Journal of Thoracic Imaging:
Cardiothoracic Magnetic Resonance Flow Imaging
Hope, Michael D. MD*; Sedlic, Tony MD*; Dyverfeldt, Petter PhD*,†,‡
*Department of Radiology, University of California, San Francisco, CA
†Department of Medical and Health Sciences, Division of Cardiovascular Medicine
‡Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
Funded by Radiologic Society of North America Research Scholar Grant 2012-2014.
The authors declare no conflicts of interest.
Reprints: Michael D. Hope, MD, Department of Radiology, University of California, San Francisco, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143-0628 (e-mail: email@example.com).
Multidimensional blood flow imaging with magnetic resonance has rapidly evolved over the last decade. The technique, often referred to as 4-dimensional (4D) flow, can now reliably image the heart and principal vessels of the chest in ≤15 minutes. In addition to dynamic 3D flow visualization, a range of unique quantitative hemodynamic markers can be calculated from 4D flow data. In this review article, we describe some of the more promising of these hemodynamic markers, including pulse wave velocity, pressure, turbulent kinetic energy, wall shear stress, and flow eccentricity. Evaluation of a range of cardiothoracic disorders has been explored with 4D flow, and many applications have been proposed. We also review the potential clinical applications of 4D flow in 4 broad contexts: the aorta, the pulmonary artery, acquired heart disease, and complex congenital heart disease. Promising preliminary results will be highlighted, including the use of abnormal systolic blood flow to risk-stratify patients for progressive valve-related aortic disease, turbulent kinetic energy to directly assess the hemodynamic impact of a stenotic lesion, and altered intracardiac flow to identify early heart failure. We discuss ongoing research efforts in the context of the larger clinical goals of 4D flow: the use of unique hemodynamic markers to (1) identify cardiovascular disease processes early in their course before clinical manifestation so that preemptive treatment can be undertaken; (2) refine the assessment of cardiovascular disease so as to better identify optimal medical or surgical therapies; and (3) enhance the evaluation and monitoring of the hemodynamic impact of different treatment options.
Magnetic resonance imaging (MRI) is routinely used for assessment of the heart and great vessels. Precise anatomic imaging is the goal of most clinical evaluations. However, with recent advances in phase-contrast (PC) MRI, a range of hemodynamic analyses are now possible that better evaluate the fundamental purpose of the cardiovascular system: the effective and efficient pumping of blood to the lungs and the body. Blood flow MRI is now being used clinically to augment traditional anatomic evaluation. The purpose of this review is to introduce advanced flow MRI and discuss its application and potential benefits in cardiothoracic imaging.
Conventional 2-dimensional (2D) cine PC-MRI, also referred to as velocity-encoded cine (VEC) MRI, can be used to measure flow volumes through blood vessels at any location in the body. This technique has several current applications in the chest. Its principal benefit is that it allows reliable flow quantification in disorders that are only qualitatively evaluated by echocardiography. Examples of this quantitative assessment include regurgitant fractions across incompetent valves, intracardiac shunt ratios (ie, Qp/Qs), differential pulmonary blood flow, and coronary sinus flow reserve. Congenital heart disease (CHD) may require a combination of these analyses, as well as other specialized applications for evaluation of complex anatomy and pathology.
3D cine PC-MRI (4D flow) affords several advantages over 2D cine PC-MRI. 4D flow allows volumetric flow imaging in a single acquisition, whereas 2D cine PC-MRI is limited to a prospectively determined imaging plane. Abnormal flow that may not be initially apparent can be analyzed retrospectively from the volumetric data set. Further, complex blood flow patterns can be intuitively visualized as they unfold in multiple dimensions over time. Flow-related parameters, also referred to as hemodynamic markers, can be calculated to provide a fuller understanding of the pathologic role of abnormal flow. Although some of these parameters can be derived from 2D cine PC-MRI, 4D flow allows for comprehensive analysis at any location within the data set. We will discuss a range of hemodynamic markers and their potential applications.
The clinical application of 4D flow is not without challenges. Scan time has long been the major limitation, with scans taking upward of 1 hour. However, an array of new techniques has greatly reduced scan time, with studies now routinely completed in ≤15 minutes. Examples of time-saving techniques include data undersampling in combination with parallel imaging and compressed sensing reconstructions.1,2 Other examples include alternative data acquisition approaches such as radial or spiral trajectories through the k-space.3,4 Novel respiratory gating techniques and advancements in hardware such as high channel count receiver coils can further reduce scan time. Data processing is another significant challenge of 4D flow. Reconstructing data, navigating complex 3D data sets, segmenting anatomic regions of interest, and calculating hemodynamic parameters are currently time-consuming and require specific operator skills. Specialized software is required and is often cumbersome to use. However, perhaps the most significant limitation is the lack of proven clinical applications in which 4D flow outperforms other types of imaging. The identification of such applications can be expected to lead to the development of tailored analysis packages.
