Artificial intelligence vs. semi-automated segmentation for assessment of dental periapical lesion volume index score: A cone-beam CT study.

INTRODUCTION: Cone beam computed tomography periapical volume index (CBCTPAVI) is a categorisation tool to assess periapical lesion size in three-dimensions and predict treatment outcomes. This index was determined using a time-consuming semi-automatic segmentation technique. This study compared artificial intelligence (AI) with semi-automated segmentation to determine AI's ability to accurately determine CBCTPAVI score. METHODS: CBCTPAVI scores for 500 tooth roots were determined using both the semi-automatic segmentation technique in three-dimensional imaging analysis software (Mimics Research™) and AI (Diagnocat™). A confusion matrix was created to compare the CBCTPAVI score by the AI with the semi-automatic segmentation technique. Evaluation metrics, precision, recall, F1-score (2×precision×recallprecision+recall), and overall accuracy were determined. RESULTS: In 84.4 % (n = 422) of cases the AI classified CBCTPAVI score the same as the semi-automated technique. AI was unable to classify any lesion as index 1 or 2, due to its limitation in small volume measurement. When lesions classified as index 1 and 2 by the semi-automatic segmentation technique were excluded, the AI demonstrated levels of precision, recall and F1-score, all above 0.85, for indices 0, 3-6; and accuracy over 90 %. CONCLUSIONS: Diagnocat™ with its ability to determine CBCTPAVI score in approximately 2 min following upload of the CBCT could be an excellent and efficient tool to facilitate better monitoring and assessment of periapical lesions in everyday clinical practice and/or radiographic reporting. However, to assess three-dimensional healing of smaller lesions (with scores 1 and 2), further advancements in AI technologies are needed.

Self-Perceived Oral Symptoms Associated with Nicotine Replacement Therapy.

PURPOSE: This study aimed to evaluate the experience of specific oral and dental symptoms or side effects as reported by patients following the use of nicotine replacement therapy (NRT) products. MATERIALS AND METHODS: The study involved paper-based confidential survey questionnaires accessible for a period of 8 months to patients attending the School of Dentistry Dental Clinic, Griffith University, Australia. This study recorded demography, smoking history, NRT use history, and specific oral and systemic symptoms. The data was assessed and grouped into three divisions: those with no history of NRT use, current and former users of NRT, and current users of NRT. RESULTS: Current users of NRT reported a statistically significantly higher incidence of all oral symptoms and increased incidence of systemic symptoms, as compared to those with no history of NRT use. There was no statistically significant difference between current and former users of NRT for almost all symptoms. CONCLUSIONS: A correlative relationship has been observed between the use of NRT products and patients' reported oral symptoms. This study showed a statistically significantly higher incidence of oral symptoms in current and former NRT users. The reported oral side effects and compounding risk profiles show an imperative need for further research into nicotine replacement therapy products' impact on oral health status and treatment outcomes in dental patients using NRT.