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Τετάρτη 14 Νοεμβρίου 2018

Visualizing and quantifying flow stasis in abdominal aortic aneurysms in men using 4D flow MRI

Publication date: Available online 13 November 2018

Source: Magnetic Resonance Imaging

Author(s): Magnus Ziegler, Martin Welander, Jonas Lantz, Marcus Lindenberger, Niclas Bjarnegård, Matts Karlsson, Tino Ebbers, Toste Länne, Petter Dyverfeldt

Abstract
Purpose

To examine methods for visualizing and quantifying flow stasis in abdominal aortic aneurysms (AAA) using 4D Flow MRI.

Methods

Three methods were investigated: conventional volumetric residence time (VRT), mean velocity analysis (MVA), and particle travel distance analysis (TDA). First, ideal 4D Flow MRI data was generated using numerical simulations and used as a platform to explore the effects of noise and background phase-offset errors, both of which are common 4D Flow MRI artifacts. Error-free results were compared to noise or offset affected results using linear regression. Subsequently, 4D Flow MRI data for thirteen (13) subjects with AAA was acquired and used to compare the stasis quantification methods against conventional flow visualization.

Results

VRT (R2 = 0.69) was more sensitive to noise than MVA (R2 = 0.98) and TDA (R2 = 0.99) at typical non-contrast signal-to-noise ratio levels (SNR = 20). VRT (R2 = 0.14) was more sensitive to background phase-offsets than MVA (R2 = 0.99) and TDA (R2 = 0.96) when considering a 95% effective background phase-offset correction. Qualitatively, TDA outperformed MVA (Wilcoxon p < 0.005, mean score improvement 1.6/5), and had good agreement (median score 4/5) with flow visualizations.

Conclusion

Flow stasis can be quantitatively assessed using 4D Flow MRI. While conventional residence time calculations fail due to error accumulation as a result of imperfect measured velocity fields, methods that do not require lengthy particle tracking perform better. MVA and TDA are less sensitive to measurement errors, and TDA generates results most similar to those obtained using conventional flow visualization.



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