4D FLOW MRI
4D flow refers to time-resolved volumetric, 3-directional PC-MRI (Fig. 1). Whereas conventional 2D cine PC-MRI is restricted to a single prospectively chosen plane, 4D flow enables extensive evaluation of time-varying blood flow through a volume of interest. Typical spatial and temporal resolutions are about 1 to 3 mm and 30 to 60 ms, respectively. Hundreds of heartbeats are required for collection of a full 4D flow data set, making real-time or breath-hold acquisitions unfeasible. Instead, data are acquired during free-breathing with the use of respiratory compensating techniques to alleviate motion artifacts.
Only a fraction of the complete data set is acquired during each heartbeat. Data acquisition is synchronized to the cardiac cycle with electrocardiography gating to create a cine series of images. Prospective gating triggered at defined points in the cardiac cycle allows for different segments of k-space to be acquired individually until completely filled. However, prospective gating does not permit acquisition of a complete cardiac cycle, and variability in cardiac cycle length limits the utility of prospective gating during late diastole. Retrospective gating, in contrast, allows for complete coverage of the cardiac cycle and is preferred over prospective gating. Image data and electrocardiography signals are acquired continuously, and a full k-space is retrospectively assembled. In reconstruction, each acquired cardiac cycle is individually stretched to minimize the impact of beat-to-beat variations.
4D Flow MRI Visualization: Vector Plots and Particle Traces
There are various postprocessing methods to visualize multidirectional blood flow data (Fig. 2). Visualization techniques include vector plots or particle trace methods such as streamlines and pathlines.5,6 A vector plot is represented as arrows corresponding to velocity for points within a region of interest in the volumetric data set and is typically color-coded according to speed. Streamlines are lines plotted through a flow field at a single time point–aligned tangent to the instantaneous velocity vectors. It should be noted that streamlines do not represent the actual path of blood flow. Such analysis must be performed with pathlines, which are calculated by integrating the vector field over time to demonstrate virtual particle trajectories. Pathlines have traditionally been colored according to flow speed, but alternative color-coding according to point of origin or departure can intuitively highlight specific flow features.7,8 Other visualization methods include isosurfaces or volume renderings, which are useful for visualizing scalar fields such as pressure, vorticity, and turbulent kinetic energy (TKE).9–11
In addition to visualizing complex cardiovascular flow, 4D flow data can be used to calculate a range of hemodynamic markers (Table 1). The many opportunities for quantitative data analysis may be the principal clinical value of 4D flow. Recent studies have started to explore the clinical utility of these hemodynamic markers in cardiothoracic imaging for early identification of disease and for risk stratification for progression (Table 2). In this section, we will introduce some of the more promising hemodynamic markers.
Flow volume is the most commonly measured hemodynamic variable, used for quantifying aspects such as stroke volume and shunt ratios. The clear advantage of 4D flow is that assessment can be made for any vessel within the volumetric acquisition. In contrast, with conventional 2D cine PC-MRI analysis, a specific vessel needs to be targeted prospectively at the time of imaging. After segmentation of the vessel lumen, the flow rate at a given time point is calculated as the average through-plane velocity multiplied by the cross-sectional area of the vessel. The total volume of flow through a vessel is obtained by integrating the flow rate over time.
Normal flow in the ascending aorta and pulmonary artery exhibits an approximate parabolic velocity profile with the highest velocity in the center of the vessel. Valvular and vascular disease has been shown to skew this velocity profile in many contexts, resulting in eccentric flow with high peripheral velocities (Fig. 3). Quantification of this abnormal eccentric flow may identify patients at risk for pathologic vascular remodeling. One quantitative approach for the ascending aorta is measuring the angle of eccentric blood flow between the left ventricular outflow tract and aortic root.13 A simpler and potentially more robust approach is to measure the displacement of systolic flow relative to the vessel centerline (Fig. 4).14
Pulse Wave Velocity (PWV)
PWV is a measure of the rate of transmission of the systolic pulse through a vessel. It is calculated from the transit time of the systolic impulse wave over a known vascular distance using an ultrasound technique (eg, global carotid-femoral measurement) or MRI. Clear advantages of MRI are that it is not limited by the geometric assumptions of ultrasound and regional analysis is possible.28 4D flow affords some potential advantages, including better estimation of PWV in tortuous anatomy, and has been shown to correlate well with conventional 2D approaches for estimating PWV.15,29
PWV reflects vascular stiffness, which increases with age, and numerous physiological, genetic, and cardiovascular risk factors. It is an independent predictor of mortality and has been shown to have a better predictive value for cardiovascular events compared with Framingham risk factors.30 In addition to this general cardiovascular risk stratification, PWV has been reported to predict progression in specific disease states.31,32
Pressure gradients are commonly used to estimate the severity of obstruction across a narrowed vessel or stenotic valve. Catheter-based measurements are the gold standard but are invasive. Imaging can be used to evaluate pressure by measuring the peak velocity associated with an obstruction and transforming it into an estimate of the peak pressure gradient using the modified Bernoulli equation: pressure gradient (mm Hg)=4×Vmax2 (where Vmax is the maximum peak systolic velocity measured in m/s). This analysis is typically performed with Doppler ultrasound, although MRI does offer advantages in anatomic regions where acoustic windows are limited.
