Detection of Early Stages Dental Caries Using Photoacoustic Signals: The Simulation Study Publisher



Arabpou S^{1, 2} ; Najafzadeh E^{1, 2} ; Farnia P^{1, 2} ; Ahmadian A^{1, 2} ; Ghadiri H^{1, 2} ; Akhoundi MSA³ Show Affiliations
Source: Frontiers in Biomedical Technologies Published:2019

Abstract

Purpose: Dental caries is known as one of the most common oral diseases in the world. Tooth decay progresses slowly, and the symptoms are not regularly visible until it reaches an irreversible phase and needs to be removed with extensive restoration treatment. If the lesions could be diagnosed at an initial stage, the progress of dental diseases would be stopped through preventive treatments. Conventional methods for caries detection are visual examinations and X-Ray imaging methods that have significant limitations such as poor sensitivity and specificity at the earliest stages of the disease due to the small size of the lesions. Materials and Methods: Photoacoustic imaging as a non-invasive hybrid imaging modality combines the high spatial resolution of ultrasound with the rich optical contrasts of optical imaging, and it is much safer than the ionizing radiation like X-ray imaging. In this study, the simulation of the light propagation and energy deposition in the tooth was done using Monte Carlo to form the initial pressure for acoustic simulations which is done by the K-Wave toolbox. The simulations were implemented by a tooth model which is including enamel, dentin, pulp, and gum layers. Results: Simulation results revealed that early tooth lesions could be detected by a broad beam light source better than the pencil beam light source in photoacoustic imaging. Also, as our simulation results proved, the amount of energy deposition for the bigger lesions is significantly higher than the smaller lesions using the broad beam light source. Conclusion: Photoacoustic imaging as a promising imaging modality which is non-contact, non- invasive and non-ionizing imaging modality could detect early-stage tooth caries and provide quantitative information for white spot lesion evaluation. © Tehran University of Medical Sciences