Histomorphometric Analysis of Oral Squamous Cell Carcinoma, Apparently Normal Adjacent Mucosa and Epithelial Dysplasia

Abstract

Oral squamous cell carcinoma (OSCC) comprises more than 90% of oral cavity cancer and remains the leading cause of death in oral disease. Limited studies have been conducted to evaluate cellular histomorphometry changes in OSCC compared to premalignant lesions such as Dysplastic leukoplakia (DL), Nondysplastic leukoplakia (NDL), and normal epithelial. This cross-sectional descriptive-analytical study was conducted on total 72 samples, including superficial areas of squamous cell carcinoma (SCCSF), Invasive Front of Squamous Cell Carcinoma (SCCIF), Apparently Normal Adjacent Oral Mucosa (SCCANM) or normal margin, Dysplastic leukoplakia (DL), Nondysplastic leukoplakia (NDL), and normal oral mucosa tissue (NOM) (N = 12 per group). ANOVA was used to compare the nucleus-to-cytoplasm ratio (N/C), nucleus area (NA), and cellular area (CA) of the stained hematoxylin and eosin (H&E) samples in the studied groups. A P value less than 0.05 was considered to be a significant level. There was a significant increase in the CA, NA, and N/C in the basal and parabasal layers from normal epithelium to dysplastic epithelium and OSCC. The highest NA, CA, and N/C were in the SCCIF and SCCSF groups, respectively, and the lowest was observed in NOM. In addition, SCCANM basal and parabasal layer cells had a significant difference in N/C compared to NOM, which indicates a high risk of SCCANM transformation into malignancy. Cell histomorphometry changes were observed from normal tissue to premalignant lesions and OSCC. These parameters can be used as indicators of the potential for transformation into malignancy in premalignant lesions.

Introduction

Most oral cavity malignant neoplasms originate from epithelium, such as oral squamous cell carcinoma (OSCC) and lymphoepithelial carcinoma. OSCC comprises more than 90% of oral cavity cancer and is more prevalent among males than females. To date, OSCC is ranked 16th in incidence, and more than 377,000 new patients and 177,000 deaths have been reported all around the world [1]. This rate can be anticipated by potentially malignant oral diseases (OPMDs) that involve both sexes with a female/male ratio equal to 1:2.3 [2]. The most common risk factors are known alcohol and tobacco consumption [3]. The main challenge is that there is no definitive panel for early diagnosis of OSCC that substantially reduces the quality of life following encounter recurrences or manifestation of second primary tumors due to field cancerization [4, 5]. Even though advances in therapeutic approaches for oral cancer patients with radio/chemotherapy and tumor resection by surgery, the 5-year survival rate has not improved [6, 7].

OSCC originates from healthy oral mucosa or precursor lesions (OPMDs). The most common OPMDs include leukoplakia, erythroplakia, lichen planus, submucous fibrosis (OSMF), and proliferative verrucous leukoplakia, which affects the oral mucosa with an increased risk of malignancy [3, 8]. OPMDs carrying dysplastic features are assumed to have a high risk of malignancy; for example, the annual transformation rate of oral leukoplakia has been estimated at approximately 2–3% [9]. Prediction of malignancy potential in oral leukoplakia strongly depends on clinical data such as non-homogeneity, anatomical site, age, gender, oral epithelial dysplasia (OED), and tobacco consumption. However, leukoplakia can transform into malignancy without dysplasia diagnosis; in contrast, the transformation of dysplastic lesions is not inevitable [3, 9]. Clinical examination can manifest OPMD earlier than the beginning tumorigenesis process, and the OSCC patients with previous OPMD showed a decrease in lymph node metastasis and mortality rate compared to OSCC patients without previous OPMD (like lichen planus). In this manner, applying diagnostic methods that are validated and fast can promote the survival of patients [10].

