Magnus Ziegler1, Martin Welander2, Jonas Lantz3, Marcus Lindenberger4, Niclas Bjarnegård5, Matts Karlsson6, Tino Ebbers3, Toste Länne2, Petter Dyverfeldt3. 1. Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. Electronic address: magnus.ziegler@liu.se. 2. Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; Department of Thoracic and Vascular Surgery, Linköping University, Linköping, Sweden. 3. Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. 4. Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden; Department of Cardiology, Linköping University, Linköping, Sweden. 5. Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden. 6. Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; Division of Applied Thermodynamics and Fluid Mechanics, Department of Management and Engineering, Linköping University, Linköping, Sweden.
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.
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.
Authors: Thekla H Oechtering; Grant S Roberts; Nikolaos Panagiotopoulos; Oliver Wieben; Alejandro Roldán-Alzate; Scott B Reeder Journal: Abdom Radiol (NY) Date: 2021-11-27