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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 fluorescen...

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Autores principales: Angelino, Keith, Shah, Pratik, Edlund, David A., Mohit, Mrinal, Yauney, Gregory
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5745686/
https://www.ncbi.nlm.nih.gov/pubmed/29284461
http://dx.doi.org/10.1186/s12903-017-0472-4
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author Angelino, Keith
Shah, Pratik
Edlund, David A.
Mohit, Mrinal
Yauney, Gregory
author_facet Angelino, Keith
Shah, Pratik
Edlund, David A.
Mohit, Mrinal
Yauney, Gregory
author_sort Angelino, Keith
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi: 10.1186/s12903-017-0472-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-57456862018-01-03 Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque Angelino, Keith Shah, Pratik Edlund, David A. Mohit, Mrinal Yauney, Gregory BMC Oral Health Technical Advance 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi: 10.1186/s12903-017-0472-4) contains supplementary material, which is available to authorized users. BioMed Central 2017-12-28 /pmc/articles/PMC5745686/ /pubmed/29284461 http://dx.doi.org/10.1186/s12903-017-0472-4 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Technical Advance
Angelino, Keith
Shah, Pratik
Edlund, David A.
Mohit, Mrinal
Yauney, Gregory
Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque
title Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque
title_full Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque
title_fullStr Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque
title_full_unstemmed Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque
title_short Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque
title_sort clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque
topic Technical Advance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5745686/
https://www.ncbi.nlm.nih.gov/pubmed/29284461
http://dx.doi.org/10.1186/s12903-017-0472-4
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