Quantitative histomorphometry (QH) is a computerized method and tool to quantitatively count or measure tissue features from digitized images so that a pathologist can evaluate cells, extracellular constituents, and microarchitecture of morphology [11]. Histopathologic assessment is still the gold standard method for diagnosis of OSCC that shows tumor differentiation (grade) based on the normal intensity distribution of squamous epithelium and tumor behavior primarily in the early disease (Stage I or II) in routine clinical practice. Histologic images can predict tumor aggressiveness, risk of progression, and outcomes. The pattern of tumor growth can be diagnosed mostly in the early stage of tumor progression prognostic by QH examination [12]. QH features have shown to be independently prognostic across different cancer types including breast [13, 14], lung [15, 16], and oral cancer [12].

Limited studies have been conducted to evaluate cellular histomorphometry changes in OSCC compared to premalignant lesions. According to the research studies, we compared OSCC, Dysplastic leukoplakia (DL), and Nondysplastic leukoplakia (NDL) (both as premalignant lesions) with normal epithelium. In addition, we evaluated OSCC in three areas (OSCC invasive front or OSCCIF, OSCC superficial areas or OSCCSF, OSCC apparently normal mucosa or OSCCANM) for more accurate morphological assessment compared to the normal tissue and leukoplakia. Histomorphometry examination of the apparently normal surgical margin of carcinoma is critical in terms of treatment and survival rate of patients.

Methods

The current study was conducted in a cross-sectional descriptive-analytical way with a total of 72 specimens, including SCCSF, SCCIF, SCCANM, DL, NDL, and normal oral mucosa tissue (NOM) that were extracted from oral and maxillofacial pathology department archives at Mashhad dentistry school and pathology department of Quaeem hospital (N = 12 per group). The Ethics Committee approved all experimental processes before the beginning of the current project (IR.MUMS.DENTISTRY.REC. 1399.125). All study participants signed the informed consent form before taking a tissue biopsy. Demographic information of patients was extracted from participants’ documents archives. Exclusion criteria were the biopsy samples with no definitive diagnosis and a low quantity of staining.

We have chosen the OSCC patients based on pathological grade (Grade I, II, and III). We have chosen leukoplakia according to the pathological manifestation as dysplastic and non-dysplastic. SCCIF is determined as the location where the deepest and possibly most aggressive cells are located. SCCSF is caused by a carcinoma in situ or severe dysplasia with focal or superficial invasion of less than 2 mm that is not deeper than the lamina propria layer [17, 18]. SCCIF and SCCSF biopsies were extracted from the tumor site, and SCCANM biopsies were selected from the clinically normal site with a distance of at least 1 cm from the tumor. For microscopic analysis, all tissue samples with embedded paraffin blocks were sliced with 4–5 μm thickness sections, and then they were stained with hematoxylin and eosin (H&E). The Lx 400 microscope (Labomed, USA) analyzed the histological sections with a magnification of 400x. From each slide, three images of suitable areas for measuring ten basal and ten parabasal cells were examined for the NOM, NDL, DL, SCCANM, and groups. In addition, 20 cells for basal and parabasal cells combined in the studied groups, and 20 for SCCSF and SCCIF were examined. We used a TrueChrome camera (Tucsen Photonics, Fujian, China) and a T capture computer software (Tucsen Photogenics). Primary parameters, including cellular area (CA) and nucleus area (NA), were determined based on microns. The obtained data was used to calculate secondary parameters, including cytoplasmic area (CytA) and nucleus-to-cytoplasm ratio (N/C). The NA was measured by tracing the nuclear border with a mouse cursor using the editing tool and the software’s measurement tool. The cell area was also measured similarly by tracing the cell border [19, 20].

N/C was calculated as below:

For statistical analysis, the Shapiro-Wilk Test assessed data distribution that deviates from a comparable normal distribution. The groups were examined regarding influencing variables such as sex and age by Fisher exact test and ANOVA, respectively. ANOVA was used to compare the N/C, NA, and CytA of the samples in the studied groups. The less than 0.05 was considered a significant level.

