In vivo diagnosis of oral dysplasia and malignancy using optical coherence tomography: preliminary studies in 50 patients

Application of Targeted Optical Coherence Tomography in Oral Cancer: A Cross-Sectional Preliminary Study

BACKGROUND/OBJECTIVES

The diagnosis of oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC) represent a significant challenge in oral medicine. Optical coherence tomography (OCT) shows promise for evaluating oral tissue microstructure but lacks standardized diagnostic protocols tailored to the structural variability and lesions of oral mucosa.

METHODS

This cross-sectional observational study aims to evaluate the diagnostic accuracy of targeted biopsy-based and site-coded OCT protocols for common OPMDs and OSCC. Adult patients clinically diagnosed with OPMDs, including oral leukoplakia (OL), oral lichen planus (OLP), and OSCC were enrolled. Clinical and OCT evaluation before and after punch scalpel-site registration preceding diagnostic biopsy on the target site was performed. Blinded observers analyzed the OCT scans for OCT-based diagnoses. Sensitivity, specificity, and diagnostic accuracy for OCT evaluations before and after punch scalpel-site registration were statistically compared with histological findings.

RESULTS

A dataset of 2520 OCT scans and 210 selected images from 21 patients was obtained. Sensitivity and specificity post-target site registration were high for OSCC (98.57%, 100.00%), OL (98.57%, 98.57%), and OLP (97.14%, 98.57%). The positive predictive values ranged from 97.14% to 100.00%, while negative predictive values ranged from 98.57% to 99.29%. Inter-observer agreements were strong for OSCC (0.84) and moderate for OL (0.54) and OLP (0.47-0.49). Targeted OCT scans significantly improved diagnostic accuracy for all conditions (p < 0.001).

CONCLUSIONS

This preliminary study supports using site-targeted OCT scans followed by a site-targeted punch biopsy, enhancing precision in oral diagnostics. This approach is foundational for developing pioneering automated algorithms guiding oral cancer and pre-cancer diagnosis via OCT imaging.

Enhancing Oral Cancer Detection: A Systematic Review of the Diagnostic Accuracy and Future Integration of Optical Coherence Tomography with Artificial Intelligence

Introduction: Optical Coherence Tomography (OCT) has emerged as an important imaging modality in non-invasive diagnosis for oral cancer and can provide real-time visualisation of tissue morphology with the required high resolution. This systematic review aims to assess the diagnostic accuracy of OCT in the detection of oral cancers, and to explore the potential integration of OCT with artificial intelligence (AI) and other imaging techniques to enhance diagnostic precision and clinical outcomes in oral healthcare. Methods: A systematic literature search was conducted across PubMed, Embase, Scopus, Google Scholar, Cochrane Central Register, and Web of Science from inception until August 2024. Studies were included if they employed OCT for oral cancer detection, reported diagnostic outcomes, such as sensitivity and specificity, and were conducted on human subjects. Data extraction and quality assessment were performed independently by two reviewers. The synthesis highlights advancements in OCT technology, including AI-enhanced interpretations. Results: A total of 9 studies met the inclusion criteria, encompassing a total of 860 events (cancer detections). The studies spanned from 2008 to 2022 and utilised various OCT techniques, including clinician-based, algorithm-based, and AI-driven interpretations. The findings indicate OCT's high diagnostic accuracy, with sensitivity ranging from 75% to 100% and specificity from 71% to 100%. AI-augmented OCT interpretations demonstrated the highest accuracy, emphasising OCT's potential in early cancer detection and precision in guiding surgical interventions. Conclusions: OCT could play a very prominent role as a new diagnostic tool for oral cancer, with very high sensitivity and specificity. Future research pointed towards integrating OCT with other imaging methods and AI systems in providing better accuracy of diagnoses, plus more clinical usability. Further development and validation with large-scale multicentre trials is imperative for the realisation of this potential in changing the way we practice oral healthcare.

Optical coherence tomography: Promising imaging technique for the diagnosis of oral mucosal diseases

OBJECTIVE

This review aims to summarize the latest application of optical coherence tomography (OCT) in oral mucosal diseases, promoting an accurate and earlier diagnosis of such disorders, which are difficult to be differentiated.

SUBJECTIVE AND METHODS

References on the application of OCT in oral mucosal diseases were mainly obtained from PubMed, Embase, Web of Science and Scopus databases, using the keywords: "optical coherence tomography and 'oral mucosa/oral cancers/oral potentially malignant diseases/oral lichen planus/oral leukoplakia/oral erythroplakia/discoid lupus erythematosus/oral autoimmune bullous diseases/oral ulcers/erythema multiforme/oral mucositis'".

RESULTS

It is found that OCT is showing a promising application potential in the early detection, diagnosis, differential diagnosis, monitoring of oral cancer and oral dysplastic lesions, as well as the delineation of tumor margins. OCT is also playing an increasingly important role in the diagnosis of oral potentially malignant disorders, oral mucosal bullous diseases, oral ulcerative diseases, erythema multiforme, and the early detection of oral mucositis.

CONCLUSION

Optical coherence tomography, as a novel optical technique featured by real-time, noninvasive, dynamic and high-resolution imaging, is of great use to serve as an adjunct tool for the diagnosis, differential diagnosis, monitoring and therapy evaluation of oral mucosal diseases.

State of the Art in the Diagnosis and Assessment of Oral Malignant and Potentially Malignant Disorders: Present Insights and Future Outlook-An Overview

Oral Potentially Malignant Disorder (OPMD) is a significant concern for clinicians due to the risk of malignant transformation. Oral Squamous Cell Carcinoma (OSCC) is a common type of cancer with a low survival rate, causing over 200,000 new cases globally each year. Despite advancements in diagnosis and treatment, the five-year survival rate for OSCC patients remains under 50%. Early diagnosis can greatly improve the chances of survival. Therefore, understanding the development and transformation of OSCC and developing new diagnostic methods is crucial. The field of oral medicine has been advanced by technological and molecular innovations, leading to the integration of new medical technologies into dental practice. This study aims to outline the potential role of non-invasive imaging techniques and molecular signatures for the early detection of Oral Malignant and Potentially Malignant Disorders.

Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges

Oral cancer is a cancer type that is widely prevalent in low-and middle-income countries with a high mortality rate, and poor quality of life for patients after treatment. Early treatment of cancer increases patient survival, improves quality of life and results in less morbidity and a better prognosis. To reach this goal, early detection of malignancies using technologies that can be used in remote and low resource areas is desirable. Such technologies should be affordable, accurate, and easy to use and interpret. This review surveys different technologies that have the potentials of implementation in primary health and general dental practice, considering global perspectives and with a focus on the population in India, where oral cancer is highly prevalent. The technologies reviewed include both sample-based methods, such as saliva and blood analysis and brush biopsy, and more direct screening of the oral cavity including fluorescence, Raman techniques, and optical coherence tomography. Digitalisation, followed by automated artificial intelligence based analysis, are key elements in facilitating wide access to these technologies, to non-specialist personnel and in rural areas, increasing quality and objectivity of the analysis while simultaneously reducing the labour and need for highly trained specialists.

