A dosimetric and robustness analysis of proton arc therapy with early energy layer and spot assignment for lung cancer versus conventional intensity modulated proton therapy
DOI:
https://doi.org/10.2340/1651-226X.2024.40549Keywords:
Treatment planning, 4D Robust optimisation, Interplay effect, UncertaintiesAbstract
Background and purpose: Intensity Modulated Proton Therapy (IMPT) faces challenges in lung cancer treatment, like maintaining plan robustness for moving tumors against setup, range errors, and interplay effects. Proton Arc Therapy (PAT) is an alternative to maintain target coverage, potentially improving organ at risk (OAR) sparing, reducing beam delivery time (BDT), and enhancing patient experience. We aim to perform a systematic plan comparison study between IMPT and energy layer (EL) and spot assignment algorithm – Proton Arc Therapy (ELSA-PAT) to assess its potential for lung cancer treatment.
Material and methods: A total of 14 Lung ELSA-PAT plans were compared retrospectively with IMPT plans. 4D worst-case minimax robust optimization was performed, including 84 scenarios (3%, 3 mm). Dosimetry assessment included target (clinical tumor volume [CTV]) and important OARs, on nominal and worst-case scenarios. Most relevant normal tissue complication probabilities (NTCP), target coverage robustness against interplay effect, and BDT were evaluated.
Results: CTV D95% and D98% showed no significant difference in comparison. PAT demonstrated better conformality by 66% (p = 0.00012) but delivered a higher heart mean dose (HMD, 23%). There was a 2% increase in NTCP 2-year mortality risk with PAT. Total BDT was comparable among techniques. IMPT was more robust than PAT against interplay effect, considering both D1% (1.0 ± 0.8 Gy vs 1.1 ± 1.4 Gy) and D98% bandwidths (0.9 ± 0.9 Gy vs 1.1 ± 1.3 Gy).
Interpretation: Both techniques provide a similar level of dose coverage to the target volume. Although PAT improved dose conformality, higher HMD translated into increased heart toxicity, presumably due to chosen planning methodology and OAR proximity to target. Increased ELs and spots raised PAT BDT, although it could improve daily treatment workflow.
Downloads
References
Chang JY, Jabbour SK, De Ruysscher D, et al. Consensus statement on proton therapy in early-stage and locally advanced non–small cell lung cancer. Int J Radiat Oncol Biol Phys. 2016;95:505–16.
https://doi.org/10.1016/j.ijrobp.2016.01.036 DOI: https://doi.org/10.1016/j.ijrobp.2016.01.036
Berman AT, Teo B-KK, Dolney D, et al. An in-silico comparison of proton beam and IMRT for postoperative radiotherapy in completely resected stage IIIA non-small cell lung cancer. Radiat Oncol. 2013;8:144.
https://doi.org/10.1186/1748-717X-8-144 DOI: https://doi.org/10.1186/1748-717X-8-144
Zhang X, Li Y, Pan X, et al. Intensity-modulated proton therapy reduces the dose to nor-mal tissue compared with intensity-modulated radiation therapy or passive scattering proton therapy and enables individualized radical radiotherapy for extensive stage IIIB non-small-cell lung cancer: a virtual clinical study. Int J Ra-diat Oncol Biol Phys. 2010;77:357–66.
https://doi.org/10.1016/j.ijrobp.2009.04.028 DOI: https://doi.org/10.1016/j.ijrobp.2009.04.028
Pastor-Serrano O, Habraken S, Lathouwers D, et al. How should we model and evaluate breathing interplay effects in IMPT? Phys Med Biol. 2021;66:235003.
https://doi.org/10.1088/1361-6560/ac383f DOI: https://doi.org/10.1088/1361-6560/ac383f
Inoue T, Widder J, van Dijk LV, et al. Limited impact of setup and range uncertainties, breathing motion, and interplay effects in robustly optimized intensity modu-lated proton therapy for stage III non-small cell lung cancer. Int J Radiat Oncol Biol Phys. 2016;96:661–9.
https://doi.org/10.1016/j.ijrobp.2016.06.2454 DOI: https://doi.org/10.1016/j.ijrobp.2016.06.2454
Ding X, Li X, Zhang JM, et al. Spot-scanning proton arc (SPArc) therapy: the first robust and delivery-efficient spot-scanning proton arc therapy. Int J Radiat Oncol Bi-ol Phys. 2016;96:1107–16.
https://doi.org/10.1016/j.ijrobp.2016.08.049 DOI: https://doi.org/10.1016/j.ijrobp.2016.08.049
Engwall E, Battinelli C, Wase V, et al. Fast robust optimization of proton PBS arc therapy plans using early energy layer selection and spot assignment. Phys Med Biol. 2022;67:065010.
https://doi.org/10.1088/1361-6560/ac55a6 DOI: https://doi.org/10.1088/1361-6560/ac55a6
Battinelli C. Proton arc therapy optimization [Internet]. diva-portal.org; 2019. Available from: https://www.diva-portal.org/smash/record.jsf?pid=diva2:1326105
Sanchez-Parcerisa D, Kirk M, Fager M, et al. Range optimization for mono- and bi-energetic proton modulated arc therapy with pencil beam scanning. Phys Med Biol. 2016;61:N565–74.
