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Hewson EA, Nguyen DT, Le A, Booth JT, Keall PJ, Mejnertsen L. Optimising multi-target multileaf collimator tracking using real-time dose for locally advanced prostate cancer patients. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac8967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 08/12/2022] [Indexed: 11/11/2022]
Abstract
Abstract
Objective. The accuracy of radiotherapy for patients with locally advanced cancer is compromised by independent motion of multiple targets. To date, MLC tracking approaches have used 2D geometric optimisation where the MLC aperture shape is simply translated to correspond to the target’s motion, which results in sub-optimal delivered dose. To address this limitation, a dose-optimised multi-target MLC tracking method was developed and evaluated through simulated locally advanced prostate cancer treatments. Approach. A dose-optimised multi-target tracking algorithm that adapts the MLC aperture to minimise 3D dosimetric error was developed for moving prostate and static lymph node targets. A fast dose calculation algorithm accumulated the planned dose to the prostate and lymph node volumes during treatment in real time, and the MLC apertures were recalculated to minimise the difference between the delivered and planned dose with the included motion. Dose-optimised tracking was evaluated by simulating five locally advanced prostate plans and three prostate motion traces with a relative interfraction displacement. The same simulations were performed using geometric-optimised tracking and no tracking. The dose-optimised, geometric-optimised, and no tracking results were compared with the planned doses using a 2%/2 mm γ criterion. Main results. The mean dosimetric error was lowest for dose-optimised MLC tracking, with γ-failure rates of 12% ± 8.5% for the prostate and 2.2% ± 3.2% for the nodes. The γ-failure rates for geometric-optimised MLC tracking were 23% ± 12% for the prostate and 3.6% ± 2.5% for the nodes. When no tracking was used, the γ-failure rates were 37% ± 28% for the prostate and 24% ± 3.2% for the nodes. Significance. This study developed a dose-optimised multi-target MLC tracking method that minimises the difference between the planned and delivered doses in the presence of intrafraction motion. When applied to locally advanced prostate cancer, dose-optimised tracking showed smaller errors than geometric-optimised tracking and no tracking for both the prostate and nodes.
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Mejnertsen L, Hewson E, Nguyen DT, Booth J, Keall P. Dose-based optimisation for multi-leaf collimator tracking during radiation therapy. Phys Med Biol 2021; 66:065027. [PMID: 33607648 DOI: 10.1088/1361-6560/abe836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Motion in the patient anatomy causes a reduction in dose delivered to the target, while increasing dose to healthy tissue. Multi-leaf collimator (MLC) tracking has been clinically implemented to adapt dose delivery to account for intrafraction motion. Current methods shift the planned MLC aperture in the direction of motion, then optimise the new aperture based on the difference in fluence. The drawback of these methods is that 3D dose, a function of patient anatomy and MLC aperture sequence, is not properly accounted for. To overcome the drawback of current fluence-based methods, we have developed and investigated real-time adaptive MLC tracking based on dose optimisation. A novel MLC tracking algorithm, dose optimisation, has been developed which accounts for the moving patient anatomy by optimising the MLC based on the dose delivered during treatment, simulated using a simplified dose calculation algorithm. The MLC tracking with dose optimisation method was applied in silico to a prostate cancer VMAT treatment dataset with observed intrafraction motion. Its performance was compared to MLC tracking with fluence optimisation and, as a baseline, without MLC tracking. To quantitatively assess performance, we computed the dose error and 3D γ failure rate (2 mm/2%) for each fraction and method. Dose optimisation achieved a γ failure rate of (4.7 ± 1.2)% (mean and standard deviation) over all fractions, which was significantly lower than fluence optimisation (7.5 ± 2.9)% (Wilcoxon sign-rank test p < 0.01). Without MLC tracking, a γ failure rate of (15.3 ± 12.9)% was achieved. By considering the accumulation of dose in the moving anatomy during treatment, dose optimisation is able to optimise the aperture to actively target regions of underdose while avoiding overdose.
