Moll Manon C M, Karssemakers Luc H E, Baarsma Milou, Braun Loes M M, Ter Beek Leon C, van der Mierden Stevie, Karakullukcu Baris, Smeele Ludi E, van Alphen Maarten J A, Valstar Matthijs H
Department of Head and Neck Surgery and Oncology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek, Plesmanlaan 121 1066 CX, Amsterdam, The Netherlands.
Academic Centre of Dentistry Amsterdam, Vrije Universiteit, Gustav Mahlerlaan 3004, 1081 LA, , Amsterdam, The Netherlands.
Eur Radiol Exp. 2025 Aug 8;9(1):70. doi: 10.1186/s41747-025-00608-8.
BACKGROUND: Technical advances in magnetic resonance imaging (MRI) acquisition and reconstruction have improved the visualization of anatomical structures such as cranial nerves (CNs) and enabled subsequent three-dimensional (3D) models for use in clinical care. However, a comprehensive overview of indications and techniques is lacking. The current study aimed to comprehensively describe and assess the techniques and applications used in MRI-based 3D modeling of CNs. METHODS: We conducted a systematic review of articles published in Medline, Embase, and Scopus databases on clinically applied MRI-based 3D models of CNs up to December 2023. We modified the Quality Assessment Tool for Diagnostic Accuracy Studies to assess the risk of bias. RESULTS: We analyzed 37 studies presenting virtual 3D models of CNs II, III, and V-X in proximity to pathologies in the head and neck area and intracranial, including vestibular schwannoma, skull base tumors, cerebellopontine angle tumors, and neurovascular compression syndrome. Certain studies explored alternative visualization modalities, including printed and augmented reality models. The creation of these 3D models involved the utilization of several MRI sequences and segmentation tools. The models demonstrate potential benefits for preoperative planning, intraoperative decision-making, and patient counseling. CONCLUSION: MRI-specific sequences and segmentation techniques render CNs in 3D models, helping before and during surgery. RELEVANCE STATEMENT: MRI-based 3D models of cranial nerves help surgeons before and during surgery and enhance patient understanding of the procedure and its risks. Wider clinical adoption requires an established workflow, technical expertise, and collaboration to ensure accessibility and knowledge sharing. KEY POINTS: 3D modeling of cranial nerves is a promising tool for preoperative planning, surgery, and patient-doctor communication. Data heterogeneity and small sample sizes hinder definitive conclusions about the best MRI techniques and segmentation protocols for 3D visualization of cranial nerves. Adopting MRI-based 3D models widely needs a set workflow, technical skills, and team collaboration.
背景：磁共振成像（MRI）采集和重建技术的进步改善了诸如颅神经（CNs）等解剖结构的可视化，并催生了后续用于临床护理的三维（3D）模型。然而，目前缺乏对适应症和技术的全面概述。本研究旨在全面描述和评估基于MRI的颅神经3D建模中使用的技术和应用。 方法：我们对截至2023年12月在Medline、Embase和Scopus数据库中发表的关于临床应用的基于MRI的颅神经3D模型的文章进行了系统综述。我们修改了诊断准确性研究的质量评估工具以评估偏倚风险。 结果：我们分析了37项研究，这些研究展示了在头颈部区域和颅内病变附近的CNs II、III和V-X的虚拟3D模型，包括前庭神经鞘瘤、颅底肿瘤、桥小脑角肿瘤和神经血管压迫综合征。某些研究探索了替代可视化方式，包括打印和增强现实模型。这些3D模型的创建涉及多种MRI序列和分割工具的使用。这些模型显示出对术前规划、术中决策和患者咨询的潜在益处。 结论：特定于MRI的序列和分割技术在3D模型中呈现颅神经，有助于手术前和手术过程中。 相关性声明：基于MRI的颅神经3D模型在手术前和手术过程中帮助外科医生，并增强患者对手术及其风险的理解。更广泛的临床应用需要既定的工作流程、技术专长和协作，以确保可及性和知识共享。 关键点：颅神经的3D建模是术前规划、手术和医患沟通的一个有前景的工具。数据异质性和小样本量阻碍了关于用于颅神经3D可视化的最佳MRI技术和分割方案得出明确结论。广泛采用基于MRI的3D模型需要一套工作流程、技术技能和团队协作。
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