Use of autofluorescence and fluorescent probes as a potential diagnostic tool for oral cancer: A systematic review

Assessment of diagnostic accuracy and reliability of reveal fluorescence dental loupes in detecting molar incisor hypomineralization in children

BACKGROUND

Molar-Incisor Hypomineralization (MIH) poses challenges to accurate diagnosis, impacting children's oral health. Traditional methods exhibit limitations, necessitating innovative approaches. This study aimed to evaluate the reliability and diagnostic accuracy Reveal Fluorescence Dental Loupes (RFDLs) for the detection of MIH METHODS: This cross-sectional study, adhering to STRAD guidelines, involved 38 healthy children (age 7-9) with MIH. Ethical approval and informed consent were obtained. Microscope images and Reveal loupes were employed for examinations. Validity was assessed against microscope results, and inter- and intra-examiner reliability were measured using ICC and Kappa coefficients. Sensitivity, specificity, and overall accuracy were calculated, with an AUC-ROC analysis for discriminatory ability.

RESULTS

Intra-examiner reliability scores were excellent (Examiner 1: ICC 0.92, Examiner 2: ICC 0.94). Inter-examiner reliability (Kappa 0.92) indicated almost perfect agreement. Reveal demonstrated high sensitivity (82.61 %) and specificity (92.59 %), with an overall accuracy of 88.70 %. AUC-ROC analysis supported its robust discriminatory ability (AUC: 0.871).

CONCLUSIONS

Reveal Fluorescence Dental Loupes emerged as a promising diagnostic tool for accurate MIH detection, particularly in outreach settings. The study highlights the transformative impact of accessible and reliable diagnostic tools on pediatric oral health outcomes. While acknowledging limitations and the absence of a gold standard, the findings contribute to advancing MIH diagnostic capabilities. Further research in diverse populations is warranted for comprehensive validation.

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.

Recent advances in small-molecule fluorescent probes with the function of targeting cancer receptors

Cancer is "the sword of Damocles" that threatens human life and health. Therefore, the diagnosis and treatment of cancer have been receiving much attention. Many overexpressed receptors on the surface of cancer cells provide us with an effective way to specifically identify the cancer cells, and receptor targeting strategies are becoming one of the hot ideas to enhance the ability of fluorescent probes to target tumors. Fluorescent probes connected to ligands are targeted at cancer cell surfaces through receptor-mediated endocytosis. Receptor-targeting probes can image and track cancer cells, determine tumor boundaries, monitor deep lesions, and play a role in clinical medicine, such as fluorescent imaging-guided surgery. In this review, based on the perspective of small molecule fluorescent probes, we reviewed the design ideas, photophysical properties, and applications of receptor-targeting probes for detecting biomarkers in imaging and tracing cancer cells and prospected the future developmental direction of such probes. We hope that this review will provide more ideas for the design and development of active targeting probes for receptors and lead to more applications in the medical field.

Clinical Experience with Autofluorescence Guided Oral Squamous Cell Carcinoma Surgery

In our study, the effect of the use of autofluorescence (Visually Enhanced Lesion Scope-VELscope) on increasing the success rate of surgical treatment in oral squamous carcinoma (OSCC) was investigated. Our hypothesis was tested on a group of 122 patients suffering from OSCC, randomized into a study and a control group enrolled in our study after meeting the inclusion criteria. The preoperative checkup via VELscope, accompanied by the marking of the range of a loss of fluorescence in the study group, was performed before the surgery. We developed a unique mucosal tattoo marking technique for this purpose. The histopathological results after surgical treatment, i.e., the margin status, were then compared. In the study group, we achieved pathological free margin (pFM) in 55 patients, pathological close margin (pCM) in 6 cases, and we encountered no cases of pathological positive margin (pPM) in the mucosal layer. In comparison, the control group results revealed pPM in 7 cases, pCM in 14 cases, and pFM in 40 of all cases in the mucosal layer. This study demonstrated that preoperative autofluorescence assessment of the mucosal surroundings of OSCC increased the ability to achieve pFM resection 4.8 times in terms of lateral margins.

Metabolomics of head and neck cancer in biofluids: an integrative systematic review

INTRODUCTION

Head and neck cancer (HNC) is the fifth most common cancer globally. Diagnosis at early stages are critical to reduce mortality and improve functional and esthetic outcomes associated with HNC. Metabolomics is a promising approach for discovery of biomarkers and metabolic pathways for risk assessment and early detection of HNC.

OBJECTIVES

To summarize and consolidate the available evidence on metabolomics and HNC in plasma/serum, saliva, and urine.