Deep Learning Techniques and Imaging in Otorhinolaryngology-A State-of-the-Art Review

Over the last decades, the field of medicine has witnessed significant progress in artificial intelligence (AI), the Internet of Medical Things (IoMT), and deep learning (DL) systems. Otorhinolaryngology, and imaging in its various subspecialties, has not remained untouched by this transformative trend. As the medical landscape evolves, the integration of these technologies becomes imperative in augmenting patient care, fostering innovation, and actively participating in the ever-evolving synergy between computer vision techniques in otorhinolaryngology and AI. To that end, we conducted a thorough search on MEDLINE for papers published until June 2023, utilizing the keywords 'otorhinolaryngology', 'imaging', 'computer vision', 'artificial intelligence', and 'deep learning', and at the same time conducted manual searching in the references section of the articles included in our manuscript. Our search culminated in the retrieval of 121 related articles, which were subsequently subdivided into the following categories: imaging in head and neck, otology, and rhinology. Our objective is to provide a comprehensive introduction to this burgeoning field, tailored for both experienced specialists and aspiring residents in the domain of deep learning algorithms in imaging techniques in otorhinolaryngology.

Characteristics of Clinically Classified Oral Lichen Planus in Optical Coherence Tomography: A Descriptive Case-Series Study

Malignant transformation of oral lichen planus (OLP) into oral squamous cell carcinoma is considered as one of the most serious complications of OLP. For the early detection of oral cancer in OLP follow-up, accurate localization of the OLP center is still difficult but often required for confirmatory biopsy with histopathological examination. Optical coherence tomography (OCT) offers the potential for more reliable biopsy sampling in the oral cavity as it is capable of non-invasively imaging the degenerated oral layer structure. In this case-series study with 15 patients, features of clinically classified forms of OLP in OCT cross-sections were registered and correlated with available histologic sections. Besides patients with reticular, atrophic, erosive and plaque-like OLP, two patients with leukoplakia were included for differentiation. The results show that OCT yields information about the epithelial surface, thickness and reflectivity, as well as the identifiability of the basement membrane and the vessel network, which could be used to complement the visual clinical appearance of OLP variants and allow a more accurate localization of the OLP center. This forms the basis for further studies on OCT-assisted non-invasive clinical classification of OLP, with the aim of enabling decision support for biopsy sampling in the future.

Efficacy of optical coherence tomography in the diagnosing of oral cancerous lesion: systematic review and meta-analysis

Non-invasive diagnostic tools that facilitate visualization of potentially malignant oral lesions and cancers have been introduced. Oral lesions detected by optical coherence tomography (OCT) were compared to reference results based on histological findings. The diagnostic odds ratio (DOR), along with summary receiver operating characteristic curve (SROC), area under SROC, sensitivity, specificity, and negative predictive values, were the outcomes. The DOR of OCT was 86.9190 (95% confidence interval [CI]: 38.7435, 194.9985), and the area under SROC was 0.951. OCT showed good sensitivity (0.9138; 95% CI: 0.8758, 0.9409) and specificity (0.9110; 95% CI: 0.8568, 0.9460), and a high negative predictive value (0.9225; 95% CI: 0.8863, 0.9478). Diagnostic sensitivity was higher when using artificial intelligence and automated algorithms compared to diagnoses made by clinicians. OCT is non-invasive, provides rapid results without radiation exposure, and can aid in the diagnosis and follow-up of oral cancer and oral precancerous lesions.

Site-Coded Oral Squamous Cell Carcinoma Evaluation by Optical Coherence Tomography (OCT): A Descriptive Pilot Study

Optical Coherence Tomography (OCT) is an emerging non-invasive method for oral diagnostics, proving to be a practicable device for epithelial and subepithelial evaluation. The potential validity of OCT in oral cancer assessment has been explored but, to date, there are very few investigations conducted with a systematic comparison between clinical/histological and OCT parameters, especially in strict reference to the anatomical site-codification of the oral mucosa. In this regard, our study performed a two-steps evaluation (in vivo OCT and histological investigations) of suspected OSCCs, progressively recruited, using as references the OCT images of the same site-coded healthy mucosa, to provide as much as possible site-specific determinants. Thirty histologically confirmed OSCCs were recruited. Specific OCT mucosal features (SEL-Stratified Epithelial Layer; BM-Basement Membrane; LP-Lamina Propria) were registered and processed using the SRQR (Standards for Reporting Qualitative Research) statement. The systematic dual descriptive OCT analysis revealed that OSCC scans present a complete alteration of epithelial (KL, SEL) and subepithelial (BM, LP) layers with a site-specificity characteristic; moreover, peculiar OCT configurations such as "icicle-like" structures could be strongly suggestive of neoplastic infiltration. This study supports the OCT use for the development of more specific optical structural models applied to oral carcinogenesis.

Optical Imaging in the Diagnosis of OPMDs Malignant Transformation

Oral potentially malignant disorders (OPMDs) are a heterogeneous group of oral lesions with a variable risk of malignant transformation to oral squamous cell carcinoma. The current OPMDs malignant transformation screening depends on conventional oral examination (COE) and is confirmed by biopsy and histologic examination. However, early malignant lesions with subtle mucosal changes are easily unnoticed by COE based on visual inspection and palpation. Optical techniques have been used to determine the biological structure, composition, and function of cells and tissues noninvasively by analyzing the changes in their optical properties. The oral epithelium and stroma undergo persistent structural, functional, and biochemical alterations during malignant transformation, leading to variations in optical tissue properties; optical techniques are thus powerful tools for detecting OPMDs malignant transformation. The optical imaging methods already used to detect OPMDs malignant transformation in vivo include autofluorescence imaging, narrowband imaging, confocal reflectance microscopy, and optical coherence tomography. They exhibit advantages over COE in detecting biochemical or morphologic changes at the molecular or cellular level in vivo; however, limitations also exist. This article comprehensively reviews the various real-time in vivo optical imaging methods used in the adjunctive diagnosis of OPMDs malignant transformation. We focus on the principles of these techniques, review their clinical application, and compare and summarize their advantages and disadvantages. Finally, we conclude with a discussion of current challenges and future directions of this field.

Identification of Biomarkers Associated with Cancerous Change in Oral Leukoplakia Based on Integrated Transcriptome Analysis

Objective

Oral leukoplakia (OLK) is the most common precancerous lesion in the oral cavity. This study aimed to explore key biomarkers for monitoring OLK for early diagnosis of oral squamous cell carcinoma (OSCC) and screen small-molecule drugs for the prevention of OSCC.

Method

The Gene Expression Omnibus (GEO) database was explored to extract two microarray datasets, namely, GSE85195 and GSE25099. The data of the normal group, OLK group, and OSCC group were analyzed by weighted gene coexpression network analysis (WGCNA) to identify the most significant gene module and differentially expressed genes (DEGs). The intersection genes were extracted as the key genes of OLK carcinogenesis. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed in the module. Connectivity Map and molecular docking were used to screen small-molecule drugs. The diagnostic values of four key genes were identified and verified in the GSE26549 dataset.

