Quantitative assessment of biomechanical changes in oral lesions at different cancerous stages using optical coherence elastography

Introduction

Oral cancer is the 6^th most common cancer worldwide, and due to its extremely malignant nature, it has a 5-year mortality rate of 50% (1,2). Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer, and generally develops from precursor lesions of oral potentially malignant disorders (OPMDs) (3). Most patients experience a long phase of OPMDs before being diagnosed with cancer, and may not present with obvious symptoms that could aid in early diagnosis (4,5).

Biopsy and histopathologic evaluation are cornerstones in the diagnosis of OPMDs and OSCC (6). Nevertheless, the invasive nature and lengthy detection procedure of biopsy limit its application in long-term monitoring and early diagnosis (7). Imaging examinations such as magnetic resonance imaging or ultrasonography are minimally invasive and can enable early cancer detection; however, these techniques have a number of shortcomings, such as high costs, limited resolution, and tissue contrast that may be insufficient for the accurate identification of oral lesions (8-12). Photographic medical imaging is a cost-effective and rapid oral screening approach, and artificial intelligence systems have achieved detection rates of 82–89% (13,14). However, three key barriers hinder the clinical adoption of such systems: operator-dependent variability (>15% diagnostic inconsistency due to lighting/angular differences), a lack of standardized quantitative biomarkers, and demanding protocol standardization requirements (13,14). Many emerging techniques have been proposed to address these shortcomings, such as fluorescence imaging and confocal microscopy, but these techniques usually pose challenges such as the need for exogenous contrast materials, complicated handling, and concerns related to user safety (15-17).

At present, several potential challenges arise during the screening and early diagnosis of OPMDs and OSCC. Optical coherence tomography (OCT) is an imaging technology that has several advantages, such as a high resolution (2–10 µm) and imaging depth (1–2 mm), good sensitivity, non-radiation damaging properties, and real-time detection (18-20). OCT has shown significant potential in oral cancer animal models for detecting disease-induced tissue alterations; however, it primarily provides structural contrast (21), and several notable limitations persist when applying OCT in clinical practice. For example, the typical penetration depth of OCT systems in oral tissues is limited to 1–2 mm, which is insufficient for evaluating deep tumor margins in advanced cases (e.g., lesions invading the submucosal or muscular layers) (22,23). Additionally, signal attenuation caused by highly keratinized regions (e.g., the dorsal tongue surface), saliva, and blood contamination reduces diagnostic accuracy by 15–20% (24,25). Our research team sought to improve the application of OCT by enhancing its contrast through the examination of the mechanical characteristics of tissues. As an elastography technique that can enable the evaluation of the biomechanical characteristics of tissues, optical coherence elastography (OCE) can be coupled to record qualitative or quantitative measurements of tissue stiffness (26,27).

In the present study, we established a shaker-based OCE (shaker-OCE) system for quantitative measurements of mechanical properties of tissues. We aimed to monitor the variability in the biomechanical course of OSCC during lesion development using OCE, and then to explore the correlation between changes in soft tissue elasticity and the degree of tissue degeneration in an oral cancer model. We present this article in accordance with the ARRIVE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2359/rc).

Methods

Animal model and protocol

Oral cancer was induced by spiking the drinking water of Sprague-Dawley (SD) rats with 4-nitroquinoline-1-oxide (4NQO). 4NQO, a water-soluble carcinogen, selectively targets oral mucosa, particularly in the tongue (28). 4NQO induces carcinogenesis through a relatively natural process, allowing for a more realistic simulation of the occurrence and development of human cancers (2,29). Therefore, it serves as a relatively ideal animal model. This is a relatively ideal animal model. The resulting changes in the course of carcinogenesis and morphological traits involving the gradual progression from hyperplasia and dysplasia to squamous cell carcinoma (SCC) contribute to the development of human OSCC (29,30). Experiments were performed under a project license (No. NCULAE-20240827001) granted by the Animal Ethics Committee of Nanchang University and in compliance with institutional guidelines for the care and use of animals.

