Mousumi Pal

A novel wavelet neural network based pathological stage detection technique for an oral precancerous condition

Aim: To describe a novel neural network based oral precancer (oral submucous fibrosis; OSF) stage detection method. Method: The wavelet coefficients of transmission electron microscopy images of collagen fibres from normal oral submucosa and OSF tissues were used to choose the feature vector which, in turn, was used to train the artificial neural network. Results: The trained network was able to classify normal and oral precancer stages (less advanced and advanced) after obtaining the image as an input. Conclusions: The results obtained from this proposed technique were promising and suggest that with further optimisation this method could be used to detect and stage OSF, and could be adapted for other conditions.

Assessment of malignant potential of oral submucous fibrosis through evaluation of p63, E-cadherin and CD105 expression

Background The assessment of malignant potential of oral submucous fibrosis grades vis-à-vis their progression towards malignancy is associated with expression of possible multiple molecular markers. Aims To analyse p63, E-cadherin and CD105 expression in this premalignant pathosis with a view to unravel and understand the expression of these molecules as markers. Methods The oral mucosal biopsies (normal, oral submucous fibrosis with and without dysplasia) were studied with routine H&E, and by immunohistochemistry for p63, E-cadherin and CD105 expression. p63 was assessed as percentage of positive nuclei. E-cadherin expression was estimated through (i) distance between basement membrane and E-cadherin expression initiation point, (ii) ratio between epithelial thickness and epithelial thickness displaying E-cadherin, and (iii) E-cadherin intensity variation along the expression path. CD105 expression was assessed qualitatively. Results The p63+ cells were highest in severely dysplastic tissues followed by other dysplastic grades, normal oral mucosa and non-dysplastic conditions. However, the p63+ cells displayed the feature of progressive maturation only in normal mucosa. There was a loss of membranous E-cadherin in basal layers of all diseased conditions; it was highest in severe dysplasia. There was significant variation (p<0.0001) in E-cadherin intensity within and between the tissues (normal and diseased). CD105 expression increased abruptly in dysplasia. Conclusions The malignant potential of this pre-cancerous condition is likely to be correlated with an increase in p63 and CD105 expression and a concomitant loss of membranous E-cadherin. This may lead to marker identification through greater validation.

Automated classification of cells in sub-epithelial connective tissue of oral sub-mucous fibrosis-An SVM based approach

Quantitative evaluation of histopathological features is not only vital for precise characterization of any precancerous condition but also crucial in developing automated computer aided diagnostic system. In this study segmentation and classification of sub-epithelial connective tissue (SECT) cells except endothelial cells in oral mucosa of normal and OSF conditions has been reported. Segmentation has been carried out using multi-level thresholding and subsequently the cell population has been classified using support vector machine (SVM) based classifier. Moreover, the geometric features used here have been observed to be statistically significant, which enhance the statistical learning potential and classification accuracy of the classifier. Automated classification of SECT cells characterizes this precancerous condition very precisely in a quantitative manner and unveils the opportunity to understand OSF related changes in cell population having definite geometric properties. The paper presents an automated classification method for understanding the deviation of normal structural profile of oral mucosa during precancerous changes.

Epithelio-mesenchymal transitional attributes in oral sub-mucous fibrosis.

