Classification of human gingival sulcus using swept-source optical coherence tomography: In vivo imaging

• Published in: Infrared physics & technology Vol. 98; pp. 155 - 160
• Main Authors: Lee, Jaeyul, Park, Jaeseok, Faizan Shirazi, Muhammad, Jo, Hosung, Kim, Pilun, Wijesinghe, Ruchire Eranga, Jeon, Mansik, Kim, Jeehyun
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2019
• Subjects: Classification algorithm; Gingival sulcus; Optical coherence tomography; Periodontal tissue; Swept-source optical coherence tomography; Periodontal tissue; Gingival sulcus; Classification algorithm; Optical coherence tomography; Swept-source optical coherence tomography
• ISSN: 1350-4495; 1879-0275
• DOI: 10.1016/j.infrared.2019.03.005

•SS-OCT was utilized to visualize human gingival sulcus in vivo for the depth identification.•The quantitative measurement was enhanced by applying the developed OCT image classification algorithm.•Total of 43 sites from the periodontal tissues of five healthy individuals was imaged.•The classification of gingival sulcus was helpful to confirm the depth of maxilla and mandible regions.•The proposed method can be anticipated that provides a powerful tool to the periodontal-OCT applications. We demonstrated a preliminary research to investigate the feasible in vivo utilization of swept-source optical coherence tomography (SS-OCT) system with 1310 nm wavelength band to obtain morphological visualizations and human gingival sulcus depth measurements. Apart from the cross-sectional analysis, pixel intensity based OCT image classification algorithm is developed to identify the depth of gingival sulcus quantitatively. A total of 43 sites from the periodontal tissues of five healthy individuals were imaged in vivo by using the OCT system. Two periodontal tissues were right and left maxillary central incisors, while the other four periodontal tissues were left and right mandibular central incisors and later incisors. The developed classification algorithm could measure the gingival sulcus depths, which are 1.15±0.21 mm of the maxilla and 1.06±0.27 mm of the mandible. The averaged total depths obtained by the system was 1.10±0.26 mm. Hence, the gingival sulcus depth could be quantitatively measured by using the swept-source OCT system with the developed image classification algorithm as well as revealing a structural visualization, which ultimately confirmed the potential applicability for gingival sulcus depth real-time assessment.