A script-enabled interactive checklist document for efficient management of electronic devices in a busy multimodality radiotherapy clinic.

PURPOSE: Develop an efficient, interactive, and instructive checklist document for the management of implanted electronic medical devices in a multimodality radiotherapy clinic. METHODS: The built-in scripting and interactivity of a popular commercial word processor was used to develop an interactive document that changes the information presented to the user based on drop-down selections. The interactivity and scripting were compatible with the radiation oncology information system (ROIS) which allows the document to be accessible by all team members and serve as a permanent record in a patient's electronic chart. RESULTS: The final interactive document, which was clinically deployed after beta testing with a group consisting of nurses and medical physicists, presents information and action plans to the user based on multiple departmental medical device decision trees that are specific to the combination of device, treatment modality, rhythm-pacing dependence for cardiac devices, and distance from the device to the treatment volume. CONCLUSION: A script-enabled interactive document was developed for a busy multimodality clinic, condensing multiple comprehensive departmental guidelines spanning multiple device types and treatment modalities into a single interactive checklist accessible within the ROIS. Given the wide accessibility of the commercial word processor, this approach could be adopted by other clinics to streamline their own respective workflows.

Radiation Dose Sensitivity of Subregions of the Larynx to Patient-Reported Swallowing Outcomes.

Purpose: To assess any correlation between swallowing dysfunction and radiation dose to 5 subregions of the larynx. Methods and Materials: A cohort of 136 patients with head and neck cancer, treated with either photon or proton radiation therapy, was assessed using an endpoint of patient-reported swallowing scores, evaluated with the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-H&N35 survey, within 1 month after treatment. Five subregions of the larynx were contoured, and dosimetric metrics were extracted for each subregion as well as the total larynx. Univariate and multivariate logistic regression statistical analyses were used to determine statistical correlation with the dose metrics and clinical variables. Univariate regression models were statistically compared using a non-nested model test. Results: Under univariate analysis, unilateral versus bilateral nodal irradiation (P = .004), concurrent chemotherapy (P = .007), and surgery (P = .015) were statistically significant predictors of poor swallowing score. Unilateral versus bilateral irradiation was statistically significant under multivariate analysis (P = .039). The epiglottis was the most predictive subregion of swallowing score, with a majority (21 of 25) of dosimetric variables being identified as statistically significant. The maximum dose to the epiglottis was the most significant dosimetric variable tested for poor swallowing score in both univariate (P = .003) and multivariate (P = .051) analyses. Comparison of univariate models indicated a general preference for epiglottic variables with the mean dose to the epiglottis being preferred at a statistically significant level in many cases. Conclusions: These results show the relatively increased sensitivity of the epiglottis compared with the rest of the larynx when considering patient-reported decrements in quality-of-life swallowing score and support both the inclusion of the epiglottis in standard larynx contours and the assessment of the epiglottis dose during plan evaluation. Our data suggest that keeping the mean and max doses to the epiglottis <20 to 37 Gy and <53 to 60 Gy, respectively, will reduce swallowing difficulties.

Multicenter Multivendor Evaluation of Dose Volume Histogram Creation Consistencies for 8 Commercial Radiation Therapy Dosimetric Systems.

PURPOSE: To evaluate dose volume histogram (DVH) construction differences across 8 major commercial treatment planning systems (TPS) and dose reporting systems for clinically treated plans of various anatomic sites and target sizes. METHODS AND MATERIALS: Dose files from 10 selected clinically treated plans with a hypofractionation, stereotactic radiation therapy prescription or sharp dose gradients such as head and neck plans ranging from prescription doses of 18 Gy in 1 fraction to 70 Gy in 35 fractions, each calculated at 0.25 and 0.125 cm grid size, were created and anonymized in Eclipse TPS, and exported to 7 other major TPS (Pinnacle, RayStation, and Elements) and dose reporting systems (MIM, Mobius, ProKnow, and Velocity) systems for comparison. Dose-volume constraint points of clinical importance for each plan were collected from each evaluated system (D0.03 cc [Gy], volume, and the mean dose were used for structures without specified constraints). Each reported constraint type and structure volume was normalized to the value from Eclipse for a pairwise comparison. A Wilcoxon rank-sum test was used for statistical significance and a multivariable regression model was evaluated adjusting for plan, grid size, and distance to target center. RESULTS: For all DVH points relative to Eclipse, all systems reported median values within 1.0% difference of each other; however, they were all different from Eclipse. Considering mean values, Pinnacle, RayStation, and Elements averaged at 1.038, 1.046, and 1.024, respectively, while MIM, Mobius, ProKnow, and Velocity reported 1.026, 1.050, 1.033, and 1.022, respectively relative to Eclipse. Smaller dose grid size improved agreement between the systems marginally without statistical significance. For structure volumes relative to Eclipse, larger differences are seen across all systems with a range in median values up to 3.0% difference and mean up to 10.1% difference. CONCLUSIONS: Large variations were observed between all systems. Eclipse generally reported, at statistically significant levels, lower values than all other evaluated systems. The nonsignificant change resulting from lowering the dose grid resolution indicates that this resolution may be less important than other aspects of calculating DVH curves, such as the 3-dimensional modeling of the structure.