In total, 45 male SD rats (5 weeks old) weighing about 200 g were purchased from GemPharmatech Co., Ltd. (Nanjing, China) [No. SCXK(SU) 2023-0009] for this study. Of the 45 rats, 35 were provided drinking water spiked with 100 µg/mL of water-soluble 4NQO (Sigma-Aldrich, St. Louis, MO, USA), and 10 control rats were not exposed to 4NQO. OCE imaging was performed at weeks 10, 12, 16, 24, and 32 following the initiation of the 4NQO treatment. At every scheduled time slot, two control and seven experimental rats were imaged (Figure 1A). The rats were anesthetized by an intraperitoneal injection of 40 mg/kg phenobarbital before being scanned. Their cheeks were cut open, and the tongue tip was carefully protruded and secured. Optical and mechanical properties were measured for each rat at three locations along the length of the tongue, and the average value of the measurements was employed to characterize the sample (Figure 1B,1C). The rats were sacrificed once the images were acquired, and their tongue tissues were excised, stained, and preserved for histological examination.

Figure 1 Experimental protocol. (A) Experimental schedule, number of rats, and experimental results. (B) Sample excitation and OCE measurement procedures. Excitation (yellow) was performed at the uppermost position of the scan, and scanned along the propagation path (black). (Black arrows: inked potential tumor and histological sections). (C) Representative photographs of the tongues of 4NQO treated rats. 4NQO, 4-nitroquinoline-1-oxide; CIS, carcinoma in situ; LGD, low-grade dysplasia; M-HGD, moderate-high-grade dysplasia; OCE, optical coherence elastography; SCC, squamous cell carcinoma; wk, week.

System setup

As Figure 2 shows, the shaker-OCE system comprises a swept-source OCT unit and an excitation unit. The swept-source OCT unit employs a scanning laser with the following properties: a center wavelength of 1,310 nm; an A-line rate of 50 kHz; and an average power of 20 mW. The optical fiber coupler divides the output light at a ratio of 90:10, such that 10% of the light enters the reference arm, and 90% enters the sample arm. After entering a 50:50 optical coupler, the interference signals from the sample and reference arms are reflected back and captured by a balanced photodetector (PDB480C-AC, Thorlabs, Newton, NJ, USA). The signal from the photodetector is collected via a waveform digitizer acquisition card (Alazar Technologies Inc., Quebec, Canada). The excitation unit is made up of a shaker exciter (Miniature Shaker Model 4810, Duluth, GA, USA), a power amplifier (PAS-00023-25, Spanawave, Roseville, CA, USA), and a function generator (AFG31102, Tektronix, Beaverton, OR, USA).

Figure 2 Schematic of the shaker-OCE system. OCE, optical coherence elastography; shaker-OCE, shaker-based OCE.

System synchronization

Figure 3 depicts the M-B scanning protocol used by the system. While acquiring elastic data from the sample, a single A-scan was conducted at position P₀ to form an A-line, which requires 20 µs. This process is repeated 1,000 times to create an M-scan, resulting in a duration of 20 µs × 1,000 = 20 ms for one complete M-scan. Subsequently, a two-dimensional (2D) galvanometer is rotated to generate a scanning beam probe at position P₁, followed by the execution of an identical M-scan. After performing 1,000 M-scans along the acquisition direction, a complete B-scan is ultimately obtained. One B-scan takes 20 ms × 1,000 = 20 s. Figure 3B displays a logical diagram of timing synchronization in the process of elasticity imaging, wherein the shaker excitation functions between 101^st and 120^th A-lines for a duration of 400 µs.

Figure 3 Schematic diagram of M-scan mode. (A) Scan protocol of the M-B mode. (B) Timing diagram of the M-B mode. OCE, optical coherence elastography; OCT, optical coherence tomography.

