Oxygen extraction fraction mapping at 3 Tesla using an artificial neural network: A feasibility study

The oxygen extraction fraction (OEF) is an important biomarker for tissue‐viability. MRI enables noninvasive estimation of the OEF based on the blood‐oxygenation‐level‐dependent (BOLD) effect. Quantitative OEF‐mapping is commonly applied using least‐squares regression (LSR) to an analytical tissue model. However, the LSR method has not yet become clinically established due to the necessity for long acquisition times. Artificial neural networks (ANNs) recently have received increasing interest for robust curve‐fitting and might pose an alternative to the conventional LSR method for reduced acquisition times. This study presents in vivo OEF mapping results using the conventional LSR and the proposed ANN method.

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