OSC Colloquium: Travis Sawyer, "Title: Identifying the Spectral Fingerprint of Disease..."

Title: Identifying the Spectral Fingerprint of Disease: Using Optical Imaging to Shed Light on Cancer 

Abstract: 

Epithelial cancers are among the most dangerous forms of cancer, often with five-year survival rates as low as 20%. Early detection can significantly improve prognosis, but very few reliable early detection techniques exist for these cancers. Optical imaging is immensely promising for early detection, as light-tissue interactions will change with the onset of disease, creating a unique “spectral fingerprint.” Detecting this spectral fingerprint could enable rapid and accurate early diagnosis, but developing clinical instrumentation and appropriate analysis techniques poses great interdisciplinary challenges. I will discuss my laboratory’s recent efforts to advance imaging technologies toward clinical diagnostics in the scope of gastrointestinal and skin cancer using spectral imaging, multiphoton imaging, and polarization imaging. Our efforts include developing advanced imaging instrumentation, conducting optical characterization of cancerous tissues, and implementing cutting-edge algorithms for automatic tissue classification. Ultimately, these technologies could enable sustainable, minimally-invasive screening of cancer, leading to improved patient outcomes in a wide range of disease treatment scenarios. 

Speaker Bio: 

Travis Sawyer is an Assistant Professor of Optical Sciences and Health Sciences. He received his BS in Optical Sciences from the UA (2017) before attending the University of Cambridge to receive his MPhil in Physics (2018). He then returned to the UA pursue his PhD in Optical Sciences (2021) where he focused on developing novel imaging techniques for ovarian cancer detection. After graduating, he joined the faculty at the College of Optical Sciences to establish the Biomedical Optics and Optical Measurement Lab. His research interests include gastrointestinal cancer detection, where he develops screening devices incorporating optical coherence tomography, fluorescence imaging, and other novel imaging modalities, with a focus on image analysis through machine learning techniques. Previously, he started a company developed visual recognition software for detailed image capture, enabling discoveries in astronomy, art preservation, and the biomedical sciences. Travis is also a strong supporter of science outreach, regularly organizing and supporting efforts to educate the community and encourage careers in science.