Journal of Oral and Maxillofacial Pathology最新文献

Background: Forensic odontology helps in the identification of individuals in crime investigations. Age estimation is one of several indicators. Besides dentistry (canine), in forensic medicine, the maxillary sinus can be used where the whole body cannot be found. CBCT allows for 3D volumetric analysis, providing a better understanding. Stacks of scanned data can be analyzed, and 3D surface models can be produced using MIMICS software. As the identification of unknown individuals is difficult during mass disasters, an attempt was made to estimate the age by measuring the volume of the maxillary canines and the maxillary sinus.

Materials and methods: Cone beam computed tomography (CBCT) scans and Materialise Interactive Medical Image Control System (MIMICS 21.0 software). MIMICS software was used to do independent 3D segmentation for the maxillary sinus and maxillary canines using CBCT imaging data. Then the results were tabulated, and statistical analysis was performed using the obtained sample size data.

Results: Multiple linear regression analysis and Pearson or Spearman correlation tests were performed. With statistically significant results (P < 0.01), a relatively strong correlation between ratio parameters and chronological age was discovered, demonstrating the regressive nature of their morphological changes with age and a fair association with the ratio parameters.

Conclusion: The obtained valid regression formula in this study can serve as a reliable tool for age estimation in forensic dentistry by further validating the formula on a larger sample size.

Background: Cyclooxygenase-2 (COX-2), an enzyme involved in prostaglandin production, regulates the development of various neoplasms and is often used to assess tumour proliferation.

Aims: We aimed to evaluate the expression of COX-2 in Radicular cysts (RCs), Dentigerous Cysts (DCs) and Odontogenic Keratocysts (OKCs) to determine their proliferative potentials.

Settings and design: Retrospective study.

Methods and materials: Forty-five paraffin-embedded tissue sections, including fifteen cases of each cyst, were stained with the COX-2 antibody. The study recorded the staining intensity and mean degree of immunoreactivity among the three groups. Cyst size was documented from case files and correlated with immunohistochemical scores to examine their relationship with cystic expansion, inflammatory response and COX-2 expression.

Statistical analysis used: Chi-square, ANOVA, post hoc Tukey and unpaired t-test evaluations were performed.

Results: RCs showed the highest immunoreactivity (4.67 ± 0.90), followed by OKCs (4.67 ± 1.35), and DCs (0.53 ± 1.13). The mean degree of immunoreactivity between RC and DC, and OKC and DC, showed significant differences. The intensity and severity of COX-2 staining increased with the cyst size and degree of inflammation. Immunoreactivity scores significantly varied with cyst size (P < 0.01) across all cyst groups.

Conclusions: COX-2 overexpression serves as an inflammatory mediator, encouraging cell proliferation and survival behaviour in RCs and OKCs, ensuring the critical role of COX-2 in the biological activity of cysts and tumours. A combination of COX-2 chemopreventive inhibitors and anti-inflammatory medications may be used to treat odontogenic cysts.

Background: Establishing the biological sex of individuals is a key component of forensic identification, especially in the analysis of degraded or partial remains. Cone beam computed tomography (CBCT) enables precise, non-invasive for evaluating craniofacial structures.

Objective: To assess the effectiveness of maxillary and frontal sinus volumes, along with facial soft tissue thickness (FSTT), obtained from CBCT scans, for estimating sex in an Indian population using statistical and machine learning techniques.

Methodology: A dataset comprising 450 CBCT scans was evaluated. FSTT was recorded at 28 standardised craniofacial points following the Steyn and Cavanagh protocol. Volumetric assessment of the maxillary and frontal sinuses was measured. Discriminant function analysis (DFA) and two artificial neural network (ANN) models were used to classify sex based on the collected data.

Results: Both sinus volumes and FSTT showed statistically significant differences between males and females (P < 0.005). DFA achieved an overall accuracy of 80%, correctly identifying 73% of males and 87% of females. Cross-validation resulted in 75.6% accuracy. FSTT varied significantly between sexes at all landmarks. ANN Model 1 achieved 72% accuracy, while Model 2 exhibited potential accuracy up to 99%.