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Affiliation(s)
- Lars Mejnertsen
- ACRF Image X Institute, Faculty of Medicine and Health, University of Sydney, NSW, Australia
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Hewson EA, Ge Y, O'Brien R, Roderick S, Bell L, Poulsen PR, Eade T, Booth JT, Keall PJ, Nguyen DT. Adapting to the motion of multiple independent targets using multileaf collimator tracking for locally advanced prostate cancer: Proof of principle simulation study. Med Phys 2020; 48:114-124. [PMID: 33124079 DOI: 10.1002/mp.14572] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 10/21/2020] [Accepted: 10/23/2020] [Indexed: 01/22/2023] Open
Abstract
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 sections, 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 calculated using the area of overexposure and underexposure of each field. The dosimetric error was estimated 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% compared 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, compared 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. CONCLUSIONS A multi-target tracking algorithm was developed and tracked the prostate and lymph nodes independently during simulated treatments. As the algorithm optimizes for target coverage, tracking both targets simultaneously may increase the dose delivered to the organs at risk.
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Affiliation(s)
- Emily A Hewson
- 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
- Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW, Australia
| | - 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, University of Technology Sydney, Sydney, NSW, Australia
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Hewson EA, Nguyen DT, O'Brien R, Poulsen PR, Booth JT, Greer P, Eade T, Kneebone A, Hruby G, Moodie T, Hayden AJ, Turner SL, Hardcastle N, Siva S, Tai KH, Martin J, Keall PJ. Is multileaf collimator tracking or gating a better intrafraction motion adaptation strategy? An analysis of the TROG 15.01 stereotactic prostate ablative radiotherapy with KIM (SPARK) trial. Radiother Oncol 2020; 151:234-241. [DOI: 10.1016/j.radonc.2020.08.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 07/17/2020] [Accepted: 08/16/2020] [Indexed: 12/30/2022]
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Glitzner M, Fast MF, de Senneville BD, Nill S, Oelfke U, Lagendijk JJW, Raaymakers BW, Crijns SPM. Real-time auto-adaptive margin generation for MLC-tracked radiotherapy. Phys Med Biol 2017; 62:186-201. [PMID: 27991457 PMCID: PMC5952335 DOI: 10.1088/1361-6560/62/1/186] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Revised: 10/16/2016] [Accepted: 11/09/2016] [Indexed: 11/12/2022]
Abstract
In radiotherapy, abdominal and thoracic sites are candidates for performing motion tracking. With real-time control it is possible to adjust the multileaf collimator (MLC) position to the target position. However, positions are not perfectly matched and position errors arise from system delays and complicated response of the electromechanic MLC system. Although, it is possible to compensate parts of these errors by using predictors, residual errors remain and need to be compensated to retain target coverage. This work presents a method to statistically describe tracking errors and to automatically derive a patient-specific, per-segment margin to compensate the arising underdosage on-line, i.e. during plan delivery. The statistics of the geometric error between intended and actual machine position are derived using kernel density estimators. Subsequently a margin is calculated on-line according to a selected coverage parameter, which determines the amount of accepted underdosage. The margin is then applied onto the actual segment to accommodate the positioning errors in the enlarged segment. The proof-of-concept was tested in an on-line tracking experiment and showed the ability to recover underdosages for two test cases, increasing [Formula: see text] in the underdosed area about [Formula: see text] and [Formula: see text], respectively. The used dose model was able to predict the loss of dose due to tracking errors and could be used to infer the necessary margins. The implementation had a running time of 23 ms which is compatible with real-time requirements of MLC tracking systems. The auto-adaptivity to machine and patient characteristics makes the technique a generic yet intuitive candidate to avoid underdosages due to MLC tracking errors.
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Affiliation(s)
- M Glitzner
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - M F Fast
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - B Denis de Senneville
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Mathematical Institute of Bordeaux, UMR 5251 CNRS/University of Bordeaux, 33405 Talence Cedex, France
| | - S Nill
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - U Oelfke
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - J J W Lagendijk
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - B W Raaymakers
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - S P M Crijns
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
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