METHODS

A systematic search of experimental research was executed using PubMed and Web of Science. Available data on areas under the curve was extracted. Metabolic pathway enrichment analysis were performed to identify metabolic pathways altered in HNC. Fifty-four studies were eligible for data extraction (33 performed in plasma/serum, 15 in saliva and 6 in urine).

RESULTS

Metabolites with high discriminatory performance for detection of HNC included single metabolites and combination panels of several lysoPCs, pyroglutamate, glutamic acid, glucose, tartronic acid, arachidonic acid, norvaline, linoleic acid, propionate, acetone, acetate, choline, glutamate and others. The glucose-alanine cycle and the urea cycle were the most altered pathways in HNC, among other pathways (i.e. gluconeogenesis, glycine and serine metabolism, alanine metabolism, etc.). Specific metabolites that can potentially serve as complementary less- or non-invasive biomarkers, as well as metabolic pathways integrating the data from the available studies, are presented.

CONCLUSION

The present work highlights utility of metabolite-based biomarkers for risk assessment, early detection, and prognostication of HNC, as well as facilitates incorporation of available metabolomics studies into multi-omics data integration and big data analytics for personalized health.

Design of reversibly charge-changeable rhodamine B modified magnetic nanoparticles to enrich phosphopeptides

In the present study, by employing ethylenediaminetetraacetic acid (EDTA), tetraethylene pentaamine (TEPA), and rhodamine B (Rb), we designed and synthesized a magnetic adsorbent (Fe₃O₄@EDTA@TEPA@Rb) on the basis of reversible charge change of Rb and applied to capture phosphopeptides. Rb existing in open planarized zwitterion form when stimulated by acidic loading buffer adsorbs negative phosphopeptides via electrostatic interaction. Under the stimulation of alkalic eluent, ring-closed structure of Rb is formed to elute the enriched phosphopeptides. TEPA containing rich amino groups is used as a crosslinking agent, which is also protonated in acidic loading buffer to bond phosphopeptides. Then phosphopeptides are eluted when TEPA deprotonates in alkalic eluent. Coupled with matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) detection, phosphopeptide signals originated from 0.4 fmol/μL β-casein digests were successfully detected. In addition, Fe₃O₄@EDTA@TEPA@Rb can also efficiently enrich phosphopeptides from skimmed milk, human serum and saliva samples (26, 4, 39 phosphopeptides, respectively), opening a new gallery for phosphopeptides-related analysis. In general, the developed adsorbent has the great potential for further application in the near future.

Status and Determinants of Early Detection of Oral Premalignant and Malignant Lesions in India

It has been over four decades since the launch of the National Cancer Control Programme in India, yet the cancer screening rates for oral cancer remain unremarkable. Moreover, India is bracing a large burden of oral cancer with poor survival rates. An effective public health programme implementation relies on a multitude of factors related to cost-effective evidence-based interventions, the healthcare delivery system, public health human resource management, community behaviour, partnership with stakeholders, identifying opportunities and political commitment. In this context, we discuss the various challenges in the early detection of oral premalignant and malignant lesions and potential solutions.

Applicability of autofluorescence and fluorescent probes in the trans-surgical of oral carcinomas: A systematic review

Oral cancer represents an important health problem, as it is the sixth most common type of cancer in the world and is associated with high rates of morbidity and mortality. The treatment considered the gold standard for this type of tumor is surgical resection with negative margins, with a distance of at least 5 mm from the tumor. This procedure is strongly associated with local control and disease-specific survival, however, in many cases, large amounts of healthy tissue are removed, resulting in surgical defects, compromising various functions and directly affecting the individual's quality of life. From this perspective, this systematic review aimed to evaluate the use of autofluorescence and fluorescent probes as potential adjuvant techniques to facilitate the delineation of surgical margins for oral cancers. A comprehensive search was performed in Pubmed, Scopus, Web of Science, LIVIVO, Embase, ProQuest Open Access Dissertations & Theses, Open Access Theses and Dissertations, and DART Europe databases, where 1948 articles were found. After the different stages of critical evaluation, 15 articles were selected, eligible for the inclusion criteria. Of these, 7 articles used autofluorescence, 7 used fluorescent probes and 1 article used both methods. As for autofluorescence, the most used device was the VELScope, and indocyanine green was the most used probe. Compared to histopathology, autofluorescence did not obtain significant and/or superiors results. In contrast to fluorescent probes that, most articles showed a good performance of margins during surgical resection, making them a promising alternative. However, it is still necessary to carry out the analysis of more articles, with more significant samples and sensitivity and specificity data to qualify the results.