Results

The biopsies of 72 participants were analyzed, including 46 men (63.9%) and 26 women (36.1%), with an average age of 57.8 years, a standard deviation of 13.77 years, and an age range of 15 to 83 years. There was no significant difference between the groups in terms of average age (p = 0.286) and sex (p > 0.99). The normality of data distribution was confirmed using the Shapiro-Wilk test. The minimum and maximum mean ages were related to the SCCANM and leukoplakia.

We showed images of histomorphometry examination in the basal and parabasal layers of NOM, NDL, DL, SCCANM, SCCSF, and SCCSF groups in Fig. 1a-f.

Fig. 1.

Histomorphometry examination in the basal and parabasal layers of (a) normal oral mucosa (NOM), (b) Nondysplastic leukoplakia (NDL), (c) Dysplastic leukoplakia (DL), (d) Apparently normal adjacent oral mucosa (SCCANM) with 400x magnification. (e) Histomorphometry examination in the basal and parabasal layers of the superficial area of squamous cell carcinoma (SCCSF) and (f) Invasive Front of Squamous Cell Carcinoma or SCCIF with highest N/C ratio, cellular area (CA), and cytoplasm area (cytA) (400x magnification)

According to Table 1, a comparison of the groups showed that all the basal, parabasal, and total cells had significant differences in average CA (p < 0.001 for each). In basal, parabasal, and total cells, the minimum and maximum CA averages were related to the normal and SCCSF groups, respectively. The pairwise comparison between groups by Games-Howell post-hoc test in basal, parabasal, and total cells showed that in the basal cell, the average CA in the normal group was significantly lower than in all groups, in the SCCANM group compared to the DL, NDL, and SCCSF groups (p < 0.001). In the parabasal cell, the average CA in the normal group was significantly lower than all groups except the SCCANM group and the SCCANM group compared to the SCCSF group (p < 0.001). In general, the average CA in the normal group was significantly lower than in all groups and the SCCANM group compared to the DL, SCCSF, and SCCIF groups. In other group comparisons, no significant differences were observed.

Table 1.

Comparison (± standard deviation) of the average cellular area, nucleus area, cytoplasm area, and nucleus-to-cytoplasm ratio between study groups by cell type

Groups	N	Cell type
		Basal	Parabasal	Total cells
Average cellular area (CA)
NOM	12	39.05 ± 5.08	40.49 ± 4.96	39.77 ± 4.98
NDL	12	82.65 ± 22.74	83.42 ± 22.66	83.04 ± 21.29
DL	12	92.96 ± 16.32	92.77 ± 20.23	92.86 ± 16.60
SCC ANM	12	57.00 ± 15.34	68.57 ± 30.41	62.78 ± 22.07
SCC SF	12	115.35 ± 37.24	114.11 ± 41.62	114.73 ± 37.23
SCC IF	12	-	-	99.13 ± 24.29
ANOVA test		F = 22.19, p < 0.001	F = 12.61, p < 0.001	F = 16.28, p < 0.001
Average of the nucleus area (NA)
NOM	12	12.48 ± 1.81	13.11 ± 1.54	12.80 ± 1.64
NDL	12	31.49 ± 7.83	31.54 ± 8.54	31.51 ± 7.73
DL	12	43.55 ± 8.13	42.80 ± 9.68	43.17 ± 8.13
SCCANM	12	32.77 ± 8.96	39.94 ± 18.90	36.36 ± 13.38
SCCSF	12	70.72 ± 23.36	69.23 ± 25.90	69.98 ± 23.40
SCCIF	12	-	-	60.89 ± 14.82
ANOVA test		F = 20.88, p < 0.001	F = 9.90, p < 0.001	F = 15.92, p < 0.001
Average of cytoplasm area (CytA)
NOM	12	26.56 ± 3.30	27.38 ± 3.47	26.97 ± 3.36
NDL	12	51.16 ± 15.09	51.88 ± 14.17	51.52 ± 13.60
DL	12	49.41 ± 8.34	49.97 ± 10.61	49.69 ± 8.53
SCCANM	12	24.23 ± 6.59	28.63 ± 11.70	26.43 ± 8.82
SCCSF	12	44.63 ± 14.48	44.88 ± 15.82	44.75 ± 14.07
SCCIF	12	-	-	38.24 ± 9.52
ANOVA test		F = 17.66, p < 0.001	F = 11.61, p < 0.001	F = 13.71, p < 0.001
Nucleus-to-cytoplasm ratio (N/C)
NOM	12	0.47 ± 0.02	0.48 ± 0.02	0.48 ± 0.01
NDL	12	0.61 ± 0.02	0.61 ± 0.02	0.61 ± 0.01
DL	12	0.89 ± 0.04	0.86 ± 0.03	0.87 ± 0.03
SCCANM	12	1.36 ± 0.12	1.37 ± 0.14	1.36 ± 0.11
SCCSF	12	1.54 ± 0.08	1.54 ± 0.07	1.54 ± 0.08
SCCIF	12	-	-	1.59 ± 0.05
ANOVA test		F = 593.55, p < 0.001	F = 469.59, p < 0.001	F = 813.85, p < 0.001

