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

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.

Review of the Role of Nanotechnology in Overcoming the Challenges Faced in Oral Cancer Diagnosis and Treatment

Throughout the world, oral cancer is a common and aggressive malignancy with a high risk of morbidity, mortality, and recurrence. The importance of early detection in cancer prevention and disease treatment cannot be overstated. Conventional therapeutic strategies have minor difficulties but considerable side effects and unfavourable consequences in clinical applications. Hence, there is a requirement for effective ways for early detection and treatment of oral cancer. At present, numerous forms of nanoparticles have piqued researchers' interest as a potentially useful tool for diagnostic probes and medicinal devices. Because of their inherent physicochemical properties and customizable surface modification, they are able to circumvent some of restrictions and accomplish the intended diagnostic and therapeutic impact. Nanotechnology is a unique field that has revolutionised the industry and is paving the way for new treatments for oral cancer. It can help with a better diagnosis with less harmful substances and is setting current guidelines for treatment. The use of nanotechnology in cancer diagnosis, therapy, and care improves clinical practise dramatically. The different types of nanoparticles that have been developed for the diagnosis and therapy of oral cancers will be covered in this study. The difficulties and potential uses of nanoparticles in the treatment and diagnosis of oral cancer are then highlighted. In order to emphasise existing difficulties and potential remedies for oral cancer, a prospective view of the future is also provided.

Label-Free Optical Metabolic Imaging in Cells and Tissues

Over the last half century, the autofluorescence of the metabolic cofactors NADH (reduced nicotinamide adenine dinucleotide) and FAD (flavin adenine dinucleotide) has been quantified in a variety of cell types and disease states. With the spread of nonlinear optical microscopy techniques in biomedical research, NADH and FAD imaging has offered an attractive solution to noninvasively monitor cell and tissue status and elucidate dynamic changes in cell or tissue metabolism. Various tools and methods to measure the temporal, spectral, and spatial properties of NADH and FAD autofluorescence have been developed. Specifically, an optical redox ratio of cofactor fluorescence intensities and NADH fluorescence lifetime parameters have been used in numerous applications, but significant work remains to mature this technology for understanding dynamic changes in metabolism. This article describes the current understanding of our optical sensitivity to different metabolic pathways and highlights current challenges in the field. Recent progress in addressing these challenges and acquiring more quantitative information in faster and more metabolically relevant formats is also discussed.

Nano-diagnostics as an emerging platform for oral cancer detection: Current and emerging trends

Globally, oral cancer kills an estimated 150,000 individuals per year, with 300,000 new cases being diagnosed annually. The high incidence rate of oral cancer among the South-Asian and American populations is majorly due to overuse of tobacco, alcohol, and poor dental hygiene. Additionally, socio-economic issues and lack of general awareness delay the primary screening of the disease. The availability of early screening techniques for oral cancer can help in carving out a niche for accurate disease prognosis and also its prevention. However, conventional diagnostic approaches and therapeutics are still far from optimal. Thus, enhancing the analytical performance of diagnostic platforms in terms of specificity and precision can help in understanding the disease progression paradigm. Fabrication of efficient nanoprobes that are sensitive, noninvasive, cost-effective, and less labor-intensive can reduce the global cancer burden. Recent advances in optical, electrochemical, and spectroscopy-based nano biosensors that employ noble and superparamagnetic nanoparticles, have been proven to be extremely efficient. Further, these sensitive nanoprobes can also be employed for predicting disease relapse after chemotherapy, when the majority of the biomarker load is eliminated. Herein, we provide the readers with a brief summary of conventional and new-age oral cancer detection techniques. A comprehensive understanding of the inherent challenges associated with conventional oral cancer detection techniques is discussed. We also elaborate on how nanoparticles have shown tremendous promise and effectiveness in radically transforming the approach toward oral cancer detection. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices Diagnostic Tools > In Vitro Nanoparticle-Based Sensing.

