Tool For Detection Of Oral Cancer Research Articles

Intelligent Deep Learning Enabled Oral Squamous Cell Carcinoma Detection and Classification Using Biomedical Images.

Oral cancer is one of the lethal diseases among the available malignant tumors globally, and it has become a challenging health issue in developing and low-to-middle income countries. The prognosis of oral cancer remains poor because over 50% of patients are recognized at advanced stages. Earlier detection and screening models for oral cancer are mainly based on experts' knowledge, and it necessitates an automated tool for oral cancer detection. The recent developments of computational intelligence (CI) and computer vision-based approaches help to accomplish enhanced performance in medical-image-related tasks. This article develops an intelligent deep learning enabled oral squamous cell carcinoma detection and classification (IDL-OSCDC) technique using biomedical images. The presented IDL-OSCDC model involves the recognition and classification of oral cancer on biomedical images. The proposed IDL-OSCDC model employs Gabor filtering (GF) as a preprocessing step to eliminate noise content. In addition, the NasNet model is exploited for the generation of high-level deep features from the input images. Moreover, an enhanced grasshopper optimization algorithm (EGOA)-based deep belief network (DBN) model is employed for oral cancer detection and classification. The hyperparameter tuning of the DBN model is performed using the EGOA algorithm which in turn boosts the classification outcomes. The experimentation outcomes of the IDL-OSCDC model using a benchmark biomedical imaging dataset highlighted its promising performance over the other methods with maximum accuy, precn, recal, and Fscore of 95%, 96.15%, 93.75%, and 94.67% correspondingly.

Ultra-Sensitive and Selective Electrochemical Bio-Fluid Biopsy for Oral Cancer Screening.

The early diagnosis of recurrence and metastasis is critically important for decreasing the morbidity and mortality associated with oral cancers. Although liquid biopsy methods hold great promise that provide a successive "time-slice" profile of primary and metastatic oral cancer, the development of non-invasive, rapid, simple, and cost-effective liquid biopsy techniques remains challenging. In this study, an ultrasensitive and selective electrochemical liquid biopsy is developed for oral cancer screening based on tracking trace amounts of cancer biomarker by functionalized asymmetric nano-channels. Detection via antigen-antibody reactions is assayed by evaluating changes in ionic current. Upon the recognition of cancer biomarker antigens in bio-fluids, the inner wall of nano-channel immobilized with the corresponding antibodies undergoes molecular conformation transformation and surface physicochemical changes, which significantly regulate the ion transport through the nano-channel and help achieve sensitivity with a detection limit of 10-12 g mL-1 . Furthermore, owing to the specificity of the monoclonal antibody for the antigen, the nano-channel exhibits high selectivity for the biomarker than for structurally similar biological molecules present in bio-fluids. The effectiveness of this technique is confirmed through the diagnosis of clinical cases of oral squamous cell carcinoma. This study presents a novel diagnostic tool for oral cancer detection in bio-fluids.

A Review: Electrochemical Biosensors for Oral Cancer

Oral cancer poses a serious threat worldwide owing to its soaring case-fatality rate and its metastatic characteristics of spreading to the other parts of the body. Despite the recent breakthroughs in biomedical sciences, the detection of oral cancer at an early stage is still challenging. Conventional diagnosis in clinics and optical techniques to detect oral cancer in the initial stages are quite complicated as well as not completely accurate. To enhance the survival rate of oral cancer patients, it is important to investigate the novel methodologies that can provide faster, simpler, non-invasive, and yet ultraprecise detection of the onset of oral cancer. In this review, we demonstrate the promising aspects of an electrochemical biosensor as an ideal tool for oral cancer detection. We discuss the cutting-edge methodologies utilizing various electrochemical biosensors targeting the different kinds of biomarkers. In particular, we emphasize on electrochemical biosensors working at the molecular levels, which can be classified into mainly three types: DNA biosensors, RNA biosensors and protein biosensors according to the types of the analytes. Furthermore, we focus on the significant electrochemical methods including cyclic voltammetry (CV), differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) to analyze the oral cancer biomarkers (such as IL-6, IL-8, CYFRA 21-1, CD 59 and CIP2A) present in body fluids including saliva and serum, using non-invasive manner. Hence, this review provides essential insights into the development of pioneering electrochemical biosensors for the detection of oral cancer at an early stage.

Hyperspectral Imaging of Neoplastic Progression in a Mouse Model of Oral Carcinogenesis.

Hyperspectral imaging (HSI) is an emerging modality for medical applications and holds great potential for noninvasive early detection of cancer. It has been reported that early cancer detection can improve the survival and quality of life of head and neck cancer patients. In this paper, we explored the possibility of differentiating between premalignant lesions and healthy tongue tissue using hyperspectral imaging in a chemical induced oral cancer animal model. We proposed a novel classification algorithm for cancer detection using hyperspectral images. The method detected the dysplastic tissue with an average area under the curve (AUC) of 0.89. The hyperspectral imaging and classification technique may provide a new tool for oral cancer detection.

