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Background: Fiducial markers are used as surrogates for tumor location during radiation therapy treatment. Developments in lung fiducial marker and implantation technology have provided a means to insert markers endobronchially for tracking of lung tumors. This study quantifies the surrogacy uncertainty (SU) when using endobronchially implanted markers as a surrogate for lung tumor position., Methods: We evaluated SU for 17 patients treated in a prospective electromagnetic-guided MLC tracking trial. Tumor and markers were segmented on all phases of treatment planning 4DCTs and all frames of pretreatment kilovoltage fluoroscopy acquired from lateral and frontal views. The difference in tumor and marker position relative to end-exhale position was calculated as the SU for both imaging methods and the distributions of uncertainties analyzed., Results: The mean (range) tumor motion amplitude in the 4DCT scan was 5.9 mm (1.7-11.7 mm) in the superior-inferior (SI) direction, 2.2 mm (0.9-5.5 mm) in the left-right (LR) direction, and 3.9 mm (1.2-12.9 mm) in the anterior-posterior (AP) direction. Population-based analysis indicated symmetric SU centered close to 0 mm, with maximum 5th/95th percentile values over all axes of -2.0 mm/2.1 mm with 4DCT, and -2.3/1.3 mm for fluoroscopy. There was poor correlation between the SU measured with 4DCT and that measured with fluoroscopy on a per-patient basis. We observed increasing SU with increasing surrogate motion. Based on fluoroscopy analysis, the mean (95% CI) SU was 5% (2%-8%) of the motion magnitude in the SI direction, 16% (6%-26%) of the motion magnitude in the LR direction, and 33% (23%-42%) of the motion magnitude in the AP direction. There was no dependence of SU on marker distance from the tumor., Conclusion: We have quantified SU due to use of implanted markers as surrogates for lung tumor motion. Population 95th percentile range are up to 2.3 mm, indicating the approximate contribution of SU to total geometric uncertainty. SU was relatively small compared with the SI motion, but substantial compared with LR and AP motion. Due to uncertainty in estimations of patient-specific SU, it is recommended that population-based margins are used to account for this component of the total geometric uncertainty., (© 2021 American Association of Physicists in Medicine.)

Purpose: In multileaf collimator (MLC) tracking, the MLC positions from the original treatment plan are continuously modified to account for intrafraction tumor motion. As the treatment is adapted in real time, there is additional risk of delivery errors which cannot be detected using traditional pretreatment dose verification. The purpose of this work is to develop a system for real-time geometric verification of MLC tracking treatments using an electronic portal imaging device (EPID)., Methods: MLC tracking was utilized during volumetric modulated arc therapy (VMAT). During these deliveries, treatment beam images were taken at 9.57 frames per second using an EPID and frame grabber computer. MLC positions were extracted from each image frame and used to assess delivery accuracy using three geometric measures: the location, size, and shape of the radiation field. The EPID-measured field location was compared to the tumor motion measured by implanted electromagnetic markers. The size and shape of the beam were compared to the size and shape from the original treatment plan, respectively. This technique was validated by simulating errors in phantom test deliveries and by comparison between EPID measurements and treatment log files. The method was applied offline to images acquired during the LIGHT Stereotactic Ablative Body Radiotherapy (SABR) clinical trial, where MLC tracking was performed for 17 lung cancer patients. The EPID-based verification results were subsequently compared to post-treatment dose reconstruction., Results: Simulated field location errors were detected during phantom validation tests with an uncertainty of 0.28 mm (parallel to MLC motion) and 0.38 mm (perpendicular), expressed as a root-mean-square error (RMS Error ). For simulated field size errors, the RMS Error was 0.47 cm 2 and field shape changes were detected for random errors with standard deviation ≥ 2.5 mm. For clinical lung SABR deliveries, field location errors of 1.6 mm (parallel MLC motion) and 4.9 mm (perpendicular) were measured (expressed as a full-width-half-maximum). The mean and standard deviation of the errors in field size and shape were 0.0 ± 0.3 cm 2 and 0.3 ± 0.1 (expressed as a translation-invariant normalized RMS). No correlation was observed between geometric errors during each treatment fraction and dosimetric errors in the reconstructed dose to the target volume for this cohort of patients., Conclusion: A system for real-time delivery verification has been developed for MLC tracking using time-resolved EPID imaging. The technique has been tested offline in phantom-based deliveries and clinical patient deliveries and was used to independently verify the geometric accuracy of the MLC during MLC tracking radiotherapy., (© 2020 American Association of Physicists in Medicine.)