Results

WGCNA obtained the red module (r = −0.91, p < 0.05) with the strongest correlation with cancerous phenotype. GO enrichment analysis showed 60 pathways, including 28 biological processes, 11 cell components, and 21 molecular functions, and KEGG enrichment analysis showed 4 pathways (p < 0.05). In the differential expression analysis, there was no intersection between the upregulated genes and the red module genes. However, the intersection of the downregulated genes and the red module genes yielded 4 key genes: dopachrome tautomerase (DCT), keratin 3 (KRT3), keratin 76 (KRT76), and FAM3 metabolic regulation signal molecule B (FAM3B). The area under the curve of the diagnostic model constructed by these four genes was 0.963 (CI = 0.913–1.000). The sensitivity was 0.933, and the specificity was 0.923. The diagnostic model was successfully verified in GSE26549 (AUC = 0.745, CI = 0.638–0.851). Compared with the diagnostic models of the previous studies, the diagnostic efficiency of this model was the highest. The small-molecule drugs, selumetinib and benidipine, were selected according to the gene expression profile and showed binding activity when docking with the above molecules.

Conclusions

This study provides new targets and drugs for OLK. These targets could be used as the key diagnostic molecules for long-term follow-up of OLK. The small-molecule drugs selumetinib and benidipine could be used for the prevention and treatment of OSCC.

A handheld fiber-optic probe to enable optical coherence tomography of oral soft tissue

This study presents a highly miniaturized, handheld probe developed for rapid assessment of soft tissue using optical coherence tomography (OCT). OCT is a non-invasive optical technology capable of visualizing the sub-surface structural changes that occur in soft tissue disease such as oral lichen planus. However, usage of OCT in the oral cavity has been limited, as the requirements for high-quality optical scanning have often resulted in probes that are heavy, unwieldy and clinically impractical. In this paper, we present a novel probe that combines an all-fiber optical design with a light-weight magnetic scanning mechanism to provide easy access to the oral cavity. The resulting probe is approximately the size of a pen (10 mm 140 mm) and weighs only 10 grams. To demonstrate the feasibility and high image quality achieved with the probe, imaging is performed on the buccal mucosa and alveolar mucosa during routine clinical assessment of six patients diagnosed with oral lichen planus. Results show the loss of normal tissue structure within the lesion, and contrast this with the clear delineation of tissue layers in adjacent inconspicuous regions. The results also demonstrate the ability of the probe to acquire a three-dimensional data volume by manually sweeping across the surface of the mucosa. The findings of this study show the feasibility of using a small, lightweight probe to identify pathological features in oral soft tissue.

Oral cancer diagnostics: An overview

Cancer was first mentioned in medicine texts by Egyptians. Ancient Indians studied oral cancer in great detail under Susruta. Cancer has continued to be a challenge to physicians from ancient times to the present. Over the years, cancer underwent a shift in management from radical surgeries toward a more preventive approach. Early diagnosis is vital in reducing cancer-associated mortality especially with oral cancer. Even though the mainstay of oral cancer diagnosis still continues to be a trained clinician and histopathologic examination of malignant tissues. Translating innovation in technological advancements in diagnostic aids for oral cancer will require both improved decision-making and a commitment toward optimizing cost, skills, turnover time between capturing data and obtaining a useful result. The present review describes the conventional to most advanced diagnostic modalities used as oral cancer diagnostics. It also includes the new technologies available and the future trends in oral cancer diagnostics.

Noninvasive in vivo imaging of oral mucosa: state-of-the-art

Technological development has interested most of the dentistry's branches leading to the use of other medical technologies non previously involved in dental practice. This study aims to evaluate the potential role of non-invasive imaging techniques in oral pathology workflow. Optical coherence tomography has been described by several authors as a promising aid for differential diagnosis of autoimmune diseases and to detect epithelial subversion of the oral mucosa before the clinical manifestation of oral mucositis. High-frequency ultrasound offers the chance to assess lesional dimensions both in benign and malignant lesions with a high dimensional reliability compared with histopathology. Reflectance confocal microscopy seems to be helpful in the early detection of cytological changes due to its high resolution, suggesting a more interesting role in the analysis of malignant lesions. The study presented highlighted the potential role of noninvasive in vivo imaging although further studies are needed for the further validation of these techniques.

Noninvasive Imaging Methods to Improve the Diagnosis of Oral Carcinoma and Its Precursors: State of the Art and Proposal of a Three-Step Diagnostic Process

Simple Summary

Oral squamous cell carcinoma (OSCC) accounts for 90–95% of malignant tumors of the lip and oral cavity and is associated with high mortality in the advanced stages. Early diagnosis is a challenge for oral pathologists and dentists, due to the ambiguous appearance of early OSCC, which is often misdiagnosed, mistreated, and associated with diagnostic delay. The gold standards for OSCC diagnosis are biopsy and histopathological assessment, but these procedures are invasive and time-consuming. Adjunctive noninvasive techniques allow the definition of the malignant features of a suspicious lesion in real time and noninvasively, thus improving the diagnostic procedure. The present review aimed to focus on some of the main promising noninvasive imaging techniques, to highlight their perspective adoption in a three-step diagnosis, which is idealistically faster and better, as well as enables the patient’s compliance.

Abstract

Oral squamous cell carcinoma (OSCC) is the most prevalent form of cancer of lips and oral cavity, and its diagnostic delay, caused by misdiagnosis at the early stages, is responsible for high mortality ratios. Biopsy and histopathological assessment are the gold standards for OSCC diagnosis, but they are time-consuming, invasive, and do not always enable the patient’s compliance, mainly in cases of follow-up with the need for more biopsies. The use of adjunctive noninvasive imaging techniques improves the diagnostic approach, making it faster and better accepted by patients. The present review aims to focus on the most consolidated diagnostic techniques, such as vital staining and tissue autofluorescence, and to report the potential role of some of the most promising innovative techniques, such as narrow-band imaging, high-frequency ultrasounds, optical coherence tomography, and in vivo confocal microscopy. According to their contribution to OSCC diagnosis, an ideal three-step diagnostic procedure is proposed, to make the diagnostic path faster, better, and more accurate.

Automated Detection and Classification of Oral Lesions Using Deep Learning to Detect Oral Potentially Malignant Disorders

Simple Summary

Oral cancer is the most common type of head and neck cancer worldwide. The detection of oral potentially malignant disorders, which carry a risk of developing into cancer, often provides the best chances for curing the disease and is therefore crucial for improving morbidity and mortality outcomes from oral cancer. In this study, we explored the potential applications of computer vision and deep learning techniques in the oral cancer domain within the scope of photographic images and investigated the prospects of an automated system for identifying oral potentially malignant disorders with a two-stage pipeline. Our preliminary results demonstrate the feasibility of deep learning-based approaches for the automated detection and classification of oral lesions in real time. The proposed model offers great potential as a low-cost and non-invasive tool that can support screening processes and improve the detection of oral potentially malignant disorders.

Abstract

Oral cancer is the most common type of head and neck cancer worldwide, leading to approximately 177,757 deaths every year. When identified at early stages, oral cancers can achieve survival rates of up to 75–90%. However, the majority of the cases are diagnosed at an advanced stage mainly due to the lack of public awareness about oral cancer signs and the delays in referrals to oral cancer specialists. As early detection and treatment remain to be the most effective measures in improving oral cancer outcomes, the development of vision-based adjunctive technologies that can detect oral potentially malignant disorders (OPMDs), which carry a risk of cancer development, present significant opportunities for the oral cancer screening process. In this study, we explored the potential applications of computer vision techniques in the oral cancer domain within the scope of photographic images and investigated the prospects of an automated system for detecting OPMD. Exploiting the advancements in deep learning, a two-stage model was proposed to detect oral lesions with a detector network and classify the detected region into three categories (benign, OPMD, carcinoma) with a second-stage classifier network. Our preliminary results demonstrate the feasibility of deep learning-based approaches for the automated detection and classification of oral lesions in real time. The proposed model offers great potential as a low-cost and non-invasive tool that can support screening processes and improve detection of OPMD.

