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 Driehuys^3,4,5,6, and Sean B Fain^1,7,8

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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