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Published March 3, 2017 | Published
Book Section - Chapter Open

Early-stage tumor detection using photoacoustic microscopy: a pattern recognition approach


We report photoacoustic microscopy (PAM) of arteriovenous (AV) shunts in early stage tumors in vivo, and develop a pattern recognition framework for computerized tumor detection. Here, using a high-resolution photoacoustic microscope, we implement a new blood oxygenation (sO_2)-based disease marker induced by the AV shunt effect in tumor angiogenesis. We discovered a striking biological phenomenon: There can be two dramatically different sO_2 values in bloodstreams flowing side-by-side in a single vessel. By tracing abnormal sO_2 values in the blood vessels, we can identify a tumor region at an early stage. To further automate tumor detection based on our findings, we adopt widely used pattern recognition methods and develop an efficient computerized classification framework. The test result shows over 80% averaged detection accuracy with false positive contributing 18.52% of error test samples on a 50 PAM image dataset.

Additional Information

© 2017 Society of Photo-Optical Instrumentation Engineers. The authors appreciate the close reading of the manuscript by Prof. James Ballard. We also thank Cheng Ma, Pengfei Hai, and Hsun-Chia Hsu for helpful discussions. This work was sponsored by National Institutes of Health Grants DP1 EB016986 (NIH Director's Pioneer Award), R01 CA186567 (NIH Director's Transformative Research Award), and R01 CA159959.

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