UI professors using 3-D lung imaging to further research
University of Iowa engineering Professor Ching-Long Lin has a passion for an unusual kind of art — 3-D lung modeling.
Lin received a five-year, $3.2 million grant in August from the National Institutes of Health to conduct analysis using a 3-D lung model to predict lung disease in both an individual and a large population range.
Lin said he has been creating 3-D lung models for nine years, which helped initiate his current project. After creating a lung image based on one specific subject, Lin’s new project will help predict lung functions on a larger population scale and predict the likelihood of lung disease in individuals.
“A fundamental part of his grant is to develop new quantitative methods for imaging the structure and function of the lung, which is what I do as a professor of radiology in cardiothoracic radiology at the University of Iowa Hospitals and Clinics,” said UI radiology professor John Newell Jr.
With the help of UI radiology Professor Eric Hoffman, UI statistics Professor Kung-Sik Chan, and Newell, Lin is using interdisciplinary work to execute the work the grant funds.
“I will be helping to determine the best way to translate any successful results that come out of Dr. Lin’s project into clinical practice and helping to analyze the results and write scientific papers and new grants best on the new results,” Newell said.
Because every person’s lung is different, Lin said, he uses four different lung subjects to help analyze how airflow differs. He is using lung subjects that have different degrees of asthma, as well as subjects that suffer from chronic obstructive pulmonary disease.
“We try to understand, what we call, structure-function relation,” Lin said. “It’s different from subject to subject, and we try to understand [the airflow and particle transport in the lung] relationship.”
However, Lin’s project is not just model based. Because the number of lung subjects Lin and his colleagues are analyzing, the team is collecting a variety of data.
“Data are one of the big things,” Chan said. “We have these data, and we are developing a new statistical method to understand these data. The lung is so complex, and there is so much information.”
Lin said that if his project is successful in collecting enough data, he hopes to create a data storage that will make it easier for doctors to determine a patient’s lung function, such as if they will develop asthma or a lung disease.
“Analysis gives us the power to be one step ahead,” Chan said.
In today's issue: