喉部解剖学与形态计量学：跨学科协作与喉部病理个性化管理的基础

文献信息

中文摘要

喉部病理需要个体化管理，因为喉部在紧凑且高度可变的解剖框架内整合了气道保护、发声、吞咽和呼吸功能。本叙述性综述探讨了喉部解剖学和形态计量学如何支持肿瘤性、狭窄性、功能性和重建性喉部疾病的跨学科协作和个性化诊疗。研究定性综合了来自形态计量学研究、CT、MRI、内窥镜检查、超声检查、三维重建、人工智能和多学科临床工作流程的证据。关键参数——包括声带长度、声门宽度、甲状软骨角度、环状软骨直径、声门下直径、前连合厚度以及声门旁和会厌前间隙的状态——为诊断、T分期、气道评估、手术规划、重建和功能康复提供了可操作的信息。形态计量学具体地指导临床决策：甲状软骨角度指导甲状软骨成形术和嗓音外科手术规划；声门下直径支持狭窄手术和气道器械操作；前连合、弹性圆锥、软骨和深部间隙的测量则完善了肿瘤分期和切缘策略。技术加速器，包括人工智能分割、放射组学、3D打印、摄影测量和超声检查，将形态计量学从静态测量扩展到预测建模和患者特异性模拟。然而，其实施仍受限于CT协议异质性、测量平面不一致、先进技术可及性不均、缺乏全球规范性数据库以及围绕人工智能验证和数据治理的未解决伦理问题。本综述支持使用平行声带平面标准化CT形态计量学，在T1声门癌中常规测量前连合厚度，将超声检查作为嗓音诊所的一线形态计量工具，并针对人群特异性形态计量学标准验证人工智能分割。因此，喉部形态计量学应成为精准喉科学常规决策框架。

英文摘要

Laryngeal pathology requires individualized management because the larynx integrates airway protection, phonation, swallowing, and respiratory function within a compact and highly variable anatomical framework. This narrative review examines how laryngeal anatomy and morphometry support interdisciplinary collaboration and personalized care in oncologic, stenotic, functional, and reconstructive laryngeal disease. Evidence from morphometric studies, CT, MRI, endoscopy, ultrasonography, three-dimensional reconstruction, artificial intelligence, and multidisciplinary clinical workflows was synthesized qualitatively. Key parameters-including vocal fold length, glottic width, thyroid cartilage angle, cricoid diameter, subglottic diameter, anterior commissure thickness, and the status of paraglottic and pre-epiglottic spaces-provide actionable information for diagnosis, T-staging, airway assessment, surgical planning, reconstruction, and functional rehabilitation. Morphometry concretely informs clinical decisions: thyroid cartilage angle guides thyroplasty and phonosurgical planning; subglottic diameter supports stenosis surgery and airway instrumentation; and anterior commissure, conus elasticus, cartilage, and deep-space measurements refine oncologic staging and margin strategy. Technological accelerators, including AI segmentation, radiomics, 3D printing, photogrammetry, and ultrasonography, extend morphometry from static measurement toward predictive modeling and patient-specific simulation. However, implementation remains limited by heterogeneous CT protocols, inconsistent measurement planes, uneven access to advanced technologies, lack of global normative databases, and unresolved ethical issues surrounding AI validation and data governance. This review supports standardizing CT morphometry using parallel vocal fold planes, routinely measuring anterior commissure thickness in T1 glottic cancer, incorporating ultrasonography as a first-line morphometric tool in voice clinics, and validating AI segmentation against population-specific morphometric norms. Laryngeal morphometry should therefore become a routine decision-making framework for precision laryngology.