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Bright-field microscopy (BFM) encrypts the optical transillumination profile of the transmitted light attenuated by the complex micro-structural tissue convolutions, manifested by the dense and compact regions of the specimen under examination. The connotations of idiosyncratic tissue interaction dynamics with the onset of pre-cancerous activity are encoded in the BFM acquired oral mucosa histopathological images (OMHI). In the present study, our analysis is focused on the sub-epithelium region of the oral mucosa, which has high clinical significance but sparsely explored in the literature from the textural domain. Histopathology being the gold-standard technique till date, we have used the light microscopic histopathology images for tissue characterization. The tissue-index transmission patches (TITP) from the sub-epithelium region are cropped under the guidance of oral onco-pathologists. After that, the TITPs are characterized for its multi-scale spatial-deformation dynamics, while keeping the intrinsic anisotropic geometry, and local contour connectivity within tolerable limits. With recent studies exhibiting multifractal's potency in diverse biological system analysis, here, we exploit the 2D multifractal detrended fluctuation analysis (2D-MFDFA) on TITPs for exploring a discriminative set of multifractal signatures for healthy, oral potentially malignant disorders and oral cancer tissue sample. The predictive model's competency is validated on an experimentally collected corpus of TITP samples and substantiated via confirmatory data statistics and analysis, showing its inter-class segregation efficacy. Moreover, the 2D-MFDFA analysis evinces the complex multifractal patterns in TITPs, which is due to the presence of composite long-range correlations in the oral mucosa tissue fabric.

Computational analysis on altered micro-nano-textural attributes of the oral mucosa may provide precise diagnostic information about oral potentially malignant disorders (OPMDs) instead of an existing handful of qualitative reports. This study evaluated micro-nano-textural features of oral epithelium from scanning electron microscopic (SEM) images and the sub-epithelial connective tissue from light microscopic (LM) and atomic force microscopic (AFM) images for normal and OPMD (namely oral sub-mucous fibrosis, i.e., OSF). Objective textural descriptors, namely discrete wavelet transform, gray-level co-occurrence matrix (GLCM), and local binary pattern (LBP), were extracted and fed to standard classifiers. Best classification accuracy of 87.28 and 93.21%; sensitivity of 93 and 96%; specificity of 80 and 91% were achieved, respectively, for SEM and AFM. In the study groups, SEM analysis showed a significant (p < 0.01) variation for all the considered textural descriptors, while for AFM, a remarkable alteration (p < 0.01) was only found in GLCM and LBP. Interestingly, sub-epithelial collagen nanoscale and microscale textural information from AFM and LM images, respectively, were complementary, namely microlevel contrast was more in normal (0.251) than OSF (0.193), while nanolevel contrast was more in OSF (0.283) than normal (0.204). This work, thus, illustrated differential micro-nano-textural attributes for oral epithelium and sub-epithelium to distinguish OPMD precisely and may be contributory in early cancer diagnostics.

Oral sub-mucous fibrosis (OSF) is a pathophysiological state of oral cavity or oropharynx having a high chance of conversion to oral squamous cell carcinoma (OSCC). It involves fibrotic transformation of sub-epithelial matrix along with epithelial abnormalities. The present work aims to unveil the mechanistic domain regarding OSF to OSCC conversion exploring the scenario of hypoxia associated oxidative stress, epithelial-mesenchymal transition (EMT), metastasis and stemness acquisition. The study involves histopathological analysis of the diseased condition along with the exploration of oxidative stress status, assessment of mitochondrial condition, immunohistochemical analysis of HIF-1α, E-cadherin, vimentin, ERK, ALDH-1, CD133, Shh, Gli-1 and survivin expressions in the oral epithelial region together with the quantitative approach towards collagen deposition in the sub-epithelial matrix. Oxidative stress was found to be associated with type-II EMT in case of OSF attributing the development of sub-epithelial fibrosis and type-III EMT in case of OSCC favoring malignancy associated metastasis. Moreover, the acquisition of stemness during OSCC can also be correlated with EMT. Alteration of Shh and Gli-1 expression pattern revealed the mechanistic association of hypoxia with the phenotypic plasticity and disease manifestation in case of OSF as well as OSCC. Shh/ Gli-1 signaling can also be correlated with survivin mediated cytoprotective phenomenon under oxidative stress. Overall, the study established the correlative network of hypoxia associated oxidative stress, EMT and manifestation of oral pre-cancerous and cancerous condition in a holistic approach that may throw rays of hope in the therapeutic domain of the concerned diseases.

Background: In the context of early diagnosis and prevention of oral cancer, precise assessment of malignant potentiality of the oral potentially malignant disorders, particularly oral submucous fibrosis (OSF) is crucial. Till date, the assessment of malignant potentiality suffers from predictive ambiguity due to the lack of precision in the gold standard techniques. This can be addressed by integrating heuristic domain knowledge with quantitative analysis. Aim: The aim of this study is to propose an index for enhancing accuracy in malignant potentiality evaluation. Materials and Methods: The present study analyzes important histomorphometric attributes (epithelial thickness, basal cell nuclear size, nuclear-to-cytoplasmic area ratio of basal cells, chromaticity of basal cell nucleus, thickness of basement membrane, ratio of vasculature in juxta-epithelial connective tissue [i.e., area covered by blood vessels/total area], collagen density in the lamina propria) of oral mucosa in dysplastic and nondysplastic OSF in association with relevant oncopathological appreciations (weightage of different features as suggested by oral pathologists) toward proposing a “Malignant Potentiality Index” (MPI). Results: Analysis of variance and notch box plot analysis depict statistically significant differences (P < 0.0001) in the histopathological features among different study groups (normal oral mucosa, OSF without dysplasia, OSF with dysplasia). Histopathological observation of one OSF patient with calculated MPI is shown. Conclusion: This newly proposed diagnostic cum prognostic decision-making parameter, the “MPI” may bring a value addition to the conventional diagnostic gold standard.

Optical coherence tomography (OCT) is widely used in Ophthalmology for visualizing retinal layers and cornea width profiles which are indexed to various pathologies. Image processing algorithms have been deployed to automatically delineate various layers for autonomous width profiles computation. Classical OCT segmentation algorithms are anchored around gradient and its derivatives. Such pixel information can vary from subject to subject so prior approximations of different layers are imposed in the name of regularization. Regularization restrains the generalization capability of the model which is crucial for segmentation in pathological subjects. The presented approach aims to model signal interactions with a tissue type through back scattered signal characteristics. During prediction phase, given an unknown interaction, the model estimates the probability of signal being backscattered from a tissue type. Sensor's ballistic models are employed to estimate the uncompressed signal statistics. These models have been experimented and evaluated on 5000 AMD (age-related macular degeneration) and 5000 normal B-scans from Duke OCT dataset. With two percent training data the delineation results are comparable to graph based approaches. The anterior retina, retinal pigment epithelium (RPE) and posterior retina are identified with sensitivity of 0.87, 0.84 and 0.91 respectively.