Evaluation of Oral Mucosal Lesions Using the IllumiScan® Fluorescence Visualisation Device: Distinguishing Squamous Cell Carcinoma

We evaluated whether fluorescence intensity (FI) and its coefficient of variation (CV) can be used to diagnose squamous cell carcinoma (SCC) through IllumiScan®, an oral mucosa fluorescence visualisation (FV) device. Overall, 190 patients with oral mucosal lesions (OMLs; SCC, 59; non-SCC OMLs, 131) and 49 patients with normal oral mucosa (NOM) were enrolled between January 2019 and March 2021. The FI of the images was analysed using image analysis software. After establishing regions of interest for SCC, non-SCC, and NOM, the average FI, standard deviation (SD), and CV were compared. There was a significant difference in the average FI for all pairs of comparisons. The SD was not significantly different between the SCC and NOM groups (p = 0.07). The CV differed significantly for NOM (p < 0.001) and non-SCC groups (p < 0.001) relative to the SCC group but was not different between NOM and non-SCC groups (p = 0.15). Univariate analysis of SCC and non-SCC groups showed significant differences for all factors, except age. However, multivariate analysis showed a significant intergroup difference only in the CV (p = 0.038). Therefore, analysing the CV in FV images of OML may be useful for the diagnosis of oral cancer.

Small-Molecule Fluorescent Probes for Detecting Several Abnormally Expressed Substances in Tumors

Malignant tumors have always been the biggest problem facing human survival, and a huge number of people die from cancer every year. Therefore, the identification and detection of malignant tumors have far-reaching significance for human survival and development. Some substances are abnormally expressed in tumors, such as cyclooxygenase-2 (COX-2), nitroreductase (NTR), pH, biothiols (GSH, Cys, Hcy), hydrogen sulfide (H₂S), hydrogen sulfide (H₂O₂), hypochlorous acid (HOCl) and NADH. Consequently, it is of great value to diagnose and treat malignant tumors due to the identification and detection of these substances. Compared with traditional tumor detection methods, fluorescence imaging technology has the advantages of an inexpensive cost, fast detection and high sensitivity. Herein, we mainly introduce the research progress of fluorescent probes for identifying and detecting abnormally expressed substances in several tumors.

Clinical label-free endoscopic imaging of biochemical and metabolic autofluorescence biomarkers of benign, precancerous, and cancerous oral lesions

Early detection is critical for improving the survival rate and quality of life of oral cancer patients; unfortunately, dysplastic and early-stage cancerous oral lesions are often difficult to distinguish from oral benign lesions during standard clinical oral examination. Therefore, there is a critical need for novel clinical technologies that would enable reliable oral cancer screening. The autofluorescence properties of the oral epithelial tissue provide quantitative information about morphological, biochemical, and metabolic tissue and cellular alterations accompanying carcinogenesis. This study aimed to identify novel biochemical and metabolic autofluorescence biomarkers of oral dysplasia and cancer that could be clinically imaged using novel multispectral autofluorescence lifetime imaging (maFLIM) endoscopy technologies. In vivo maFLIM clinical endoscopic images of benign, precancerous, and cancerous lesions from 67 patients were acquired using a novel maFLIM endoscope. Widefield maFLIM feature maps were generated, and statistical analyses were applied to identify maFLIM features providing contrast between dysplastic/cancerous vs. benign oral lesions. A total of 14 spectral and time-resolved maFLIM features were found to provide contrast between dysplastic/cancerous vs. benign oral lesions, representing novel biochemical and metabolic autofluorescence biomarkers of oral epithelial dysplasia and cancer. To the best of our knowledge, this is the first demonstration of clinical widefield maFLIM endoscopic imaging of novel biochemical and metabolic autofluorescence biomarkers of oral dysplasia and cancer, supporting the potential of maFLIM endoscopy for early detection of oral cancer.

Clinical Evaluation of the Optical Filter for Autofluorescence Glasses for Oral Cancer Curing Light Exposed (GOCCLES®) in the Management of Potentially Premalignant Disorders: A Retrospective Study

Background: Any oral potentially malignant disorders (OPMDs) must be regularly monitored through clinical examination to detect any possible malignant transformation. Conventional intraoral exams, however, can be difficult because these conditions may resemble benign lesions. For this reason, several non-invasive diagnostic technologies have been developed to help the clinician in detecting and distinguishing between cancerous and benign lesions. Epithelial dysplasia can be considered the most important predictor of malignant evolution. Therefore, in this study we aim to evaluate the ability of an optical filter for autofluorescence Glasses for Oral Cancer Curing Light Exposed (GOCCLES^®) and of toluidine blue staining in identifying dysplastic areas in patients with OPMDs. Methods: In this retrospective study, medical records, photographs and videos of 25 patients with oral lesions were analyzed. Forty-two biopsy samples in 25 patients with OPMDs and at least one suspicious oral mucosa lesion that were evaluated in white light, autofluorescence with optical filter GOCCLES^®, toluidine blue staining and then biopsied with histopathological analysis were analyzed. Results: The sensitivity and specificity for the autofluorescence evaluation with GOCCLES^® for identifying dysplasia or carcinoma were 66% and 48%, respectively. The positive and negative predictive values were 34% and 77%, respectively, and the accuracy was 53%. The sensitivity and specificity for toluidine blue staining were 91% and 68%, respectively. The positive and negative predictive values were 55% and 95%, respectively, and the accuracy was 75%. Conclusions: The optical filter for autofluorescence (GOCCLES^®) and toluidine blue staining are simple, inexpensive, rapid and non-invasive procedures that can assist the clinician in distinguishing OPMDs from healthy mucosa but they are not able to distinguish benign and malignant lesions.

