Biomedical Engineering Distinguished Speaker Lectures on Early Detection of Oral Cancer

Photo by Kara Karstedt

Kristen Maitland of Texas A&M delivers her lecture.

On Friday, Oct. 20, the Department of Biomedical Engineering hosted seminar speaker Kristen Maitland, an associate professor in the Department of Biomedical Engineering at Texas A&M University. In her seminar, titled "Reflectance Confocal and Fluorescence Lifetime Endoscopy in the Oral Cavity," Maitland explained that although the oral cavity is a relatively accessible organ, mortality rates from oral cancer remain regrettably high.

Delayed diagnosis is believed to be one of the main causes for the low survival rate, compared to other cancers. Precancerous lesions can be diffuse, heterogeneous, and multifocal, complicating accurate diagnosis of pre-malignancy. Development of noninvasive clinical tools that can help the clinician identify the most accurate sites of precancerous lesions is therefore of great importance and can potentially increase the diagnostic yield of the overall screening process.

In an effort to improve early detection, Maitland explained how she and her colleagues have developed a multi-modal, multi-scale optical imaging system based on macroscopic fluorescence lifetime imaging (FLIM) and high resolution reflectance confocal microscopy (RCM) for imaging of the oral mucosa in humans. FLIM provides biochemical screening by probing the endogenous fluorescence of structural proteins (collagen) and metabolic cofactors (NADH, FAD), and RCM provides information on nuclear morphology and overall tissue architecture. Maitland and her colleagues have developed handheld endoscopes for FLIM and RCM designed to access the oral cavity. Following informed consent, patients presenting with oral lesions are imaged with the FLIM and RCM endoscopes prior to excisional tissue biopsy, which is processed for histopathology for diagnostic purposes. Maitland also presented preliminary results from a pilot clinical study, and explained that if this technology proves successful, it may enable real-time detection of premalignant and malignant oral mucosa, surgical margin detection, and treatment monitoring.