Wednesday, April 22, 2015

URSP Student Caitlin Johnson Diagnoses Neck and Head Trauma from TCD Signals

There are many branches in the bioengineering field and many ways to invent oneself as a member of that community. For me, it was very difficult to pick which way I wanted to go and where my interests lie inside of the vast abyss of bioengineering knowledge. But, like most bioengineers, I knew that I wanted to make a meaningful impact on the future of medicine and healthcare. This, I realized could only be done by getting involved in research.
My mentors, Dr, Dianna Purvis and Dr. Siddhartha Sikdar, approached me with a project that promised to be a breakthrough in the way of diagnosing cervical vascular injuries which could lead to stroke risk analysis in trauma patients. As part of an ongoing study, of which the results have been very promising, my role would be to extract data from a larger number of patient Doppler ultrasound screenings. By expanding the number of patient data sets, we can effectively improve the statistics on and our certainty of the effectiveness of a newer, easier, and more cost-effective way to diagnose major head and neck trauma in patients.

In a typical day, I work with a Spencer Technology’s transcranial Doppler ultrasound examining hemodynamic flow (blood flow) images for various parts of arteries in the neck and the head. I may have to adjust image variables depending on the signal envelope and record the data into an excel sheet for statistical analysis. What I have discovered along the way is that the huge amount of signal variation between patients makes adjusting variables a very subjective process and introduces extraneous errors that may impact results. Extracting valid data is very time intensive and must be done with the utmost attention to detail.