Applications of artificial intelligence in the analysis of dental panoramic radiographs: an overview of systematic reviews.

IF 2.9 2区医学 Q1 DENTISTRY, ORAL SURGERY & MEDICINE Dento maxillo facial radiology Pub Date : 2023-10-01 Epub Date: 2023-09-04 DOI:10.1259/dmfr.20230284

Natalia Turosz, Kamila Chęcińska, Maciej Chęciński, Anita Brzozowska, Zuzanna Nowak, Maciej Sikora

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Abstract

Objectives: This overview of systematic reviews aimed to establish the current state of knowledge on the suitability of artificial intelligence (AI) in dental panoramic radiograph analysis and illustrate its changes over time.

Methods: Medical databases covered by the Association for Computing Machinery, Bielefeld Academic Search Engine, Google Scholar, and PubMed engines were searched. The risk of bias was assessed using ROBIS tool. Ultimately, 12 articles were qualified for the qualitative synthesis. The results were visualized with timelines, tables, and charts.

Results: In the years 1988-2023, a significant development of information technologies for the analysis of DPRs was observed. The latest analyzed AI models achieve high accuracy in detecting caries (91.5%), osteoporosis (89.29%), maxillary sinusitis (87.5%), periodontal bone loss (93.09%), and teeth identification and numbering (93.67%). The detection of periapical lesions is also characterized by high sensitivity (99.95%) and specificity (92%). However, due to the small number of heterogeneous source studies synthesized in systematic reviews, the results of this overview should be interpreted with caution.

Conclusion: Currently, AI applications can significantly support dentists in dental panoramic radiograph analysis. As systematic reviews on AI become outdated quickly, their regular updating is recommended. PROSPERO registration number: CRD42023416048.

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人工智能在牙科全景放射学分析中的应用：系统综述。

目的：本系统综述旨在建立人工智能（AI）在牙科全景放射学分析中的适用性的当前知识状态，并说明其随时间的变化。方法：检索计算机协会、Bielefeld学术搜索引擎、Google Scholar和PubMed引擎覆盖的医学数据库。使用ROBIS工具评估偏倚风险。最终，12篇文章获得了定性综合的资格。结果通过时间线、表格和图表进行可视化。结果：在1988-2023年，用于DPRs分析的信息技术得到了显著发展。最新分析的AI模型在检测龋齿（91.5%）、骨质疏松症（89.29%）、上颌窦炎（87.5%）、牙周骨丢失（93.09%）和牙齿识别和编号（93.67%）方面实现了高准确率。根尖周病变的检测也具有高灵敏度（99.95%）和高特异度（92%）的特点。然而，由于系统综述中综合的异质来源研究数量较少，应谨慎解释本综述的结果。结论：目前，人工智能应用可以显著支持牙医进行牙科全景照片分析。由于人工智能的系统评价很快就过时了，建议定期更新。PROSPERO注册号：CRD42023416048。

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来源期刊

Dento maxillo facial radiology 医学-核医学

CiteScore

5.60

自引率

9.10%

发文量

审稿时长

4-8 weeks

期刊介绍： Dentomaxillofacial Radiology (DMFR) is the journal of the International Association of Dentomaxillofacial Radiology (IADMFR) and covers the closely related fields of oral radiology and head and neck imaging. Established in 1972, DMFR is a key resource keeping dentists, radiologists and clinicians and scientists with an interest in Head and Neck imaging abreast of important research and developments in oral and maxillofacial radiology. The DMFR editorial board features a panel of international experts including Editor-in-Chief Professor Ralf Schulze. Our editorial board provide their expertise and guidance in shaping the content and direction of the journal. Quick Facts: - 2015 Impact Factor - 1.919 - Receipt to first decision - average of 3 weeks - Acceptance to online publication - average of 3 weeks - Open access option - ISSN: 0250-832X - eISSN: 1476-542X