Kazimierczak Wojciech, Wajer Róża, Wajer Adrian, Kiian Veronica, Kloska Anna, Kazimierczak Natalia, Janiszewska-Olszowska Joanna, Serafin Zbigniew
Department of Radiology and Diagnostic Imaging, Collegium Medicum, Nicolaus Copernicus University in Torun, Jagiellońska 13-15, 85-067 Bydgoszcz, Poland.
Department of Radiology and Diagnostic Imaging, University Hospital no 1 in Bydgoszcz, Marii Skłodowskiej Curie 9, 85-094 Bydgoszcz, Poland.
J Clin Med. 2024 May 4;13(9):2709. doi: 10.3390/jcm13092709.
: Periapical lesions (PLs) are frequently detected in dental radiology. Accurate diagnosis of these lesions is essential for proper treatment planning. Imaging techniques such as orthopantomogram (OPG) and cone-beam CT (CBCT) imaging are used to identify PLs. The aim of this study was to assess the diagnostic accuracy of artificial intelligence (AI) software Diagnocat for PL detection in OPG and CBCT images. : The study included 49 patients, totaling 1223 teeth. Both OPG and CBCT images were analyzed by AI software and by three experienced clinicians. All the images were obtained in one patient cohort, and findings were compared to the consensus of human readers using CBCT. The AI's diagnostic accuracy was compared to a reference method, calculating sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and F1 score. : The AI's sensitivity for OPG images was 33.33% with an F1 score of 32.73%. For CBCT images, the AI's sensitivity was 77.78% with an F1 score of 84.00%. The AI's specificity was over 98% for both OPG and CBCT images. : The AI demonstrated high sensitivity and high specificity in detecting PLs in CBCT images but lower sensitivity in OPG images.
根尖周病变（PLs）在牙科放射学中经常被检测到。准确诊断这些病变对于正确的治疗计划至关重要。诸如全景曲面断层片（OPG）和锥形束CT（CBCT）成像等成像技术被用于识别PLs。本研究的目的是评估人工智能（AI）软件Diagnocat在OPG和CBCT图像中检测PLs的诊断准确性。
该研究纳入了49名患者，共1223颗牙齿。OPG和CBCT图像均由AI软件和三名经验丰富的临床医生进行分析。所有图像均取自同一患者队列，并将结果与使用CBCT的人类读者的共识进行比较。将AI的诊断准确性与一种参考方法进行比较，计算灵敏度、特异度、准确度、阳性预测值（PPV）、阴性预测值（NPV）和F1分数。
AI对OPG图像的灵敏度为33.33%，F1分数为32.73%。对于CBCT图像，AI的灵敏度为77.78%，F1分数为84.00%。AI对OPG和CBCT图像的特异度均超过98%。
AI在检测CBCT图像中的PLs时表现出高灵敏度和高特异度，但在OPG图像中的灵敏度较低。