Data-processing process

As per the below equations, the axial phase shifts Δφ of two adjacent A-lines are determined once the raw data of the interfering signals from the sample tissue are processed by the system using a phase-resolved Doppler OCT algorithm (31):

Δφ=tan−1Im(Fm×Fm+1*)Re(Fm×Fm+1*)[1]

where F_m and F*_m+1 are conjugate complex numbers, and Im() and Re() indicate real and imaginary parts of the complex signals, respectively, at the acquisition point and the next acquisition point. Using the Doppler phase shift (32), the axial displacement of the tongue tissue induced by the excitation is then calculated using the following equation:

Δd=λ04πnΔφ[2]

where λ0 is the laser’s central wavelength and n is the sample’s refractive index. The vibrational displacement can be used to reconstruct the x-t 2D image of Doppler OCT, where x is the propagation distance of the shear wave, and t is the propagation time of the shear wave in the acquisition direction. The ratio x-t can be used to calculate the velocity of the shear wave (33) and thus the shear modulus according to the following equation:

μ=ρ×VS2[3]

The parameters ρ, Vs, and µ correspond to the density of the tongue (assumed to be 1,000 kg/m³) (34), shear wave velocity, and shear modulus, respectively. Herein, Young’s modulus was employed to quantify biomechanical properties. The correlation between the shear modulus (µ) and Young’s modulus (E) (35) is expressed as follows:

E=2μ(1+ν)[4]

The Poisson’s ratio of the biological tissue is estimated to be υ=0.5 (34,36). Therefore, Young’s modulus of the biological tissue can be expressed as follows:

E=3×ρ×VS2[5]

Histopathology

The tissue samples were embedded in paraffin blocks and cut into 4-µm sections, such that the region lined up with the OCE B scanning position (the histology section). The tissue sections were treated with hematoxylin and eosin (HE) staining, Masson’s trichrome staining, and Gomori’s aldehyde-fuchsin (AF) staining for the immunohistochemical analysis. The experimenter was blinded to the experimental samples, and the reviewer was unaware of the group assignments during the histological analysis.

The HE staining of the tissue sections was performed for pathological gradation. OSCC staging was performed as per the Cancer Staging Manual (5^th edition) of American Joint Committee on Cancer (37) as follows: (I) normal; (II) hyperplasia; (III) low-grade dysplasia (LGD); (IV) moderate-high-grade dysplasia (M-HGD); (V) carcinoma in situ (CIS); and (VI) SCC. The degree of collagen fiber expression per unit area was analyzed by Masson’s trichrome staining, while the dispersion of elastic fibers per unit area was observed using Gomori’s AF staining. Cancer-associated fibroblasts (CAFs) were detected through the immunohistochemical staining of alpha-smooth muscle actin (α-SMA). A semi-quantitative method was employed to determine the number of positive cells and to analyze the intensity of the α-SMA staining (38). Based on the method of Tuxhorn et al. (39), the immunostaining results were evaluated based on the intensity and percentage of α-SMA-positive cells. The percentage of the α-SMA-positive cells in the tumor stroma was scored as follows: 0, no positive cells; 1, 1–33% positive cells; 2, 34–66% positive cells; and 3, 67–100% positive cells. While staining was scored as follows: 0, no staining; 1, weak staining; 2, moderate staining; and 3, strong staining. The immunoreactivity score (IRS) was then calculated as follows: IRS = positive cell score × staining intensity score. The IRS was classified as follows: zero (0 points), low (1–2 points), moderate (3–4 points), and high (6–9 points) (40). Five images were randomly selected under a 10× field of a Zeiss high-magnification optical microscope (Vectra 3 PerkinElmer), and the images were analyzed using ImageJ 1.46 (National Institute of Health, Bethesda, MD, USA).