In basal, parabasal, and total cells, the minimum and maximum average of NA were related to the normal group and SCCSF group. Comparison between the groups in all basal, parabasal, and total cells showed statistically significant differences in terms of the average NA (p < 0.001 for each) (Table 1). The pairwise comparison between groups showed that in the basal cell, the average NA in the normal group was significantly lower than all groups, in the leukoplakia group compared to the DL and SCCSF groups, in the DL and SCCANM group compared to the SCCSF groups. However, in the DL, the group was significantly higher than SCCANM. In the parabasal cell, the average NA in the normal group was significantly lower than all groups, in the leukoplakia group compared to the DL and SCCSF groups, and in the DL and SCCANM groups compared to the SCCSF groups. In general, the average NA in the normal group was significantly lower than all groups in the leukoplakia group compared to the DL and SCCSF, and SCCIF groups, in the DL and SCCANM groups, compared to the SCCSF and SCCIF groups.

The minimum and maximum averages of CytA in basal and total cells were related to the SCCANM and leukoplakia groups, respectively. The minimum and maximum CytA averages were related to the normal and leukoplakia groups in the parabasal cell, respectively. In all basal, parabasal, and total cells, the study groups demonstrated significant differences with each other in terms of average cytoplasm (p < 0.001 for each) (Table 1). The pairwise comparison of the groups in the basal, parabasal, and total cells showed that in the basal cell, the average CytA in the normal and SCCANM groups was significantly lower than in all groups. In the parabasal cell, the average CytA in the normal group was significantly lower than in all groups, and the average CytA in the SCCANM group was significantly lower than in all groups except the SCCSF group. The average CytA in normal and SCCANM groups was significantly lower than in all groups.

In the N/C in basal and parabasal cells, the minimum and maximum averages of N/C were related to the normal and SCCSF groups, respectively. The minimum and maximum averages of N/C were generally related to the normal and SCCIF groups. The basal, parabasal, and total cell groups were significantly different regarding the average N/C (p < 0.001 for each). The pairwise comparison of the groups in each of the basal, parabasal, and total cells demonstrated that the average N/C in the basal and parabasal cells in the normal group compared to all groups, in the leukoplakia group compared to the DL, SCCANM and SCCSF, in the DL group compared to the SCCANM and SCCSF, in SCCANM compared to the SCCSF groups, was significantly low. In general, the average N/C in the normal group compared to all groups, in the leukoplakia group compared to the DL, SCCANM, SCCSF, and SCCIF groups, in the DL group compared to the SCCANM, SCCSF, and SCCIF groups, in SCCANM group compared to SCCSF and SCCIF groups were significantly low. Finally, in comparison, the N/C ratio in the basal layer of SCCSF was the highest, and the normal tissue had the lowest ratio. In comparing the N/C ratio in the parabasal layer, SCCSF had the highest ratio, and normal tissue had the lowest ratio. The comparison results of N/C ratio in total basal and parabasal cells were as follows:

Normal < DL < NDL < SCCANM < SCCSF = SCCIF.

