Artificial Intelligence Evaluation of Periodontal Health Using Selfie Intraoral Photography

The first part of this study will collect buccal view of intraoral photo and clinical gum indices from 300 patients visiting Prince Philip Dental Hospital (PPDH). These intraoral photo will be taken by patients using smartphone (iphone) mounted with apparatus (Scanbox) in a standardized way and the quality supervised by clinical staff. Clinical gum indices will be taken by a trained and calibrated clinical staff. Alternatively clinical photo may be assessed by an experienced clinician to locate the inflamed/health gum. This synthesized data set imported into neural network to learn the image characteristics of inflamed and health gum and train the computer.

The second part of this study will recruit 150 patients with gingivitis and longitudinally follow up their gum condition pre- and post- gum treatment in PPDH using standardized intraoral photo and clinical gum indices. The clinical gum indices are the gold standard reflecting the changes in the gum condition.

All photos collected would be analyzed by computer (software: MatLab) to identify key features that help with screening and monitoring of gum condition. Data would then be collected for building a program that quantifies the identified features which may include the following:

1. Color of marginal gum tissues

2. Texture of marginal gum tissues

3. Volume of marginal gum tissues, with reference to the clinical gum indices.

Data and sample size analysis: The computer will be trained with the photo and clinical indices/assessment obtained in the part I of this study. The trained computer will then use to monitor changes of periodontal condition of patients in part II of this study based on photo only. The sensitivity (detect true disease), specificity (detect true health) and the area under these curves (with reference to the gold standard clinical gum indices) will be calculated and are the main outcome of this study. The training of computer is a continuous process and the endpoint comes when the sensitivity, specificity and the area under these curves (AUC) reach plateau (saturation). Therefore, the training of computer will be staged into three phrases with 100, 200 and 300 of cases in the part I of this study and observe the changes in the sensitivity, specificity and AUC.

Patient reported outcome on the use of smartphone selfie would be recorded in visual analogue scale (VAS) as secondary outcome.

Sample size determination: Each tooth represents one unit and assume each subject has 20 teeth, there will be more than 300 subjects X 20 teeth =6000 units for training. For the part 2 study, 150 subjects will be recruited and 130X20=2600 units for testing of the computer.

All new patients attending Prince Philip Dental Hospital will be screen for gum inflammation and periodontal diseases by clinical examination.

Basic periodontal examination (BPE, including visual examination and mechanical probing of gum) will be performed for all of them and assign to the undergraduate students for patient care according to the severity.

Computer record can retrieve patients with gum inflammation (BPE score 2). Data handling All data will be kept reviewed by unblended member (YHL) to check the quality. Only the data that related to the study outcomes will be disclosed. All the data will be kept for another two years since the study finishes. After that, the data will be destroyed completely. Primary investigator will have access to the personal data during and after the study.