A ratiometric fluorescent probe for sensing hypochlorite in physiological saline, bovine serum albumin and fetal bovine/calf serum

HClO/ClO^-, as one of important reactive oxygen species, is a highly reactive unavoidable by-product generated from normal cell metabolism. In recent years, efficient method for detectiing HClO/ClO^- is of great important to research its pathological or physiological function in bio-systems. In this work, we have constructed a fluorescent probe (P-Hc) with ratiometric signal for sensing HClO/ClO^- in aqueous solution, physiological saline and different serums based on 2-(benzo[d]thiazol-2-yl)phenol dye. The structure of P-Hc was characterized by NMR and HRMS spectrum. The sensing mechanism has also been verified by ¹H NMR spectrum. The P-Hc displays good sensitivity and selectivity for HClO/ClO^- with a limit of detection (LOD) of 2.03 × 10^-6 M. Furthermore, P-Hc has been applied for sensing HClO/ClO^- in physiological saline and different serums. Thus, P-Hc may provide a novel method for ratiometric fluorescent sensing HClO/ClO^- in bio-samples.

Role of Artificial Intelligence in the Early Diagnosis of Oral Cancer. A Scoping Review

The early diagnosis of cancer can facilitate subsequent clinical patient management. Artificial intelligence (AI) has been found to be promising for improving the diagnostic process. The aim of the present study is to increase the evidence on the application of AI to the early diagnosis of oral cancer through a scoping review. A search was performed in the PubMed, Web of Science, Embase and Google Scholar databases during the period from January 2000 to December 2020, referring to the early non-invasive diagnosis of oral cancer based on AI applied to screening. Only accessible full-text articles were considered. Thirty-six studies were included on the early detection of oral cancer based on images (photographs (optical imaging and enhancement technology) and cytology) with the application of AI models. These studies were characterized by their heterogeneous nature. Each publication involved a different algorithm with potential training data bias and few comparative data for AI interpretation. Artificial intelligence may play an important role in precisely predicting the development of oral cancer, though several methodological issues need to be addressed in parallel to the advances in AI techniques, in order to allow large-scale transfer of the latter to population-based detection protocols.

Band-Selection of a Portal LED-Induced Autofluorescence Multispectral Imager to Improve Oral Cancer Detection

This aim of this study was to find effective spectral bands for the early detection of oral cancer. The spectral images in different bands were acquired using a self-made portable light-emitting diode (LED)-induced autofluorescence multispectral imager equipped with 365 and 405 nm excitation LEDs, emission filters with center wavelengths of 470, 505, 525, 532, 550, 595, 632, 635, and 695 nm, and a color image sensor. The spectral images of 218 healthy points in 62 healthy participants and 218 tumor points in 62 patients were collected in the ex vivo trials at China Medical University Hospital. These ex vivo trials were similar to in vivo because the spectral images of anatomical specimens were immediately acquired after the on-site tumor resection. The spectral images associated with red, blue, and green filters correlated with and without nine emission filters were quantized by four computing method, including summated intensity, the highest number of the intensity level, entropy, and fractional dimension. The combination of four computing methods, two excitation light sources with two intensities, and 30 spectral bands in three experiments formed 264 classifiers. The quantized data in each classifier was divided into two groups: one was the training group optimizing the threshold of the quantized data, and the other was validating group tested under this optimized threshold. The sensitivity, specificity, and accuracy of each classifier were derived from these tests. To identify the influential spectral bands based on the area under the region and the testing results, a single-layer network learning process was used. This was compared to conventional rules-based approaches to show its superior and faster performance. Consequently, four emission filters with the center wavelengths of 470, 505, 532, and 550 nm were selected by an AI-based method and verified using a rule-based approach. The sensitivities of six classifiers using these emission filters were more significant than 90%. The average sensitivity of these was about 96.15%, the average specificity was approximately 69.55%, and the average accuracy was about 82.85%.