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March 7, 2022

DOVER, Del. – Delaware State University has received a four-year $431,000 grant from the National Institute of General Medical Sciences under the National Institute of Health for a research project entitled “Image Analysis and Machine Learning Methods for Biomarkers of Age-related and Metabolic Diseases.”

The Principal Investigator of the grant is Dr. Sokratis Makrogiannis, associate professor in the Division of Physics, Engineering, Mathematics, and Computer Science. The award is a competitive renewal grant, which follows a previous four-year $255,000 grant that funded Del State research on quantitative image analysis techniques for the studies of aging phenotypes and age-related diseases.

The current funded research will build on recent advances in medical imaging analysis to contribute novel and non-invasive techniques for studying the human body composition and its changes. This is especially in relation to age-related metabolic diseases such as type-2 diabetes mellitus, cardiovascular disease, obesity, and osteoporosis – all of which have become worldwide medical challenges.

Dr. Makrogiannis said the research will also develop machine learning (artificial intelligence) methods to achieve timely diagnosis and prognosis.

“We will work to develop ways in which artificial intelligence can be utilized to understand imaging data to assist physicians in making medical diagnoses,” Dr. Makrogiannis said. “For underserved communities, this could lower health care costs, as it will take less time for analysis, and speed up diagnostics.”

Dr. Makrogiannis and his graduate-level researchers will use imaging and clinical data collected by the Baltimore Longitudinal Study of Aging – the longest ongoing epidemiology study in the United States – as well as publicly available datasets. Among his team of researcher is Chelsea, a Del State Ph.D student from Felton, Del.

As the University possesses imaging technology capable of delineating the many different types of muscles in the body, the research will develop improved imaging techniques and artificial intelligence methods relating to the longitudinal changes in body composition and form – which is strongly linked to metabolic diseases. The research will also involve the analysis of accumulation of adipose tissue in the human body and the changes in its regional distribution, which is associated with type-2 diabetes, cardiovascular disease and the metabolic syndrome.