Recent advances in point-of-care diagnostics for oral cancer

Early-stage diagnosis is a crucial step in reducing the mortality rate in oral cancer cases. Point-of-care (POC) devices for oral cancer diagnosis hold great future potential in improving the survival rates as well as the quality of life of oral cancer patients. The conventional oral examination followed by needle biopsy and histopathological analysis have limited diagnostic accuracy. Besides, it involves patient discomfort and is not feasible in resource-limited settings. POC detection of biomarkers and diagnostic adjuncts has emerged as non- or minimally invasive tools for the diagnosis of oral cancer at an early stage. Various biosensors have been developed for the rapid detection of oral cancer biomarkers at the point-of-care. Several optical imaging methods have also been employed as adjuncts to detect alterations in oral tissue indicative of malignancy. This review summarizes the different POC platforms developed for the detection of oral cancer biomarkers, along with various POC imaging and cytological adjuncts that aid in oral cancer diagnosis, especially in low resource settings. Various immunosensors and nucleic acid biosensors developed to detect oral cancer biomarkers are summarized with examples. The different imaging methods used to detect oral tissue malignancy are also discussed herein. Additionally, the currently available commercial devices used as adjuncts in the POC detection of oral cancer are emphasized along with their characteristics. Finally, we discuss the limitations and challenges that persist in translating the developed POC techniques in the clinical settings for oral cancer diagnosis, along with future perspectives.

Preliminary evaluation of the utility of optical coherence tomography in detecting structural changes during photobiomodulation treatment in patients with atrophic-erosive oral lichen planus

INTRODUCTION

Oral lichen planus (OLP) is a common oral inflammatory condition. Against symptomatic atrophic-erosive OLP, topical steroids, or photobiomodulation (PBM) are deployed. Optical coherence tomography (OCT) provides a real-time, non-invasive, tissue investigation. Aim of this study was to evaluate modifications of OCT pattern in patients with painful atrophic-erosive OLP, before and after treatment with PBM, comparing those results with patients treated with topical steroid.

METHODS

Two groups of 20 OLP patients were evaluated. Group A underwent two daily application of 0.05 % clobetasol propionate for 8 weeks; group B was treated with eight weekly PBM sessions using a 980/645 nm diode laser. OCT scans were performed before and after treatment, and six months after end of the proposed protocol. Changes of width of stratified epithelium (EP) and lamina propria (LP) were quantified.

RESULTS

After 8-weeks, both groups experienced a significant increase of EP width (p < 0.05), and a significant decrease of LP width (p < 0.05), with Δ-EP in Group A significantly higher than Group B (p = 0.0015); conversely, Δ-LP was not significantly different (p > 0.05). After six months, significant increase of EP width remained only in group B (p = 0.01), with no significant decrease of LP mean width in both groups (p > 0.05).

CONCLUSIONS

Increase of EP and decrease of LP might be explained as consequence of clobetasol and PBM ability to promote epithelial healing, and to reduce interface inflammation. When investigated with OCT, clobetasol appears to provide more significant short-term structural changes, whereas PBM might guarantee long-term alterations.

Application of optical coherence tomography to study the structural features of oral mucosa in biopsy tissues of oral dysplasia and carcinomas

OBJECTIVE

This study aims to examine the ability of optical coherence tomography (OCT) to differentiate ex vivo epithelial structure of benign disorders, dysplastic, and oral squamous cell carcinoma (OSCC) in comparison with the structure of normal marginal mucosa of oral biopsies. As a secondary objective, we examined the inter- and intra-observer variations of OCT measurements of two calibrated assessors.

MATERIALS AND METHODS

Oral biopsies (n = 44) were scanned using the swept source OCT (SSOCT) and grouped by pathology diagnosis to benign, dysplasia or carcinoma. Two trained and calibrated assessors scored on the five OCT variables: thickness of keratin layer (KL), epithelial layer (EL), homogeneity of lamina propria (LP), basement membrane integrity (BMI), and the degree of reflection of the epithelial layer (Ep Re). Chi-square tests and Fischer's exact method were used to compare the data.

RESULTS

The OCT images showed breached BM status in all the OSCC samples (100%). Epithelial reflection was noted to be hyper-reflective in all the OSCC and oral dysplasia samples (100%). An increase in KL in 66.67% of the OSCC and 100% of the oral dysplasia samples was found. EL was increased in all the OSCC samples (100%) and 85.72% of the oral dysplasias. Kappa values showed that there was very good agreement (over 0.7) when scoring individual parameters between the two assessors.

CONCLUSION

The study showed that the BM status was a key parameter in the detection of SCC and for differentiating SCC from oral dysplasia or benign disorders.

CLINICAL RELEVANCE

OCT is a non-invasive and non-radioactive adjunct diagnostic tool that can provide immediate results on the structure of oral mucosa. The BM status measured ex vivo was a key parameter in the detection of SCC and for differentiating SCC from oral dysplasia or benign disorders.

Novel endoscopic optical diagnostic technologies in medical trial research: recent advancements and future prospects

Novel endoscopic biophotonic diagnostic technologies have the potential to non-invasively detect the interior of a hollow organ or cavity of the human body with subcellular resolution or to obtain biochemical information about tissue in real time. With the capability to visualize or analyze the diagnostic target in vivo, these techniques gradually developed as potential candidates to challenge histopathology which remains the gold standard for diagnosis. Consequently, many innovative endoscopic diagnostic techniques have succeeded in detection, characterization, and confirmation: the three critical steps for routine endoscopic diagnosis. In this review, we mainly summarize researches on emerging endoscopic optical diagnostic techniques, with emphasis on recent advances. We also introduce the fundamental principles and the development of those techniques and compare their characteristics. Especially, we shed light on the merit of novel endoscopic imaging technologies in medical research. For example, hyperspectral imaging and Raman spectroscopy provide direct molecular information, while optical coherence tomography and multi-photo endomicroscopy offer a more extensive detection range and excellent spatial-temporal resolution. Furthermore, we summarize the unexplored application fields of these endoscopic optical techniques in major hospital departments for biomedical researchers. Finally, we provide a brief overview of the future perspectives, as well as bottlenecks of those endoscopic optical diagnostic technologies. We believe all these efforts will enrich the diagnostic toolbox for endoscopists, enhance diagnostic efficiency, and reduce the rate of missed diagnosis and misdiagnosis.