Statistical analysis

All the statistical analyses were performed using SPSS 27 software (SPSS, Inc., Chicago, IL, USA). The correlation between collagen or elastic fibers and the pathological grading of cancer was determined by Spearman correlation analysis. Changes in α-SMA expression in lesions at different stages were evaluated using cross-tabulation and Chi-squared test (also χ² test). One-way analysis of variance and Tamhane’s T2 post-hoc multiple comparisons were used to determine differences in the shear modulus and Young’s modulus at different lesion stages. A (two-sided) P value <0.05 indicated statistical significance.

Results

Animal experiments and histological analysis results

The experimental results of 45 specimens at different time points are displayed in Figure 1. In total, the results showed that 10 samples were normal (Figure 4A, A1), five were hyperplastic (Figure 4A, A2), eight were LGDs (Figure 4A, A3), eight were M-HGDs (Figure 4A, A4), seven were CISs (Figure 4A, A5), and seven were SCCs (Figure 4A, A6).

Figure 4 HE, elastic fiber, collagenous fiber, and immunohistochemical staining during each progression stage of TSCC, and their correlations with (A1-D1) normal tongue mucosa, (A2-D2) hyperplastic tissues, (A3-D3) LGD, (A4-D4) M-HGD, (A5-D5) CIS, and (A6-D6) SCC. (A1-A6) HE staining; (B1-B6) Masson’s trichrome staining of collagenous fibers; (C1-C6) Gomori’s AF staining of elastic fibers; (D1-D6) immunohistochemical staining of α-SMA. α-SMA, alpha-smooth muscle actin; AF, aldehyde-fuchsin; CIS, carcinoma in situ; HE, hematoxylin and eosin; LGD, low-grade dysplasia; M-HGD, moderate-high-grade dysplasia; SCC, squamous cell carcinoma; TSCC, tongue squamous cell carcinoma.

Expression of collagen fibers at various stages of cancer progression

In the healthy tongue (Figure 4B, B1), the collagen fibers were bluish, thin, and long, and displayed a linear pattern through the lamina propria (LP), while the core connective tissue of the tongue papilla displayed very few collagen fibers. The collagen fibers of the hyperplastic (Figure 4B, B2) and LGD (Figure 4B, B3) tissues were not significantly different from those of the normal tissue. However, in the M-HGD (Figure 4B, B4) and CIS (Figure 4B, B5) samples, the collagen fibers were more slender in the core connective tissue, and the collagen fiber bundles in the LP of the mucous membrane were thick and densely arranged. The SCC samples (Figure 4B, B6) had a significantly higher number of collagen fibers than the other sample types that showed thick and dense deposition in the LP and tight fiber distribution. The Spearman correlation test results revealed a positive correlation between the expression of collagen fibers and tumor progression (r=0.353, P<0.05).

Expression of elastic fibers at various stages of cancer progression

In the healthy tongue tissue (Figure 4C, C1), the LP was enriched in AF-positive elastic fibers. The elastic fibers of the hyperplastic (Figure 4C, C2) and LGD (Figure 4C, C3) tissues had morphological characteristics similar to those of the normal tongue mucosa. In both the M-HGD (Figure 4C, C4) and CIS (Figure 4C, C5) tissue samples, the AF-positive elastic fibers of the LP were disrupted and shortened, and exhibited a diluted distribution. The LP of the SCC tissue sample (Figure 4C, C6) rarely showed AF-positive elastic fibers. The Spearman correlation test results revealed that the expression of the elastic fibers progressively declined as the malignancy of the tongue cancer progressed (r=−0.776, P<0.05).

Expression of α-SMA at various stages of cancer progression

As detailed in Table 1, no cancerous fibroblasts were observed in the stroma of the normal (Figure 4D, D1), hyperplasia (Figure 4D, D2), and LGD (Figure 4D, D3) specimens (which had scores of 0). Among the eight M-HGD (Figure 4D, D4) samples, six showed no cancerous fibroblasts (scores of 0) and two samples exhibited low α-SMA expression. Among the seven CIS (Figure 4D, D5) specimens, two showed no cancerous fibroblasts (scores of 0), four samples had low α-SMA expression, and one sample showed moderate α-SMA expression. All the SCC (Figure 4D, D6) samples exhibited varying degrees of α-SMA-positive staining. Specifically, one sample had a low score, five had moderate scores, and one had a high score. Based on the results of the χ² test, the α-SMA scores of the CIS and SCC samples were significantly higher than those of the normal, simple hyperplasia, LGD, and M-HGD samples (P<0.05).

