Morphometric analysis of connective tissue in oral submucous fibrosis using open-source software

INTRODUCTION

Oral submucous fibrosis (OSF) is an oral potentially malignant disorder characterized by inflammation and progressive fibrosis in the lamina propria with accumulation of collagen, reduced collagen breakdown, and epithelial atrophy.^[1] In 1966, Pindborg and Sirsat described OSF as “an insidious, chronic disease that affects any part of the oral cavity and sometimes the pharynx. Although occasionally preceded by, or associated with, the formation of vesicles, it is always associated with a juxta-epithelial inflammatory reaction followed by fibroelastic change of the lamina propria and epithelial atrophy that leads to stiffness of the oral mucosa and causes trismus and inability to eat.”^[2] Studies have indicated that the risk of OSF increases markedly with the higher frequency of betel quid consumption. The four major alkaloids present in betel nut are arecoline, arecaidine, guvacine, and guvacoline. Among them, arecoline is a primary contributor to the development of OSF.^[3,4] The other causative factors of OSF include deficiency of vitamins (Vitamin B and Vitamin C) and minerals (zinc and iron), intake of spicy foods and alcohol, human papillomavirus infection, genetic mutations, and smoking.^[3] Clinical manifestations of OSF include dry mouth, restricted mouth opening, burning sensation in the affected region, orofacial pain, dysgeusia, and dysphagia.^[5] Microscopically, OSF presents with epithelial atrophy, loss of rete ridges, increased deposition of collagen, juxta-epithelial chronic inflammatory cell infiltrate, reduced or increased vascularity, and hyalinization of the submucosal tissue.^[1] Although the variations in the blood vessel morphometry are present in various stages of OSF, it is observed that the same microscopic fields of OSF show diverse variations ranging from normal to dilated and constricted blood vessels.^[6]

ImageJ is an extensively utilized open-source software for image analysis. This software facilitates the extraction of data from images, including morphometric analysis, quantitative assessments, and fractal analysis. The information obtained through ImageJ can be stored and reproduced.^[7] In the literature, morphometric studies on OSF vasculature yield variable results. This study was conducted to determine the morphometric changes in the connective tissue vasculature of OSF and to compare it with normal mucosa using computer-aided image analysis software, ImageJ.

MATERIALS AND METHODS

The study was conducted in the Department of Oral Pathology and Oral Microbiology, Ragas Dental College and Hospital, Chennai, India, and ethical clearance was obtained from the Institutional Review Board, number RIEC/20240618/OP, dated June 3, 2024. Fifteen histopathologically diagnosed OSF slides and ten slides of normal mucosa were taken from the archives for the morphometric study. Photographs of five random fields with blood vessels were captured at ×40 objective for each case, and five blood vessels were chosen within each field. Twenty-five blood vessels were measured in each sample. A photomicrograph of the stage micrometer was captured at a ×40 objective, the distances across the five intervals on the stage micrometer image were measured, and their mean value was computed to calibrate the software. The parameters evaluated for morphometric analysis include mean vascular area (MVA), mean lumen area (MLA), blood vessel wall thickness, and mean vascular density (MVD). The MVA of blood vessels was determined by manual tracing of the periphery of the blood vessel outline [Figure 1a], as well as schematic representation of this parameter [Figure 1b]. The MLA was determined by manual tracing of the blood vessel lumen in the ImageJ software [Figure 2a], and a the schematic representation of this parameter is shown [Figure 2b]. The thickness of the blood vessel wall is quantified by subtracting the mean blood vessel area (MBVA) from the MLA, as illustrated in Figure 3a and b. The total number of blood vessels in five representative fields of each sample was calculated as mean vessel density [Figure 4].

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Figure 1:

(a) Blood vessel wall manually traced (red markings) in the ImageJ software (numbers 1-5), (b) Shaded area in red was calculated as mean blood vessel area.

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Figure 2:

(a) Manual tracing of lumen of blood vessel (red markings) in the ImageJ software (numbers 1-5), (b) Schematic representation of mean lumen area. Area shaded in red was calculated as mean lumen area.

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Figure 3

(a) Blood vessel (numbers 1-5) wall thickness traced (red markings), (b) Schematic illustration of the blood vessel wall thickness.

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Figure 4:

Mean vascular density.

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Blood vessel wall thickness = MBVA − MLA.

Data were transferred into a Microsoft Excel spreadsheet, and mean values were calculated for the statistical analysis.

This was done using the Statistical Package for the Social Sciences 2.0 software. The Mann–Whitney U-test was used to compare the morphometric variation of blood vessels between the two study groups, OSF and normal mucosa.

RESULTS

The results of morphometric analysis show a decrease in the mean vascular area (1454.60 ± 473.26 mm²) and mean lumen area (692.20 ± 389.43mm²) in OSF, compared to that of the normal mucosa (MVA: 1604.95 ± 439.62 mm²), (MLA: 970.91 ± 413.89 mm²). The reduction in the MVA is not statistically significant (P = 0.3), but there is a significant reduction in the mean lumen area (P = 0.001). The blood vessel wall thickness is increased in the OSF (763.09 ± 328.92 mm²) than in the normal mucosa (634.04 ± 282.25 mm²) (P = 0.09). The MVD is significantly increased in OSF (55.72 ± 18.95 mm) in comparison to normal mucosa (34.38 ± 8.12 mm) (P = 0.001) [Table 1].

