A new supernumerary tooth occurring in the same region during follow-up after supernumerary tooth extraction: A case report

Objectives: The objective was to study the position and morphological characteristics of supernumerary teeth (ST) based on the cone beam computed tomography (CBCT) data to provide a reference for clinical diagnosis and treatment. Materials and Methods: CBCT imaging data and patient characteristics of 113 patients visiting our institution between January 2020 and January 2021 were collected and analyzed. The Chi square test was used to compare enumeration data between different groups, while the Student's t-test was used for measurement data. Results: Overall, 156 ST were found in 113 patients (82 men and 31 women). Among them, 73 patients had 1 ST, 37 had 2, and 3 had 3. The supernumeraries were maxillary and mandibular in 103 and 10 patients, respectively. A total of 136 teeth were found in the anterior area, of which 30 were in the midline region. Three teeth were in the premolar and molar regions. The teeth were mainly conical (118 teeth), followed by supplementary (24 teeth), tuberculate (10 teeth), and odontomatous (4 teeth), including 2 compound odontomas and 2 complex odontomas; 66 teeth were normally oriented, 62 were inverted, and 28 were transverse. There was a statistically significant relationship in ST between shape and arch, location and shape, and morphology and sagittal position and orientations (P < 0.05). Conclusion: CBCT is an essential tool for diagnosis, and it provides valuable information about the position and morphology of teeth, especially the relationship of teeth to adjacent structures objectively, stereoscopically, and comprehensively.

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Usefulness of Generative Artificial Intelligence (AI) Tools in Pediatric Dentistry

Kusaka,

Akitomo,

Hamada

et al. 2024

Diagnostics

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Background/Objectives: Generative artificial intelligence (AI) such as ChatGPT has developed rapidly in recent years, and in the medical field, its usefulness for diagnostic assistance has been reported. However, there are few reports of AI use in dental fields. Methods: We created 20 questions that we had encountered in clinical pediatric dentistry, and collected the responses to these questions from three types of generative AI. The responses were evaluated on a 5-point scale by six pediatric dental specialists using the Global Quality Scale. Results: The average scores were >3 for the three types of generated AI tools that we tested; the overall average was 3.34. Although the responses for questions related to “consultations from guardians” or “systemic diseases” had high scores (>3.5), the score for questions related to “dental abnormalities” was 2.99, which was the lowest among the four categories. Conclusions: Our results show the usefulness of generative AI tools in clinical pediatric dentistry, indicating that these tools will be useful assistants in the dental field.

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A new supernumerary tooth occurring in the same region during follow-up after supernumerary tooth extraction: A case report

Cited by 6 publications

References 10 publications

Unique oral finding in a patient with Pitt-Hopkins Syndrome

Unique oral finding in a patient with Pitt-Hopkins Syndrome

A cone-beam computed tomography study of supernumerary teeth

Usefulness of Generative Artificial Intelligence (AI) Tools in Pediatric Dentistry

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