These results showed that as we move from normal tissue to dysplasia and OSCC, the N/C ratio increases, and this finding can be used in early diagnosis and treatment of oral disease. In comparing the CA in the basal and parabasal layers, the normal group had the smallest area, and the SCCSF group had the largest area. In comparing the NA in the basal and parabasal layers, the SCCSF group showed the highest NA and the normal group demonstrated the lowest NA. Comparing the CytA of basal and parabasal, the normal group had the lowest area, and SCCIF, SCCSF, and dysplasia had the highest area. In the comparison of the total basal and parabasal CA, the results were as follows:

Normal < SCCANM < DL and NDL < SCCSF and SCCIF.

In the comparison of the NA in total basal and parabasal, the results were as follows:

Normal < NDL < DL and SCCSF < SCC ANM and SCCIF.

In the comparison of the CytA in total basal and parabasal, the results were as follows:

Normal < SCCANM < DL and NDL < SCCSF and SCCIF.

Discussion

Early diagnosis of OSCC remains a challenge due to the unclear characteristics at the early stages and confounding parameters or co-morbidities that can be underestimated by the subjects suffering from this neoplasia. To better identify the early signs of OSCC and prognosticate its behavior once diagnosed, OSCC can be approached by different definitive parameters [21, 22]. In this manner, histomorphology features of OPMDs and oral malignant lesions such as OSCC should be assessed based on accurate and valid parameters. We selected histomorphometry since we aimed to assess cellular histopathological changes in different grades of OSCC and apparently normal adjacent tissue. In addition, the safe margin is very important for the survival rate of patients, so we decided to compare the N/C changes in normal samples, normal apparent tissue adjacent to OSCC, and OSCC with different grades (different morphological changes). As the correlation between different grades (histopathological factor) and morphometric changes is so important, we first attempt to asses this correlation like other papers [19, 23]. In further studies, we can evaluate the prognosis of patients. Moreover, in the present study, we evaluate leukoplakia as the most common premalignant oral lesion. Evaluation of the nuclear changes and comparison with OSCC is critical for early treatment of this lesion. The pivotal factor in histomorphology examination is the N/C ratio to evaluate normal to non-dysplastic, dysplastic, and cancer transition. These are the strength points of the present study. However, we did not have the condition to study more patients in each group which restricted us from following up with them and evaluating the prognosis and survival of patients.

Lu et al. [12] evaluated features of nuclear morphology by quantitatively digitized histomorphometry-based images for better detection of high-risk OSCC patients compared with standard clinical and pathologic criteria. They reported that high-risk patients had significantly poorer disease-specific survival (DFS) than controls by T/N-stage, resection margins, smoking status, and positive classifier results. They proposed improving the survival rate and reducing treatment-related morbidity by applying quantitative histomorphometry features of digitized H&E slides as predictive independent prognosis factors [12]. Compared to our study, they applied tissue microarray and a new set of quantitative histomorphometric features, called local co-occurrence of morphology, which tries to capture similarity statistics of nuclear shape, size, and texture within cell clusters. While, we used histomorphometry and assessed CA, NA, and CytA in addition to the N/C ratio. Moreover, we divided OSCC groups into SCCIF, SCCSF, and SCCANM and compared them with DL and NDL groups. In 2017 Gnananandar et al. [23]. studied 400 participants comprised of OSCC (N = 200) and oral dysplasia (N = 200). The comparison of N/C between well- and moderately differentiated OSCC and OSCC to severe epithelial dysplasia was significant. They reported that the N/C ratio decreased in grade I and increased in grade III, which was a statistically significant difference between the two grades. They proposed applying Bryne’s grading system as a reliable diagnostic tool in the grading of OSCC at infratemporal fossa (ITF) for assessing tumor aggressiveness to inhibit inter-observer variations [23]. They evaluated more study participants (N = 200 in each group) in comparison to the present study (N = 12 in each group), and evaluated the N/C ratio by grades, while we compared CA, NA, and CytA in addition to the N/C ratio in divided OSCC groups into SCCIF, SCCSF, and SCCANM and compared them with DL and NDL groups.

