Abstract #2086

The impact of compressed sensing L1-ESPIRiT reconstruction on the velocity vector fields acquired by 4D-flow MRI: A comparison to L2-ESPIRiT

Ali Nahardani^1,2, Simon Leistikow^2,3, Martin Krämer^1,4, Karl-Heinz Herrmann¹, Wan-Ting Zhao^1,2, Daniel Güllmar¹, Lars Linsen³, Jürgen R. Reichenbach¹, and Verena Hoerr^1,2,5

¹Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany, ²Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany, ³Institute of Computer Science, Department of Mathematics and Computer Science, Westfälische Wilhelms-Universität Münster, Muenster, Germany, ⁴Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany, ⁵Clinic for Radiology, University Hospital Muenster, Muenster, Germany

Compressed Sensing (CS) is a popular reconstruction technique supporting 4D-flow MRI acquisitions. Many literature studied the velocity changes after CS simplifying the velocity vector field into a scalar field along the time domain. The aim of our investigation was to assess how CS influences reconstructed velocity vector fields in space. Our results showed that CS underestimated the maximum velocity values, broadened the full-width-at-half-maximum of the velocity profiles, and preserved the directional information of the velocity vector fields compared to L2-ESPIRiT. The results of CS were in agreement for differently undersampled data, while the L2-ESPIRiT reconstruction provided differing outputs.

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