Multidimensional quantitative characterization of the tumor microenvironment by multicontrast nonlinear microscopy

Characterization of the microenvironment features of tumors, such as its microstructures, biomolecular metabolism, and functional dynamics, may provide essential pathologic information about the tumor, tumor margin, and adjacent normal tissue for early and intraoperative diagnosis. However, it can be particularly challenging to obtain faithful and comprehensive pathological information simultaneously from unperturbed tissues due to the complexity of the microenvironment in organisms. Super-multiplex nonlinear optical imaging system emerged and matured as an attractive tool for acquisition and elucidation of the nonlinear properties correlated with tumor microenvironment. Here, we introduced a nonlinear effects-based multidimensional optical imaging platform and methodology to simultaneously and efficiently capture contrasting and complementary nonlinear optical signatures of freshly excised human skin tissues. The qualitative and quantitative analysis of autofluorescence (FAD), collagen fiber, and intracellular components (lipids and proteins) illustrated the differences about morphological changes and biomolecular metabolic processes of the epidermis and dermis in different skin carcinogenic types. Interpretation of multi-parameter stain-free histological findings complements conventional H&E-stained slides for investigating basal cell carcinoma and pigmented nevus, validates the platform's versatility and efficiency for classifying subtypes of skin carcinoma, and provides the potential to translate endogenous molecule into biomarker for assisting in rapid cancer screening and diagnosis.

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.

Validation of a Point-of-Care Optical Coherence Tomography Device with Machine Learning Algorithm for Detection of Oral Potentially Malignant and Malignant Lesions

Non-invasive strategies that can identify oral malignant and dysplastic oral potentially-malignant lesions (OPML) are necessary in cancer screening and long-term surveillance. Optical coherence tomography (OCT) can be a rapid, real time and non-invasive imaging method for frequent patient surveillance. Here, we report the validation of a portable, robust OCT device in 232 patients (lesions: 347) in different clinical settings. The device deployed with algorithm-based automated diagnosis, showed efficacy in delineation of oral benign and normal (n = 151), OPML (n = 121), and malignant lesions (n = 75) in community and tertiary care settings. This study showed that OCT images analyzed by automated image processing algorithm could distinguish the dysplastic-OPML and malignant lesions with a sensitivity of 95% and 93%, respectively. Furthermore, we explored the ability of multiple (n = 14) artificial neural network (ANN) based feature extraction techniques for delineation high grade-OPML (moderate/severe dysplasia). The support vector machine (SVM) model built over ANN, delineated high-grade dysplasia with sensitivity of 83%, which in turn, can be employed to triage patients for tertiary care. The study provides evidence towards the utility of the robust and low-cost OCT instrument as a point-of-care device in resource-constrained settings and the potential clinical application of device in screening and surveillance of oral cancer.

Mesoscopic fluorescence lifetime imaging: Fundamental principles, clinical applications and future directions

Fluorescence lifetime imaging (FLIm) is an optical spectroscopic imaging technique capable of real-time assessments of tissue properties in clinical settings. Label-free FLIm is sensitive to changes in tissue structure and biochemistry resulting from pathological conditions, thus providing optical contrast to identify and monitor the progression of disease. Technical and methodological advances over the last two decades have enabled the development of FLIm instrumentation for real-time, in situ, mesoscopic imaging compatible with standard clinical workflows. Herein, we review the fundamental working principles of mesoscopic FLIm, discuss the technical characteristics of current clinical FLIm instrumentation, highlight the most commonly used analytical methods to interpret fluorescence lifetime data and discuss the recent applications of FLIm in surgical oncology and cardiovascular diagnostics. Finally, we conclude with an outlook on the future directions of clinical FLIm.

Luminescence lifetime imaging of three-dimensional biological objects

A major focus of current biological studies is to fill the knowledge gaps between cell, tissue and organism scales. To this end, a wide array of contemporary optical analytical tools enable multiparameter quantitative imaging of live and fixed cells, three-dimensional (3D) systems, tissues, organs and organisms in the context of their complex spatiotemporal biological and molecular features. In particular, the modalities of luminescence lifetime imaging, comprising fluorescence lifetime imaging (FLI) and phosphorescence lifetime imaging microscopy (PLIM), in synergy with Förster resonance energy transfer (FRET) assays, provide a wealth of information. On the application side, the luminescence lifetime of endogenous molecules inside cells and tissues, overexpressed fluorescent protein fusion biosensor constructs or probes delivered externally provide molecular insights at multiple scales into protein-protein interaction networks, cellular metabolism, dynamics of molecular oxygen and hypoxia, physiologically important ions, and other physical and physiological parameters. Luminescence lifetime imaging offers a unique window into the physiological and structural environment of cells and tissues, enabling a new level of functional and molecular analysis in addition to providing 3D spatially resolved and longitudinal measurements that can range from microscopic to macroscopic scale. We provide an overview of luminescence lifetime imaging and summarize key biological applications from cells and tissues to organisms.

