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Abstract #1041

An Adaptive K-means Approach for Assessment of Ventilation Defects in Asthma and Cystic Fibrosis Using Hyperpolarized Helium-3 MRI

Wei Zha 1 , Stanley J Kruger 1 , Robert V Cadman 1 , David Mummy 2 , David J Niles 1 , Scott K Nagle 1,3 , and Sean B Fain 1,3

1 Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 2 Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, United States, 3 Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States

A recent study proposed K-means-based defect segmentation (Kirby method) and evaluated its performance on 15 subjects. In our study, 83 asthma and 8 cystic fibrosis subjects underwent spirometry and hyperpolarized helium-3 MRI. The percent ventilation defect (%VD) was determined using manual segmentation and semi-automatically with the Kirby method and an improved adaptive K-means approach. The adaptive K-means approach corrected for B1 inhomogeneity, excluded pulmonary vasculature and determined defects adaptively. The %VD measured using either manual segmentation or this improved K-means-based approach was correlated with the spirometric measures, whereas correlation was not observed with the Kirby method.

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