Alu Hypomethylation in Smoke-Exposed Epithelia and Oral Squamous Carcinoma

Alu elements are one of the most common repetitive sequences that now constitute more than 10% of the human genome and potential targets for epigenetic alterations. Correspondingly, methylation of these elements can result in a genome-wide event that may have an impact in cancer. However, studies investigating the genome-wide status of Alu methylation in cancer remain limited. Oral squamous cell carcinoma (OSCC) presents with high incidence in South-East Asia and thus the aim of this study was to evaluate the Alu methylation status in OSCCs and explore with the possibility of using this information for diagnostic screening. We evaluated Alu methylation status in a) normal oral mucosa compared to OSCC; b) peripheral blood mononuclear cells (PBMCs) of normal controls comparing to oral cancer patients; c) among oral epithelium of normal controls, smokers and oral cancer patients. Alu methylation was detected by combined bisulfite restriction analysis (COBRA) at 2 CpG sites. The amplified products were classified into three patterns; hypermethylation ((m)C(m)C), partial methylation (uC(m)C+(m)C(u)C), and hypomethylation ((u)C(u)C). The results demonstrate that the %(m)C(m)C value is suitable for differentiating normal and cancer in oral tissues (p=0.0002), but is not significantly observe in PBMCs. In addition, a stepwise decrease in this value was observed in the oral epithelium from normal, light smoker, heavy smoker, low stage and high stage OSCC (p=0.0003). Furthermore, receiver operating characteristic (ROC) curve analyses demonstrated the potential of combined %mC or %(m)C(m)C values as markers for oral cancer detection with sensitivity and specificity of 86.7% and 56.7%, respectively. Alu hypomethylation is likely to be associated with multistep oral carcinogenesis, and might be developed as a screening tool for oral cancer detection.

Clinical evaluation of an autofluorescence diagnostic device for oral cancer detection

The prognosis for patients with oral squamous cell carcinoma remains poor despite advances in multimodal treatment concepts. Early diagnosis and treatment is the key to improved patient survival. A device (VELscope) that uses autofluorescence technology, allowing direct fluorescence visualization of the oral cavity, might be a useful tool for oral cancer detection or as an adjunct to standard clinical examination. A total of 289 patients with oral premalignant lesions were randomly divided into two groups for clinical examination of precancerous oral lesions. In group 1, 166 patients were examined conventionally with white light, and in group 2, 123 patients were examined with the autofluorescence visualization device (VELscope) in addition to the white light examination. Biopsies were obtained from all suspicious areas identified in both examination groups (n=52). In the first step, baseline characteristics of the two groups (only white light vs. white light and VELscope) were compared to exclude selection bias. In the second step, for the group examined with white light and VELscope (123 patients), the diagnostic strategies were compared with regard to sensitivity and specificity using biopsy as the gold standard. The results showed that using the VELscope leads to higher sensitivity (100% instead of 17%), but to lower specificity (74% instead of 97%). Thus, we can conclude that the VELscope is a useful new diagnostic device for detection of oral cancer diseases.

Aberrant DNA methylation of tumor‐related genes in oral rinse

The early detection of oral squamous cell carcinoma (OSCC) is important, and a screening test with high sensitivity and specificity is urgently needed. Therefore, in this study, the authors investigated the methylation status of tumor-related genes with the objective of establishing a noninvasive method for the detection of OSCC. Oral rinse samples were obtained from 34 patients with OSCC and from 24 healthy individuals (controls). The methylation status of 13 genes was determined by using methylation-specific polymerase chain reaction analysis and was quantified using a microchip electrophoresis system. Promoter methylation in each participant was screened by receiver operating characteristic analysis, and the utility of each gene's methylation status, alone and in combination with other genes, was evaluated as a tool for oral cancer detection. Eight of the 13 genes had significantly higher levels of DNA methylation in samples from patients with OSCC than in controls. The genes E-cadherin (ECAD), transmembrane protein with epidermal growth factor-like and 2 follistatin-like domains 2 (TMEFF2), retinoic acid receptor beta (RARβ), and O-6 methylguanine DNA methyltransferase (MGMT) had high sensitivity (>75%) and specificity for the detection of oral cancer. OSCC was detected with 100% sensitivity and 87.5% specificity using a combination of ECAD, TMEFF2, RARβ, and MGMT and with 97.1% sensitivity and 91.7% specificity using a combination of ECAD, TMEFF2, and MGMT. The aberrant methylation of a combination of marker genes present in oral rinse samples was used to detect OSCC with >90% sensitivity and specificity. The detection of methylated marker genes from oral rinse samples has great potential for the noninvasive detection of OSCC.

Autofluorescence characteristics of healthy oral mucosa at different anatomical sites.

Autofluorescence spectroscopy is a promising tool for oral cancer detection. Its reliability might be improved by using a reference database of spectra from healthy mucosa. We investigated the influence of anatomical location on healthy mucosa autofluorescence. Spectra were recorded from 97 volunteers using seven excitation wavelengths (350-450 nm), 455-867 nm emission. We studied intensity and applied principal component analysis (PCA) with classification algorithms. Class overlap estimates were calculated. We observed differences in fluorescence intensity between locations. These were significant but small compared to standard deviations (SD). Normalized spectra looked similar for locations, except for the dorsal side of the tongue (DST) and the vermilion border (VB). Porphyrin-like fluorescence was observed frequently, especially at DST. PCA and classification confirmed VB and DST to be spectrally distinct. The remaining locations showed large class overlaps. No relevant systematic spectral differences have been observed between most locations, allowing the use of one large reference database. For DST and VB separate databases are required.