Turosz Natalia, Chęcińska Kamila, Chęciński Maciej, Sielski Marcin, Sikora Maciej
National Medical Institute of the Ministry of Interior and Administration, Wołoska 137 Str., 02-507 Warsaw, Poland.
Department of Maxillofacial Surgery, Hospital of the Ministry of Interior, Wojska Polskiego 51, 25-375 Kielce, Poland.
J Clin Med. 2024 Nov 14;13(22):6859. doi: 10.3390/jcm13226859.
The role of artificial intelligence (AI) in dentistry is becoming increasingly significant, particularly in diagnosis and treatment planning. This study aimed to assess the sensitivity, specificity, accuracy, and precision of AI-driven software in analyzing dental panoramic radiographs (DPRs) in patients with permanent dentition. Out of 638 DPRs, 600 fulfilled the inclusion criteria. The radiographs were analyzed by AI software and two researchers. The following variables were assessed: (1) missing tooth, (2) root canal filling, (3) endodontic lesion, (4) implant, (5) abutment, (6) pontic, (7) crown, (8) and sound tooth. The study revealed very high performance metrics for the AI algorithm in detecting missing teeth, root canal fillings, and implant abutment crowns, all greater than 90%. However, it demonstrated moderate sensitivity and precision in identifying endodontic lesions and the lowest precision (65.30%) in detecting crowns. AI software can be a valuable tool in clinical practice for diagnosis and treatment planning but may require additional verification by clinicians, especially for identifying endodontic lesions and crowns. Due to some limitations of the study, further research is recommended.
人工智能(AI)在牙科领域的作用日益显著,尤其是在诊断和治疗计划方面。本研究旨在评估人工智能驱动的软件在分析恒牙列患者的牙科全景X线片(DPR)时的敏感性、特异性、准确性和精确性。在638张DPR中,600张符合纳入标准。这些X线片由人工智能软件和两名研究人员进行分析。评估了以下变量:(1)缺失牙,(2)根管充填,(3)牙髓病变,(4)种植体,(5)基牙,(6)桥体,(7)牙冠,(8)以及健康牙。研究显示,人工智能算法在检测缺失牙、根管充填和种植体基牙牙冠方面具有非常高的性能指标,均大于90%。然而,它在识别牙髓病变方面表现出中等的敏感性和精确性,在检测牙冠方面的精确性最低(65.30%)。人工智能软件在临床实践中可作为诊断和治疗计划的有价值工具,但可能需要临床医生进行额外验证,特别是在识别牙髓病变和牙冠方面。由于本研究存在一些局限性,建议进一步开展研究。