Real-time optical detection of endodontic infection using bacterial autofluorescence

Eun-Song Lee; Elbert de Josselin de Jong; Euiseong Kim; Baek-Il Kim

doi:10.1016/j.jdent.2023.104600

Real-time optical detection of endodontic infection using bacterial autofluorescence

J Dent. 2023 Sep:136:104600. doi: 10.1016/j.jdent.2023.104600. Epub 2023 Jun 29.

Authors

Eun-Song Lee¹, Elbert de Josselin de Jong², Euiseong Kim³, Baek-Il Kim⁴

Affiliations

¹ Department of Preventive Dentistry & Public Oral Health, BK21 FOUR Project, Yonsei University College of Dentistry, Seoul, Korea.
² Department of Preventive Dentistry & Public Oral Health, BK21 FOUR Project, Yonsei University College of Dentistry, Seoul, Korea; Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam, Amsterdam, The Netherlands; Inspektor Research Systems BV, Amsterdam, The Netherlands.
³ Microscope Center, Department of Conservative Dentistry and Oral Science Research Center, Yonsei University College of Dentistry, Seoul, Korea; Department of Electrical & Electronic Engineering, Yonsei University College of Engineering, Seoul, Korea.
⁴ Department of Preventive Dentistry & Public Oral Health, BK21 FOUR Project, Yonsei University College of Dentistry, Seoul, Korea. Electronic address: baekil.kim@gmail.com.

PMID: 37392816
DOI: 10.1016/j.jdent.2023.104600

Abstract

Objectives: For successful root canal treatment (RCT), it is essential to objectively assess the presence and activity of bacteria in the root canal system. However, current methods rely on subjective observations of root canal exudates. This study aimed to confirm whether real-time optical detection using bacterial autofluorescence can evaluate endodontic infection status by assessing the red fluorescence (RF) detected from root canal exudates.

Methods: During RCT, endodontic paper points were used to collect root canal exudates scored using conventional organoleptic tests to assess the severity of root canal infections. RF on the paper points was assessed using quantitative light-induced fluorescence (QLF) technology. RF intensity and area from the paper points were quantified, and their correlations with infection severity were assessed using their organoleptic scores. The oral microbiome composition of RF samples was compared with non-red fluorescent (non-RF) samples.

Results: The RF detection rate was nil and >98% in the non-infectious and severe groups. The RF intensity and area significantly increased with infection severity (p<0.001) and showed strong correlations with organoleptic scores (r=0.72, 0.82, respectively). The diagnostic accuracy for detecting root canal infection using RF intensity was good to excellent (AUC = 0.81-0.95) and increased with infection severity. The microbial diversity of the RF samples was significantly lower than that of the non-RF samples. Gram-negative anaerobic bacteria such as Prevotella and Porphyromonas were more predominant in RF samples.

Conclusions: Optical detection using bacterial autofluorescence can objectively evaluate endodontic infection status in real-time by assessing the RF of endodontic root canal exudates.

Clinical significance: This real-time optical technology can be utilised to detect endodontic bacterial infection without conventional incubation, allowing clinicians to determine the endpoint of chemomechanical debridement and increase the positive outcomes of RCTs.

Keywords: Diagnostic systems; Endodontic infection; Optical detection; Quantitative light-induced fluorescence; Red fluorescence.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Bacteria*
Dental Pulp Cavity / diagnostic imaging
Dental Pulp Cavity / microbiology
Root Canal Therapy*