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Ha, Huh, Yang, and Kim: Quantification of Hemodynamic Parameters Using Four-Dimensional Flow MRI
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Journal of the Korean Society of Radiology 2019; 80(2): 239-258.

Published online: 31 March 2019

DOI: https://doi.org/10.3348/jksr.2019.80.2.239

Quantification of Hemodynamic Parameters Using Four-Dimensional Flow MRI

Hojin Ha, PhD1, Hyungkyu Huh, PhD2, Dong Hyun Yang, MD3, Namkug Kim, PhD3, 4

1Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, Korea.

2Medical Device Development Center, Daegu-Gyungbuk Medical Innovation Foundation, Daegu, Korea.

3Department of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.

4Department of Convergence Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.

Corresponding author: Hojin Ha, PhD. Department of Mechanical and Biomedical Engineering, Kangwon National University, 1 Gangwondaehak-gil, Chuncheon 24341, Korea. Tel 82-33-250-6310, Fax 82-33-279-2169, hojinha@kangwon.ac.kr

Received 23 January 2019       Revised 6 March 2019       Accepted 18 March 2019

Copyrights © 2019 The Korean Society of Radiology

The Korean Society of Radiology

(open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

MRI provides non-invasive and non-ionizing methods for the accurate anatomic depiction of the cardiovascular system. Based on the inherent flow sensitivity, MRI can be used to investigate hemodynamic features in patients with anatomical data within a single measurement. In particular, time-resolved and three-dimensional (3D) characterization of blood flow using 4D flow MRI has achieved considerable progress in recent years. The present article reviews the principle and procedures of 4D Flow MRI. Various fluid dynamic biomarkers for possible clinical usage are also described, including wall shear stress, turbulent kinetic energy, and relative pressure. Finally, this article provides an overview of the clinical applications of 4D Flow MRI in various cardiovascular regions.

Keywords: Magnetic Resonance Imaging, Heart, Blood, Hemodynamics

Figures and Tables

Fig. 1

Principles of 4D Flow MRI.

4D = four-dimensional
Adapted from Ha et al. Korean J Radiol 2016;17:445-462, with premission of The Korean Society of Radiology (10).
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Fig. 2

Velocity visualization and quantification of the flow rate.

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Fig. 3

WSS estimation using four-dimensional phase contrast-MRI.

WSS = wall shear stress
Adapted from Ha et al. Korean J Radiol 2016;17:445-462, with permission of The Korean Society of Radiology (10).
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Fig. 4

Principle of TKE estimation.

IVSD = intravoxel velocity standard deviation, TKE = turbulent kinetic energy
Adapted from Ha et al. Korean J Radiol 2016;17:445-462, with permission of The Korean Society of Radiology (10).
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Fig. 5

Procedures for the estimation of the relative pressure field. Adapted from Ha et al. Korean J Radiol 2016;17:445-462, with permission of The Korean Society of Radiology (10).

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Fig. 6

Streamline visualization of the aortic flow. Visualization of the aortic flow in a normal subject (A), patient with aortic stenosis (B), and patient with aortic regurgitation and aortic root dilatation at systole (C) and diastole (D). Note that aortic flow in aortic stenosis causes helical flow patterns; aortic flow in aortic dilatation causes impinging flow pattern during systole, and a substantial amount of regurgitation flow is observed. Adapted from Ha et al. Korean J Radiol 2016;17:445-462, with permission of The Korean Society of Radiology (10).

jksr-80-239-g006
Fig. 7

Streamline visualization of a normal control and a patient. Comparison of patients with (A) normal and (B) replaced tissue-valve. Note that only the aortic blood flow with the replaced tissue-valve generates complex helical blood flow.

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Fig. 8

Flow visualization of stenotic flow. Visualization of flow velocity (A) and TKE (B) in a patient with severe aortic stenosis.

TKE = turbulent kinetic energy
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Fig. 9

Visualization of vertical flow in an aortic sinus.

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Table 1

Summary of Hemodynamic Parameters and Their Clinical Applications

jksr-80-239-i001
Parameter Definition Physiological Implication Application in Previous Studies Notes
Flow velocity & flow rate Amount of blood transported Abnormal increase or decrease in blood flow indicates possible ischemia or local contraction of vessel 1. WSS increase in patients with BAV Sufficient spatial and temporal resolutions are required
2. Low & oscillatory WSS in carotid artery
3. WSS increase in intracranial aneurysms
WSS Frictional shearing force on vessel Abnormal alteration of flow pattern near vessel wall influences vascular dysfunction 1. WSS increase in patients with BAV WSS can be influenced by spatial resolution
2. Low & oscillatory WSS in carotid artery
3. WSS increase in intracranial aneurysms
Vortex Rotational structure of blood flow Abnormal appearance of vortical flow indicates abnormal alteration of flow pattern 1. Development of vortex flow atpulmonary hypertension Vortex identification can be highly influenced by noise Vortex identification can be highly influenced by noise
TKE Turbulent kinetic energy Increased TKE indicates more energy loss of blood flow 1. Increased TKE at aortic stenosis More than two acquisitions are required
2. Increased TKE at cardiomyopathy
Relative pressure Pressure gradient from arbitrary reference Increased pressure drop indicates decreased blood flow or increased work load of heart 1. Pressure gradient through stenosisin aorta and carotid, iliac, and renal arteries Influence of turbulence on pressure field cannot be included
2. Pressure distribution at intracardiac plaque

BAV = bicuspid aortic valve, TKE = turbulent kinetic energy, WSS = wall shear stress

Adapted from Ha et al. Korean J Radiol 2016;17:445-462, with permission of The Korean Society of Radiology (10).

Acknowledgments

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (2018R1D1A1A02043249).

Notes

Conflicts of Interest The authors have no potential conflicts of interest to disclose.

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