https://doi.org/10.1088/0031-9155/61/21/N565 DOI: https://doi.org/10.1088/0031-9155/61/21/N565
Langner U, Eley J, Guerrero M, et al. A method to deliver energy modulated planar proton arc therapy (EMPPAT) [Internet]. 2017. https://api.semanticscholar.org/CorpusID:126351052
Cao W, Li Y, Zhang X, et al. Intensity modulated proton arc therapy via geometry-based energy selection for ependymoma. J Appl Clin Med Phys. 2023;24:e13954.
https://doi.org/10.1002/acm2.13954 DOI: https://doi.org/10.1002/acm2.13954
Bertolet A, Carabe A. Proton monoenergetic arc therapy (PMAT) to enhance LETd within the target. Phys Med Biol. 2020;65:165006.
https://doi.org/10.1088/1361-6560/ab9455 DOI: https://doi.org/10.1088/1361-6560/ab9455
de Jong BA, Battinelli C, Free J, et al. Spot scanning proton arc therapy reduces toxicity in oropharyngeal cancer patients. Med Phys. 2023;50:1305–17.
https://doi.org/10.1002/mp.16098 DOI: https://doi.org/10.1002/mp.16098
Liu G, Li X, Qin A, et al. Improve the dosimetric outcome in bilateral head and neck cancer (HNC) treatment using spot-scanning proton arc (SPArc) therapy: a feasibility study. Radiat Oncol. 2020;15:21.
https://doi.org/10.1186/s13014-020-1476-9 DOI: https://doi.org/10.1186/s13014-020-1476-9
Ding X, Zhou J, Li X, et al. Improving dosimetric outcome for hippocampus and cochlea sparing whole brain radiotherapy using spot-scanning proton arc therapy. Acta Oncol. 2019;58:483–90.
https://doi.org/10.1080/0284186X.2018.1555374 DOI: https://doi.org/10.1080/0284186X.2018.1555374
Ding X, Li X, Qin A, et al. Have we reached proton beam therapy dosimetric limitations? – a novel robust, delivery-efficient and continuous spot-scanning proton arc (SPArc) therapy is to improve the dosimetric outcome in treating prostate cancer. Acta Oncol. 2018;57:435–7.
https://doi.org/10.1080/0284186X.2017.1358463 DOI: https://doi.org/10.1080/0284186X.2017.1358463
Chang S, Liu G, Zhao L, et al. Feasibility study: spot-scanning proton arc therapy (SPArc) for left-sided whole breast radiotherapy. Radiat Oncol. 2020;15:232.
https://doi.org/10.1186/s13014-020-01676-3 DOI: https://doi.org/10.1186/s13014-020-01676-3
Li X, Kabolizadeh P, Yan D, et al. Improve dosimetric outcome in stage III non-small-cell lung cancer treatment using spot-scanning proton arc (SPArc) therapy. Radiat Oncol. 2018;13:35.
https://doi.org/10.1186/s13014-018-0981-6 DOI: https://doi.org/10.1186/s13014-018-0981-6
Di Perri D, Lee JA, Bol A, et al. Evolution of [18F]fluorodeoxyglucose and [18F]fluoroazomycin arabinoside PET uptake distributions in lung tumours during radiation therapy. Acta Oncol. 2017;56:516–24.
https://doi.org/10.1080/0284186X.2017.1287943 DOI: https://doi.org/10.1080/0284186X.2017.1287943
Janssens G, Jacques L, Orban de Xivry J, et al. Diffeomorphic registration of images with variable contrast enhancement. Int J Biomed Imaging. 2011;2011:891585.
https://doi.org/10.1155/2011/891585 DOI: https://doi.org/10.1155/2011/891585
Wanet M, Sterpin E, Janssens G, et al. Validation of the mid-position strategy for lung tu-mors in helical TomoTherapy. Radiother Oncol. 2014;110:529–37.
https://doi.org/10.1016/j.radonc.2013.10.025 DOI: https://doi.org/10.1016/j.radonc.2013.10.025
Di Perri D, Lee JA, Bol A, et al. Correlation analysis of [18F]fluorodeoxyglucose and [18F]fluoroazomycin arabinoside uptake distributions in lung tumours dur-ing radiation therapy. Acta Oncol. 2017;56:1181–8.
https://doi.org/10.1080/0284186X.2017.1329594 DOI: https://doi.org/10.1080/0284186X.2017.1329594
Badiu V, Souris K, Buti G, et al. Improved healthy tissue sparing in proton therapy of lung tumors using statistically sound robust optimization and evaluation. Phys Med. 2022;96:62–9.
https://doi.org/10.1016/j.ejmp.2022.02.018 DOI: https://doi.org/10.1016/j.ejmp.2022.02.018
Fredriksson A, Forsgren A, Hårdemark B. Minimax optimization for handling range and setup uncertainties in proton therapy. Med Phys. 2011;38:1672–84.