Conclusion: Morphometric data obtained from CBCT scans-such as sinus volumes and FSST-serve as reliable indicators for estimating sex. When combined with artificial intelligence models, these measurements provide an effective and practical approach to forensic identification within the Indian population.

Background: Ameloblastoma is a benign, slow-growing odontogenic neoplasia that can infiltrate soft tissue and penetrate bone. Molecular markers like IHC staining with Osteopontin and CD10 antibodies can help understand the abnormalities and predict malignant transformation. This study aims to improve diagnosis and treatment by tracking these indicators alongside other clinicopathological aspects.

Material and methods: The study analyzed the correlation between OPN and CD10 expression and ameloblastoma aggressiveness and malignant transformation using 35 paraffin blocks. IHC staining was performed using OPN and CD10 markers, and cell counts and staining intensities were calculated using the IRS method. The IRS score was correlated with clinicopathological parameters using statistical tests (P < 0.05).

Results: The results of the OPN expression examination are strong (37.2%), moderate (37.2%), weak (17.1%), and negative (8.5%) Meanwhile, the results of the CD10 expression examination are moderate (28.6%), weak (54.2%), and negative (17.2%). Correlation test for OPN and CD10 expression is P = 0.940. Correlation test for OPN expression and each clinicopathological feature is radiographic appearance P = 0.708, root resorption P = 0.063, tumour progression P = 0.640, tumour size P = 0.428, tumour duration P = 0.477, and regional lymph nodes enlargement P = 0.687. Correlation test for CD10 expression and each clinicopathological feature is radiographic appearance P = 0.342, tumour progression P = 0.623, root resorption P = 0.940, tumor size P = 0.003, tumor duration P = 0.138, and regional lymph nodes enlargement P = 0.858.

Conclusions: Ameloblastoma aggressiveness is indicated by high OPN and CD10 expression, while malignancy transformation potential is indicated by high OPN and low CD10 expression, with CD10 expression correlated with tumor size.

Background: Macrophages are essential cellular elements of innate and adaptive immunity and one of the most common cell types in chronic inflammatory conditions such as oral lichen planus (OLP) and oral squamous cell carcinoma (OSCC). However, the roles of M1 and M2 macrophages in the pathogenesis of erosive OLP (E-OLP) which has the highest malignant potential remain unclear.

Objective: To evaluate and compare the immunohistochemical expression of M1 and M2 macrophages in OLP and OSCC.

Materials and methods: Paraffin-embedded tissue sections of 20 OLP (9 erosive, 11 non-erosive) and 30 OSCC (16 well, 8 moderate, and 6 poorly differentiated) cases were subjected to immunohistochemical staining for CD68 (M1) and CD163 (M2). The slides were examined for distribution, intensity, and localisation of CD68 and CD163 expression. Quantitative assessment of the staining was done with the help of Image Pro Plus software. Statistical analysis using Fisher exact test for qualitative assessment and Student t-test and one-way ANOVA for quantitative analysis were done.

Results: Although there was an increase in the density of CD68+ and CD163+ macrophages in E-OLP, a statistically significant difference was not observed between the subgroups of OLP. However, the density of CD68 and CD163-positive macrophages was relatively higher in moderately differentiated OSCC with no statistically significant difference. However, the staining pattern, intensity, and localisation between CD68 and CD163 in OLP and OSCC showed significant difference.

Conclusion: An increase in the density of CD68+ and CD163+ macrophages in E-OLP may be associated with the pathogenesis of OLP into malignant transformation.

Context: Head and neck carcinomas are one of the most common malignancies worldwide and account for 30% of all cancers in India. Amongst it, oral cavity carcinomas alone comprised 30% and 90% of these are squamous cell carcinoma. Evaluation of various patterns of invasion (POI) is a simple, inexpensive procedure which can be incorporated into routine reporting as advised in cancer protocol templates (CAP).

