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

BACKGROUND: Significant numbers of adults and children have untreated plaque due to poor oral hygiene and consequently suffer from associate dental and systemic diseases. METHODS: A handheld device equipped with 405 nm light-emitting diodes was constructed to examine the prevalence of red fluorescence signatures associated with dental plaque. This device was used for in vivo imaging of all four incisors and all four canines of twenty-eight consenting human subjects. The same areas were further imaged under white light illumination with a commercial image-processing based plaque-imaging device, and evaluated by a hygienist and dentist. A custom computer vision algorithm using pixel information was developed to calculate plaque coverage ratios ranging from 0 (no plaque) to 1 (complete plaque coverage) for images captured by both devices. RESULTS: The algorithm calculated red fluorescence-based plaque coverage ratios ranging from 0.011 to 0.211 for the subjects imaged. Clinical assessment and statistical analyses of associated plaque ratios of the 405 nm device images indicated high sensitivity and specificity in detecting dental plaque by the experimental device compared to the commercial reference device. CONCLUSIONS: The low-cost and open source 405 nm device and the associated computer vision algorithm successfully captured red fluorescence signatures associated with dental plaque and demonstrated comparable performance to a commercially available device. Therefore, a proof of concept validation was provided for the construction and application of a sensitive cost-effective plaque-detecting device. A miniaturized mobile adaptable version of the device was also provided, together with and a step-by-step guide for device assembly and webhost the associated software, to facilitate open-source access to a cost-effective at-home, in-clinic oral care technology. TRIAL REGISTRATION: ClinicalTrials.gov NCT03379337, December 19 2017. Retrospectively registered.

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.

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.

Technology-enabled examinations of cardiac rhythm, optic nerve, oral health, tympanic membrane, gait and coordination evaluated jointly with routine health screenings: an observational study at the 2015 Kumbh Mela in India.

OBJECTIVES: Technology-enabled non-invasive diagnostic screening (TES) using smartphones and other point-of-care medical devices was evaluated in conjunction with conventional routine health screenings for the primary care screening of patients. DESIGN: Dental conditions, cardiac ECG arrhythmias, tympanic membrane disorders, blood oxygenation levels, optic nerve disorders and neurological fitness were evaluated using FDA-approved advanced smartphone powered technologies. Routine health screenings were also conducted. A novel remote web platform was developed to allow expert physicians to examine TES data and compare efficacy with routine health screenings. SETTING: The study was conducted at a primary care centre during the 2015 Kumbh Mela in Maharashtra, India. PARTICIPANTS: 494 consenting 18-90 years old adults attending the 2015 Kumbh Mela were tested. RESULTS: TES and routine health screenings identified unique clinical conditions in distinct patients. Intraoral fluorescent imaging classified 63.3% of the population with dental caries and periodontal diseases. An association between poor oral health and cardiovascular illnesses was also identified. Tympanic membrane imaging detected eardrum abnormalities in 13.0% of the population, several with a medical history of hearing difficulties. Gait and coordination issues were discovered in eight subjects and one subject had arrhythmia. Cross-correlations were observed between low oxygen saturation and low body mass index (BMI) with smokers (p=0.0087 and p=0.0122, respectively), and high BMI was associated with elevated blood pressure in middle-aged subjects. CONCLUSIONS: TES synergistically identified clinically significant abnormalities in several subjects who otherwise presented as normal in routine health screenings. Physicians validated TES findings and used routine health screening data and medical history responses for comprehensive diagnoses for at-risk patients. TES identified high prevalence of oral diseases, hypertension, obesity and ophthalmic conditions among the middle-aged and elderly Indian population, calling for public health interventions.