OCT/OCE evaluation

OCT images of the normal oral epithelium tissue (Figure 5A, A1) showed clear mucosal layer contours with a visible keratinized layer (KL), epithelial layer (EP), LP, and basement membrane (BM). The BM was continuous and intact. Figure 5A, A2 shows the corresponding histopathologic image. The OCT images showed no significant differences between normal and hyperplastic tissues, and sometimes the KL seemed more luminous and reflective (Figure 5B, B1); Figure 5B, B2 shows the corresponding histopathological images. The LGD samples (Figure 5C, C1) displayed a wide layer that had a strong signal, thicker epithelium, clearly distinguishable epithelial and LP layers, and a visible BM; Figure 5C, C2 shows the corresponding histopathological images. OCT images of the M-HGD samples (Figure 5D, D1) were consistent with the histopathology findings (Figure 5D, D2), highlighting the significant thickening of the epithelium. The individual mucosal layers were sometimes indistinct, and the border between the EP and LP was no longer visible. Compared to the BM in the normal mucosa, during the development of SCC, the BM undergoes significant changes. In the OCT image of early CIS tissue (Figure 5E, E1), the BM could not be clearly identified due to severe epithelial dysplasia; Figure 5E, E2 shows the corresponding histopathology images. For the SCC samples (Figure 5F, F1), the epithelium showed varying degrees of thickness, and sometimes tended to be irregular, with areas of erosion and extensive downward growth and invasion into the sub-EP; Figure 5F, F2 shows the corresponding histopathological images.

Figure 5 OCT images and corresponding HE-stained histopathological images of different pathological stages of disease development, including (A1,A2) normal mucosa, (B1,B2) hyperplasia, (C1,C2) LGD, (D1,D2) M-HGD, (E1,E2) CIS, (F1,F2) SCC. The red arrows show the increase in epithelial thickness and the apparent loss of the regular layered structure of the oral mucosa with the increasing severity of tissue dysplasia. The yellow lines show the BM, which is the boundary between the EP and LP. BM, basement membrane; CIS, carcinoma in situ; EP, epithelial layer; HE, hematoxylin and eosin; KL, keratinized layer; LGD, low-grade dysplasia; LP, lamina propria; M-HGD, moderate-high-grade dysplasia; OCT, optical coherence tomography; OSCC, oral squamous cell carcinoma; SCC, squamous cell carcinoma.

The M-B mode protocol was employed to successfully identify elastic waves inside the tissue. The images illustrated the 2D shear wave propagation in the normal tongue tissue (Figure 6A) and cancerous tongue tissue (Figure 6B) at six different time points. As the propagation distance increased, the amplitude gradually decreased. Notably, there were significant distinct differences between the healthy and cancerous tissues in terms of the speed of propagation and the amplitude decay rate of the elastic wave. We reconstructed the three-dimensional (3D) images to visualize the propagation of the shear wave across the entire transverse scanning range. The vibration amplitude of the elastic wave of the normal tissue (Figure 6C) exceeded that of the elastic wave of the cancerous tissue (Figure 6D). We produced spatio-temporal Doppler OCT images through the 2D reconstruction of 3D elastic waves along the x-t plane. The 2D OCT structural maps of tongue lesion tissues at various cancerous stages and during normal development were correlated with spatiotemporal Doppler OCT images, which are displayed in Figure 7. The slope became flatter during the progression of the lesion.

