Deep convolutional neural network algorithm for the automatic segmentation of oral potentially malignant disorders and oral cancers.

This study aimed to develop an algorithm to automatically segment the oral potentially malignant diseases (OPMDs) and oral cancers (OCs) of all oral subsites with various deep convolutional neural network applications. A total of 510 intraoral images of OPMDs and OCs were collected over 3 years (2006-2009). All images were confirmed both with patient records and histopathological reports. Following the labeling of the lesions the dataset was arbitrarily split, using random sampling in Python as the study dataset, validation dataset, and test dataset. Pixels were classified as the OPMDs and OCs with the OPMD/OC label and the rest as the background. U-Net architecture was used and the model with the best validation loss was chosen for the testing among the trained 500 epochs. Dice similarity coefficient (DSC) score was noted. The intra-observer ICC was found to be 0.994 while the inter-observer reliability was 0.989. The calculated DSC and validation accuracy across all clinical images were 0.697 and 0.805, respectively. Our algorithm did not maintain an excellent DSC due to multiple reasons for the detection of both OC and OPMDs in oral cavity sites. A better standardization for both 2D and 3D imaging (such as patient positioning) and a bigger dataset are required to improve the quality of such studies. This is the first study which aimed to segment OPMDs and OCs in all subsites of oral cavity which is crucial not only for the early diagnosis but also for higher survival rates.

Orofacial manifestations of rheumatoid arthritis and systemic lupus erythematosus: a narrative review.

Both rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are classified as autoimmune diseases, where the body's own immune response causes it to attack the host tissues, as if the latter were antigens. RA is the most common autoimmune disease that affects joints. The clinical diagnosis of RA is based on the history and examination, integrated with laboratory tests including blood tests on inflammatory markers, serology, and imaging. There are no diagnostic criteria, but there are classification criteria. SLE affects most major organ systems in the body. The diagnosis of SLE relies on the constellation of characteristic symptoms, signs, and laboratory findings in the appropriate clinical context and after excluding other reasonable diagnoses. Epidemiologically, both conditions show a definitive female predilection. The focus of this review article is epidemiology, and the major clinical features with an emphasis on the orofacial manifestations. The relevant clinical points for the dental practitioner area summarized.