Evaluating molecular attributes in association with its epithelial and sub-epithelial changes of oral sub-mucous fibrosis is meaningful in exploring the plausibility of an epithelio-mesenchymal transition (EMT) and malignant potentiality of this pathosis. In this study histopathological and histochemical attributes for basement membrane and connective tissue in biopsies of oral sub-mucous fibrosis (n = 55) and normal oral mucosa (n = 16) were assessed and expressions of p63, E-cadherin, β-catenin, N-cadherin and TWIST were analyzed immunohistochemically. The p63 and its isoforms (TA and ∆N), PARD3, E-cadherin and β-catenin were also assessed transcriptomically by q-PCR and EMT players like TWIST1, ZEB1, MMP9 and micro-RNA 205 were searched in gene expression microarrays. Oral epithelium demonstrating impairment in progressive maturation in oral sub-mucous fibrosis concomitantly experienced an increase in basement membrane thickness and collagen deposition along with alteration in target molecular expressions. In comparison to non-dysplastic conditions dysplastic stages exhibited significant increase in p63 and p63∆N expressions whereas, E-cadherin and β-catenin exhibited loss from the membrane with concurrent increase in cytoplasm. Further the N-cadherin and TWIST were gained remarkably along with the appearance of nuclear accumulation features of β-catenin. The microarray search had noticed the up-regulation of TWIST1, ZEB1 and MMP9 along with down regulation of micro-RNA 205. The simultaneous increase in basement membrane thickness and sub-epithelial collagen deposition were the plausible indicators for increased matrix stiffness with expected impact on oral epithelial functional homoeostasis. This was corroborated with the increase in expressions of epithelial master regulator p63 and its oncogenic isoform (∆N) along with membranous loss of E-cadherin (EMT hallmark) and its associate β-catein and gain of mesenchymal markers like N-cadherin and TWIST. These also became indicative for the induction of epithelial to mesenchymal transitional mechanism in oral sub-mucous fibrosis when connoted here with the relevant modulation in expressions of EMT regulators.

Structural markers for normal oral mucosa and oral sub-mucous fibrosis

This article presents a quantitative approach for the characterization of normal oral mucosa (NOM) in respect to thickness and textural properties of its entire epithelial layer. Histological images of oral mucosa depict that both thickness and tissue architecture at cellular and tissue level undergo change, as mucosa converts from normal to precancerous or cancerous state. In this study the thickness and fractal dimension of the mucosal epithelium of NOM and oral sub-mucous fibrosis (OSF) condition have been computed using 83 normal and 29 OSF images of oral mucosa. The result shows significant delineation between NOM and OSF in respect of both the epithelial thickness (in microm) and fractal dimensions. This quantitative characterization of oral epithelium will be of immense help for oral onco-pathologists and researchers to assess the biological nature of normal and diseased (OSF) mucosa with higher accuracy. Moreover, further differential applications may enable them to find out newer accurate quantitative diagnostic procedures to that of the usual histopathological gold standard for the assessment of malignant potentiality.

NMR (1H and 13C) based signatures of abnormal choline metabolism in oral squamous cell carcinoma with no prominent Warburg effect

At functional levels, besides genes and proteins, changes in metabolome profiles are instructive for a biological system in health and disease including malignancy. It is understood that metabolomic alterations in association with proteomic and transcriptomic aberrations are very fundamental to unravel malignant micro-ambient criticality and oral cancer is no exception. Hence deciphering intricate dimensions of oral cancer metabolism may be contributory both for integrated appreciation of its pathogenesis and to identify any critical but yet unexplored dimension of this malignancy with high mortality rate. Although several methods do exist, NMR provides higher analytical precision in identification of cancer metabolomic signature. Present study explored abnormal signatures in choline metabolism in oral squamous cell carcinoma (OSCC) using (1)H and (13)C NMR analysis of serum. It has demonstrated down-regulation of choline with concomitant up-regulation of its break-down product in the form of trimethylamine N-oxide in OSCC compared to normal counterpart. Further, no significant change in lactate profile in OSCC possibly indicated that well-known Warburg effect was not a prominent phenomenon in such malignancy. Amongst other important metabolites, malonate has shown up-regulation but d-glucose, saturated fatty acids, acetate and threonine did not show any significant change. Analyzing these metabolomic findings present study proposed trimethyl amine N-oxide and malonate as important metabolic signature for oral cancer with no prominent Warburg effect.

