Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque

Mobile Health (mHealth) Technology in Early Detection and Diagnosis of Oral Cancer-A Scoping Review of the Current Scenario and Feasibility

Objective

Oral cancer is one of the most common types of cancer with dreadful consequences. But it can be detected early without much expensive equipment. Screening and early detection of oral cancer using Mobile health (mHealth) technology are reported due to the availability of the extensive network of mobile phones across populations. Therefore, we aimed to explore the existing literature regarding mHealth feasibility in the early detection of oral cancer. Materials and Method. An extensive search was conducted to explore the literature on the feasibility of mobile health for early oral cancer. Clinical studies reporting kappa agreement between on-site dentists and offsite health care workers/dentists in the early detection of oral cancer were included in this review. Studies describing the development of a diagnostic device, app development, and qualitative interviews among practitioners trained in using mobile health were also included in this review for a broader perspective on mHealth.

Results

While most of the studies described various diagnostic accuracies using mHealth for oral cancer early detection, few studies reported the development of mobile applications, novel device designs for mHealth applications, and the feasibility of a few mHealth programs for early oral cancer detection. Community health workers equipped with a mobile phone-based app could identify "abnormal" oral lesions. Overall, many studies reported high sensitivity, specificity, and Kappa value of agreement. Effectiveness, advantages, and barriers in oral cancer screening using mHealth are also described.

Conclusion

The overall results show that remote diagnosis for early detection of oral cancer using mHealth was found useful in remote settings.

Detection of invisible dental biofilm using light-induced autofluorescence in adult patients-A systematic review

BACKGROUND

Autofluorescence (AF) spectroscopy is a potent yet non-invasive technique with diagnostic and therapeutic applications. It identifies and characterizes changes occurring in the human body based on the changes in the fluorescence signatures.

AIM

The primary purpose of this systematic review is to address the question "Is it feasible to detect dental plaque using light-induced auto-fluorescence in adult patients with invisible grade 1 plaque?"

MATERIALS AND METHODS

The literature search was conducted independently MEDLINE, Embase, Cochrane Library, Web of Science, Google Scholar, and Scopus databases for relevant studies from January 2000 and June 2021, using the following terms in various combinations: detection, dental biofilm, plaque, light, auto-fluorescence, caries, gingivitis, sensitivity and specificity. Studies describing various fluorescence techniques for the detection of plaque, including sensitivity and specificity, were included.

RESULTS

The majority of the studies indicated that AF spectroscopy allows fluorescence-based detection of various diseases, including early-stage dental plaque. While results of conventional plaque detection techniques are inconsistent, the data from the AF technique is reliable and reproducible, which can be used for patient documentation. However, a wide range of non-uniformity existed in these studies. AF spectroscopy, as a non-invasive technique, represents a viable and patient-friendly clinical tool for the early detection of dental biofilm plaque, and its meticulous removal has been directly responsible for the prevention of this disease.

CONCLUSION

Despite the heterogeneity and limitations of studies included in this review, the future for light-induced autofluorescence spectroscopy technologies in diagnostic dentistry certainly presents an accurate and potentially applicable option.

A comprehensive review on LED-induced fluorescence in diagnostic pathology

Sensitivity, specificity, mobility, and affordability are important criteria to consider for developing diagnostic instruments in common use. Fluorescence spectroscopy has been demonstrating substantial potential in the clinical diagnosis of diseases and evaluating the underlying causes of pathogenesis. A higher degree of device integration with appropriate sensitivity and reasonable cost would further boost the value of the fluorescence techniques in clinical diagnosis and aid in the reduction of healthcare expenses, which is a key economic concern in emerging markets. Light-emitting diodes (LEDs), which are inexpensive and smaller are attractive alternatives to conventional excitation sources in fluorescence spectroscopy, are gaining a lot of momentum in the development of affordable, compact analytical instruments of clinical relevance. The commercial availability of a broad range of LED wavelengths (255-4600 nm) has opened up new avenues for targeting a wide range of clinically significant molecules (both endogenous and exogenous), thereby diagnosing a range of clinical illnesses. As a result, we have specifically examined the uses of LED-induced fluorescence (LED-IF) in preclinical and clinical evaluations of pathological conditions, considering the present advancements in the field.

O-pH: Optical pH Monitor to Measure Oral Biofilm Acidity and Assist in Enamel Health Monitoring

OBJECTIVE

Bacteria in the oral biofilm produce acid after consumption of carbohydrates which if left unmonitored leads to caries formation. We present O-pH, a device that ca measure oral biofilm acidity and provide quantitative feedback to assist in oral health monitoring.

METHOD

O-pH utilizes a ratiometric pH sensing method by capturing fluorescence of Sodium Fluorescein, an FDA approved chemical dye. The device was calibrated to a lab pH meter using buffered fluorescein solution with a correlation coefficient of 0.97. The calibration was further verified in vitro on additional buffered solution, artificial, and extracted teeth. An in vivo study on 30 pediatric subjects was performed to measure pH before (rest pH) and after a sugar rinse (drop pH), and the resultant difference in pH (diff pH) was calculated. The study enrolled subjects with low (Post-Cleaning) and heavy (Pre-Cleaning) biofilm load, having both unhealthy/healthy surfaces. Further, we modified point-based O-pH to an image-based device using a multimode-scanning fiber endoscope (mm-SFE) and tested in vivo on one subject.