Aim: To evaluate the association of worst pattern of invasion (WPOI) in oral squamous cell carcinoma (SCC) with clinicopathological factors.

Settings and design: Retrospective hospital-based study.

Methods and materials: Histopathological sections were reviewed for a duration of three years. All the relevant clinical and demographic data were obtained from the medical records. Cases were also analysed for all histopathological variables and results documented.

Statistical analysis used: Data were analysed using SPSS software, and appropriate statistical tests were used for analysis.

Results: The association between WPOI and clinicopathological parameters was evaluated using the Fischer's exact/Chi-square test. Out of 52 patients, 38.5% (n = 20) and 61.6% (n = 32) had WPOI I-III and IV-V, respectively. There is significant association between WPOI score and N Stage, grade of tumour, perineural and depth of invasion. However, no association was observed with T stage, lymphovascular emboli, margin status, tumour, and lymph node size.

Conclusions: The pattern of invasion is an easily recognizable histopathological variable which must be included in the reporting of oral SCCs. WPOI IV and V had a worse clinical outcome and are associated with PNI, DOI, and high-grade tumour.

Introduction: Research has been intensive on the possibility of using the ideal oral fluids in the prediction and diagnosis of periodontal disease.

Objectives: This study aimed to detect the most accurate biomarkers that can be used to predict and diagnose periodontal disease.

Methods: Gingival crevicular fluid (GCF) and subgingival plaque samples were collected. The levels of biomarkers ( Human Cathelicidine LL-37 (LL-37), Matrix Metalloproteinase -8 (MMP-8), Matrix Metalloproteinase -9 (MMP-9), interleukin (IL)-6, interleukin (IL)-1β, tumour necrosis factor-α (TNF-α), osteoprotegerin (OPG), OC and PGE2) were quantified by Enzyme-Linked Immunosorbent Assay (ELISA), while the subgingival periodontal pathogens (T. forsythia, T. denticola, P. gingivalis and A.a) were identified using Real-time Polymerase Chain Reaction (RT-PCR). Cumulative Risk Score (CRS), a new statistical approach, was used to evaluate the accuracy of applying oral biomarkers in the diagnosis of periodontal disease based on three selected biomarkers.

Results: The results of this study showed that MMP-8, IL-1β, PGE2 and IL-6 in GCF are associated with increased count of periodontal pathogens and different clinical periodontal parameters when compared to the other biomarkers. This association increased significantly by using CRS, which had 2 to 3 times higher odds ratios than the use of any selected biomarkers alone.

Conclusions: In conclusion, this study showed that the levels of biomarkers in the GCF, mainly MMP-8, IL-1β, PGE2 and IL-6, if used separately, could be useful in the prediction and diagnosis of periodontal disease to a certain degree of accuracy. The study also showed that the combination of three GCF biomarkers in a single biomarker package to establish the CRS index is more precise in the prediction and diagnosis of periodontal disease than the use of other biomarkers.

Background: Betel leaf has been documented to be rich in phytochemicals with diverse pharmaceutical properties. Betel leaf from plants grown in Tirur, Malappuram district, Kerala is Geographically indicated and referred as Tirur betel leaf is famous for its flavour and aroma due to its high amounts of essential oils. The anti-cancer phytochemicals in betel leaf extracts have the potential to be used as a chemo preventive or anti-cancer agents in oral carcinogenesis.

Aim: Identify and profile the anti-cancer compounds in the ethyl acetate extracts of Tirur betel leaf (Piper Betel L. Var Puthukodi) by chemical analysis.

Methodology: The betel leaves are sourced from the plantations in Tirur, Malappuram district, Kerala. Betel leaf extract was prepared with ethyl acetate as solvent in Soxlant apparatus. Preliminary phytochemical analysis was done with standard methods. Phytochemical compounds profiled using gas chromatography mass spectroscopy.

