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Clinical implementation of MR-Linac systems in adaptive radiation therapy for head and neck cancer
Wu Runye, Yi Junlin
Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
Abstract Adaptive radiation therapy (ART) has been proposed as a method to account for changes in head and neck cancer and normal tissues to enhance the therapeutic ratios. Online magnetic resonance-guided radiotherapy (MRgRT) using hybrid MR-Linac systems is a novel innovative application in ART for head and neck cancer. The concept of MR-Linac systems is the ability to acquire MR images for ART and also online imaging during treatment delivery. Daily ART allows to improve the targeting accuracy while avoiding organs at risk for head and neck cancer. Although an increasing number of studies related to clinical application and technical aspect of MRgRT in head and neck cancer have been published, MRgRT for ART of head and neck cancer remains in its infancy. The purpose of this article is to summarize and discuss the rationale, clinical implementation, and prospect of this promising adaptive radiotherapy modality for treating head and neck cancer.
Corresponding Authors:
Yi Junlin, Email:yijunlin1969@163.com
Cite this article:
Wu Runye,Yi Junlin. Clinical implementation of MR-Linac systems in adaptive radiation therapy for head and neck cancer[J]. Chinese Journal of Radiation Oncology, 2022, 31(1): 20-23.
Wu Runye,Yi Junlin. Clinical implementation of MR-Linac systems in adaptive radiation therapy for head and neck cancer[J]. Chinese Journal of Radiation Oncology, 2022, 31(1): 20-23.
[1] VERESEZAN O, TROUSSIER I, LACOUT A, et al. Adaptive radiation therapy in head and neck cancer for clinical practice:state of the art and practical challenges[J]. Jpn J Radiol, 2017, 35(2):43-52. DOI:10.1007/s11604-016-0604-9.
[2] BHATNAGAR P, SUBESINGHE M, PATEL C, et al. Functional imaging for radiation treatment planning, response assessment, and adaptive therapy in head and neck cancer[J]. Radiographics, 2013, 33(7):1909-1929. DOI:10.1148/rg.337125163.
[3] WINKEL D, BOL GH, KROON PS, et al. Adaptive radiotherapy:The Elekta Unity MR-linac concept[J]. Clin TranslRadiat Oncol, 2019, 18:54-59. DOI:10.1016/j.ctro.2019.04.001.
[4] ECCLES CL, ADAIR SMITH G, BOWER L, et al. Magnetic resonance imaging sequence evaluation of an MR Linac system;early clinical experience[J]. Tech Innov Patient Support Radiat Oncol, 2019, 12:56-63. DOI:10.1016/j.tipsro.2019.11.004.
[5] RAGHAVAN G, KISHAN AU, CAO M, et al. Anatomic and dosimetric changes in patients with head and neck cancer treated with an integrated MRI-tri-(60) Co teletherapy device[J]. Br J Radiol, 2016, 89(1067):20160624. DOI:10.1259/bjr.20160624.
[6] FAST M, VAN DE SCHOOT A, VAN DE LINDT T, et al. Tumor Trailing for Liver SBRT on the MR-Linac[J]. Int J Radiat Oncol Biol Phys, 2019, 103(2):468-478. DOI:10.1016/j.ijrobp.2018.09.011.
[7] GANI C, BOEKE S, MCNAIR H, et al. Marker-less online MR-guided stereotactic body radiotherapy of liver metastases at a 1.5 T MR-Linac-Feasibility, workflow data and patient acceptance[J]. Clin TranslRadiat Oncol, 2021, 26:55-61. DOI:10.1016/j.ctro.2020.11.014.
[8] SPINDELDREIER CK, KLüTER S, HOEGEN P, et al. MR-guided radiotherapy of moving targets[J]. Radiologe, 2021. DOI:10.1007/s00117-020-00781-4.
[9] MATOBA M, TUJI H, SHIMODE Y, et al. Fractional change in apparent diffusion coefficient as an imaging biomarker for predicting treatment response in head and neck cancer treated with chemoradiotherapy[J]. AJNR Am J Neuroradiol, 2014, 35(2):379-385. DOI:10.3174/ajnr. A3706.
[10] VANDECAVEYE V, DIRIX P, DE KEYZER F, et al. Predictive value of diffusion-weighted magnetic resonance imaging during chemoradiotherapy for head and neck squamous cell carcinoma[J]. Eur Radiol, 2010, 20(7):1703-1714. DOI:10.1007/s00330-010-1734-6.
[11] VANDECAVEYE V, DIRIX P, DE KEYZER F, et al. Diffusion-weighted magnetic resonance imaging early after chemoradiotherapy to monitor treatment response in head-and-neck squamous cell carcinoma[J]. Int J Radiat Oncol Biol Phys, 2012, 82(3):1098-1107. DOI:10.1016/j.ijrobp.2011.02.044.
[12] KOOREMAN ES, VAN HOUDT PJ, NOWEE ME, et al. Feasibility and accuracy of quantitative imaging on a 1.5 T MR-linear accelerator[J]. Radiother Oncol, 2019, 133:156-162. DOI:10.1016/j.radonc.2019.01.011.
[13] YANG Y, CAO M, SHENG K, et al. Longitudinal diffusion MRI for treatment response assessment:preliminary experience using an MRI-guided tri-cobalt 60 radiotherapy system[J]. Med Phys, 2016, 43(3):1369-1373. DOI:10.1118/1.4942381.
[14] MCDONALD BA, VEDAM S, YANG J, et al. Initial feasibility and clinical implementation of daily mr-guided adaptive head and neck cancer radiation therapy on a 1.5T MR-Linac system:prospective R-IDEAL 2a/2b systematic clinical evaluation of technical innovation[J]. Int J Radiat Oncol Biol Phys, 2021, 109(5):1606-1618. DOI:10.1016/j.ijrobp.2020.12.015.
[15] HAGUE C, MCPARTLIN A, LEE LW, et al. An evaluation of MR based deep learning auto-contouring for planning head and neck radiotherapy[J]. Radiother Oncol, 2021, 158:112-117. DOI:10.1016/j.radonc.2021.02.018.
[16] BAHIG H, YUAN Y, MOHAMED A, et al. Magnetic resonance-based response assessment and dose adaptation in human papilloma virus positive tumors of the oropharynx treated with radiotherapy (MR-ADAPTOR):an R-IDEAL stage 2a-2b/bayesian phase Ⅱ trial[J]. Clin TranslRadiat Oncol, 2018, 13:19-23. DOI:10.1016/j.ctro.2018.08.003.