基于U-HRCT的面神经管三维分段标注方法的建立及长度测量研究OA
Study on Three-dimensional Labeling,Segmentation,and Length Measurement of the Facial Nerve Canal Based on Ultra-high-resolution Computed Tomography
建立面神经管三维标注方法及分段的统一标准,并基于此测量正常人群的面神经管各段长度参数,从而提供初步的量化参考数据.纳入 47例健康受试者的超高分辨力 CT颞骨图像数据,建立统一的面神经管全长三维手动标注方法,得到面神经管三维重建结果.标记面神经管特征点,将面神经管分为 4段:迷路段、膝状神经节段、鼓室段和乳突段,并对各段进行长度测量.面神经管各段长度分别为 2.89(2.31,3.64)mm、(2.52±0.86)mm、(11.75±2.16)mm、(16.06±2.07)mm,面神经管总长度为(33.31±1.97)mm.各段长度间存在显著性差异,其中乳突段最长,鼓室段次之,迷路段与膝状神经节段最短且二者间无统计学差异.本研究通过建立标准化面神经管标注方法,提出包括膝状神经节段在内的 4段分段标准,得到正常成人面神经管各段长度的初步量化参考数据,可为后续面神经相关疾病的影像学研究提供正常对照参考依据,并为后续自动化测量算法的开发奠定数据基础.
We developed a protocol for three-dimensional(3D)annotation and segmentation of the facial nerve canal and measured the length parameters of each segment in healthy individuals to provide preliminary quantitative reference data.Ultra-high-resolution computed tomography(U-HRCT)images of the temporal bone were acquired from 47 healthy individuals.A 3D manual annotation protocol for the entire course of the facial nerve canal was established,and 3D reconstruction was performed.A four-segment classification scheme for the facial nerve canal was proposed by identifying the following anatomical landmarks:the labyrinthine,geniculate ganglion,tympanic,and mastoid segments;the length of each segment was measured as 2.89(2.31,3.64)mm,(2.52±0.86)mm,(11.75±2.16)mm,and(16.06±2.07)mm,respectively.The total length of the facial nerve canal was(33.31±1.97)mm.Statistically significant differences were observed among the lengths of the four segments,with the mastoid segment being the longest,followed by the tympanic.The labyrinthine and geniculate ganglion segments were the shortest,with no statistically significant differences between them.By establishing a facial nerve canal annotation protocol and proposing a four-segment classification that includes the geniculate ganglion as an independent segment,this study provides preliminary quantitative reference data for normal adult facial nerve canal lengths.These findings provide a reference for imaging studies on facial nerve-related diseases and establish a foundation for the future development of automated measurement algorithms.
张景茜;任玉雪;郭琦涵;郭思慧;周辰;赵鹏飞;尹红霞
首都医科大学附属北京友谊医院 放射科,北京 100050||首都医科大学附属北京友谊医院 医学工程处,北京 100050首都师范大学 交叉科学研究院,北京 100048首都师范大学 数学科学学院,北京 100048首都医科大学附属北京友谊医院 放射科,北京 100050首都医科大学医学技术学院,北京 100069首都医科大学附属北京友谊医院 放射科,北京 100050首都医科大学附属北京友谊医院 放射科,北京 100050||首都医科大学附属北京友谊医院 医学工程处,北京 100050||首都医科大学附属北京友谊医院 院士实验室(精准与智慧影像实验室),北京 100050||专用 CT/MR 精细成像设备创新与转化北京市重点实验室,北京 100050
医药卫生
超高分辨力CT面神经管分段面神经管长度
ultra-high-resolution CTfacial nerve canalsegmentationlength of facial nerve canal
《CT理论与应用研究》 2026 (5)
896-905,10
北京市科技计划项目(耳鼻喉双源锥形束计算机体层摄影设备示范应用(Z241100009024020))北京市自然科学基金面上项目(基于U-HRCT的耳科手术面神经损伤风险智能预警关键技术研究(7252281))国家自然科学基金面上项目(基于医学知识介导的中耳病变超高分辨力CT智能判读关键技术研究(62371316)).
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