DISCUSSION

Histomorphometry is the quantitative evaluation of microscopic structures. It was initially performed on bone tissues to study bone remodeling and bone defects, such as osteoporosis.^[8] Histomorphometric evaluation of oral potentially malignant disorders such as leukoplakia, lichen planus, and oral epithelial dysplasia has been done to analyze the cellular and nuclear architecture.^[9-12] Similarly, histomorphometry was used to evaluate the OSF vasculature in this study. In 1952, Schwartz identified five Indian women from East Africa with “atrophia idiopathica tropica mucosae oris.”^[13] In 1953, Joshi from India coined the term submucous fibrosis of the palate and pillars. OSF has also been described as diffuse OSF idiopathic scleroderma of the mouth, idiopathic palatal fibrosis, and sclerosing stomatitis.^[13] OSF is characterized by a juxta-epithelial inflammatory reaction followed by fibroelastic changes in the lamina propria, epithelial atrophy, decreased collagenase activity, and progressive scarring of the oral mucosa.^[14,15] The prevalence of OSF in India is 0.62–6.42%. The malignant transformation rate of OSF ranges from 1.3% to 23%.^[5,14] Morphometric studies based on clinical and histological staging criteria in OSF present with diverse observations. The grading and staging systems in OSF are not universally acceptable.^[16-18]

The National Institutes of Health developed the Image program in 1987, before the introduction of ImageJ. Sun Microsystems launched the ImageJ software using Java programming language.^[7] ImageJ, a widely used software tool in the biomedical field, aids in image visualization, allowing researchers to interpret and understand underlying patterns and structures within the images. It also facilitates advanced image processing, including noise reduction, contrast enhancement, and edge detection, which are essential for the accurate analysis of radiographic or histopathologic images. In addition, ImageJ can be integrated with deep learning models for image classification and segmentation.^[19]

The MVA was decreased in OSF in the present study. MVA was increased initially and decreased in later stages according to the morphometric studies by Murgod et al., Debnath et al., Singh et al., and Garg and Mehrotra, which aligns with the findings of the present study.^[6,20-22] Morphometric variations in stromal vasculature of OSF are reviewed and summarized in Table 2.

In our study, MLA was significantly decreased in OSF. Mean vascular luminal diameter (MVLD) decreased as the disease progressed, in the studies conducted by Murgod et al., Debnath et al., Nitheash et al., and Singh et al., which is in concurrence with the present study findings.^[6,21-23] An increase in MVLD in the advanced stages was reported by Desai et al., Rajendran et al., and Nitheash et al.^[23-25] Blood vessel wall thickness is increased, but the increase is not statistically significant compared to normal mucosa in the present study. The morphometric reduction in the MVA and MLA can be due to an increase in the extracellular matrix (ECM), which increases collagen concentration. This increased collagen deposition can lead to the constriction and obstruction of blood vessels. As more and more collagen is deposited, fibrosis can impede cell signal communication, and cell migration resulting in reduced vascular surface area.^[5,26] In this study, the number of blood vessels was significantly increased, which aligns with the findings of Desai et al., and Rajendran et al., who reported that MVD increases as the disease progresses.^[24,25] According to the morphometric studies by Murgod et al., Debnath et al., Pandiar and Shameena, and Nitheash et al., MVD was increased in the initial stages and decreased in later stages.^[6,22,23,27] In this study, the number of blood vessels was significantly increased in OSF in comparison to normal mucosa.

The increase in the number of blood vessels results from a reduction in the blood vessel size, which subsequently leads to hypoxia. This, in turn, triggers the expression of hypoxiainducible factor-1a (HIF-1a), a critical regulator of cellular responses that lowers oxygen levels. HIF-1a is significantly upregulated in fibrotic conditions such as OSF.^[3] HIF-1a also participates in the upregulation of various growth factors associated with angiogenesis and fibrogenesis, such as vascular endothelial growth factor, transforming growth factor, fibroblast growth factor, and platelet-derived growth factor.^[5,28] An increase in blood vessel count is an adaptive response of the mucosa to hypoxia. Angiogenesis occurs as a compensatory mechanism in the initial stages; however, in later stages, it leads to fibrosis by stimulating ECM deposition.^[28]

Fibrosis and angiogenesis are interrelated in OSF. Understanding the molecular mechanisms that regulate angiogenesis and the link between angiogenesis and fibrosis in OSF can help design molecular therapies for OSF.^[28] The limitations of the study are the small sample size and interobserver bias, which can occur due to manual tracing of blood vessels. The morphometric variation in vasculature has not been assessed across the various grades of OSF to understand the vascular changes with the progression of OSF.

CONCLUSION

The reduction in MVA and MLA, with concomitant increase in the number of blood vessels in OSF in the present study, supports the literature evidence that vascular alteration is an important event in the pathogenesis of OSF. The current treatment strategies in OSF include anti-fibrotic drugs, steroids, antioxidants, and surgical removal of fibrotic bands. Understanding the concept of fibrogenesis and its association with angiogenesis in OSF will aid in the development of newer treatment strategies in managing OSF.