June Tong

Biomedical Engineering

June Tong joined a project at the Beckman Laser Institute that was using spatial frequency domain imaging to assess tissue health by calculating and generating images of tissue oxygen saturation. Her work involved developing a MATLAB algorithm to calculate color differences between digital images and, while she was primarily working as a programmer, she was able to observe closely the experimental process behind the research. June is particularly grateful to Dr. Adrien Ponticorvo, who played an integral role in mentoring her throughout the project. She hopes to continue her education by going on to medical school and studying to become a prosthetist.triangle.gif (504 bytes)




Tissue transfer techniques using tissue flaps are commonly used in reconstructive surgery to replace damaged tissue. While typically successful, tissue flaps that require additional surgery have a 40–60% failure rate. The current technique to diagnose tissue flap failure is to monitor the flap hourly and look for signs of discoloration. The chance of salvaging a tissue flap improves the earlier a problem becomes apparent; therefore, a technique that can detect changes before they are visually noticeable has the potential to improve post-operative flap management. This project used spatial frequency domain imaging (SFDI) to generate images of tissue oxygen saturation and compare the results to imaged clinical appearance. To mimic different levels of tissue failure, flaps were created in a swine model in which blood flow was monitored with ultrasound probes and controlled with vascular occlusion cuffs. Blood flow was reduced by 25%, 50%, 75%, and 100% of baseline values. The color changes were recorded in digital camera images and quantified to predict which occlusion conditions would be visible to the human eye. The results were compared to the SFDI oxygen saturation images. Results indicate that while the human eye can reliably perceive changes at 100% occlusion, SFDI is able to detect changes as small as 25%, thereby improving response time and reducing the potential for flap failure.triangle.gif (504 bytes)

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Faculty Mentor                                                                                                                

Anthony J. Durkin

School of Physical Sciences

Early identification of surgically reconstructed tissue in the post-operative period is critical to reducing complications. We are developing new quantitative optical imaging techniques that have potential to enable rapid identification of early changes that indicate flap dysfunction. In order to assess the performance of our new methods, we must also quantify current approaches to flap surveillance. The most commonly employed existing approach to flap surveillance is simple visual inspection. The work presented here quantifies the color changes associated with visual inspection (using digital photography as a record) in order to enable a performance comparison to the metrics associated with our new technology, which is based on near infrared light.triangle.gif (504 bytes)

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