Quantitative dimensions of histopathological attributes and status of GSTM1–GSTT1 in oral submucous fibrosis

Oral submucous fibrosis (OSF) is a precancerous condition of the oral cavity and oropharynx and a significant number of such cases transform into oral squamous cell carcinoma (OSCC). Presently, diagnosis of OSF is done mainly through qualitative histopathological techniques and in the level of diagnostic molecular biology no specific genetic marker is evident. Keeping these facts in mind this study evaluates histopathological changes in the epithelium and subepithelial connective tissue of OSF through quantitative digital image analysis in respect to specific candidate features and analyses null mutations in the GSTM1 and GSTT1 by PCR amplification. The analysis revealed that there are subtle quantitative differences in the histological images of OSF compared to NOM. The thickness of the epithelium and cell population in its different zones, radius of curvature of rete-ridges and connective tissue papillae were decreased but length of rete-ridges and connective tissue papillae, fibrocity and the number of cellular components (predominantly inflammatory cells) in the subepithelial connective tissue were increased in OSF. The PCR study revealed that there is no significant difference in the allelic variants in GSTM1 between OSF and normal, while GSTT1 null gene showed significantly higher frequencies in this precancerous condition. This study establishes a distinct quantitative difference between normal oral mucosa (NOM) and OSF in respect to their histological features and GST null gene frequencies.

Computer Vision Approach to Morphometric Feature Analysis of Basal Cell Nuclei for Evaluating Malignant Potentiality of Oral Submucous Fibrosis

This research work presents a quantitative approach for analysis of histomorphometric features of the basal cell nuclei in respect to their size, shape and intensity of staining, from surface epithelium of Oral Submucous Fibrosis showing dysplasia (OSFD) to that of the Normal Oral Mucosa (NOM). For all biological activity, the basal cells of the surface epithelium form the proliferative compartment and therefore their morphometric changes will spell the intricate biological behavior pertaining to normal cellular functions as well as in premalignant and malignant status. In view of this, the changes in shape, size and intensity of staining of the nuclei in the basal cell layer of the NOM and OSFD have been studied. Geometric, Zernike moments and Fourier descriptor (FD) based as well as intensity based features are extracted for histomorphometric pattern analysis of the nuclei. All these features are statistically analyzed along with 3D visualization in order to discriminate the groups. Results showed increase in the dimensions (area and perimeter), shape parameters and decreasing mean nuclei intensity of the nuclei in OSFD in respect to NOM. Further, the selected features are fed to the Bayesian classifier to discriminate normal and OSFD. The morphometric and intensity features provide a good sensitivity of 100%, specificity of 98.53% and positive predicative accuracy of 97.35%. This comparative quantitative characterization of basal cell nuclei will be of immense help for oral onco-pathologists, researchers and clinicians to assess the biological behavior of OSFD, specially relating to their premalignant and malignant potentiality. As a future direction more extensive study involving more number of disease subjects is observed.

Automated characterization of sub-epithelial connective tissue cells of normal oral mucosa: Bayesian approach

The objective of this paper is to develop an automated cell classification system based on Bayesian classifier followed by segmentation using color deconvolution and feature extraction for characterizing various types of sub-epithelial connective tissue (SECT) cells from histological images. In the histological sections of oral mucosa, SECT layer mainly consists of three types of cells - inflammatory, fibroblast and endothelial cells; out of which only first two play significant role pertaining to precancerous changes in oral mucosa. In order to discriminate inflammatory and fibroblast cells, a set of mathematical features viz., area, perimeter, eccentricity, compactness, Zernike moments and Fourier descriptors are extracted followed by cell segmentation using color deconvolution method. The features are statiatically analysed to show its significance in cell discrimination. Thereafter, Bayesian classifier is implemented based on the defined feature space for characterizing inflammatory and fibroblast cells in order to observe the cell distribution in healthy state. The performance of this proposed system is evaluated with 97.19% overall classification accuracy.

Computer-aided molecular pathology interpretation in exploring prospective markers for oral submucous fibrosis progression

Evaluation of molecular pathology markers using a computer‐aided quantitative assessment framework would help to assess the altered states of cellular proliferation, hypoxia, and neoangiogenesis in oral submucous fibrosis and could improve diagnostic interpretation in gauging its malignant potentiality.