Optical Coherence Tomography as an Oral Cancer Screening Adjunct in a Low Resource Settings

• Published in: IEEE journal of selected topics in quantum electronics Vol. 25; no. 1; pp. 1 - 8
• Main Authors: Heidari, Andrew Emon, Sunny, Sumsum P., James, Bonney L., Lam, Tracie M., Tran, Anne V., Yu, Junxiao, Ramanjinappa, Ravindra D., K., Uma, Birur, Praveen, Suresh, Amritha, Kuriakose, Moni A., Chen, Zhongping, Wilder-Smith, Petra
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: biomedical image processing; biomedical optical imaging; Cancer; Diagnostic systems; Image classification; Image processing; Image resolution; Lesions; Medical imaging; Medical screening; optical coherence tomo-graphy; Optical Coherence Tomography; Oral cancer; Probes; Tomography; Visual observation; Visualization
• DOI: 10.1109/JSTQE.2018.2869643
• ISSN: 1077-260X

Oral cancer is the sixth most common cancer worldwide, predominantly seen in low and middle-income countries (LMIC). Two thirds of all cases are detected at a late stage when prognosis and treatment outcomes are poor. Oral lesions are commonly detected by visual inspection, followed by invasive surgical biopsy and time-consuming histopathological analysis. Optical coherence tomography (OCT), a minimally invasive tomographic imaging technology, can be used to non-invasively identify premalignant or malignant change in the oral mucosa. In this study, a mobile OCT imaging system was designed, constructed, and tested for its performance as a point-of-care oral diagnostic device in an LMIC. 20 patients with suspicious oral lesions and 10 healthy subjects were enrolled in this pilot study. Two-dimensional (2-D) OCT images as well as clinical examination data, risk habit history, and histopathology were collected. OCT images for healthy oral mucosa, dysplasia, and malignancy were evaluated in a blinded fashion by visual scoring and computed image processing techniques. It was found that the OCT image processing algorithm performed at or exceeded the performance of visual observer scoring of OCT images.