ALERT‐RA: an aperture library‐enabled real‐time respiratory motion adaptive framework for 4D‐VMAT. Issue 11 (9th October 2022)

• Record Type: Journal Article
• Authors: Christiansen, Eric Jessie; Xu, Tong; Heath, Emily
• Is Part Of: Medical physics. Volume 49:Issue 11(2022)
• Page Start: 6774
• Page End: 6793
• Publication Date: 2022-10-09
• Subjects: 4D‐VMAT -- respiratory motion -- robust optimization; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.15984
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract: Purpose: To develop a framework for robust optimization of real‐time respiratory motion adaptive VMAT treatment plans, and to evaluate the robustness of resulting plans to variations in tumor trajectory during delivery. Methods: The proposed framework is called aperture library‐enabled real‐time robust adaptation (ALERT‐RA). A patient‐specific library of optimized MLC apertures is defined for each combination of gantry angle and respiratory phase. The method assumes that the tumor is tracked in real‐time throughout delivery, and the aperture corresponding to the current phase and gantry angle will be delivered. The aperture library is optimized by considering all possible tumor trajectories determined by a probabilistic respiratory motion model. Plan robustness to trajectory variations was evaluated by sampling a trajectory, and determining the corresponding dose, from the respiratory model for each fraction. The cumulative dose of the full treatment course was simulated 50 times. Percentile dose–volume histograms (PDVHs) were computed from these simulated treatments. The resulting plan quality and robustness of this method were compared to other previously published motion 4D‐VMAT methods, including: an optimized tracking approach that assumes reproducible tumor motion, conformal tracking with aperture deformation, and a motion‐encompassing method. Two fractionation schemes were tested to determine the possible effect on robustness: a conventional fractionation of 66 Gy in 33 fractions, and an SBRT course with 60 Gy in 5 fractions. Results: When considering target coverage, the ALERT‐RA method was found to produce a plan which was more robust than those produced using the optimized or conformal tracking methods. Using the PDVH analysis, the 5th and 95th percentiles of the prescription dose volume for the conventionally fractioned plan were found to be (respectively) 79% and 82% for the optimized tracking approach, 81% and 83% for the conformal tracking approach, and 92% and 97% using the new ALERT‐RA method. The motion‐encompassing plan was slightly more robust than the ALERT‐RA plan, with 5th and 95th percentiles at 94% and 95%, respectively. This came at a cost of higher dose to OARs, with the volume of lung receiving 5 Gy or more equal to 48% for the motion‐encompassing plan versus 44% for the ALERT‐RA plan. For the SBRT plan, the conformal tracking plan was similarly not robust, with 5th and 95th percentiles of the prescription dose volume equal to 88% and 89%. The optimized tracking SBRT plan gave values of 93% and 95%, and the motion‐encompassing plan 94% and 95%, while the ALERT‐RA gave values of 93% and 96%. The volume of lung receiving 20 Gy or more was slightly higher for the optimized tracking and motion‐encompassing plans compared to the ALERT‐RA plan, at 15%, 15%, and 14%, respectively. Conclusions: Compared to other motion‐adaptive VMAT approaches, the ALERT‐RA algorithm is capable of delivering high‐quality plans which are robust to variations in tumor motion trajectories.