Metabolic syndrome is a â€œclusteringâ€ of metabolic abnormalities and cardiovascular risk factors that afflict an estimated 47 million Americans. While the underlying causes of metabolic syndrome are not fully understood, recent research has identified central obesity, i.e. excessive abdominal adipose tissue, as a dominant risk factor. However, the international medical community lacks consensus on diagnostic criteria for measuring central obesity, which severely hinders prospective diagnosis and epidemiological studies. To meet this need, we propose a non-invasive quantitative measurement technique for central obesity, termed â€œadiposity MRIâ€, which will facilitate efficient and cost-effective clinical screening of metabolic syndrome in the population at large. The proposed method uses chemical-shift-based MRI methods to acquire separated fat and water images of the abdomen, and employs a signal-clustering algorithm for automatically isolating adipose tissue and segmenting visceral adipose tissue (VAT) for direct volume measurement. The advantages of this method over current approaches are complete patient safety, truly quantitative and accurate VAT estimation, and minutes instead of hours of processing time with minimal operator intervention and training.
May 2010 to September 2010
This project led by: Scott B Reeder, MD, PhD