Yang Yang, Xu Xinlin, Lacke Margaret, Zhuang Peiyun
Department of Voice, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Department of Surgery, Division of Otolaryngology-Head and Neck Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin.
J Voice. 2025 Jul;39(4):987-995. doi: 10.1016/j.jvoice.2023.01.003. Epub 2023 Jan 31.
To apply diffusion tensor imaging (DTI) in measurement of the diffusion characteristics of water molecules in vocal fold scar tissue, combined with the analysis of textural characteristics of collagen fibers in the cover layer of the vocal folds to explore the feasibility of DTI in the qualitative and quantitative diagnosis of vocal fold scars and the evaluation of microstructural changes of vocal fold scar tissue.
A unilateral injury was created using micro-cup forceps in the left vocal fold of six beagles. The contralateral normal vocal fold was used as a self-control. Five months postinjury, the larynges were excised and placed into a magnetic resonance imaging (MRI) system (9.4T BioSpec MRI, Bruker, German) for scanning and extraction of the diffusion parameters, fractional anisotropy (FA) and tensor trace in the anterior, middle, and posterior portions of the vocal fold cover layer. These parameters were then analyzed for statistical significance between the scarred vocal fold and the normal vocal fold. After MRI scanning, the tissue of the vocal folds was divided into anterior, middle, and posterior parts for sectioning and staining with hematoxylin and eosin, and samples were subsequently digitally scanned for texture analysis. The irregularity parameters, energy, contrast, correlation, and homogeneity, of collagen fibers of the vocal folds and the mean gray value of collagen fibers were calculated by the gray-level co-occurrence matrix (GLCM) texture analysis method. The differences in the mean value of the two sides of the vocal fold were compared. In addition, Pearson correlation analysis was performed between DTI parameters and irregularity parameters.
The FA of the left vocal fold cover layer was significantly lower compared to the self-control group (P = 0.0366), and the tensor trace value on the left vocal fold cover layer was significantly higher compared to the self-control group (P = 0.0353). The FA was significantly higher in the anterior part of the right vocal fold cover layer compared to the middle and posterior parts of the same side (P = 0.0352), and the tensor trace was significantly lower in the anterior part of the right vocal fold cover layer compared to the middle and posterior parts of the same side (P = 0.0298). There were no significant differences in FA and tensor trace between the middle and posterior parts of the vocal fold cover layer. The mean gray value of the left vocal folds cover layer was significantly smaller than the right vocal fold cover layer (P = 0.0219), the energy of the left vocal fold cover layer was significantly smaller than that of the right vocal fold cover layer (P < 0.0001), the contrast of the left vocal folds cover layer was significantly larger than that of the right vocal fold cover layer (P = 0.0002), the correlation of the left vocal folds cover layer was significantly smaller than the right vocal fold cover layer (P = 0.0002), and the homogeneity of the left vocal folds cover layer was significantly smaller than the right vocal fold cover layer (P = 0.0003). Pearson correlation analysis yielded values of r = 0.926, P = 0.000 between the FA and mean gray value; r = -0.918, P = 0.000 between FA and energy; r = -0.924, P = 0.000 between the FA and homogeneity, r = -0.949, P = 0.000 between tensor trace and mean gray value; r = 0.893, P = 0.000 between the tensor trace and energy; and r = 0.929, P = 0.000 between the tensor trace and homogeneity.
FA and tensor trace can be used as effective parameters to reflect microstructural changes in vocal fold scars. DTI is an objective and quantitative method of analyzing vocal fold scarring, and it noninvasively evaluates the microstructure of vocal fold collagen fibers.
应用扩散张量成像(DTI)测量声带瘢痕组织中水分子的扩散特性,并结合声带覆盖层胶原纤维的纹理特征分析,探讨DTI在声带瘢痕定性和定量诊断以及评估声带瘢痕组织微观结构变化方面的可行性。
使用微型杯状钳在6只比格犬的左侧声带造成单侧损伤。将对侧正常声带作为自身对照。损伤后5个月,切除喉部并放入磁共振成像(MRI)系统(9.4T BioSpec MRI,布鲁克,德国)进行扫描,提取声带覆盖层前部、中部和后部的扩散参数,即分数各向异性(FA)和张量迹。然后分析这些参数在瘢痕化声带与正常声带之间的统计学意义。MRI扫描后,将声带组织分为前、中、后三部分进行切片,并用苏木精和伊红染色,随后对样本进行数字扫描以进行纹理分析。通过灰度共生矩阵(GLCM)纹理分析方法计算声带胶原纤维的不规则度参数、能量、对比度、相关性和均匀性以及胶原纤维的平均灰度值。比较声带两侧的平均值差异。此外,对DTI参数与不规则度参数进行Pearson相关性分析。
左侧声带覆盖层的FA显著低于自身对照组(P = 0.0366),左侧声带覆盖层的张量迹值显著高于自身对照组(P = 0.0353)。右侧声带覆盖层前部的FA显著高于同侧中部和后部(P = 0.0352),右侧声带覆盖层前部的张量迹显著低于同侧中部和后部(P = 0.0298)。声带覆盖层中部和后部之间的FA和张量迹无显著差异。左侧声带覆盖层的平均灰度值显著小于右侧声带覆盖层(P = 0.0219),左侧声带覆盖层的能量显著小于右侧声带覆盖层(P < 0.0001),左侧声带覆盖层的对比度显著大于右侧声带覆盖层(P = 0.0002),左侧声带覆盖层的相关性显著小于右侧声带覆盖层(P = 0.0002),左侧声带覆盖层的均匀性显著小于右侧声带覆盖层(P = 0.0003)。Pearson相关性分析得出,FA与平均灰度值之间r = 0.926,P = 0.000;FA与能量之间r = -0.918,P = 0.000;FA与均匀性之间r = -0.924,P = 0.000;张量迹与平均灰度值之间r = -0.949,P = 0.000;张量迹与能量之间r = 0.893,P = 0.000;张量迹与均匀性之间r = 0.929,P = 0.000。
FA和张量迹可作为反映声带瘢痕微观结构变化的有效参数。DTI是一种分析声带瘢痕形成的客观定量方法,可无创评估声带胶原纤维的微观结构。