Figure 6 Representative Doppler OCT B-scans and 3D images of shear propagation images. (A) Doppler OCT B-scans images of the control normal group at 2.2, 4.2, 6.2, 8.2, 10.2, and 12.2 ms. (B) Doppler OCT B-scan images of the carcinoma group at 2.2, 4.2, 6.2, 8.2, 10.2, and 12.2 ms. (C) 3D image of shear wave propagation in the phantom of the control normal group. (D) 3D image of shear wave propagation in the phantom of the cancer group. The scale bars in depth (z) are used to describe the tissue vibration depth induced by the excitation unit. 3D, three-dimensional; OCT, optical coherence tomography.

Figure 7 The corresponding spatiotemporal Doppler OCT images of the tongue tissue at different lesion stages: (A) normal, (B) hyperplasia, (C) LGD, (D) M-HGD, (E) CIS, and (F) SCC. CIS, carcinoma in situ; LGD, low-grade dysplasia; M-HGD, moderate-high-grade dysplasia; OCT, optical coherence tomography; SCC, squamous cell carcinoma.

The velocity of the shear wave can be calculated from the slope of the spatiotemporal image and Eq. [3], while the corresponding Young’s modulus can be derived from Eqs. [4] and [6]. Table 2 sets out the experimental results. Figure 8A depicts a plot of the average phase velocity of the tongue tissue during lesion progression to illustrate the trend. As the lesion progressed, the velocity of the phases increased by 118.95%. The shear modulus and Young’s modulus results at different stages of the lesion are illustrated and compared in box plots shown in Figure 8B. It is evident that the shear modulus and Young’s modulus gradually increased along with the progression of the lesion. The M-HGD, CIS, and SCC samples had statistically significantly higher Young’s modulus values than the LGD, hyperplasia, and normal tissue samples (P<0.05).

Figure 8 The biomechanical properties of the tongue at different stages of pathology. (A) Averaged phase velocity for experiments at different lesion stages. (B) Box plot showing the biomechanical properties of the tongue at different lesion stages: the shear modulus and Young’s modulus values for experiments at different lesion stages (where the box is the inter-quartile range, and the central horizontal line is the median). Significant differences are indicated by different letters in the same group (P<0.05). Lowercase letters compare differences between the shear modulus groups, uppercase letters compare differences between the Young’s modulus groups. CIS, carcinoma in situ; LGD, low-grade dysplasia; M-HGD, moderate-high-grade dysplasia; SCC, squamous cell carcinoma.

Discussion

In the present study, we first employed a shaker-OCE to identify variations in elasticity between tongue tissues of healthy rats and rats with 4NQO-induced SCC lesions at different stages. This technique improved the identification and differentiation of benign or malignant oral lesions by employing a two-pronged approach using OCE, based on elasticity and structural metrics. In addition, we showed that the 4NQO-induced OSCC model exhibited significant similarities to naturally occurring OSCC in humans, which supports the clinical value of the results presented in this study (29,41).

Previous studies have suggested that the integrity of the BM and the thickness of the epithelial tissue could serve as indicators for distinguishing between benign and malignant oral lesions (42-44). However, in the case of malignant lesions, changes in the integrity of the BM or thickness of epithelial cells can be similar, which poses challenges in determining if these variations occur in response to a local stimulus or as a part of the carcinogenesis process (4,45,46). Further, the normal thickness of the epithelium varies slightly in different areas of an individual’s oral cavity (46,47).

The stiffness of the soft tissue is important in determining if tissue can retain the normal structure and function (48,49). The elastography analysis revealed changes in the stiffness of the tissue. OCE has been recently used to study characteristics of malignant tumors, specifically breast and prostate tumors. However, this was the first study to employ OCE to measure changes in the elasticity of the tissue during the progression of OSCC disease. In this study, the Young’s modulus indicating the stiffness of the tongue SCC (TSCC) and healthy samples was 120.06±16.32 and 24.94±3.11 kPa, respectively (P<0.05). Consistent with other studies, these findings highlight that the stiffness of TSCC tissue is much higher than that of normal tissue and premalignant tumors (50,51).