Improving Oral Cancer Outcomes with Imaging and Artificial Intelligence

Early diagnosis is the most important determinant of oral and oropharyngeal squamous cell carcinoma (OPSCC) outcomes, yet most of these cancers are detected late, when outcomes are poor. Typically, nonspecialists such as dentists screen for oral cancer risk, and then they refer high-risk patients to specialists for biopsy-based diagnosis. Because the clinical appearance of oral mucosal lesions is not an adequate indicator of their diagnosis, status, or risk level, this initial triage process is inaccurate, with poor sensitivity and specificity. The objective of this study is to provide an overview of emerging optical imaging modalities and novel artificial intelligence-based approaches, as well as to evaluate their individual and combined utility and implications for improving oral cancer detection and outcomes. The principles of image-based approaches to detecting oral cancer are placed within the context of clinical needs and parameters. A brief overview of artificial intelligence approaches and algorithms is presented, and studies that use these 2 approaches singly and together are cited and evaluated. In recent years, a range of novel imaging modalities has been investigated for their applicability to improving oral cancer outcomes, yet none of them have found widespread adoption or significantly affected clinical practice or outcomes. Artificial intelligence approaches are beginning to have considerable impact in improving diagnostic accuracy in some fields of medicine, but to date, only limited studies apply to oral cancer. These studies demonstrate that artificial intelligence approaches combined with imaging can have considerable impact on oral cancer outcomes, with applications ranging from low-cost screening with smartphone-based probes to algorithm-guided detection of oral lesion heterogeneity and margins using optical coherence tomography. Combined imaging and artificial intelligence approaches can improve oral cancer outcomes through improved detection and diagnosis.

In Vivo Endoscopic Optical Coherence Tomography of the Healthy Human Oral Mucosa: Qualitative and Quantitative Image Analysis

To date, there is still a lack of reliable imaging modalities to improve the quality of consultation, diagnostic and medical examinations of the oral mucosa in dentistry. Even though, optical technologies have become an important element for the detection and treatment of different diseases of soft tissue, for the case of oral screenings the evidence of the benefit in comparison to conventional histopathology is mostly still pending. One promising optical technology for oral diagnostics is optical coherence tomography (OCT). To prove the potential of OCT, even the amount of freely accessible OCT data is not sufficient to describe the variance of healthy human oral soft tissue in vivo. In order to remedy this deficiency, the present study provides in vivo OCT cross sections of the human oral mucosa of the anterior and posterior oral cavity as well as the oropharynx of 47 adult volunteers. A collection of representative OCT cross sections forms the basis for a randomized blinded image analysis by means of seven criteria to assess the main features of the superficial layers of the human oral mucosa and to determine its correlation to regional features known from hematoxylin and eosin (HE) stained histology.

Influence of tissue fixation on depth-resolved birefringence of oral cavity tissue samples

SIGNIFICANCE

To advance our understanding of the contrast observed when imaging with polarization-sensitive optical coherence tomography (PS-OCT) and its correlation with oral cancerous pathologies, a detailed comparison with histology provided via ex vivo fixed tissue is required. The effects of tissue fixation, however, on such polarization-based contrast have not yet been investigated.

AIM

A study was performed to assess the impact of tissue fixation on depth-resolved (i.e., local) birefringence measured with PS-OCT.

APPROACH

A PS-OCT system based on depth-encoded polarization multiplexing and polarization-diverse detection was used to measure the Jones matrix of a sample. A wide variety of ex vivo samples were measured freshly after excision and 24 h after fixation, consistent with standard pathology. Some samples were also measured 48 h after fixation.

RESULTS

The tissue fixation does not diminish the birefringence contrast. Statistically significant changes were observed in 11 out of 12 samples; these changes represented an increase in contrast, overall, by 11% on average.

CONCLUSIONS

We conclude that the fixed samples are suitable for studies seeking a deeper understanding of birefringence contrast in oral tissue pathology. The enhancement of contrast removes the need to image immediately postexcision and will facilitate future investigations with PS-OCT and other advanced polarization-sensitive microscopy methods, such as mapping of the local optic axis with PS-OCT and PS-optical coherence microscopy.

Strategies to improve diagnosis and risk assessment for oral cancer patients

To realise the benefits of new diagnostic techniques for the prediction of oral cancer, further validation and multicentre analyses are needed to determine their clinical impact in contemporary practice.

The use of optical coherence tomography and convolutional neural networks to distinguish normal and abnormal oral mucosa

Incomplete surgical resection of head and neck squamous cell carcinoma (HNSCC) is the most common cause of local HNSCC recurrence. Currently, surgeons rely on preoperative imaging, direct visualization, palpation and frozen section to determine the extent of tissue resection. It has been demonstrated that optical coherence tomography (OCT), a minimally invasive, nonionizing near infrared mesoscopic imaging modality can resolve subsurface differences between normal and abnormal head and neck mucosa. Previous work has utilized two-dimensional OCT imaging which is limited to the evaluation of small regions of interest generated frame by frame. OCT technology is capable of performing rapid volumetric imaging, but the capacity and expertise to analyze this massive amount of image data is lacking. In this study, we evaluate the ability of a retrained convolutional neural network to classify three-dimensional OCT images of head and neck mucosa to differentiate normal and abnormal tissues with sensitivity and specificity of 100% and 70%, respectively. This method has the potential to serve as a real-time analytic tool in the assessment of surgical margins.

Value of Full-Field Optical Coherence Tomography Imaging for the Histological Assessment of Head and Neck Cancer

BACKGROUND AND OBJECTIVES

In head and neck surgery, intraoperative and postoperative evaluation of tumor margins is achieved by histopathological assessment, which is a multistep process. Intraoperative analysis of tumor margins to obtain a preliminary diagnosis is usually carried out on frozen sections. Analysis of frozen sections is challenging due to technical difficulties in processing. Full-field optical coherence tomography (FFOCT) provides ex vivo images of fresh tissue samples at a microscopic scale without tissue processing. The objectives of our study were to define the diagnostic criteria required to interpret head and neck FFOCT images and to evaluate the reliability of a histological diagnosis made on an "optical biopsy" produced by head and neck FFOCT imaging compared with conventional histology.

STUDY DESIGN/MATERIALS AND METHODS

First, we established an atlas of comparative images (FFOCT/standard histology) and defined the diagnostic criteria based on FFOCT images. Two pathologists subsequently performed a blinded review on 57 FFOCT images (32 patients). Specificity and sensitivity were measured by comparison with the standard histological diagnosis. The primary endpoint was major concordance, defined as two classifications leading to the same therapeutic decision (treatment/no treatment).

RESULTS

Pathologists identified four main criteria for tissue diagnosis on FFOCT images: heterogeneous cell distribution, stromal reaction, coiling, and keratinization abnormalities. The correlation study showed good results, with sensitivity from 88% to 90% and specificity from 81% to 87%, regardless of whether the FFOCT image review was performed by a pathologist with or without previous experience in optical imaging.

CONCLUSIONS

Our results demonstrate that FFOCT images can be used by pathologists for differential diagnosis, and that high-resolution FFOCT imaging can provide an assessment of microscopic architecture in head and neck tissues without tissue processing requirements. Lasers Surg. Med. © 2020 Wiley Periodicals, Inc.

Prospective evaluation of oral premalignant lesions using a multimodal imaging system: a pilot study

BACKGROUND

Multimodal optical imaging, incorporating reflectance and fluorescence modalities, is a promising tool to detect oral premalignant lesions in real-time.

