Background: Optical coherence tomography (OCT) is a recently developed compact technology which uses infrared light to perform cross-sectional imaging on a micrometer scale. Since OCT provides imaging at a resolution comparable to conventional histology and does not require direct contact with the tissue surface, a role in real-time surgical diagnostics represents a logical extension. In this work, we test the feasibility of OCT for surgical diagnostics by demonstrating imaging in tissue relevent to microsurgical intervention, a previously undescribed observation. Materials and methods: Over 50 sites on nervous, reproductive, and microvascular specimens from 10 patients were examined postmortem with OCT. After imaging, tissue was registered with microinjections of dye, under visible light laser guidance, followed by routine histologic processing to confirm the identity of microstructure. Results: The 16 ± 1 μm resolution allowed subsurface microstructure to be identified at unprecedented resolution. Structures identified included fascicles of peripheral nerves, the internal elastic membrane of microvessels, and the granular layer of the cerebellum. Conclusions: The ability of OCT to provide micrometer-scale definition of tissue microstructure suggests a role in surgical diagnostics. Future in vivo investigations are merited to establish its utility for morbidity reduction associated with surgical intervention.

Optical Biopsy with Optical Coherence Tomography: Feasibility for Surgical Diagnostics

BACKGROUND
Early detection of premalignant/malignant lesions in the oral cavity can certainly improve the patient's prognosis. This study presents fluorescence imaging with the topical application of 5-aminolevulinic as a way to improve detection of various oral tissue pathologies. This procedure depends mainly on comparing the intensity of red and green fluorescence emitted from tissues during examination.


MATERIALS AND METHODS
Seventy-one patients who presented with clinically suspicious oral leukoplakia were recruited for this study. Each of the patients was required to have 5-aminolevulinic acid in the form of mouth rinse prior to fluorescence imaging. Following this a surgical biopsy was acquired from the exact examination site. The results of the fluorescence spectroscopy have been compared with histopathology.


RESULTS
A Student's t-test was applied to test the viability of the ratio between red and green fluorescence. The red-to-green ratio was found to increase significantly when the lesion was identified as dysplastic or carcinoma in situ. By applying a threshold line to discriminate between normal and dysplastic lesions; a sensitivity of 83-90% and specificity of 79-89% were obtained.


CONCLUSION
Fluorescence spectroscopy combined with 5-aminolevulinic acid-induced protoporphyrin IX was found as a valuable tool in the diagnosis of oral premalignancy. This technique offers the potential to be advantageous over other non-optical techniques in terms of providing real-time diagnosis, in situ monitoring, cost effectiveness and more tolerated by patient compared to surgical biopsy.

Fluorescence spectroscopy combined with 5-aminolevulinic acid induced protoporphyrin IX fluorescence in detecting oral premalignancy

The paper proposes an innovative deep convolutional neural network (DCNN) combined with texture map for detecting cancerous regions and marking the ROI in a single model automatically. The proposed DCNN model contains two collaborative branches, namely an upper branch to perform oral cancer detection, and a lower branch to perform semantic segmentation and ROI marking. With the upper branch the network model extracts the cancerous regions, and the lower branch makes the cancerous regions more precision. To make the features in the cancerous more regular, the network model extracts the texture images from the input image. A sliding window is then applied to compute the standard deviation values of the texture image. Finally, the standard deviation values are used to construct a texture map, which is partitioned into multiple patches and used as the input data to the deep convolutional network model. The method proposed by this paper is called texture-map-based branch-collaborative network. In the experimental result, the average sensitivity and specificity of detection are up to 0.9687 and 0.7129, respectively based on wavelet transform. And the average sensitivity and specificity of detection are up to 0.9314 and 0.9475, respectively based on Gabor filter.

Texture-Map-Based Branch-Collaborative Network for Oral Cancer Detection

Population-based oral cancer screening appears to be a promising health promotion strategy (especially in high-risk individuals) with significant increases in quality-adjusted life years saved. However, the current protocol, conventional visual inspection, and palpation of oral soft tissues for the early detection of pre-malignant or malignant changes, appears to be deficient. The adjunctive application of technology to highlight such lesions may increase the diagnostic yield. The purpose of this pilot study was to collect data, which might support the hypothesis that oral soft tissues exhibit features similar to the cervical epithelium following an acetic acid wash and visual inspection under chemiluminescent illumination. The data provides strong evidence to support the hypothesis. Epithelium with hyperkeratinization, hyperparakeratinization, and/or chronic inflammatory infiltrate reflects the diffuse, low-level, blue-white chemiluminescent light more strongly and appears amplified. Similarly, epithelium with an altered nuclear-cytoplasmic ratio also reflects the diffuse, low-level, blue-white chemiluminescent light. In such cases, the lesions become clinically discernible and appear \"acetowhite.\" Large-scale studies are required to further refine issues related to the selectivity and specificity of the technology.

Acetic acid wash and chemoluminescent illumination as an adjunct to conventional oral soft tissue examination for the detection of dysplasia: a pilot study

Altered peritumoral microRNA expression predicts head and neck cancer patients with a high risk of recurrence.

Head and neck cancer (HNC) is the sixth most common cancer worldwide,[1] which includes cancers of the aerodigestive tract, including lip, oral cavity, nasal cavity, paranasal sinuses, pharynx, larynx, oropharynx, hypopharynx, salivary glands, and local lymph nodes.[2] More than 90% of these are head and neck squamous cell carcinomas (HNSCC), arising from the mucosal lining in these regions.[3, 4]

/pdf/contemporary-assessment-and-management-of-head-and-neck-vq232di0t4.pdf

Contemporary Assessment and Management of Head and Neck Cancer Surgical Margins

Oral and pharyngeal cancers combined rank within the top ten most common malignancies in the world for men, with an estimated global incidence of oral cancer alone at approximately 275,000 [1]. Over 90 % of oral cancers affecting the lips, gingiva, tongue, buccal mucosa, floor of mouth and hard palate arise from the squamous epithelium and are thus termed oral squamous cell carcinomas (OSCCs) [2, 3]. Conversely, neoplasms originating from the epithelial lining of oropharynx are called oropharyngeal squamous cell carcinomas (OPSCCs) [1].

Advances in Early Detection and Diagnostic Adjuncts in Oral Cavity Cancer

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Contemporary Assessment and Management of Head and Neck Cancer Surgical Margins

Advances in Early Detection and Diagnostic Adjuncts in Oral Cavity Cancer