Several factors, such as the quantity and state of the extracellular matrix (ECM) in the tumor microenvironment and the infiltration of inflammatory cells, influence the mechanical properties of TSCC (52). The stiffness of tumor cells is lower than that of the surrounding normal cells (9,53,54). Nevertheless, the stiffness of the ECM components is higher than that of tumor cells. The deposition of stromal components and the subsequent structural alterations ultimately result in the characteristic increase in the elastic modulus of the tongue cancer tissue (55,56).

The ECM is a vital component of the tumor microenvironment, and its remodeling is critical for tissue hardening and tumor progression (57). One key indicator of the potential of a cell to undergo invasion and become carcinogenic is ECM stiffness (58,59). As predominant structural proteins in ECM components, collagen fibers are involved in cancer fibrosis (60). In line with the findings of Shibata et al. (50), our histological analysis results revealed a positive correlation between the increase in collagen fibers and tissue stiffness. Although r fell within the weak-to-moderate correlation range, this was consistent with the complex interaction mechanisms among biological variables. The expression of collagen fibers may be regulated by multiple factors, which limits the strength of its correlation with the progression of tongue cancer (61,62). These factors include the enhanced activity of matrix-degrading enzymes leading to collagen degradation, as well as the variability and distribution characteristics of sample data (60,63).

Further, we observed more variations in the elasticity of the diseased tissue, probably because each lesion sample progressed differently and caused different degrees of alterations in the distribution and accumulation of collagen. We also noted a negative correlation between elastic fiber content and tissue stiffness. In line with the observations of Lakiotaki et al. (64), our results showed a noteworthy decline in the accumulation of elastic fibers surrounding and adjacent to the malignant tissue. One might speculate that the breakage of the elastic fibers in the LP accelerates the process of carcinogenesis by facilitating the deeper entry of cancer cells into the tissue.

In comparison to the normal and OPMD tissues, the OSCC tissues had a noticeably higher expression of α-SMA, a commonly used marker for CAFs (65). CAFs, which are characterized by a firm and retractile texture, are part of the stroma of various invasive and metastatic malignant tumors (58). The CAF-mediated production of collagen and stimulation of lysyl oxidase synthesis contribute to increased stiffness, collagen cross-connections, and ECM reorganization (50,51). In addition, CAFs are known to secrete matrix metalloproteinases (MMPs) through cell-cell interactions. The absence of any elastic fibers in the cancerous areas of the tissue may be attributed to their breakdown and destruction by MMPs (64).

The present study had several limitations. First, in addition to collagen fibers and elastic fibers, the tumor ECM components also include fibronectin, laminin, and other components (49,51), which were not studied. Second, every lesion examined in this study was a well-differentiated tumor. Bordoloi et al. (60) used polarized light microscopy to record changes in collagen fibers of different histological grades of OSCC. Consequently, we anticipated that the OCE results of highly differentiated TSCC would differ from low differentiation results. Third, as this was an in vivo investigation, the possible motion artifacts and anatomical constraints of the equipment were not considered. Fourth, the results could be affected by the mechanical compression of the shaker-OCE system’s probe against the mucosa (26).

Conclusions

We found that the biomechanical properties of the tongue tissue with various degrees of lesions can be precisely measured using the shaker-OCE technique. We identified a range of elasticity values of the tongue tissue that are correlated with different stages of tongue cancer, and could thus provide a strong basis for evaluating changes during the progression of tongue cancer. OCE is a promising diagnostic tool that could serve as a key technology for early screening of TSCC.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the ARRIVE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-2359/rc.

Funding: This work was supported by the National Natural Science Foundation of China (No. 82460185), the Natural Science Foundation Projects of Jiangxi Province (No. 20232ACB206028), and the Science and Technology Program of Jiangxi Provincial Health Committee (No. 202410286).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2359/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Experiments were performed under a project license (No. NCULAE-20240827001) granted by the Animal Ethics Committee of Nanchang University and in compliance with institutional guidelines for the care and use of animals.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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