Assessment of landmark detection in cephalometric radiographs with different conditions of brightness and contrast using the an artificial intelligence software.

OBJECTIVES: To evaluate the reliability and reproducibility of an artificial intelligence (AI) software in identifying cephalometric points on lateral cephalometric radiographs considering four settings of brightness and contrast. METHODS AND MATERIALS: Brightness and contrast of 30 lateral cephalometric radiographs were adjusted into four different settings. Then, the control examiner (ECont), the calibrated examiner (ECal), and the CEFBOT AI software (AIs) each marked 19 cephalometric points on all radiographs. Reliability was assessed with a second analysis of the radiographs 15 days after the first one. Statistical significance was set at p < 0.05. RESULTS: Reliability of landmark identification was excellent for the human examiners and the AIs regardless of the type of brightness and contrast setting (mean intraclass correlation coefficient >0.89). When ECont and ECal were compared for reproducibility, there were more cephalometric points with significant differences on the x-axis of the image with the highest contrast and the lowest brightness, namely N(p = 0.033), S(p = 0.030), Po(p < 0.001), and Pog'(p = 0.012). Between ECont and AIs, there were more cephalometric points with significant differences on the image with the highest contrast and the lowest brightness, namely N(p = 0.034), Or(p = 0.048), Po(p < 0.001), A(p = 0.042), Pog'(p = 0.004), Ll(p = 0.005), Ul(p < 0.001), and Sn(p = 0.001). CONCLUSIONS: While the reliability of the AIs for cephalometric landmark identification was rated as excellent, low brightness and high contrast seemed to affect its reproducibility. The experienced human examiner, on the other hand, did not show such faulty reproducibility; therefore, the AIs used in this study is an excellent auxiliary tool for cephalometric analysis, but still depends on human supervision to be clinically reliable.

Oral mucosa lesions in confirmed and non-vaccinated cases for COVID-19: A systematic review.

This systematic review purposed to investigate reports of oral lesions in confirmed COVID-19 patients summarizing clinical characteristics, histological findings, treatment and correlation of oral lesions and COVID-19 severity. Electronic search was conducted on November 2021 using seven databases to identify case reports/series describing lesions in oral mucosa in COVID-19 confirmed cases. A total of 5,179 studies were found, being 39 eligible from 19 countries, totalling 116 cases. It was observed only COVID-19 non-vaccinated cases and no sex or age predilection. The oral lesions presentation was mostly single location (69.8%), commonly in the tongue, lips, and palate, being ulcer the main clinical presentation. According to severity index for COVID-19, the reports were more frequent in patients with mild and moderate symptoms, being 75.8% in acute phase. The oral lesion appearance in post-acute COVID-19 were described after 14 to two months after patient recovery. Histologically, keratinocytes with perinuclear vacuolization, thrombosis and mononuclear inflammatory infiltrate were also described with the presence of the virus in keratinocytes, endothelial cells, and minor salivary glands. In conclusion, health care professionals should consider COVID-19 association when patient present ulcerated oral lesions and mild to moderate symptoms for COVID-19 or had acute-COVID-19.