Results: Alkaloids (14 mg/mL), phenolics (5.13 mg/mL), and terpenoids (7.21 mg/mL) were found to be the main constituents of betel leaf extract by preliminary chemical analysis. Gas chromatography mass spectroscopy identified 75 compounds in the extract, and 11 of these compounds identified had documented anti-cancer properties.

Conclusion: Betel leaf extracts especially extracts from Tirur betel leaf are rich with compounds with antineoplastic effects and possibly they can be used as chemo preventive or as anti-cancer agent in the management of oral cancer.

Context: Retroviral infection and its treatment induce significant changes in oral epithelium and can infect and affect keratinocytes. The cytomorphometric alterations caused by human immunodeficiency virus (HIV) on oral epithelium in patients with and without highly active anti-retroviral therapy (HAART) can establish the relation with treatment regimen.

Aim: To assess and compare cytomorphometric changes in exfoliated oral epithelial cells with respect to their cytoplasmic area (CA), nuclear area (NA) and nuclear-cytoplasmic area ratio (NA: CA) in HIV seropositive subjects without HAART, with short-term HAART and long-term HAART.

Settings and design: This cross-sectional study included 120 participants. They were selected by a purposive sampling technique as per selection criteria and categorised into four groups of thirty each (untreated seropositives, short-term HAART, long-term HAART, and control groups).

Methods: Oral liquid rinse samples were collected, centrifuged, and stained (H and E and PAP stains). Morphometric measurements were taken for 50 cells per sample using specialised software, assessed and analysed.

Statistical analysis: SPSS V23 (IBM) was used. One-way analysis of variance was performed to compare groups, while Tukey's multiple post hoc procedures were applied for pairwise comparisons.

Result: CA: Control > Long-term HAART > Short-term HAART > Untreated. NA: Untreated > Short-term HAART > Long-term HAART > Control and NA: CA: Highest in untreated, lowest in controls. Cellular changes persisted despite HAART, though improvements were noted over time.

Conclusion: HIV infection causes significant oral epithelial alterations. HAART reduces these changes but does not restore baseline values, indicating a persistent impact of HIV. Monitoring oral cytomorphometry may aid in tracking disease progression and therapy effectiveness.

Background: MALAT1 (Metastasis-Associated Lung Adenocarcinoma Transcript 1) is a long non-coding RNA that helps in disease prognosis.

Objective: The aim of the study is to provide updated evidence on the expression rate of MALAT1 in oral squamous cell carcinoma (OSS) compared to normal cells and its other histopathological gradings, like well-differentiated, moderately differentiated, and poorly differentiated OSCC.

Materials and methods: The review adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered in PROSPERO with the registration number CRD42024598836. A thorough search of databases was conducted from January 2000 to April 2024 to identify studies reporting the MALAT1 expression in OSCC cells compared to normal cells and its histological gradings of OSCC. Quality assessment was performed using the Newcastle Ottawa scale (NOS) for included studies. The standardized mean difference (SMD) was used for continuous outcomes, while odds ratio (OR) and risk ratio (RR) were applied for categorical outcomes, depending on the data reported. A random-effects model was used for all analyses, with statistical significance set at P < 0.05.

Results: Seven studies qualified for inclusion, with four undergoing meta-analysis. Quality assessment indicated a moderate to low risk of bias. The meta-analysis revealed increased MALAT1 expression in OSCC cells (SMD = 3.90, 1.20-6.61) compared to normal tissue. Among OSCC grades, MALAT1 expression was higher in moderately differentiated OSCC than in well-differentiated (SMD = 5.50, -15.08-26.08), lower in moderately differentiated than in poorly differentiated (SMD = 10.50, -27.16-6.61), and lower in well-differentiated than in poorly differentiated OSCC (SMD = 1.50, -2.48-0.52). No publication bias was detected in the funnel plot.

Conclusion: MALAT1 is a therapeutic factor in OSCC; its increased expression is related to OSCC growth and could help control metastasis, with overall good clinical relevance, making it a promising prognostic marker for OSCC.