Optical Biopsy of the Upper GI Tract Using Fluorescence Lifetime and Spectra

Screening and surveillance for gastrointestinal (GI) cancers by endoscope guided biopsy is invasive, time consuming, and has the potential for sampling error. Tissue endogenous fluorescence spectra contain biochemical and physiological information, which may enable real-time, objective diagnosis. We first briefly reviewed optical biopsy modalities for GI cancer diagnosis with a focus on fluorescence-based techniques. In an ex vivo pilot clinical study, we measured fluorescence spectra and lifetime on fresh biopsy specimens obtained during routine upper GI screening procedures. Our results demonstrated the feasibility of rapid acquisition of time-resolved fluorescence (TRF) spectra from fresh GI mucosal specimens. We also identified spectroscopic signatures that can differentiate between normal mucosal samples obtained from the esophagus, stomach, and duodenum.

Extended Blind End-member and Abundance Extraction for Biomedical Imaging Applications

In some applications of biomedical imaging, a linear mixture model can represent the constitutive elements (end-members) and their contributions (abundances) per pixel of the image. In this work, the extended blind end-member and abundance extraction (EBEAE) methodology is mathematically formulated to address the blind linear unmixing (BLU) problem subject to positivity constraints in optical measurements. The EBEAE algorithm is based on a constrained quadratic optimization and an alternated least-squares strategy to jointly estimate end-members and their abundances. In our proposal, a local approach is used to estimate the abundances of each end-member by maximizing their entropy, and a global technique is adopted to iteratively identify the end-members by reducing the similarity among them. All the cost functions are normalized, and four initialization approaches are suggested for the end-members matrix. Synthetic datasets are used first for the EBEAE validation at different noise types and levels, and its performance is compared to state-of-the-art algorithms in BLU. In a second stage, three experimental biomedical imaging applications are addressed with EBEAE: m-FLIM for chemometric analysis in oral cavity samples, OCT for macrophages identification in post-mortem artery samples, and hyper-spectral images for in-vivo brain tissue classification and tumor identification. In our evaluations, EBEAE was able to provide a quantitative analysis of the samples with none or minimal a priori information.

Fluorescence lifetime imaging for intraoperative cancer delineation in transoral robotic surgery

This study evaluates the potential for fluorescence lifetime imaging (FLIm) to enhance intraoperative decisionmaking during robotic-assisted surgery of oropharyngeal cancer. Using a custom built FLIm instrument integrated with the da Vinci robotic surgical platform, we first demonstrate that cancer in epithelial tissue diagnosed by histopathology can be differentiated from surrounding healthy epithelial tissue imaged in vivo prior to cancer resection and ex vivo on the excised specimen. Second, we study the fluorescence properties of tissue imaged in vivo at surgical resection margins (tumor bed). Fluorescence lifetimes and spectral intensity ratios were calculated for three spectral channels, producing a set of six FLIm parameters. Current results from 10 patients undergoing TORS procedures demonstrate that healthy epithelium can be resolved from cancer (P < .001) for at least one FLIm parameter. We also showed that a multiparameter linear discriminant analysis approach provides superior discrimination to individual FLIm parameters for tissue imaged both in vivo and ex vivo. Overall, this study highlights the potential for FLIm to be developed into a diagnostic tool for clinical cancer applications of the oropharynx. This technique could help to circumvent the issues posed by the lack of tactile feedback associated with robotic surgical platforms to better enable cancer delineation.

Nanotechnology: a promising method for oral cancer detection and diagnosis

Oral cancer is a common and aggressive cancer with high morbidity, mortality, and recurrence rate globally. Early detection is of utmost importance for cancer prevention and disease management. Currently, tissue biopsy remains the gold standard for oral cancer diagnosis, but it is invasive, which may cause patient discomfort. The application of traditional noninvasive methods-such as vital staining, exfoliative cytology, and molecular imaging-is limited by insufficient sensitivity and specificity. Thus, there is an urgent need for exploring noninvasive, highly sensitive, and specific diagnostic techniques. Nano detection systems are known as new emerging noninvasive strategies that bring the detection sensitivity of biomarkers to nano-scale. Moreover, compared to current imaging contrast agents, nanoparticles are more biocompatible, easier to synthesize, and able to target specific surface molecules. Nanoparticles generate localized surface plasmon resonances at near-infrared wavelengths, providing higher image contrast and resolution. Therefore, using nano-based techniques can help clinicians to detect and better monitor diseases during different phases of oral malignancy. Here, we review the progress of nanotechnology-based methods in oral cancer detection and diagnosis.

Quantitative Live Cell FLIM Imaging in Three Dimensions

In this chapter, the concept of fluorescence lifetime and its utility in quantitative live cell imaging will be introduced, along with methods to record and analyze FLIM data. Relevant applications in 3D tissue and live cell imaging, including multiplexed FLIM detection, will also be detailed.