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Abstract #2150

Comparison of quantitative algorithms for calculating VDP from hyperpolarized 129Xe MRI – testing reproducibility of a biomarker of airway obstruction

Wei Zha1, Mu He2, Bastiaan Driehuys3,4,5,6, and Sean B Fain1,7,8

1Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 2Department of Electrical and Computer Engineering, Duke University, NC, United States, 3Department of Biomedical Engineering, Duke University, NC, United States, 4Department of Medical Physics, Duke University, NC, United States, 5Department of Radiology, Duke University, NC, United States, 6Center for In Vivo Microscopy, Duke University, NC, United States, 7Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 8Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States

There is a need to establish robust quantification pipelines to analyze 129Xe ventilation MRI for multi-center studies. Moreover, there is increasing interest in quantifying not only ventilation defect percent, but also regions of low and high ventilation. To this end, we sought to determine inter-method agreement between two different semi-automated quantitative mapping approaches — linear binning and adaptive K-means. The results suggest that once bias field corrections are applied consistently, both ventilation analysis methods agree well when classifying ventilation into 4 bins. Thus, with key steps outlined here, either method can be readily deployed in multi-center studies.

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