AccScience Publishing / CP / Online First / DOI: 10.36922/cp.5395
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ORIGINAL RESEARCH ARTICLE

Evaluating the clinical feasibility of magnetic resonance imaging positioning plates for head and neck radiotherapy through image registration

Xueqi Bai1 ,  Xiaoying Zhang2 ,  Ying Lu1 ,  Yannan Xu1 ,  Rong Li1*
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1 Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, Shanxi, China
2 Cancer Center, Shanxi Provincial Traditional Chinese Medicine Hospital, Taiyuan, Shanxi, China
CP, 5395 https://doi.org/10.36922/cp.5395
Received: 22 October 2024 | Revised: 10 August 2025 | Accepted: 3 December 2025 | Published online: 8 January 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Conventional computed tomography-magnetic resonance imaging (CT-MRI) fusion for head and neck radiotherapy is often limited by registration uncertainty from inconsistent positioning and immobilization between diagnostic MRI and CT simulation. This study evaluates the practicality of using MRI positioning plates for head and neck tumors through image registration. A total of 35 patients with head and neck tumors were retrospectively included. Two sets of MRI data were obtained, with and without the positioning plate. These scans were fused with simulated CT images using either rigid registration (RIR) or deformable registration, generating four image combinations: CT/MRI positioning plate_RIR, CT/MRI positioning plate_DIR, CT/MRI_RIR, and CT/MRI_DIR (referred to as SETS1-4). Gross tumor volume (GTV) and organs at risk (OARs) were delineated on each image set. GTVs, OARs, and dose distributions from SET1 were used as reference values, and the overlap of GTV with OAR and dose variations were compared with SETS2-4. Image registration accuracy was assessed using geometric evaluation metrics, including the dice similarity coefficient (DSC), Jaccard similarity coefficient (JSC), Hausdorff distance (HD), and mean distance to agreement (MDA). Compared with the reference registration method, all registration methods for GTVs and most OARs showed statistically significant differences in DSC, JSC, HD, and MDA (p<0.05), except for the brainstem. Notably, compared with MRI images without the positioning plate, the GTV and OAR volumes in SETS1 and SETS2 demonstrated high three-dimensional overlap (DSC > 0.7) and close margin agreement (MDA < 2 mm). For head and neck tumors, MRI images obtained with the positioning plate in the treatment position showed substantial geometric similarity to simulated CT scans through RIR. This similarity enables the use of MRI for radiotherapy target delineation, providing a significant advantage for clinical practice in hospitals without MRI simulators.

Keywords
Magnetic resonance imaging positioning plate
Rigid registration
Deformable registration
Head and neck tumors
Funding
None.
Conflict of interest
The authors declare they have no competing interests.
References
  1. Xia C, Dong X, Li H, et al. Cancer statistics in China and United States, 2022: Profiles, trends, and determinants. Chin Med J (Engl). 2022;135(5):584-590. doi: 10.1097/cm9.0000000000002108

 

  1. Marur S, Forastiere AA. Head and neck squamous cell carcinoma: Update on epidemiology, diagnosis, and treatment. Mayo Clin Proc. 2016;91(3):386-396. doi: 10.1016/j.mayocp.2015.12.017

 

  1. Zhang S, Zeng N, Yang J, et al. Advancements of radiotherapy for recurrent head and neck cancer in modern era. Radiat Oncol. 2023;18(1):166. doi: 10.1186/s13014-023-02342-0

 

  1. Van Der Veen J, Gulyban A, Nuyts S. Interobserver variability in delineation of target volumes in head and neck cancer. Radiother Oncol. 2019;137:9-15. doi: 10.1016/j.radonc.2019.04.006

 

  1. Jensen K, Al-Farra G, Dejanovic D, et al. Imaging for target delineation in head and neck cancer radiotherapy. Semin Nucl Med. 2021;51(1):59-67. doi: 10.1053/j.semnuclmed.2020.07.010

 

  1. Metcalfe P, Liney GP, Holloway L, et al. The potential for an enhanced role for MRI in radiation-therapy treatment planning. Technol Cancer Res Treat. 2013;12(5):429-446. doi: 10.7785/tcrt.2012.500342

 

  1. Wong KH, Panek R, Bhide SA, Nutting CM, Harrington KJ, Newbold KL. The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: An oncologist’s perspective. Br J Radiol. 2017;90(1071):20160768. doi: 10.1259/bjr.20160768

 

  1. Palmér E, Nordström F, Karlsson A, Petruson K, Ljungberg M, Sohlin M. Head and neck cancer patient positioning using synthetic CT data in MRI-only radiation therapy. J Appl Clin Med Phys. 2022;23(4):e13525. doi: 10.1002/acm2.13525

 

  1. Geevarghese R, O’Gorman Tuura R, Lumsden DE, Samuel M, Ashkan K. Registration accuracy of CT/MRI fusion for localisation of deep brain stimulation electrode position: An imaging study and systematic review. Stereotact Funct Neurosurg. 2016;94(3):159-163. doi: 10.1159/000446609

 

  1. Djan I, Petrović B, Erak M, Nikolić I, Lucić S. Radiotherapy treatment planning: Benefits of CT-MR image registration and fusion in tumor volume delineation. Vojnosanit Pregl. 2013;70(8):735-739. doi: 10.2298/vsp110404001d

 

  1. Joint Head and Neck MRI-Radiotherapy Development Cooperative, Kiser K, Meheissen MAM, et al. Prospective quantitative quality assurance and deformation estimation of MRI-CT image registration in simulation of head and neck radiotherapy patients. Clin Transl Radiat Oncol. 2019;18:120-127. doi: 10.1016/j.ctro.2019.04.018

 

  1. Paulson ES, Crijns SP, Keller BM, et al. Consensus opinion on MRI simulation for external beam radiation treatment planning. Radiother Oncol. 2016;121(2):187-192. doi: 10.1016/j.radonc.2016.09.018

 

  1. Keall PJ, Brighi C, Glide-Hurst C, et al. Integrated MRI-guided radiotherapy - opportunities and challenges. Nat Rev Clin Oncol. 2022;19(7):458-470. doi: 10.1038/s41571-022-00631-3

 

  1. Lagendijk JJ, Raaymakers BW, Van Vulpen M. The magnetic resonance imaging-linac system. Semin Radiat Oncol. 2014;24(3):207-209. doi: 10.1016/j.semradonc.2014.02.009

 

  1. Potter R, Kirisits C, Fidarova EF, et al. Present status and future of high-precision image guided adaptive brachytherapy for cervix carcinoma. Acta Oncol. 2008;47(7):1325-1336. doi: 10.1080/02841860802282794

 

  1. Kuperman VY, Figueiredo G. Technical note: New similarity index for radiotherapy and medical imaging. Med Phys. 2020;47(9):4325-4331. doi: 10.1002/mp.14234

 

  1. Taha AA, Hanbury A. Metrics for evaluating 3D medical image segmentation: Analysis, selection, and tool. BMC Med Imaging. 2015;15:29. doi: 10.1186/s12880-015-0068-x

 

  1. Brock KK, Mutic S, McNutt TR, Li H, Kessler ML. Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM radiation therapy committee task group no. 132. Med Phys. 2017;44(7):e43-e76. doi: 10.1002/mp.12256

 

  1. Junn JC, Soderlund KA, Glastonbury CM. Imaging of head and neck cancer with CT, MRI, and US. Semin Nucl Med. 2021;51(1):3-12. doi: 10.1053/j.semnuclmed.2020.07.005

 

  1. Chung NN, Ting LL, Hsu WC, Lui LT, Wang PM. Impact of magnetic resonance imaging versus CT on nasopharyngeal carcinoma: Primary tumor target delineation for radiotherapy. Head Neck. 2004;26(3):241-246. doi: 10.1002/hed.10378

 

  1. Jonsson J, Nyholm T, Söderkvist K. The rationale for MR-only treatment planning for external radiotherapy. Clin Transl Radiat Oncol. 2019;18:60-65. doi: 10.1016/j.ctro.2019.03.005

 

  1. Scholey JE, Rajagopal A, Vasquez EG, Sudhyadhom A, Larson PEZ. Generation of synthetic megavoltage CT for MRI-only radiotherapy treatment planning using a 3D deep convolutional neural network. Med Phys. 2022;49(10): 6622-6634. doi: 10.1002/mp.15876

 

  1. Choi JH, Lee D, O’Connor L, et al. Bulk anatomical density based dose calculation for patient-specific quality assurance of MRI-only prostate radiotherapy. Front Oncol. 2019;9:997. doi: 10.3389/fonc.2019.00997

 

  1. Yuen J, Barber J, Ralston A, et al. An international survey on the clinical use of rigid and deformable image registration in radiotherapy. J Appl Clin Med Phys. 2020;21(10):10-24. doi: 10.1002/acm2.12957

 

  1. Barber J, Yuen J, Jameson M, et al. Deforming to best practice: Key considerations for deformable image registration in radiotherapy. J Med Radiat Sci. 2020;67(4):318-332. doi: 10.1002/jmrs.417

 

  1. Dowling JA, O’Connor LM. Deformable image registration in radiation therapy. J Med Radiat Sci. 2020;67(4):257-259. doi: 10.1002/jmrs.446

 

  1. Kai Y, Arimura H, Toya R, et al. Comparison of rigid and deformable image registration for nasopharyngeal carcinoma radiotherapy planning with diagnostic position PET/CT. Jpn J Radiol. 2020;38(3):256-264. doi: 10.1007/s11604-019-00911-6

 

  1. Fortin D, Basran PS, Berrang T, Peterson D, Wai ES. Deformable versus rigid registration of PET/CT images for radiation treatment planning of head and neck and lung cancer patients: A retrospective dosimetric comparison. Radiat Oncol. 2014;9:50. doi: 10.1186/1748-717x-9-50

 

  1. Reitz D, Muecke J, Da Silva Mendes V, et al. Intrafractional monitoring of patients using four different immobilization mask systems for cranial radiotherapy. Phys Imaging Radiat Oncol. 2022;23:134-139. doi: 10.1016/j.phro.2022.07.002

 

  1. Prusator MT, Zhao T, Kavanaugh JA, et al. Evaluation of a new secondary dose calculation software for Gamma Knife radiosurgery. J Appl Clin Med Phys. 2020;21(1):95-102. doi: 10.1002/acm2.12794

 

  1. Christiansen RL, Johansen J, Zukauskaite R, et al. Accuracy of automatic structure propagation for daily magnetic resonance image-guided head and neck radiotherapy. Acta Oncol. 2021;60(5):589-597. doi: 10.1080/0284186x.2021.1891282

 

  1. Hanvey S, McJury M, Tho LM, et al. The influence of MRI scan position on patients with oropharyngeal cancer undergoing radical radiotherapy. Radiat Oncol. 2013;8:129. doi: 10.1186/1748-717x-8-129
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Cancer Plus, Electronic ISSN: 2661-3840 Print ISSN: 2661-3832, Published by AccScience Publishing
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