Sensitivity and specificity of gingivitis diagnosis using smartphone-based intraoral photographs

Chu Thi Quynh Huong, Luu Thanh Trung, Pham Duong Hieu, Pham Le Huong Linh, Luu Van Tuong

Main Article Content

Abstract

This study evaluated the sensitivity and specificity of gingivitis diagnosis using smartphone-based intraoral photographs among 170 adults in Thanh Xuan district, Hanoi, in 2025. Gingivitis was determined by clinical examination based on the Gingival Index (GI) and Bleeding on Probing (BOP), and was independently assessed using standardized intraoral photographs. The image-based diagnosis achieved a sensitivity of 86.6%, a specificity of 75.3%, and an overall diagnostic accuracy of 81.8%, with substantial agreement compared with clinical examination (Kappa = 0.625). Inter-rater agreement between two independent image assessors was satisfactory (Kappa = 0.74). These findings indicate that smartphone-based image diagnosis is a reliable and feasible approach for community-based gingivitis screening, particularly in settings with limited availability of oral and maxillofacial care professionals.

Article Details

References

1. Tonetti MS, Jepsen S, Jin L, et al. Impact of the global burden of periodontal diseases on health, nutrition and wellbeing: a call for global action. J Clin Periodontol. 2017; 44(5): 456-462.
2. Tran DQ, Vu CTQ, Phan QN, et al. Prevalence of periodontal disease among Vietnamese adults: a systematic review and meta-analysis. Dent Med Probl. 2023; 60(1):145-152.
3. World Health Organization. Global oral health status report: towards universal health coverage for oral health by 2030. Geneva: World Health Organization; 2022.
4. Mehta A, Janakiram C, Venkitachalam R. Teledentistry in periodontal screening and diagnosis: current evidence and future directions. J Dent Sci. 2023; 18(2): 789-797.
5. Estai M, Kanagasingam Y, Tennant M, Bunt S. A systematic review of the research evidence for the benefits of teledentistry. J Telemed Telecare. 2022; 28(3): 147-156.
6. Löe H, Silness J. Periodontal disease in pregnancy. I. Prevalence and severity. Acta Odontol Scand. 1963; 21: 533-551.
7. Greene JC, Vermillion JR. The simplified oral hygiene index. J Am Dent Assoc. 1964; 68:7-13.
8. Lang NP, Joss A, Orsanic T, et al. Bleeding on probing. A predictor for the progression of periodontal disease? J Clin Periodontol. 1986;13(6): 590-596.
9. Trombelli L, Farina R, Silva CO, Tatakis DN. Plaque-induced gingivitis: case definition and diagnostic considerations. J Clin Periodontol. 2018; 45(Suppl 20): S44-S67.
10. Bossuyt PM, Reitsma JB, Bruns DE, et al. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ. 2015; 351: h5527.
11. Kim JH, Park Y, Lee JH. Standardized intraoral image acquisition protocols for periodontal diagnosis. Diagnostics (Basel). 2023; 13(9): 1654.
12. Liu Y, Cheng Y, Song Y, et al. Oral screening of dental calculus, gingivitis and dental caries through segmentation on intraoral photographic images using deep learning. BMC Oral Health. 2024; 24: 1287.
13. Ahmed J, Askarian M, Schwendicke F. Accuracy of smartphone-based photographs for gingivitis assessment: a diagnostic accuracy study. BMC Oral Health. 2022; 22: 198.
14. Kim HN, Kim K, Lee Y. Intra-oral photograph analysis for gingivitis screening in orthodontic patients. Int J Environ Res Public Health. 2023; 20(4): 3705.
15. Terry PD, Wilson OL, Heaton ML, et al. Accuracy of digital photographs for assessing inflammatory gum disease in epidemiologic studies. Front Oral Health. 2025; 6.