RESULTS AND CONCLUSION

We found significant difference between Post-Cleaning and Pre-Cleaning group using drop pH and diff pH. Additionally, in Pre-Cleaning group, the rest and drop pH is lower at the caries surfaces compared to healthy surfaces. Similar trend was not noticed in the Post-Cleaning group. mm-SFE pH scope recorded image-based pH heatmap of a subject with an average average diff pH of 1.5.

SIGNIFICANCE

This work builds an optical pH prototype and presents a pioneering study for non-invasively measuring pH of oral biofilm clinically.

Noninvasive multimodal imaging by integrating optical coherence tomography with autofluorescence imaging for dental applications

We report the development of an integrated multifunctional imaging system capable of providing anatomical (optical coherence tomography, OCT), functional (OCT angiography, OCTA) and molecular imaging (light-induced autofluorescence, LIAF) for in vivo dental applications. Blue excitation light (405 nm) was used for LIAF imaging, while the OCT was powered by a 1310 nm swept laser source. A red-green-blue digital camera, with a 450 nm cut-on broadband optical filter, was used for LIAF detection. The exciting light source and camera were integrated directly with the OCT scanning probe. The integrated system used two noninvasive imaging modalities to improve the speed of in vivo OCT data collection and to better target the regions of interest. The newly designed system maintained the ability to detect differences between healthy and hypomineralized teeth, identify dental biofilm and visualize the microvasculature of gingival tissue. The development of the integrated OCT-LIAF system provides an opportunity to conduct clinical studies more efficiently, examining changes in oral conditions over time.

Automated Process Incorporating Machine Learning Segmentation and Correlation of Oral Diseases with Systemic Health

Imaging fluorescent disease biomarkers in tissues and skin is a non-invasive method to screen for health conditions. We report an automated process that combines intraoral fluorescent porphyrin biomarker imaging, clinical examinations and machine learning for correlation of systemic health conditions with periodontal disease. 1215 intraoral fluorescent images, from 284 consenting adults aged 18-90, were analyzed using a machine learning classifier that can segment periodontal inflammation. The classifier achieved an AUC of 0.677 with precision and recall of 0.271 and 0.429, respectively, indicating a learned association between disease signatures in collected images. Periodontal diseases were more prevalent among males (p=0.0012) and older subjects (p=0.0224) in the screened population. Physicians independently examined the collected images, assigning localized modified gingival indices (MGIs). MGIs and periodontal disease were then cross-correlated with responses to a medical history questionnaire, blood pressure and body mass index measurements, and optic nerve, tympanic membrane, neurological, and cardiac rhythm imaging examinations. Gingivitis and early periodontal disease were associated with subjects diagnosed with optic nerve abnormalities (p<; 0.0001) in their retinal scans. We also report significant co-occurrences of periodontal disease in subjects reporting swollen joints (p=0.0422) and a family history of eye disease (p=0.0337). These results indicate cross-correlation of poor periodontal health with systemic health outcomes and stress the importance of oral health screenings at the primary care level. Our screening process and analysis method, using images and machine learning, can be generalized for automated diagnoses and systemic health screenings for other diseases.

Fluorescence image and microbiological analysis of biofilm retained around healthy and inflamed orthodontic miniscrews

INTRODUCTION

Peri-miniscrew inflammation is one of the causes of orthodontic miniscrew failure.

OBJECTIVE

The aim of this study was to correlate and quantify throughout autofluorescence images, PCR and microbiologic count of biofilm retained around orthodontic miniscrew and the presence of Porphyromonas gingivalis.

MATERIALS AND METHODS

Forty miniscrews used for orthodontic treatment were evaluated during orthodontic treatment, collected from patients and divided into two groups: healthy and inflamed miniscrews. To be considered inflamed, the samples should present: loss of stability checked by periotest®, clinical presence of mucositis, red aspect of the gum or bleeding around the miniscrew. Immediately after removal of the miniscrews, they were photographed using a macro 100 lens and a Pentax camera coupled to a fluorescent equipment - Qscan (AioBio - Korea) with 405 nm excitation wavelength and a blue band filter. A microbiologic sample was collected with a sterile microbrush scrubbed around the miniscrew tread. Fluorescent images were analyzed with ImageJ software to quantify fluorescent intensity and fluorescent area and microbiological samples were submitted to CFU count for total contamination and q-PCR assay to quantify Porphyromonas gingivalis.

RESULTS

The results showed a good correlation between CFU count and fluorescent intensity and PCR/fluorescent area. The healthy miniscrews presented less fluorescent intensity and lower CFU count when compared to inflamed miniscrews. q-PCR analysis showed a higher number of P. gingivalis contamination around inflamed miniscrews.

CONCLUSION

Quantification of biofilm retained by miniscrew by images of autofluorescence is a simple and reliable method with great potential for clinical use to monitory inflammation around miniscrew and risk of loss.

Digital reconstruction of teeth using near-infrared light

Cone beam computed tomography has demonstrated value by offering enhanced conceptualization of features of teeth in the 3D space. However, these systems require higher effective radiation doses to image teeth. Previous research from our group has used non-ionizing near-infrared (NIR) light for diagnosing demineralization and caries in human tooth enamel. However, use of safe NIR radiation for rapid, 3D imaging of tooth anatomy has not been described previously. Here we describe a optical setup to rapidly laser scan teeth ex vivo using 1310nm NIR laser diode. We also detail a novel process that uses laser scanning to create stacks of images of extracted teeth, and construct highly accurate 3D models. Our 3D reconstructive models offer promising starting points to recover anatomical details using pixel intensities within these images as projection data to diagnose carious lesions, and can assist in providing rapid and affordable technology-enabled early caries screenings to patients.