More precise measurement of local pressure differences is now possible with MRI. Using the Navier-Stokes equation, the velocity vector field that 4D flow provides can be used to calculate relative pressure differences and generate 3D pressure maps.16,17 One assumption of this approach is nonturbulent flow, which makes the technique of only limited value for many important obstructive lesions in which turbulence is present, including valvular stenosis and aortic coarctation. Intracardiac flow, however, has minimal turbulence and is thus a promising application for pressure mapping (Fig. 5).
Turbulence refers to chaotic flow with apparently random fluctuations in velocity. It stands in distinct contrast to the ordered, typically laminar flow of the normal cardiovascular system and is seen with many forms of cardiovascular disease. 4D flow has recently been extended to permit estimation of turbulence intensity and TKE.18,33 The technique is based on an MRI signal model that describes how the distribution of velocities within a voxel is related to the overall signal amplitude.34 Validation studies have demonstrated good agreement with reference methods.18,35 Turbulence mapping has potential for a range of applications, including the identification of vascular regions at risk for endothelial cell damage and thrombus formation and estimation of pressure loss in areas of vascular narrowing, valvular stenosis, or regurgitation; it is also used in patients with prosthetic heart valves (Fig. 6).11,33
Wall Shear Stress (WSS)
WSS is the frictional force on the endothelium resulting from flowing blood. It is defined as the product of the dynamic viscosity and the near-wall velocity gradient, or wall shear rate. The near-wall gradients captured by 4D flow have been used to estimate WSS. MRI typically underestimates actual WSS because of limited spatiotemporal resolution, segmentation errors, and partial volume effects.19,36 Therefore, although the absolute MRI measurements of WSS are of limited value, relative measurements may be useful for identifying regions of abnormal hemodynamic stress. For example, a steep near-wall velocity gradient results in a relative increase in WSS in the context of eccentric systolic flow with aortic valve disease.37,38 Areas of abnormal WSS have been shown to predispose to atherosclerosis, plaque rupture, and vascular remodeling.39,40
Flow Connectivity and Distribution
Pathlines have traditionally been used for dynamic flow visualization; however, they are also valuable for quantitative analysis of flow connectivity. As pathlines can be traced both forward and backward in time, they can unveil the point of departure (ie, “where did you come from”) or destination (ie, “where are you going”) for individual virtual blood particles. This can be used to classify various subcomponents of flow within complex regions such as the ventricles or to determine the distribution of flow into branching vessels.7,8,41 Streamlines should not be used for these purposes when there is pulsatile flow, as they reflect the flow field only at a given moment in time.
4D flow can now reliably image the heart and principal vessels of the chest within a reasonable scan time. Evaluation of a range of pathologies has been explored, and many clinical applications have been proposed. Promising preliminary results suggest that 4D flow may play a unique role in better understanding how altered flow interrelates with adverse vascular remodeling and progression of cardiovascular disease. In this section, we will review potential clinical applications of 4D flow in 4 broad contexts: the aorta, the pulmonary artery, acquired heart disease, and complex CHD. Emphasis will be placed on specific applications in which quantitative flow markers have been correlated with key clinical endpoints.
Aortic pathology is typically evaluated with computed tomography (CT) or echocardiography in the acute setting. MRI plays a role in surveillance imaging and can precisely determine aortic dimensions or the extent of aortic dissection without radiation exposure. The current anatomy-based approach to evaluating aortic disease, however, overlooks the considerable role that hemodynamics play in vascular homeostasis. Abnormal aortic flow may not just reflect anatomic alterations but may also have a causative role in disease progression.