In 2016 Gupta et al. [24] evaluated 75 patients, including moderate and poorly differentiated cases of OSCC, DL, and normal mucosa (N = 15 in each group). They showed computerized images of stained histological sections, which significantly enabled the evaluation of cellular and nuclear changes and the behavior of lesions. This quantitative histomorphometry technique showed a statistically significant increase in basal nuclear and cellular dimensions as lesions progressed from normal mucosa to DL to poorly differentiated OSCC. They revealed NA increased in DL and OSCC increased DNA synthesis, which showed more excellent biological activity in the nucleus. Increased cellular and nuclear size in leukoplakia demonstrated that it potentially had a malignant transformation. They reported that NA and CA increased significantly from leukoplakia to poorly differentiated OSCC. They suggested that nuclear size can help differentiate normal tissue, potentially malignant leukoplakia, and OSCC [24]. Except for the OSCC different divided subgroups in our study, their study participants and the results were aligned with ours.

In 2015, Babji et al. [19] evaluated histological changes between OSCC (N = 30), ANM (at least 1 cm away from OSCC region), and NOM. They reported significant changes in the CA and NA in the superficial and invasive island of OSCC compared to ANM. The basal cells of ANM demonstrated a significant reduction in CA, NA, and N/C compared to NOM. The basal cells of ANM manifested significant changes in CA, NA, and nuclear-CytA compared to NOM, proposing a change in the field with a high risk of malignant transformation. They emphasized that histomorphometry parameters can differentiate OSCC from ANM, and NOM can be applied as an indicator of field cancerization [19]. Similar to our study, they divided OSCC into subgroups and also evaluated ANM adjacent to OSCC tissue and proposed studying cancerization in ANM adjacent to OSCC in larger sample size can be helpful in the treatment and prognosis of the patient. In 2015, Christopher et al. [25] showed that nuclear diameter, NA, CA, and N/C significantly increased in leukoplakia, oral verrucous carcinoma (OVC), and OSCC patients compared to normal oral mucosa. Cell diameter statistically decreased significantly in OL, OVC, and OSCC patients compared to the normal. Cellular and nuclear parameters manifested statistically significant changes in leukoplakia, OVC, and OSCCs compared to normal oral mucosa [25]. In comparison to the present study, they studied OVC patients, too. The number of participants in each group and their results in cytomorphometry parameters were similar to ours.

Advances in computer-assisted imaging systems provide us with more accurate and validated histomorphometry parameters. Among the imaging techniques, high-frequency ultrasound imaging, confocal microscopy, optical coherence tomography, and vascular imaging were proposed to be applied effectively before surgery or treatment for lesions dubious to be oral cancer [21]. By morphometric computer-assisted images in different grades of OSCC (N = 50), Ananjan et al. [26] in 2018 showed the NA and nuclear perimeter (NP) increased in OSCC patients in comparison to normal mucosa and reduced with dedifferentiation of OSCC. In addition, the N/C ratio increased from normal mucosa due to the higher grades of OSCC with poorly differentiated OSCC. In addition, CA and CytA were reduced from normal mucosa with dedifferentiation of OSCC. They concluded that cellular and nuclear characteristics reveal a more valid indication of tumor aggressiveness than any single factor. Morphometric analysis can be an accurate method to determine objectively the degree of malignancy at the invasive tumor front [26]. Kumar et al. [27] assessed the changes in cell perimeter, NP, CA, NA, and N/C by computer-assisted morphometry in OSCC (N = 20) and normal oral mucosa (N = 10). They reported a highly significant difference between OSCCs and controls concerning CA, NP, and NA. A highly significant difference was observed in N/C between the means of OSCCs and control groups. They suggested quantified nuclear and cellular changes to evaluate malignancy and provide an objective basis for grading dysplasia and tumors [27]. Bose et al. [28] suggested nuclear fractal dimension (nFD) analysis as a digital pathology-based biomarker that integrates multiple histopathological features of the tumor microenvironment, including proliferation and immune infiltration, into a single digital pathology-based biomarker. Prospective validation of their study outcome revealed nFD to be a valuable tool for the clinical management of OSCC patients (N = 107) [28].