METHODS

Images were acquired from 171 sites in 66 patient visits for clinical evaluation of oral lesions. An automated algorithm was used to classify lesions as high- or low-risk for neoplasia. Biopsies were acquired at clinically indicated sites and those classified as high-risk by imaging, at the surgeon's discretion.

RESULTS

Twenty sites were biopsied based on clinical examination or imaging. Of these, 12 were indicated clinically and by imaging; 58% were moderate dysplasia or worse. Four biopsies were indicated by imaging evaluation only; 75% were moderate dysplasia or worse. Finally, four biopsies were indicated by clinical evaluation only; 75% were moderate dysplasia or worse.

CONCLUSION

Multimodal imaging identified more cases of high-grade dysplasia than clinical evaluation, and can improve detection of high grade precancer in patients with oral lesions.

Epithelial tissue thickness improves optical coherence tomography's ability in detecting oral cancer

BACKGROUND

OCT is a non-invasive imaging technique that enables the measurement of epithelial thickness and architectural changes, which can help in the diagnosis of pre-cancerous and cancerous lesions. The purpose of the study was to assess whether epithelial tissue thickness improves optical coherence tomography's ability in detecting oral cancer.

PATIENTS AND METHODS

Surgically resected oral margins from 60 patients diagnosed with oral squamous cell carcinoma were subjected to OCT. Three OCT measurements (immediate, 1 h and 24 h post-resection) were conducted per resected tissue specimen to look at the effect of saline and formalin on the specimen and its effect on the reproducibility of the OCT. OCT was, then, used to measure the epithelial tissue thickness in cancer-free and cancer-involved margins in eight oral anatomical locations. This data was, then, combined with architectural changes data to calculate the sensitivity and specificity.

RESULTS

An overall of 189 cancer-free margins and 51 cancer-involved margins had their epithelial thickness measured using OCT and compared to histopathology. With regards to the validity of the OCT and histopathological measurements, epithelial thickness showed good correlation between different readings at all oral sites. With regards to the reproducibility of the OCT measurements, the mean epithelial thickness for all measurements at first (immediate) and second (1 h post-resection - saline preserved) measurements was not significantly different. Underestimation of the epithelial depth in cancer-free margins was 20 μm, while in the cancer-involved margins was 10 μm. Combining data from architectural changes and epithelial thickness, a sensitivity of 92% and a specificity of 94% was achieved.

CONCLUSION

Oral epithelium measurements using OCT were valid compared to those made with gold standard pathology. Measurements made using OCT was also reproducible with minor underestimation. Epithelial thickness, combined with architectural changes, led to high accuracy in differentiating between cancer-free and cancer-involved margins.

Measurement of Oral Epithelial Thickness by Optical Coherence Tomography

Optical coherence tomography (OCT) is a real-time, in-situ, non-invasive imaging device that is able to perform a cross-sectional evaluation of tissue microstructure based on the specific intensity of back-scattered and reflected light. The aim of the present study was to define normal values of epithelial thickness within the oral cavity. OCT measurements of epithelial thickness were performed in 28 healthy patients at six different locations within the oral cavity. Image analysis was performed using Image J 1.52 software. The healthy epithelium has a mean thickness of 335.59 ± 150.73 µm. According to its location within the oral cavity, the epithelium showed highest values in the region of the buccal mucosa (659.79 µm) and the thinnest one was observed in the mouth’s floor (100.07 µm). OCT has been shown to be useful for the evaluation of oral mucosa in vivo and in real time. Our study provides reference values for the epithelial thickness of multiple sites within the oral cavity. Knowledge of the thickness values of healthy mucosa is, therefore, of fundamental importance.

Advances in oral cancer detection

High incidence of oral carcinoma and its late-stage presentation are the major global healthcare issues. The World Health Organization (WHO) has set early diagnosis and prevention of oral cancer as their primary objective. It is important to consider the time of oral screening, as it plays a pivotal role in understanding the disease prognosis. Critical signs and symptoms that can be identified during initial oral screening can improve the chances of patient's survival. Reports suggest that socio-economic factors, lack of public awareness and delays from primary health care centers are few of the major parameters that contribute to patient's mortality and morbidity. Conventional technique of visual examination of the oral lesion can effectively monitor patient mortality when exposed to risk factors. However, several disadvantages limit the clinical utility of this technique. Thus, screening aids that efficiently differentiate between a benign and malignant lesion as well as deliver information about early OSCC can ameliorate the complications associated with oral cancer diagnosis. Recent advances in optical imaging systems, such as tissue-fluorescence imaging and optical coherence tomography have been proved to be considerably efficient. Additionally, extensive research has been directed towards nanoparticle-based immunosensors, DNA analysis, and salivary proteomics. However, lack of proper clinical trials and correlation with biopsy result hinder the usage of these screening techniques in clinics. In this review, we highlight the importance of early diagnosis of oral cancer as well as discuss about the effectiveness and limitations of the recent diagnostic aids. It can be stated that public awareness regarding routine oral examination and employing screening methods that are non-invasive, robust, and economic, would enhance early stage diagnosis of oral cancer and have a positive impact on patient's survival.

Depth-resolved birefringence imaging of collagen fiber organization in the human oral mucosa in vivo

Stromal collagen organization has been identified as a potential prognostic indicator in a variety of cancers and other diseases accompanied by fibrosis. Changes in the connective tissue are increasingly considered for grading dysplasia and progress of oral squamous cell carcinoma, investigated mainly ex vivo by histopathology. In this study, polarization-sensitive optical coherence tomography (PS-OCT) with local phase retardation imaging is used for the first time to visualize depth-resolved (i.e., local) birefringence of healthy human oral mucosa in vivo. Depth-resolved birefringence is shown to reveal the expected local collagen organization. To demonstrate proof-of-principle, 3D image stacks were acquired at labial and lingual locations of the oral mucosa, chosen as those most commonly affected by cancerous alterations. To enable an intuitive evaluation of the birefringence images suitable for clinical application, color depth-encoded en-face projections were generated. Compared to en-face views of intensity or conventional cumulative phase retardation, we show that this novel approach offers improved visualization of the mucosal connective tissue layer in general, and reveals the collagen fiber architecture in particular. This study provides the basis for future prospective pathological and comparative in vivo studies non-invasively assessing stromal changes in conspicuous and cancerous oral lesions at different stages.

Role of modern imaging techniques for the in vivo diagnosis of lichen planus

Lichen planus (LP) is a chronic inflammatory skin disease that can sometimes affect mucosal surfaces, with unknown pathogenesis, even though it appears to be an autoimmune disease. The diagnosis of lichen planus is usually based on histopathological examination of the lesions. Nowadays, the classical invasive diagnostic methods are replaced by modern non-invasive techniques. In this review, we present the main non-invasive imaging methods (dermoscopy, reflectance confocal microscopy, optical coherence tomography, ultrasound and diffuse reflection spectrophotometry) used in the diagnosis and therapeutic monitoring of lichen planus. Dermoscopy is a non-invasive method initially used for diagnosis of pigmented tumors but now is used also for inflammatory and infectious skin diseases. In lichen planus, the dermoscopy increases the accuracy of diagnosis, avoids skin biopsies commonly used and can be useful in the therapeutic monitoring by repeated investigation at different stages of treatment. Reflectance confocal microscopy (RCM) is a novel non-invasive imaging technique that is prevalently used for the diagnosis of skin tumors and inflammatory skin diseases. This technology has been mostly employed for bedside, real-time microscopic evaluation of psoriasis, lichen planus, contact dermatitis, revealing specific confocal features to support clinical diagnosis and assist with patient management. Optical coherence tomography (OCT) is an emergent imaging technique, developed over the last decade, based on the interaction of the infrared radiation (900–1,500 nm) and the living tissues. A limited information exists on the benefits of OCT technology for the in vivo diagnosis of LP but could be a useful auxiliary tool in the in vivo differential diagnosis, especially in clinical equivocal settings like mucosal lesions, and in monitoring the response to treatment. Our review shows the possibility of using modern imaging techniques for the in vivo diagnosis and also for evaluation of the treatment response.

