New techniques for diagnosing respiratory abnormalities

Just last week, UGA hosted a symposium on Research Experiences for Undergraduates, a program that brought promising young researchers to campus for ten weeks this summer to work with and be mentored by some of our best faculty members. The theme of the first day's presentations was computational biology, and if you're curious about research pursuits within that confluence of disciplines, a new study demonstrates what it is quite well:

Though it only affects a small number of people annually, ciliary dyskinesia can mimic the symptoms of less serious diseases. New research published in the journal Science Translational Medicine identifies a new technique to help clinicians make more accurate early diagnoses.

"The disorder causes the cilia to not move properly. Without the proper motion, they can't clear out mucus and with that you get anything from flu-like symptoms, all the way up to lung scarring necessitating lung transplants," said the study's lead author Shannon Quinn, an assistant professor of computer science at the University of Georgia.

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Clinicians go through a series of steps to diagnose ciliary dyskinesia, and no single method produces a certain diagnosis. Electron microscopy detects structural abnormalities, measuring the frequency at which the cilia beat. Nasal cultures from patients are plated for biopsy and grown in the lab. Then, their motions are analyzed with video microscopy. From the videos, clinicians or researchers make a determination about whether the motion is normal.

"It's that last step that we're focusing on," Quinn said. "Researchers or clinicians making this determination based on their own training and experience is the current state of the art, but it is subjective, laborious and error prone. There is no cross-institutional commonality for making the diagnoses. So our goal was to provide a quantitative baseline for that particular step in the diagnostic process."

Extraordinary work at the leading edge of new developments in interdisciplinary application of computational expertise and medical science. Quinn was himself a former REU participant and worked with an undergraduate researcher this summer. What better experience than learning from someone who knows first hand the value of such a program. Congratulations to Quinn and his collaborators at UPitt on this excellent work, which will have a significant impact on diagnoses as well as the training of future clinicians. 

Image: color graphic of cilia and still from a video accompanying the study both courtesy of Science Translational Medicine.