Purpose: Multileaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and pelvic motion during radiotherapy. The purpose of this work was to characterize the performance of two MLC leaf-fitting algorithms, direct optimization and piecewise optimization, for real-time motion compensation with different plan complexity and tumor trajectories., Methods: To test the algorithms, both in silico and phantom experiments were performed. The phantom experiments were performed on a Trilogy Varian linac and a HexaMotion programmable motion platform. High and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC leaf-fitting algorithms, the plans were run with their corresponding patient trajectories. To compare algorithms, the average exposure errors, i.e., the difference in shape between ideal and fitted MLC leaves by the algorithm, plan complexity and system latency of each experiment were calculated., Results: Comparison of exposure errors for the in silico and phantom experiments showed minor differences between the two algorithms. The average exposure errors for in silico experiments with low/high plan complexity were 0.66/0.88 cm 2 for direct optimization and 0.66/0.88 cm 2 for piecewise optimization, respectively. The average exposure errors for the phantom experiments with low/high plan complexity were 0.73/1.02 cm 2 for direct and 0.73/1.02 cm 2 for piecewise optimization, respectively. The measured latency for the direct optimization was 226 ± 10 ms and for the piecewise algorithm was 228 ± 10 ms. In silico and phantom exposure errors quantified for each treatment plan demonstrated that the exposure errors from the high plan complexity (0.96 cm 2 mean, 2.88 cm 2 95% percentile) were all significantly different from the low plan complexity (0.70 cm 2 mean, 2.18 cm 2 95% percentile) (P < 0.001, two-tailed, Mann-Whitney statistical test)., Conclusions: The comparison between the two leaf-fitting algorithms demonstrated no significant differences in exposure errors, neither in silico nor with phantom experiments. This study revealed that plan complexity impacts the overall exposure errors significantly more than the difference between the algorithms., (© 2019 American Association of Physicists in Medicine.)

Purpose: Most modern radiotherapy machines are built with a 2D kV imaging system. Combining this imaging system with a 2D-3D inference method would allow for a ready-made option for real-time 3D tumor tracking. This work investigates and compares the accuracy of four existing 2D-3D inference methods using both motion traces inferred from external surrogates and measured internally from implanted beacons., Method: Tumor motion data from 160 fractions (46 thoracic/abdominal patients) of Synchrony traces (inferred traces), and 28 fractions (7 lung patients) of Calypso traces (internal traces) from the LIGHT SABR trial (NCT02514512) were used in this study. The motion traces were used as the ground truth. The ground truth trajectories were used in silico to generate 2D positions projected on the kV detector. These 2D traces were then passed to the 2D-3D inference methods: interdimensional correlation, Gaussian probability density function (PDF), arbitrary-shape PDF, and the Kalman filter. The inferred 3D positions were compared with the ground truth to determine tracking errors. The relationships between tracking error and motion magnitude, interdimensional correlation, and breathing periodicity index (BPI) were also investigated., Results: Larger tracking errors were observed from the Calypso traces, with RMS and 95th percentile 3D errors of 0.84-1.25 mm and 1.72-2.64 mm, compared to 0.45-0.68 mm and 0.74-1.13 mm from the Synchrony traces. The Gaussian PDF method was found to be the most accurate, followed by the Kalman filter, the interdimensional correlation method, and the arbitrary-shape PDF method. Tracking error was found to strongly and positively correlate with motion magnitude for both the Synchrony and Calypso traces and for all four methods. Interdimensional correlation and BPI were found to negatively correlate with tracking error only for the Synchrony traces. The Synchrony traces exhibited higher interdimensional correlation than the Calypso traces especially in the anterior-posterior direction., Conclusion: Inferred traces often exhibit higher interdimensional correlation, which are not true representation of thoracic/abdominal motion and may underestimate kV-based tracking errors. The use of internal traces acquired from systems such as Calypso is advised for future kV-based tracking studies. The Gaussian PDF method is the most accurate 2D-3D inference method for tracking thoracic/abdominal targets. Motion magnitude has significant impact on 2D-3D inference error, and should be considered when estimating kV-based tracking error., (© 2018 American Association of Physicists in Medicine.)