Summary
Objective
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.
Methods
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.
Results
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.
Conclusion
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.
Key Words
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Article info
Publication history
Published online: January 30, 2023
Accepted:
January 3,
2023
Publication stage
In Press Corrected ProofFootnotes
This study was supported by the National Natural Science Foundation (No. 81970871).
The authors had no conflict of interest to declare.
Identification
Copyright
© 2023 The Voice Foundation. Published by Elsevier Inc. All rights reserved.
