependency of dose‐volume histogram (DVH) behavior and precision on underlying discretization using shapes and dose distributions with known analytical DVHs for five commercial DVH calculators.MethodsDVHs and summary metrics were extracted from all five systems using synthetic cone and cylinder objects for which the true volume and DVH curves were known. Trends in the curves and metrics were explored by varying the underlying voxelization of the CT image, structure set, and dose grid as well by varying the geometry of the structure and direction of a linear dose gradient. Using synthetic structures allowed for comparison with ground truth DVH curves to assess their accuracy while an algorithm was additionally developed to assess the precision of each system. The precision was calculated with a novel algorithm that treats any “stair step” behavior in a DVH curve as an uncertainty band and calculates the width, characterized as a percent difference, of the band for various DVH metrics. The underlying voxelization was additionally changed and DVHs were extracted for two clinical examples. The details of how each system calculated DVHs were also investigated and tendencies in the calculated curves, metrics, and precision were related to choices made in the calculation methodology.ResultsCalculation methodology differences that had a noticeable impact on the DVH curves and summary metrics include supersampling beyond the input grids and interpretation of the superior and inferior ends of the structures. Among the systems studied, the median precision ranged from 0.902% to 3.22%, and interquartile ranges varied from 1.09% to 3.91%.ConclusionsCommercial dose‐evaluation solutions can calculate different DVH curves, structure volume measures, and dose statistics for the same input data due to differences in their calculation methodologies. This study highlights the importance of understanding and investigating the DVH calculation when considering a new clinical system and when using more than one system for data transfer.

AbstractPurposeTo develop an online graphic processing unit (GPU)‐accelerated Monte Carlo‐based adaptive radiation therapy (ART) workflow for pencil beam scanning (PBS) proton therapy to address interfraction anatomical changes in patients treated with PBS.Methods and MaterialsA four‐step workflow was developed using our in‐house developed GPU‐accelerated Monte Carlo‐based treatment planning system to implement online Monte Carlo‐based ART for PBS. The first step conducts diffeomorphic demon‐based deformable image registration (DIR) to propagate contours on the initial planning CT (pCT) to the verification CT (vCT) to form a new structure set. The second step performs forward dose calculation of the initial plan on the vCT with the propagated contours after manual approval (possible modifications involved). The third step triggers a reoptimization of the plan depending on whether the verification dose meets the clinical requirements or not. A robust evaluation will be done for both the verification plan in the second step and the reopotimized plan in the third step. The fourth step involves a two‐stage (before and after delivery) patient‐specific quality assurance (PSQA) of the reoptimized plan. The before‐delivery PSQA is to compare the plan dose to the dose calculated using an independent fast open‐source Monte Carlo code, MCsquare. The after‐delivery PSQA is to compare the plan dose to the dose recalculated using the log file (spot MU, spot position, and spot energy) collected during the delivery. Jaccard index (JI), dice similarity coefficients (DSCs), and Hausdorff distance (HD) were used to assess the quality of the propagated contours in the first step. A commercial plan evaluation software, ClearCheck™, was integrated into the workflow to carry out efficient plan evaluation. 3D Gamma analysis was used during the fourth step to ensure the accuracy of the plan dose from reoptimization. Three patients with three different disease sites were chosen to evaluate the feasibility of the online ART workflow for PBS.ResultsFor all three patients, the propagated contours were found to have good volume conformance [JI (lowest‐highest: 0.833–0.983) and DSC (0.909–0.992)] but suboptimal boundary coincidence [HD (2.37–20.76 mm)] for organs‐at‐risk. The verification dose evaluated by ClearCheck™ showed significant degradation of the target coverage due to the interfractional anatomical changes. Reoptimization on the vCT resulted in great improvement of the plan quality to a clinically acceptable level. 3D Gamma analyses of PSQA confirmed the accuracy of the plan dose before delivery (mean Gamma index = 98.74% with a threshold of 2%/2 mm/10%), and after delivery based on the log files (mean Gamma index = 99.05% with a threshold of 2%/2 mm/10%). The average time cost for the complete execution of the workflow was around 858 s, excluding the time for manual intervention.ConclusionThe proposed online ART workflow for PBS was demonstrated to be efficient and effective by generating a reoptimized plan that significantly improved the plan quality.