Abstract #3802

Morphological Characterization of Hepatic Steatosis Using Stereology and Spatial Statistics

Jinyang Wang¹, Changqing Wang¹, Scott B. Reeder^2,3,4,5,6, and Diego Hernando^2,3

¹School of Biomedical Engineering, Anhui Medical University, Heifei, China, ²Radiology, University of Wisconsin-Madison, Madison, WI, United States, ³Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ⁴Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, ⁵Medicine, University of Wisconsin-Madison, Madison, WI, United States, ⁶Emergency Medicine, University of Wisconsin-Madison, Madison, WI, United States

Synopsis

Monte Carlo modeling enables characterization of MR signals in various tissues, and has been applied to liver MR in the presence of fat. However, Monte Carlo modeling requires accurate information about the underlying tissue properties. In this work, we investigate the size and clustering of fat droplets in the liver using stereology and spatial statistics for three human liver biopsy samples with steatosis. Results show that the generalized gamma distribution function can accurately determine the size and location distributions of fat droplets. This may enable analysis of the underlying biophysical mechanisms between fat fraction and R2* from microscopic magnetic sensitivity.

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