Early Impact of Proton Beam Therapy on Electrophysiological Characteristics in a Porcine Model.

BACKGROUND: Particle therapy is a noninvasive, catheter-free modality for cardiac ablation. We previously demonstrated the efficacy for creating ablation lesions in the porcine heart. Despite several earlier studies, the exact mechanism of early biophysical effects of proton and photon beam delivery on the myocardium remain incompletely resolved. METHODS: Ten normal and 9 infarcted in situ porcine hearts received proton beam irradiation (40 Gy) delivered to the left ventricular myocardium with follow-up for 8 weeks. High-resolution electroanatomical mapping of the left ventricular was performed at baseline and follow-up. Bipolar voltage amplitude, conduction velocity, and connexin-43 were determined within the irradiated and nonirradiated areas. RESULTS: The irradiated area in normal hearts showed a significant reduction of bipolar voltage amplitude (10.1±4.9 mV versus 5.7±3.2, P<0.0001) and conduction velocity (85±26 versus 55±13 cm/s, P=0.03) beginning at 4 weeks after irradiation. In infarcted myocardium after irradiation, bipolar voltage amplitude of the infarct scar (2.0±2.9 versus 0.8±0.7 mV, P=0.008) was significantly reduced as well as the conduction velocity in the infarcted heart (43.7±15.7 versus 26.3±11.4 cm/s, P=0.02). There were no significant changes in bipolar voltage amplitude and conduction velocity in nonirradiated myocardium. Myocytolysis, capillary hyperplasia, and dilation were seen in the irradiated myocardium 8 weeks after irradiation. Active caspase-3 and reduction of connexin-43 expression began in irradiated myocardium 1 week after irradiation and decreased over 8 weeks. CONCLUSIONS: Irradiation of the myocardium with proton beams reduce connexin-43 expression, conduction velocity, and bipolar conducted electrogram amplitude in a large porcine model. The changes in biomarkers preceded electrophysiological changes after proton beam therapy.

Assessment of dose-volume histogram precision for five clinical systems.

PURPOSE: To 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. METHODS: DVHs 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. RESULTS: Calculation 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%. CONCLUSIONS: Commercial 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.

Managing treatment-related uncertainties in proton beam radiotherapy for gastrointestinal cancers.

In recent years, there has been rapid adaption of proton beam radiotherapy (RT) for treatment of various malignancies in the gastrointestinal (GI) tract, with increasing number of institutions implementing intensity modulated proton therapy (IMPT). We review the progress and existing literature regarding the technical aspects of RT planning for IMPT, and the existing tools that can help with the management of uncertainties which may impact the daily delivery of proton therapy. We provide an in-depth discussion regarding range uncertainties, dose calculations, image guidance requirements, organ and body cavity filling consideration, implanted devices and hardware, use of fiducials, breathing motion evaluations and both active and passive motion management methods, interplay effect, general IMPT treatment planning considerations including robustness plan evaluation and optimization, and finally plan monitoring and adaptation. These advances have improved confidence in delivery of IMPT for patients with GI malignancies under various scenarios.

A Monte-Carlo-based and GPU-accelerated 4D-dose calculator for a pencil beam scanning proton therapy system.

PURPOSE: The presence of respiratory motion during radiation treatment leads to degradation of the expected dose distribution, both for target coverage and healthy tissue sparing, particularly for techniques like pencil beam scanning proton therapy which have dynamic delivery systems. While tools exist to estimate this degraded four-dimensional (4D) dose, they typically have one or more deficiencies such as not including the particular effects from a dynamic delivery, using analytical dose calculations, and/or using nonphysical dose-accumulation methods. This work presents a clinically useful 4D-dose calculator that addresses each of these shortcomings. METHODS: To quickly compute the 4D dose, the three main tasks of the calculator were run on graphics processing units (GPUs). These tasks were (a) simulating the delivery of the plan using measured delivery parameters to distribute the plan amongst 4DCT phases characterizing the patient breathing, (b) using an in-house Monte Carlo simulation (MC) dose calculator to determine the dose delivered to each breathing phase, and (c) accumulating the doses from the various breathing phases onto a single phase for evaluation. The accumulation was performed by individually transferring the energy and mass of dose-grid subvoxels, a technique that models the transfer of dose in a more physically realistic manner. The calculator was run on three test cases, with lung, esophagus, and liver targets, respectively, to assess the various uncertainties in the beam delivery simulation as well as to characterize the dose-accumulation technique. RESULTS: Four-dimensional doses were successfully computed for the three test cases with computation times ranging from 4-6 min on a server with eight NVIDIA Titan X graphics cards; the most time-consuming component was the MC dose engine. The subvoxel-based dose-accumulation technique produced stable 4D-dose distributions at subvoxel scales of 0.5-1.0 mm without impairing the total computation time. The uncertainties in the beam delivery simulation led to moderate variations of the dose-volume histograms for these cases; the variations were reduced by implementing repainting or phase-gating motion mitigation techniques in the calculator. CONCLUSIONS: A MC-based and GPU-accelerated 4D-dose calculator was developed to estimate the effects of respiratory motion on pencil beam scanning proton therapy treatments. After future validation, the calculator could be used to assess treatment plans and its quick runtime would make it easily usable in a future 4D-robust optimization system.