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Purpose: Long treatment sessions are a limitation within magnetic resonance imaging guided adaptive radiation therapy (MRIgART). This work aims for significantly enhancing the delivery efficiency on the magnetic resonance linear accelerator (MR-linac) by introducing dedicated optimization and delivery techniques for volumetric modulated arc therapy (VMAT). VMAT plan and delivery quality during MRIgART is compared with step-and-shoot intensity-modulated radiation therapy (IMRT) for prostate stereotactic body radiation therapy., Methods and Materials: Ten patients with prostate cancer previously treated on a 1.5T MR-linac were retrospectively replanned to 36.25 Gy in 5 fractions using step-and-shoot IMRT and the clinical Hyperion optimizer within Monaco (Hyp-IMRT), the same optimizer with a VMAT technique (Hyp-VMAT), and a research-based optimizer called optimal fluence levels and pseudo gradient descent with VMAT (OFL+PGD-VMAT). The plans were then adapted onto each daily magnetic resonance imaging data set using 2 different optimization strategies to evaluate the adapt-to-position workflow: "optimize weights" (IMRT-Weights and VMAT-Weights) and "optimize shapes" (IMRT-Shapes and VMAT-Shapes). Treatment efficiency was evaluated by measuring optimization time, delivery time, and total time (optimization+delivery). Plan quality was assessed by evaluating organ at risk sparing. Ten patient plans were measured using a modified linac control system to assess delivery accuracy via a gamma analysis (2%/2 mm). Delivery efficiency was calculated as average dose rate divided by maximum dose rate., Results: For Hyp-VMAT and OFL+PGD-VMAT, the total time was reduced by 124 ± 140 seconds (P = .020) and 459 ± 110 seconds (P < .001), respectively, as compared with the clinical Hyp-IMRT group. Speed enhancements were also measured for adapt-to-position with reductions in total time of 404 ± 55 (P < .001) for VMAT-Weights as compared with the clinical IMRT-Shapes group. Bladder and rectum dosimetric volume histogram (DVH) points were within 1.3% or 0.8 cc for each group. All VMAT plans had gamma passing rates greater than 96%. The delivery efficiency of VMAT plans was 89.7 ± 2.7 % compared with 50.0 ± 2.2 % for clinical IMRT., Conclusions: Incorporating VMAT into MRIgART will significantly reduce treatment session times while maintaining equivalent plan quality., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: To assess overall robustness and accuracy of a modified particle filter-based tracking algorithm for magnetic resonance (MR)-guided radiation therapy treatments., Methods and Materials: An improved particle filter-based tracking algorithm was implemented, which used a normalized cross-correlation function as the likelihood calculation. With a total of 5 healthy volunteers and 8 patients, the robustness of the algorithm was tested on 24 dynamic magnetic resonance imaging (MRI) time series with varying resolution, contrast, and signal-to-noise ratio. The complete data set included data acquired with different scan parameters on a number of MRI scanners with varying field strengths, including the 1.5T MR linear accelerator. Tracking errors were computed by comparing the results obtained by the particle filter algorithm with experts' delineations., Results: The ameliorated tracking algorithm was able to accurately track abdominal as well as thoracic tumors, whereas the previous Bhattacharyya distance-based implementation failed in more than 50% of the cases. The tracking error, combined over all MRI acquisitions, is 1.1 ± 0.4 mm, which demonstrated high robustness against variations in contrast, noise, and image resolution. Finally, the effect of the input/control parameters of the model was very similar across all cases, suggesting a class-based optimization is possible., Conclusions: The modified particle filter tracking algorithm is highly accurate and robust against varying image quality. This makes the algorithm a promising candidate for automated tracking on the MR linear accelerator., (Copyright © 2017 Elsevier Inc. All rights reserved.)