Abstract
The purpose of the paper was the assessment of the success of an artificial intelligence (AI) algorithm formed on a deep-convolutional neural network (D-CNN) model for the segmentation of apical lesions on dental panoramic radiographs. A total of 470 anonymized panoramic radiographs were used to progress the D-CNN AI model based on the U-Net algorithm (CranioCatch, Eskisehir, Turkey) for the segmentation of apical lesions. The radiographs were obtained from the Radiology Archive of the Department of Oral and Maxillofacial Radiology of the Faculty of Dentistry of Eskisehir Osmangazi University. A U-Net implemented with PyTorch model (version 1.4.0) was used for the segmentation of apical lesions. In the test data set, the AI model segmented 63 periapical lesions on 47 panoramic radiographs. The sensitivity, precision, and F1-score for segmentation of periapical lesions at 70% IoU values were 0.92, 0.84, and 0.88, respectively. AI systems have the potential to overcome clinical problems. AI may facilitate the assessment of periapical pathology based on panoramic radiographs.
Highlights
Chronic apical periodontitis is an infection of tissues surrounding the dental apex induced by pulpal disease, mostly because of bacterial disease in the root canal complex developing during untreated or incorrectly treated dental caries [1–3]
In 5 cases without apical lesions, lesions were segmented by the artificial intelligence (AI) model (False Positives) (Table 1)
The findings showed the ability of current CNN architectures for automatic dental radiographic interpretation and diagnosis on panoramic radiographs [25]
Summary
Chronic apical periodontitis is an infection of tissues surrounding the dental apex induced by pulpal disease, mostly because of bacterial disease in the root canal complex developing during untreated or incorrectly treated dental caries [1–3]. Epidemiological studies have reported that apical periodontitis is present in 7% of teeth and 70% of the general population. The diagnosis of acute apical periodontitis is made clinically, but the detection of chronic apical periodontitis is done by radiography [4]. Apical periodontitis manifests as a widened periodontal ligament space or visible lesions. Such radiolucencies, called apical lesions, tend to be detected incidentally or by radiographic follow-up of endodontically treated teeth [6, 7]. Apical periodontitis can be detected on periapical and panoramic radiographs and by cone-beam computed tomography (CBCT). Periapical and panoramic radiographs are the most frequently used techniques in the diagnosis and treatment of apical lesions [2].
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