The clinical usefulness of optical coherence tomography during cancer interventions

INTRODUCTION

Tumor detection and visualization plays a key role in the clinical workflow of a patient with suspected cancer, both in the diagnosis and treatment. Several optical imaging techniques have been evaluated for guidance during oncological interventions. Optical coherence tomography (OCT) is a technique which has been widely evaluated during the past decades. This review aims to determine the clinical usefulness of OCT during cancer interventions focussing on qualitative features, quantitative features and the diagnostic value of OCT.

METHODS

A systematic literature search was performed for articles published before May 2018 using OCT in the field of surgical oncology. Based on these articles, an overview of the clinical usefulness of OCT was provided per tumor type.

RESULTS

A total of 785 articles were revealed by our search, of which a total of 136 original articles were available for analysis, which formed the basis of this review. OCT is currently utilised for both preoperative diagnosis and intraoperative detection of skin, oral, lung, breast, hepatobiliary, gastrointestinal, urological, and gynaecological malignancies. It showed promising results in tumor detection on a microscopic level, especially using higher resolution imaging techniques, such as high-definition OCT and full-field OCT.

CONCLUSION

In the near future, OCT could be used as an additional tool during bronchoscopic or endoscopic interventions and could also be implemented in margin assessment during (laparoscopic) cancer surgery if a laparoscopic or handheld OCT device will be further developed to make routine clinical use possible.

Effect of self-etch adhesives on the internal adaptation of composite restoration: a CP-OCT Study

Despite improvements in dental adhesive materials, internal adaptation remains a challenge in bonded restorations. The aim of this study was to compare microgaps and internal floor adaptation between two different self-etch adhesives in class-V cavities using cross-polarization optical coherence tomography (CP-OCT). In this in vitro study, standardized round class-V cavities were prepared in 20 non-carious human upper central incisor teeth. They were randomly divided into two groups, TN and SE, with each group receiving a different dental adhesive. In TN group, the adhesive used was all-in-one Tetric N-Bond Self-Etch (TN; Ivoclar/Vivadent, Liechtenstein), while SE group was bonded with two-step self-etch Clearfil SE Bond 2 adhesive (SE; Kuraray Noritake Dental Inc, Japan). The prepared cavities were restored with flowable composite and then stored in distilled water for 24 h. Next, they were immersed in silver nitrate, followed by immersion in a photo-developing solution. Optical comparison was carried out by CP-OCT to assess microgaps and composite adaptation at the cavity floor. A Mann-Whitney test was applied to the data, which showed a statistically significant difference in composite adaptation among the two groups (p < 0.001) with the SE group showing superior adaptation. CP-OCT is a reliable tool for non-invasive imaging that gives an insight into composite performance. Better adaptation was found with the two-step self-adhesive for the composite used in this study.

Optical coherence tomography assessment of gingival epithelium inflammatory status in periodontal - Systemic affected patients

INTRODUCTION

Optical coherence tomography (OCT) is an imaging tool used in various medical fields (ophthalmology, dermatology), which allows the observation of morphological particularities on the surface of tissues or internal constructive details of about 2-3mms in depth. In periodontology, it has been used as an experimental tool for periodontal pocket analysis (depth, calculus deposits) but not for the assessment of periodontal inflammation in the gingival tissues, which has been the subject of our in-vitro study.

MATERIAL AND METHOD

Gingival samples were collected from three types of patients: patients with periodontal disease; patients with periodontal disease and a systemic comorbidity; periodontal and systemic healthy patients. The samples were scanned with an OCT light beam, resulting two-dimensional images of the gingival tissue (full thickness epithelium and partial connective tissue). The images were assessed using dedicated software, which allowed the quantification of pixels on a given segment in the epithelium. The average pixel densities were then calculated for each patient group and statistically analyzed.

RESULTS

The resulted pixel densities were highest for the control group samples, while the lowest pixel densities were found in samples originating from periodontal patients with diabetes mellitus. For the other possible periodontal comorbidity, chronic hepatitis C, image assessment also exhibited lower pixel densities than those of the periodontal group, suggesting that this condition could also have an added effect on the tissular changes induced by periodontal disease.

CONCLUSION

OCT has proven that in an in-vitro environment it can be a useful tool for the assessment of periodontal inflammation in gingival samples of periodontal patients. In terms of inflammatory tissular changes observed by OCT analysis, chronic hepatitis C could be regarded as possible periodontal disease's comorbidity.

Combination of structural and vascular optical coherence tomography for differentiating oral lesions of mice in different carcinogenesis stages

Differentiating between early malignancy and benign lesions in oral cavities is difficult using current optical tools. As has been shown in previous studies, microvascular changes in squamous epithelium can be regarded as a key marker for diagnosis. We propose the combination of structural and vascular optical coherence tomography (OCT) imaging for the investigation of disease related changes. Progressive thickness changes of epithelium and the destruction of underlying lamina propria was observed during cancer development in a 4- nitroquinoline-1-oxide (4NQO) mouse model. At the same time, microvascular changes in hyperplasia, dysplasia, carcinoma in situ and advanced cancer were observed. Findings from OCT imaging were compared with histology.

Noninvasive diagnostic adjuncts for the evaluation of potentially premalignant oral epithelial lesions: current limitations and future directions

Potentially premalignant oral epithelial lesions (PPOELs) are a group of clinically suspicious conditions, of which a small percentage will undergo malignant transformation. PPOELs are suboptimally diagnosed and managed under the current standard of care. Dysplasia is the most well-established marker to distinguish high-risk PPOELs from low-risk PPOELs, and performing a biopsy to establish dysplasia is the diagnostic gold standard. However, a biopsy is limited by morbidity, resource requirements, and the potential for underdiagnosis. Diagnostic adjuncts may help clinicians better evaluate PPOELs before definitive biopsy, but existing adjuncts, such as toluidine blue, acetowhitening, and autofluorescence imaging, have poor accuracy and are not generally recommended. Recently, in vivo microscopy technologies, such as high-resolution microendoscopy, optical coherence tomography, reflectance confocal microscopy, and multiphoton imaging, have shown promise for improving PPOEL patient care. These technologies allow clinicians to visualize many of the same microscopic features used for histopathologic assessment at the point of care.

