Quantitative evaluation of the human vocal fold extracellular matrix using multiphoton microscopy and optical coherence tomography

Sensitivity of Phonation Onset Pressure to Vocal Fold Stiffness Distribution

Phonation onset is characterized by the unstable growth of vocal fold (VF) vibrations that ultimately results in self-sustained oscillation and the production of modal voice. Motivated by histological studies, much research has focused on the role of the layered structure of the vocal folds in influencing phonation onset, wherein the outer "cover" layer is relatively soft and the inner "body" layer is relatively stiff. Recent research, however, suggests that the body-cover (BC) structure over-simplifies actual stiffness distributions by neglecting important spatial variations, such as inferior-superior (IS) and anterior-posterior gradients and smooth transitions in stiffness from one histological layer to another. Herein, we explore sensitivity of phonation onset to stiffness gradients and smoothness. By assuming no a priori stiffness distribution and considering a second-order Taylor series sensitivity analysis of phonation onset pressure with respect to stiffness, we find two general smooth stiffness distributions most strongly influence onset pressure: a smooth stiffness containing aspects of BC differences and IS gradients in the cover, which plays a role in minimizing onset pressure, and uniform increases in stiffness, which raise onset pressure and frequency. While the smooth stiffness change contains aspects qualitatively similar to layered BC distributions used in computational studies, smooth transitions in stiffness result in higher sensitivity of onset pressure than discrete layering. These two general stiffness distributions also provide a simple, low-dimensional, interpretation of how complex variations in VF stiffness affect onset pressure, enabling refined exploration of the effects of stiffness distributions on phonation onset.

Versatile fiber-reinforced hydrogels to mimic the microstructure and mechanics of human vocal-fold upper layers

Human vocal folds are remarkable soft laryngeal structures that enable phonation due to their unique vibro-mechanical performances. These properties are tied to their specific fibrous architecture, especially in the upper layers, which comprise a gel-like composite called lamina propria. The lamina propria can withstand large and reversible deformations under various multiaxial loadings. Despite their importance, the relationships between the microstructure of vocal folds and their resulting macroscopic properties remain poorly understood. There is a need for versatile models that encompass their structural complexity while mimicking their mechanical features. In this study, we present a candidate model inspired by histological measurements of the upper layers of human vocal folds. Bi-photonic observations were used to quantify the distribution, orientation, width, and volume fraction of collagen and elastin fibers between histological layers. Using established biomaterials, polymer fiber-reinforced hydrogels were developed to replicate the fibrillar network and ground substance of native vocal fold tissue. To achieve this, jet-sprayed poly(ε-caprolactone) fibrillar mats were successfully impregnated with poly(L-lysine) dendrimers/polyethylene glycol hydrogels. The resulting composites exhibited versatile structural, physical and mechanical properties that could be customized through variations in the chemical formulation of their hydrogel matrix, the microstructural architecture of their fibrous networks (i.e., fiber diameter, orientation and volume fraction) and their assembly process. By mimicking the collagen network of the lamina propria with polymer fibers and the elastin/ground substance with the hydrogel composition, we successfully replicated the non-linear, anisotropic, and viscoelastic mechanical behavior of the vocal-fold upper layers, accounting for inter/intra-individual variations. The development of this mimetic model offers promising avenues for a better understanding of the complex mechanisms involved in voice production. STATEMENT OF SIGNIFICANCE: Human vocal folds are outstanding vibrating soft living tissues allowing phonation. Simple physical models that take into account the histological structure of the vocal fold and recapitulate its mechanical features are scarce. As a result, the relations between tissue components, organisation and vibro-mechanical performances still remain an open question. We describe here the development and the characterization of fiber-reinforced hydrogels inspired from the vocal-fold microstructure. These systems are able to reproduce the mechanics of vocal-fold tissues upon realistic cyclic and large strains under various multi-axial loadings, thus providing a mimetic model to further understand the impact of the fibrous network microstructure in phonation.

Using Diffusion Tensor Imaging to Explore the Changes in the Microstructure of Canine Vocal Fold Scar Tissue

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.

Identification of human ovarian cancer relying on collagen fiber coverage features by quantitative second harmonic generation imaging

Ovarian cancer has the highest mortality rate among all gynecological cancers, containing complicated heterogeneous histotypes, each with different treatment plans and prognoses. The lack of screening test makes new perspectives for the biomarker of ovarian cancer of great significance. As the main component of extracellular matrix, collagen fibers undergo dynamic remodeling caused by neoplastic activity. Second harmonic generation (SHG) enables label-free, non-destructive imaging of collagen fibers with submicron resolution and deep sectioning. In this study, we developed a new metric named local coverage to quantify morphologically localized distribution of collagen fibers and combined it with overall density to characterize 3D SHG images of collagen fibers from normal, benign and malignant human ovarian biopsies. An overall diagnosis accuracy of 96.3% in distinguishing these tissue types made local and overall density signatures a sensitive biomarker of tumor progression. Quantitative, multi-parametric SHG imaging might serve as a potential screening test tool for ovarian cancer.

Optical Microscopy and the Extracellular Matrix Structure: A Review

Biological tissues are not uniquely composed of cells. A substantial part of their volume is extracellular space, which is primarily filled by an intricate network of macromolecules constituting the extracellular matrix (ECM). The ECM serves as the scaffolding for tissues and organs throughout the body, playing an essential role in their structural and functional integrity. Understanding the intimate interaction between the cells and their structural microenvironment is central to our understanding of the factors driving the formation of normal versus remodelled tissue, including the processes involved in chronic fibrotic diseases. The visualization of the ECM is a key factor to track such changes successfully. This review is focused on presenting several optical imaging microscopy modalities used to characterize different ECM components. In this review, we describe and provide examples of applications of a vast gamut of microscopy techniques, such as widefield fluorescence, total internal reflection fluorescence, laser scanning confocal microscopy, multipoint/slit confocal microscopy, two-photon excited fluorescence (TPEF), second and third harmonic generation (SHG, THG), coherent anti-Stokes Raman scattering (CARS), fluorescence lifetime imaging microscopy (FLIM), structured illumination microscopy (SIM), stimulated emission depletion microscopy (STED), ground-state depletion microscopy (GSD), and photoactivated localization microscopy (PALM/fPALM), as well as their main advantages, limitations.