Abstract #3240

Semi-automated analysis to reduce operator variability in oxygen extraction fraction using susceptometry-based oximetry

Bo-Jhen Su¹, Pei-Hsin Wu¹, Rajiv S Deshpande², and Felix W Wehrli²

¹Department of Electrical Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, ²Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States

Synopsis

Keywords: Data Analysis, OxygenationSvO₂ and OEF were estimated via susceptometry-based oximetry (SBO). The impact of user-defined ROI was investigated in this study. The results show that (1) the consistency of SvO₂ estimation depends on operators’ comprehension of MR-oximetry, (2) SvO₂ might be under-estimated with manual ROI selection, and (3) the operator-induced bias can be eliminated by the semi-automatic analysis. The preliminary data indicate the feasibility of the constructed semi-automatic analysis for consistent estimation of SvO₂ among operators and its potential for bulk analysis and clinical use.

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