https://doi.org/10.1118/1.3556559 DOI: https://doi.org/10.1118/1.3556559
van Herk M, Remeijer P, Rasch C, et al. The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys. 2000;47:1121–35.
https://doi.org/10.1016/S0360-3016(00)00518-6 DOI: https://doi.org/10.1016/S0360-3016(00)00518-6
Sterpin E, Rivas ST, Van den Heuvel F, et al. Development of robustness evaluation strate-gies for enabling statistically consistent reporting. Phys Med Biol. 2021;66:045002.
https://doi.org/10.1088/1361-6560/abd22f DOI: https://doi.org/10.1088/1361-6560/abd22f
Korevaar EW, Habraken SJM, Scandurra D, et al. Practical robustness evaluation in radio-therapy – a photon and proton-proof alternative to PTV-based plan evalua-tion. Radiother Oncol. 2019;141:267–74.
https://doi.org/10.1016/j.radonc.2019.08.005 DOI: https://doi.org/10.1016/j.radonc.2019.08.005
Wase V, Marthin O, Fredriksson A, et al. Optimizing the traversal time for gantry trajecto-ries for proton arc therapy treatment plans [Internet]. arXiv [physics.med-ph]. 2023. Available from: http://arxiv.org/abs/2310.12731
Wuyckens S, Dasnoy D, Janssens G, et al. OpenTPS – open-source treatment planning system for research in proton therapy. arXiv [physics.med-ph]. 2023. Available from: http://arxiv.org/abs/2303.00365
Souris K, Lee JA, Sterpin E. Fast multipurpose Monte Carlo simulation for proton therapy using multi- and many-core CPU architectures. Med Phys. 2016;43:1700.
https://doi.org/10.1118/1.4943377 DOI: https://doi.org/10.1118/1.4943377
Seco J, Gu G, Marcelos T, et al. Proton arc reduces range uncertainty effects and improves conformality compared with photon volumetric modulated arc therapy in ste-reotactic body radiation therapy for non-small cell lung cancer. Int J Radiat Oncol Biol Phys. 2013;87:188–94.
https://doi.org/10.1016/j.ijrobp.2013.04.048 DOI: https://doi.org/10.1016/j.ijrobp.2013.04.048
Engwall E, Marthin O, Wase V, et al. Partitioning of discrete proton arcs into interlaced subplans can bring proton arc advances to existing proton facilities. Med Phys. 2023;50:5723–33.
https://doi.org/10.1002/mp.16617 DOI: https://doi.org/10.1002/mp.16617
Tringale KR, Casey DL, Niyazov G, et al. Second cancer risk in childhood cancer survivors treated with intensity-modulated radiation therapy: an updated analysis of more than 10 years of follow-up. Pediatr Blood Cancer. 2022;69:e29600.
https://doi.org/10.1002/pbc.29600 DOI: https://doi.org/10.1002/pbc.29600
Stokkevåg CH, Schneider U, Muren LP, et al. Radiation-induced cancer risk predictions in proton and heavy ion radiotherapy. Phys Med. 2017;42:259–62.
https://doi.org/10.1016/j.ejmp.2017.04.022 DOI: https://doi.org/10.1016/j.ejmp.2017.04.022
de Jong BA, Korevaar EW, Maring A, et al. Proton arc therapy increases the benefit of pro-ton therapy for oropharyngeal cancer patients in the model based clinic. Ra-diother Oncol. 2023;184:109670.
https://doi.org/10.1016/j.radonc.2023.109670 DOI: https://doi.org/10.1016/j.radonc.2023.109670
Mazal A, Vera Sanchez JA, Sanchez-Parcerisa D, et al. Biological and mechanical synergies to deal with proton therapy pitfalls: minibeams, FLASH, arcs, and gantryless rooms. Front Oncol. 2020;10:613669.
https://doi.org/10.3389/fonc.2020.613669 DOI: https://doi.org/10.3389/fonc.2020.613669
Draguet C, Barragán-Montero AM, Vera MC, et al. Automated clinical decision support system with deep learning dose prediction and NTCP models to evaluate treatment complications in patients with esophageal cancer. Radiother On-col. 2022;176:101–7.
https://doi.org/10.1016/j.radonc.2022.08.031 DOI: https://doi.org/10.1016/j.radonc.2022.08.031
Darby SC, Ewertz M, McGale P, et al. Risk of ischemic heart disease in women after radio-therapy for breast cancer. N Engl J Med. 2013;368:987–98.
https://doi.org/10.1056/NEJMoa1209825 DOI: https://doi.org/10.1056/NEJMoa1209825
Additional Files
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2023 Macarena S. Chocan, Sophie Wuyckens, Damien Dasnoy, Dario Di Perri, Elena Borderias Villarruel, Erik Engwall, John A. Lee, Ana M. Barragan-Montero, Edmond Sterpin
This work is licensed under a Creative Commons Attribution 4.0 International License.
