Adapting to the motion of multiple independent targets using multileaf collimator tracking for locally advanced prostate cancer: Proof of principle simulation study Emily A. Hewson a) ACRF Image X Institute, University of Sydney Medical School, Sydney, NSW, Australia Yuanyuan Ge Nelune Comprehensive Cancer Centre, Prince of Wales Hospital, Sydney, NSW, Australia Ricky O’Brien ACRF Image X Institute, University of Sydney Medical School, Sydney, NSW, Australia Stephanie Roderick and Linda Bell Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia Per R. Poulsen Department of Oncology and Danish Center for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark Thomas Eade Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia Jeremy T. Booth Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia School of Physics, University of Sydney, Sydney, NSW, Australia Paul J. Keall ACRF Image X Institute, University of Sydney Medical School, Sydney, NSW, Australia Doan T. Nguyen ACRF Image X Institute, University of Sydney Medical School, Sydney, NSW, Australia School of Biomedical Engineering, Universityof Technology Sydney, Sydney, NSW, Australia (Received 11 September 2020; revised 21 October 2020; accepted for publication 23 October 2020; published 23 November 2020) Purpose: For patients with locally advanced cancer, multiple targets are treated simultaneously with radiotherapy. Differential motion between targets can compromise the treatment accuracy, yet there are currently no methods able to adapt to independent target motion. This study developed a multileaf collimator (MLC) tracking algorithm for differential motion adaptation and evaluated it in simulated treatments of locally advanced prostate cancer. Methods: A multi-target MLC tracking algorithm was developed that consisted of three steps: (a) dividing the MLC aperture into two possibly overlapping sections assigned to the prostate and lymph nodes, (b) calculating the ideally shaped MLC aperture as a union of the individually translated sec- tions, and (c) fitting the MLC positions to the ideal aperture shape within the physical constraints of the MLC leaves. The multi-target tracking method was evaluated and compared with two existing motion management methods: single-target tracking and no tracking. Treatment simulations of six locally advanced prostate cancer patients with three prostate motion traces were performed for all three motion adaptation methods. The geometric error for each motion adaptation method was calcu- lated using the area of overexposure and underexposure of each field. The dosimetric error was esti- mated by calculating the dose delivered to the prostate, lymph nodes, bladder, rectum, and small bowel using a motion-encoded dose reconstruction method. Results: Multi-target MLC tracking showed an average improvement in geometric error of 84% com- pared to single-target tracking, and 83% compared to no tracking. Multi-target tracking maintained dose coverage to the prostate clinical target volume (CTV) D98% and planning target volume (PTV) D95% to within 4.8% and 3.9% of the planned values, compared to 1.4% and 0.7% with single-target tracking, and 20.4% and 31.8% with no tracking. With multi-target tracking, the node CTV D95%, PTV D90%, and gross tumor volume (GTV) D95% were within 0.3%, 0.6%, and 0.3% of the planned values, com- pared to 9.1%, 11.2%, and 21.1% for single-target tracking, and 0.8%, 2.0%, and 3.2% with no tracking. The small bowel V57% was maintained within 0.2% to the plan using multi-target tracking, compared to 8% and 3.5% for single-target tracking and no tracking, respectively. Meanwhile, the bladder and rectum V50% increased by up to 13.6% and 5.2%, respectively, using multi-target tracking, compared to 2.7% and 1.9% for single-target tracking, and 11.2% and 11.5% for no tracking. 114 Med Phys 48 (1), January 2021 0094-2405/2021/48(1)/114/11 © 2020 American Association of Physicists in Medicine 114