Early diagnosis is the most important determinant of oral and oropharyngeal squamous cell carcinoma (OPSCC) outcomes, yet most of these cancers are detected late, when outcomes are poor. Typically, nonspecialists such as dentists screen for oral cancer risk, and then they refer high-risk patients to specialists for biopsy-based diagnosis. Because the clinical appearance of oral mucosal lesions is not an adequate indicator of their diagnosis, status, or risk level, this initial triage process is inaccurate, with poor sensitivity and specificity. The objective of this study is to provide an overview of emerging optical imaging modalities and novel artificial intelligence–based approaches, as well as to evaluate their individual and combined utility and implications for improving oral cancer detection and outcomes. The principles of image-based approaches to detecting oral cancer are placed within the context of clinical needs and parameters. A brief overview of artificial intelligence approaches and algorithms is presented, and studies that use these 2 approaches singly and together are cited and evaluated. In recent years, a range of novel imaging modalities has been investigated for their applicability to improving oral cancer outcomes, yet none of them have found widespread adoption or significantly affected clinical practice or outcomes. Artificial intelligence approaches are beginning to have considerable impact in improving diagnostic accuracy in some fields of medicine, but to date, only limited studies apply to oral cancer. These studies demonstrate that artificial intelligence approaches combined with imaging can have considerable impact on oral cancer outcomes, with applications ranging from low-cost screening with smartphone-based probes to algorithm-guided detection of oral lesion heterogeneity and margins using optical coherence tomography. Combined imaging and artificial intelligence approaches can improve oral cancer outcomes through improved detection and diagnosis.
Trabecular bone around successful dental implants exhibits lower fractal dimension values 6 months after prosthodontic loading and displays stable bony microstructure at 12 months of follow-up.
The choice of imaging system may effect radiopacity measurements. It is possible that radiopacity as recorded on traditional or digitized films is not indicative of the radiopacity as recorded on a digital sensor.
Dental professionals have always been meticulous about infection control due to high risk of cross-contamination during dental procedures. Nevertheless, there is an urgent need to review and revise our current practice of infection control and develop more strict protocols that will prevent nosocomial spread of infection during COVID-19 outbreak and future pandemics. The risk of contamination is high during dental radiography if proper disinfection techniques are not applied. This document provides advice and guidance for infection control when practicing dental radiography during COVID-19 pandemic.
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