A first in biomedical imaging statistics

A new center in the RSPH is the only one in the nation dedicated to biomedical imaging statistics.

Directed by DuBois Bowman, the Center for Biomedical Imaging Statistics (cbis) helps Emory researchers improve disease prevention, diagnosis, treatment, and public health. cbis drives research and patient care by developing specialized statistical techniques tailored for the data collected through biomedical imaging studies of the body. It includes two other core faculty members—John Carew and Ying Guo—several affiliate members, and doctoral students in biostatistics.

When Bowman joined the Department of Biostatistics in 2000, he was the lone statistician dedicated to the nascent field of biomedical imaging.

“Once I began to work in this field, I quickly realized that the demand at Emory exceeded my capacity,” he says.

“What we are trying to do is develop statistical algorithms that can help us identify characteristics of a medical image that may be indicative of breast cancer and to localize specific areas of concern,” says Bowman. “Biopsy is still the gold standard, but our methods will help method to other psychiatric disorders such as depression.”

James W. Curran, MD, MPH Dean

Initially, Bowman worked with medical researchers on imaging studies of the brain. His collaborations grew to include cardiac imaging, liver imaging, and cancer applications, breast and prostate imaging in particular. Breast imaging has come to be a special area of interest, given the American Cancer Society recommendation that women at high risk for breast cancer be screened with magnetic resonance imaging (mri) in addition to mammography. Bowman is working with experts at the Emory Winship Cancer Institute and the Georgia Institute of Technology to develop a screening method for breast cancer based on the data captured during functional mri.

better identify women who are likely candidates for breast cancer.”

Bowman, Guo, and Emory psychiatrist Clinton Kilts hope to develop a predictive algorithm for schizophrenia by creating a model to predict changes in brain pattern activity in patients following treatment. “We are developing a model to pinpoint areas of concern in the brain, identified by using baseline functional scans along with any relevant patient history to predict how someone is likely to respond to treatment,” Bowman explains. “Eventually, we might be able to extend this cbis is using a similar but expanded methodology to study cardiac perfusion and function in heart patients and those with liver disease. Researchers are comparing data captured a week and a year after heart attack to see which areas of the heart have improved. Also, researchers are investigating new methods to detect liver diseases based on perfusion properties of tracer­enhanced mri.

In Bowman’s view, the lines between medicine and public health overlap in cbis. “We’re working on problems that are major public health concerns such as mental illness, Alzheimer’s disease, heart disease, and cancer. The bottom line is that we’re trying to mitigate the burden of those illnesses through our research.”