基于多模态医学影像融合的数字化技术在颌面部复杂肿瘤治疗中的研究进展

doi:10.13591/j.cnki.kqyx.2025.10.012

摘要/Abstract

摘要：

颌面部复杂肿瘤由于解剖结构复杂,毗邻多个重要神经血管,手术难度及风险较大,对外科医生而言是个巨大的挑战。传统单模成像常需医师综合不同的影像特点进行分析,这种分离式诊断为临床带来极大的不便。近年来,随着数字化技术逐渐应用于颌面部肿瘤的治疗,可以更立体直观地显示肿瘤部位、侵袭范围及其与神经血管的关系,大大降低了手术风险。本文主要就多模态医学影像融合技术在复杂颌面部肿瘤中的临床应用及其与快速成型技术、混合现实技术、手术导航、手术机器人、人工智能等数字化外科技术的联合应用作一综述和展望。

关键词: 颌面部, 影像融合, 混合现实技术, 手术导航, 手术机器人, 人工智能

Abstract:

Complex tumors of the maxillofacial region are difficult and risky to operate due to the complex anatomical structure and the proximity of multiple important neurovascular vessels, which is a great challenge for surgeons. Traditional single-mode imaging often requires physicians to synthesize different image features for analysis, and this kind of detached diagnosis brings great inconvenience to clinical practice. In recent years, with the increasing application of digital technology in the treatment of maxillofacial tumors, it is possible to display the tumor site, invasion range and its relationship with neurovascularity in a more three-dimensional and intuitive way, which greatly reduces the risk of surgery. In this paper, we focus on the clinical application of multimodal medical image fusion technology in complex maxillofacial tumors and its joint application with digital surgical technologies such as rapid prototyping technology, mixed reality technology, surgical navigation, surgical robotics, artificial intelligence, etc., to give an overview and outlook.

Key words: maxillofacial, image fusion, mixed reality technology, surgical navigation, surgical robotics, artificial intelligence

中图分类号:

R739.8
R782

陈媛媛, 章旺茹, 李志萍, 孟箭. 基于多模态医学影像融合的数字化技术在颌面部复杂肿瘤治疗中的研究进展[J]. 口腔医学, 2025, 45(10): 789-794.

CHEN Yuanyuan, ZHANG Wangru, LI Zhiping, MENG Jian. Research progress of digital technology based on multimodal medical image fusion in the treatment of complex tumors of the maxillofacial region[J]. Stomatology, 2025, 45(10): 789-794.

参考文献 47

[1]	Ehrl D, Brueggemann A, Broer PN, et al. Scalp reconstruction after malignant tumor resection: An analysis and algorithm[J]. J Neurol Surg B Skull Base, 2020, 81(2): 149-157.
[2]	Kraeima J, Dorgelo B, Gulbitti HA, et al. Multi-modality 3D mandibular resection planning in head and neck cancer using CT and MRI data fusion: A clinical series[J]. Oral Oncol, 2018, 81: 22-28. doi: S1368-8375(18)30115-5 pmid: 29884410
[3]	Huang B, Yang F, Yin MX, et al. A review of multimodal medical image fusion techniques[J]. Comput Math Methods Med, 2020, 2020: 8279342.
[4]	Jiang XY, Hu ZJ, Wang SH, et al. Deep learning for medical image-based cancer diagnosis[J]. Cancers, 2023, 15(14): 3608.
[5]	Yang R, Lu H, Wang Y, et al. CT-MRI image fusion-based computer-assisted navigation management of communicative tumors involved the infratemporal-middle cranial Fossa[J]. J Neurol Surg B Skull Base, 2021, 82(Suppl 3): e321-e329.
[6]	Haribabu M, Guruviah V, Yogarajah P. Recent advancements in multimodal medical image fusion techniques for better diagnosis: An overview[J]. Curr MedImaging, 2023, 19(7): 673-694.
[7]	黄渝萍, 李伟生. 医学图像融合方法综述[J]. 中国图象图形学报, 2023, 28(1): 118-143.
[8]	Azam MA, Khan KB, Salahuddin S, et al. A review on multimodal medical image fusion: Compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics[J]. Comput Biol Med, 2022, 144: 105253.
[9]	Xu H, Yuan JT, Ma JY. MURF: Mutually reinforcing multi-modal image registration and fusion[J]. IEEE Trans Pattern Anal Mach Intell, 2023, 45(10): 12148-12166.
[10]	Chen YH, Liu AP, Liu Y, et al. Multi-dimensional medical image fusion with complex sparse representation[J]. IEEE Trans Biomed Eng, 2024, 71(9): 2728-2739.
[11]	Tang L, Hui Y, Yang H, et al. Medical image fusion quality assessment based on conditional generative adversarial network[J]. Front Neurosci, 2022, 16: 986153.
[12]	郭建徕, 聂斐, 周绪经, 等. CT和MRI融合配准在口腔颌面部肿瘤中的应用[J]. 医学理论与实践, 2023, 36(11): 1920-1922.
[13]	Kraeima J, Schepers RH, van Ooijen PM, et al. Integration of oncologic margins in three-dimensional virtual planning for head and neck surgery, including a validation of the software pathway[J]. J Craniomaxillofac Surg, 2015, 43(8): 1374-1379. doi: 10.1016/j.jcms.2015.07.015 pmid: 26302937
[14]	Jian ZH, Li JY, Wu KH, et al. Surgical effects of resecting skull base tumors using pre-operative multimodal image fusion technology: A retrospective study[J]. Front Neurol, 2022, 13: 895638.
[15]	谭铭昱, 花浩镪, 熊奇炜, 等. 基于微电流刺激的多强度分级虚拟触觉反馈[J]. 计算机研究与发展, 2023, 60(9): 2015-2027.
[16]	Choi HY, Yoon DY, Kim ES, et al. Diagnostic performance of CT, MRI, and their combined use for the assessment of the direct cranial or intracranial extension of malignant head and neck tumors[J]. Acta Radiol, 2019, 60(3): 301-307. doi: 10.1177/0284185118778883 pmid: 29804473
[17]	Hu LH, Zhang WB, Yu Y, et al. Accuracy of multimodal image fusion for oral and maxillofacial tumors: A revised evaluation method and its application[J]. J Craniomaxillofac Surg, 2020, 48(8): 741-750.
[18]	Tarsitano A, Ricotta F, Baldino G, et al. Navigation-guided resection of maxillary tumours: The accuracy of computer-assisted surgery in terms of control of resection margins: A feasibility study[J]. J Craniomaxillofac Surg, 2017, 45(12): 2109-2114. doi: S1010-5182(17)30332-3 pmid: 29092758
[19]	Zrnc TA, Wallner J, Zemann W, et al. Assessment of tumor margins in head and neck cancer using a 3D-navigation system based on PET/CT image-fusion: A pilot study[J]. J Craniomaxillofac Surg, 2018, 46(4): 617-623.
[20]	Debacker JM, Schelfhout V, Brochez L, et al. High-resolution ¹⁸F-FDG PET/CT for assessing three-dimensional intraoperative margins status in malignancies of the head and neck, a proof-of-concept[J]. J Clin Med, 2021, 10(16): 3737.
[21]	Yu Y, Zhang WB, Liu XJ, et al. Three-dimensional image fusion of ¹⁸F-fluorodeoxyglucose-positron emission tomography/computed tomography and contrast-enhanced computed tomography for computer-assisted planning of maxillectomy of recurrent maxillary squamous cell carcinoma and defect reconstruction[J]. J Oral Maxillofac Surg, 2017, 75(6): 1301.e1-1301301.e15.
[22]	Shimada K, Miyake K, Yamaguchi I, et al. Efficacy of utilizing both 3-dimensional multimodal fusion image and intra-arterial indocyanine green videoangiography in cerebral arteriovenous malformation surgery[J]. World Neurosurg, 2023, 169: e260-e269.
[23]	Yajima H, Koizumi S, Kanda T, et al. Possible association between recurrent chronic subdural hematoma and dural arteriovenous fistula: A case report with three-dimensional fusion images[J]. NMC Case Rep J, 2023, 10: 41-45. doi: 10.2176/jns-nmc.2022-0301 pmid: 37020742
[24]	樊文慧, 劳峥, 石慧烽, 等. 3D打印可分离式口腔支架在口腔癌放疗中的摆位准确性研究[J]. 中国口腔颌面外科杂志, 2022, 20(5): 466-470.
[25]	Herpel C, Schwindling FS, Held T, et al. Individualized 3D-printed tissue retraction devices for head and neck radiotherapy[J]. Front Oncol, 2021, 11: 628743.
[26]	冯孟昭, 王国庆, 张晓阳, 等. 3D打印技术在颅底肿瘤显微手术中的临床应用[J]. 郑州大学学报(医学版), 2019, 54(1): 123-126.
[27]	Park BJ, Hunt SJ, Martin C 3rd, et al. Augmented and mixed reality: Technologies for enhancing the future of IR[J]. J Vasc Interv Radiol, 2020, 31(7): 1074-1082. doi: S1051-0443(19)30825-5 pmid: 32061520
[28]	Bartella AK, Hoshal SG, Lethaus B, et al. Computer assisted skull base surgery: A contemporary review[J]. Innov Surg Sci, 2023, 8(3): 149-157.
[29]	Bollen E, Awad L, Langridge B, et al. The intraoperative use of augmented and mixed reality technology to improve surgical outcomes: A systematic review[J]. Int J Med Robot, 2022, 18(6): e2450.
[30]	闫大勇, 蔡晓清, 郭乐乐, 等. 多模态混合现实技术在颅颌面头颈肿瘤中的临床应用[J]. 口腔医学, 2021, 41(8): 709-714.
[31]	Liu SF, Wang H, Wang CX, et al. Intra-operative 3D hologram support with mixed reality technique based on CT-MRI fusion images: Operation guidance for brain brachytherapy[J]. J Contemp Brachytherapy, 2021, 13(2): 205-210.
[32]	Zhuang A, Wang SY, Yuan QY, et al. Surgical repair of large orbital floor and medial wall fractures with destruction of the inferomedial strut: Initial experience with a combined endoscopy navigation technique[J]. J Plast Reconstr Aesthet Surg, 2023, 77: 104-110. doi: 10.1016/j.bjps.2022.11.005 pmid: 36563635
[33]	Topley M, Richards JG. A comparison of currently available optoelectronic motion capture systems[J]. J Biomech, 2020, 106: 109820.
[34]	Pietruski P, Majak M, Świᶏtek-Najwer E, et al. Replacing cutting guides with an augmented reality-based navigation system: A feasibility study in the maxillofacial region[J]. Int J Med Robot, 2023, 19(3): e2499.
[35]	Fang DD, Yang C, Zhou HY, et al. Effects of CT/MRI image fusion on cerebrovascular protection, postoperative complications, and limb functional recovery in patients with anterior and middle skull base tumors: Based on a retrospective cohort study[J]. Contrast Media Mol Imaging, 2022, 2022: 7855576.
[36]	Ranz-Colio Á, Almeida-Parra F, De Leyva-Moreno P, et al. Navigation-guided resection of locally advanced midface malignancies. Does it improve the safety of oncologic resection?[J]. Oral Oncol, 2023, 143: 106455.
[37]	Tang ZN, Hu LH, Soh HY, et al. Accuracy of mixed reality combined with surgical navigation assisted oral and maxillofacial tumor resection[J]. Front Oncol, 2021, 11: 715484.
[38]	Tang ZN, Hu LH, Yu Y, et al. Mixed reality combined with surgical navigation in resection of micro- and mini-tumors of the parotid gland: A pilot study[J]. Laryngoscope, 2024, 134(4): 1670-1678.
[39]	Chan HHL, Haerle SK, Daly MJ, et al. An integrated augmented reality surgical navigation platform using multi-modality imaging for guidance[J]. PLoS One, 2021, 16(4): e0250558.
[40]	Wojtera B, Szewczyk M, Pieńkowski P, et al. Artificial intelligence in head and neck surgery: Potential applications and future perspectives[J]. J Surg Oncol, 2024, 129(6): 1051-1055.
[41]	靳能皓, 孟凡皓, 乔波, 等. 多模态图像自动配准融合技术联合手术机器人在面侧深区肿瘤诊疗中的应用[J]. 中国医学影像学杂志, 2023, 31(6): 572-576.
[42]	Saeidi H, Opfermann JD, Kam M, et al. Autonomous robotic laparoscopic surgery for intestinal anastomosis[J]. Sci Robot, 2022, 7(62): eabj2908.
[43]	Bramhe S, Pathak SS. Robotic surgery: A narrative review[J]. Cureus, 2022, 14(9): e29179.
[44]	Peng ZY, Wang YM, Wang YX, et al. Application of radiomics and machine learning in head and neck cancers[J]. Int J Biol Sci, 2021, 17(2): 475-486. doi: 10.7150/ijbs.55716 pmid: 33613106
[45]	Khanagar SB, Alkadi L, Alghilan MA, et al. Application and performance of artificial intelligence (AI) in oral cancer diagnosis and prediction using histopathological images: A systematic review[J]. Biomedicines, 2023, 11(6): 1612.
[46]	Kong WW, Li C, Lei Y. Multimodal medical image fusion using convolutional neural network and extreme learning machine[J]. Front Neurorobot, 2022, 16: 1050981.
[47]	Le WT, Vorontsov E, Romero FP, et al. Cross-institutional outcome prediction for head and neck cancer patients using self-attention neural networks[J]. Sci Rep, 2022, 12(1): 3183. doi: 10.1038/s41598-022-07034-5 pmid: 35210482