In an interesting study in 2023, Mustansar et al. [29] showed that the histological features of nuclear and cellular diameters changed significantly between the KRAS mutated and unmutated OSCC patients and different grades. Besides the determination of histological characteristics of OSCC, the PCR and DNA sequencing were performed by bioinformatic analysis to investigate the structural and functional impact of the mutations on the encoding of proteins [29]. We can design studies like Mustansar et al. to understand molecular changes in tumorigenesis, metastasis, invasion processes, and histomorphological parameters.

In 2021, Suresh et al. [30]. proposed cytomorphometric quantitative techniques for early diagnosis of oral malignancy and premalignancy lesions by evaluating leukoplakia (N = 20), OSCC (N = 20), and control (N = 10) participants. They emphasized that applying this technique increases the speed and accuracy of cytological measurements, which are repeatable.

Although biopsy and histological assessment are the gold standard diagnostic methods for OSCC, these processes are invasive and need to be accurately managed due to the conventional imaging techniques, which are time-consuming and expensive and may fail for beginning tumors and small lesions. Noninvasive imaging technologies in real-time can propose further details through the clinical examination of non-definitive diagnosis lesions that can exclude some of these restrictions and challenges [21]. Since tumorigenesis is a continuous and complex process, there are discordances among the pathologist’s reports in the microscopic morphological findings which can reach up to 25% of patients [31]. These discordances provide challenges in patient management, increase requests for more investigations, and impose the burden of costs on patients. However, maybe histomorphometry analysis can be applied as an efficient, economical, and acceptable method as a supplement to routine histological examinations.

Conclusion

Based on the results of our cross-sectional study, we compared CA, NA, CytA, and N/Cyt in basal and parabasal layers of the epithelium between different groups, including normal mucosa, DL, NDL, SCCIF, SCCSF, and SCCANM. In general, increasing indices were observed in all parameters from normal mucosa to different types of leukoplakia (DL and NDL) and different regions of SCC (SCCIF, SCCSF, and SCCANM) which was aligned with progression in tissue changes from normal oral mucosa to premalignant and malignant lesions. In addition, histomorphometry analysis can be a relatively reliable and useful method to diagnose premalignant and malignant lesions from normal oral mucosa. In future studies, we may achieve quantitative indices for predicting dysplastic changes in premalignant lesions.

Funding

Mashhad University of Medical Sciences, Faculty of Dentistry, funded this study in full, grant number [991558]. This article was extracted from a student thesis.

Data Availability

The corresponding author can present Consent, Data, Materials, and/or Code availability at any time for reasonable reasons.

Declarations

Ethics Approval

The Ethics Committee of Mashhad University of Medical Sciences confirmed all experimental processes before the beginning of the current project (IR.MUMS.DENTISTRY.REC.1399.125). All study participants signed the consent form before taking a tissue biopsy.

Informed Consent

All study participants signed the consent form before taking a tissue biopsy based on the Ethics Committee of XX principles.

Competing Interests

The authors declare that they have no conflicts of interest, real or perceived, financial or nonfinancial, in this article.

Research Involving Human Participants and/or Animals

The study was approved (Grant number: 991558) by the Ethics Committee of XX University of Medical Sciences (IR.MUMS.DENTISTRY.REC.1399.125) and certify that the study was performed by the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.