Characterizing biochemical and morphological variations of clinically relevant anatomical locations of oral tissue in vivo with hybrid Raman spectroscopy and optical coherence tomography technique

This study aims to characterize biochemical and morphological variations of the clinically relevant anatomical locations of in vivo oral tissue (ie, alveolar process, lateral tongue and floor of the mouth) by using hybrid Raman spectroscopy (RS) and optical coherence tomography (OCT) technique. A total of 1049 in vivo fingerprint (FP: 800-1800 cm^-1 ) and high wavenumber (HW: 2800-3600 cm^-1 ) Raman spectra were acquired from different oral tissue (alveolar process = 331, lateral tongue = 339 and floor of mouth = 379) of 26 normal subjects in the oral cavity under the OCT imaging guidance. The total Raman dataset were split into 2 parts: 80% for training and 20% for testing. Tissue optical attenuation coefficients of alveolar process, lateral tongue and the floor of the mouth were derived from OCT images, revealing the inter-anatomical morphological differences; while RS uncovers subtle FP/HW Raman spectral differences among different oral tissues that can be attributed to the differences in inter- and intra-cellular proteins, lipids, DNA and water structures and conformations, enlightening biochemical variability of different oral tissues at the molecular level. Partial least squares-discriminant analysis implemented on the training dataset show that the integrated tissue optical attenuation coefficients and FP/HW Raman spectra provide diagnostic sensitivities of 99.6%, 82.3%, 50.2%, and specificities of 97.0%, 75.1%, 92.1%, respectively, which are superior to using either RS (sensitivities of 90.2%, 77.5%, 48.8%, and specificities of 95.8%, 72.1%, 88.8%) or optical attenuation coefficients derived from OCT (sensitivities of 75.0%, 78.2%, 47.2%, and specificities of 96.2%, 67.7%, 85.0%) for the differentiation among alveolar process, lateral tongue and the floor of the mouth. Furthermore, the diagnostic algorithms applied to the independent testing dataset based on hybrid RS-OCT technique gives predictive diagnostic sensitivities of 100%, 76.5%, 51.3%, and specificities of 95.1%, 77.6%, 89.6%, respectively, for the classifications among alveolar process, lateral tongue and the floor of the mouth, which performs much better than either RS or optical attenuation coefficient derived from OCT imaging. This work suggests that inter-anatomical morphological and biochemical variability are significant which should be considered as an important parameter in the interpretation and rendering of hybrid RS-OCT technique for oral tissue diagnosis and characterization.

Microvascular imaging and monitoring of human oral cavity lesions in vivo by swept-source OCT-based angiography

We report the development of optical coherence tomography- (OCT) based angiography (OCTA) to image blood flow within microcirculatory tissue beds in human oral cavity in vivo with a field of view at 10 mm × 10 mm. Three-dimensional (3D) structural and vascular images of labial mucosa tissue are obtained at a single 3D acquisition. Pathologic mucosal sites with mouth ulcers are examined using the OCT tomograms and angiograms, upon which to monitor the lesion healing process over a period of 2 weeks. Quantitative metrics of the capillary loop density within the lamina propria layer are evaluated, providing statistically significant difference between healthy and diseased conditions over time. Furthermore, tissue anatomy and vessel morphology of other susceptible sites to ulcer, such as tongue, alveolar mucosa, and labial frenulum, are also imaged to demonstrate the promise of the proposed method as a clinically useful tool for the diagnosis and monitoring of therapeutic treatment of oral tissue abnormalities.

The potential role of in vivo optical coherence tomography for evaluating oral soft tissue: A systematic review

BACKGROUND

The introduction of optical coherence tomography (OCT) in dentistry enabled the integration of already existing clinical and laboratory investigations in the study of the oral cavity. This systematic review presents an overview of the literature, to evaluate the usefulness of in vivo OCT for diagnosing oral soft tissues lesions, to compare the OCT results with traditional histology, and to identify limitations in prior studies so as to improve OCT applications.

METHODS

We performed a review of the literature using different search engines (PubMed, ISI Web of Science, and the Cochrane Library) employing MeSH terms such as "optical coherence tomography" and "OCT" in conjunction with other terms. We utilized the Population, Intervention, Comparison, Outcomes, and Study design (PICOS) method to define our study eligibility criteria.

RESULTS

Initial results were 3155. In conclusion, there were only 27 studies which met our selection criteria. We decided to allocate the 27 selected items into three groups: healthy mucosa; benign, premalignant, and malignant lesions; and oral manifestations of systemic therapies or pathological conditions.

CONCLUSIONS

Although the OCT is an easy-to-perform test and it offers an attractive diagnostic and monitoring prospect for soft tissues of the oral cavity, further studies are needed to complete the current knowledge of this imaging technique.

Automated analysis of multimodal fluorescence lifetime imaging and optical coherence tomography data for the diagnosis of oral cancer in the hamster cheek pouch model

It is known that the progression of oral cancer is accompanied by changes in both tissue biochemistry and morphology. A multimodal imaging approach combining functional and structural imaging modalities could therefore provide a more comprehensive prognosis of oral cancer. This idea forms the central theme of the current study, wherein this premise is examined in the context of a multimodal imaging system that combines fluorescence lifetime imaging (FLIM) and optical coherence tomography (OCT). Towards this end, in the first part of the present study, the diagnostic advantage obtained by using both fluorescence intensity and lifetime information is assessed. In the second part of the study, the diagnostic potential of FLIM-derived biochemical features is compared with that of OCT-derived morphological features. For an objective assessment, several quantitative biochemical and morphological features from FLIM and OCT data, respectively, were obtained using signal and image processing techniques. These features were subsequently used in a statistical classification framework to quantify the diagnostic potential of different features. The classification accuracy for combined FLIM and OCT features was estimated to be 87.4%, which was statistically higher than accuracy based on only FLIM (83.2%) or OCT (81.0%) features. Moreover, the complimentary information provided by FLIM and OCT features, resulted in highest sensitivity and specificity for the combined FLIM and OCT features for discriminating benign (88.2% sens., 92.0% spec.), pre-cancerous (81.5% sens., 96.0% spec.), and cancerous (90.1% sens., 92.0% spec.) classes.

A novel multimodal optical imaging system for early detection of oral cancer

OBJECTIVES

Several imaging techniques have been advocated as clinical adjuncts to improve identification of suspicious oral lesions. However, these have not yet shown superior sensitivity or specificity over conventional oral examination techniques. We developed a multimodal, multi-scale optical imaging system that combines macroscopic biochemical imaging of fluorescence lifetime imaging with subcellular morphologic imaging of reflectance confocal microscopy for early detection of oral cancer. We tested our system on excised human oral tissues.

STUDY DESIGN

In total, 4 tissue specimens were imaged. These specimens were diagnosed as either clinically normal, oral lichen planus, gingival hyperplasia, or superficially invasive squamous cell carcinoma. The optical and fluorescence lifetime properties of each specimen were recorded.

RESULTS

Both quantitative and qualitative differences among normal, benign, and squamous cell carcinoma lesions can be resolved with fluorescence lifetime imaging reflectance confocal microscopy. The results demonstrate that an integrated approach based on these two methods can potentially enable rapid screening and evaluation of large areas of oral epithelial tissue.

CONCLUSIONS

Early results from ongoing studies of imaging human oral cavity illustrate the synergistic combination of the 2 modalities. An adjunct device based on such optical characterization of oral mucosa can potentially be used to detect oral carcinogenesis in early stages.