Early detection of oral cancer is essential for improving patient survival rates and leads to higher chances of successful treatment, reduced cost of complex treatments, and improved quality of life of patients. Oral cancer often arises from oral potentially malignant disorders (OPMDs), among which leukoplakia is the most common. Numerous chairside diagnostic aids and imaging modalities have been reviewed for screening detection of OPMDs and oral cancer, but these techniques have limitations. Novel optical diagnostic modalities work on the assumption that neoplastic and dysplastic tissues have different absorbance and reflectance properties when exposed to specific wavelengths of light. Optical coherence tomography (OCT) imaging is a promising new technology in the field of oral oncology. The ability of OCT to provide real-time, nondestructive, high-resolution, radiation-free images makes it an ideal modality for screening and detection of neoplastic changes in the oral mucosa, but interpretation of OCT images requires training and expertise. To overcome this limitation, artificial intelligence-based diagnostic algorithms are being combined with OCT imaging to assist professionals in achieving high-accuracy interpretation of OCT images. This review highlights the applications and scope of artificial intelligence in OCT imaging for the screening and detection of early-stage oral cancer.
Keywords: artificial intelligence; early detection of cancer; optical coherence tomography; oral cancer; oral potentially malignant disorders.