Valve-related Aortic Disease
Ascending aortic disease has been linked to aortic valve disease through the long-observed phenomenon of poststenotic dilation. A clear association between aortic and valve disease is recognized with bicuspid aortic valve (BAV), a common congenital abnormality seen in up to 2% of individuals. Aortic dilation is common with BAV, but the causal effect of hemodynamic factors remains unclear, and there is considerable evidence of an underlying connective tissue disorder that contributes.42 Abnormal flow patterns, however, are frequently seen with BAV.38 Whereas echocardiography is widely used for evaluation of BAV, MRI has a unique role in assessing these abnormal flow patterns and their hemodynamic impact on the ascending aorta (Fig. 3).
4D flow reveals characteristic alterations in aortic flow with BAV that are seen even in the absence of aortic aneurysm or stenosis. Helical systolic flow is often seen with peak velocities peripherally and with relatively lower velocities at the vessel center. This flow pattern is associated with eccentric systolic flow jets that result in focal WSS alterations in which aneurysms are known to form with BAV.37,43,44 Different jet orientations have been identified that correlate with the type of valve leaflet fusion.38 These findings contribute to the understanding of valve-related aortic disease and to the broader significance of abnormal flow patterns. They suggest a new risk stratification tool based on 4D flow for identifying patients at risk for development or progression of aortic dilatation and possibly dissection with BAV and aortic valve disease in general.45 Preliminary data show a good correlation between the degree of eccentric systolic flow with BAV and progressive aortic dilation.22
Aortic coarctation refers to a congenital aortic obstruction, typically occurring at the aortic isthmus, distal to the origin of the left subclavian artery. Affected patients need lifelong surveillance imaging because of the high rate of complications, even if the lesion is successfully repaired. MRI has become the imaging modality of choice for aortic coarctation as it offers both anatomic and functional assessment without ionizing radiation. Cross-section area is the best anatomic variable for predicting a significant coarctation. Functional assessment includes estimation of pressure gradients with the modified Bernoulli equation, collateral flow calculation, and assessment of flow versus time profiles in the descending aorta. Collateral flow develops to maintain distal perfusion beyond the coarctation through vessels that bypass the obstruction. Collateral flow is quantified by comparing flow immediately distal to the coarctation to that at the level of the diaphragm. Normal flow should drop over this interval as blood exits through intercostal vessels; however, it will increase if collateral flow is present.46 Flow versus time profiles can also be useful for identifying a significant coarctation. Delayed return of flow to baseline after systole with persistence of flow into diastole is indicative of a hemodynamically significant obstruction.47,48
The utility of 4D flow evaluation in the setting of aortic coarctation has been demonstrated before and after endovascular or surgical repair.49
4D flow correlates very well with conventional 2D cine PC-MRI in assessing collateral flow.21 4D flow also offers information beyond flow quantification. Downstream abnormal flow patterns are seen, including vortical flow in regions of poststenotic dilatation and marked helical flow with angulated aortic arch anatomy, which is associated with exercise-induced hypertension.21,50
Marfan syndrome is an inherited connective tissue disorder. Degeneration of the aortic media places patients at substantially increased risk for aortic dilatation, dissection, and rupture. Diseased segments of the aorta with Marfan syndrome have been shown to be measurably stiffer using PWV estimation. Moreover, PWV can predict progressive aortic dilatation and assess treatment response.31,51,52 Medical treatment typically includes β-adrenergic blockers, which can slow down the rate of aortic dilatation and complications, presumably by reducing the impact of hemodynamic drivers of disease.53 Abnormal flow patterns have been observed in Marfan patients at relatively early stages of disease using 4D flow, but these have yet to be incorporated into a coherent model of disease progression.54 4D flow has a distinct advantage in the evaluation of Marfan patients in terms of being able to measure the local or regional PWV in addition to other regional hemodynamic markers. The detection of focally increased PWV and/or altered systolic flow may identify patients at elevated risk for aortic aneurysm and dissection and also act as a better monitor for treatment response.
Type A aortic dissection is an emergency requiring surgical management. There is little role for MRI or complex flow imaging. However, type B dissection is commonly managed medically with frequent surveillance imaging and variable clinical outcome. At present, aortic size is the main imaging parameter used to guide intervention in patients with type B dissection. Other imaging features may be important as well. For example, partial false lumen thrombosis is associated with poor prognosis. It is thought to restrict outflow from the false lumen and result in higher pressures and consequently increased disease progression.55 Given the implication that hemodynamics are central to disease progression in patients with chronic type B dissection, 4D flow could play a pivotal role in their clinical monitoring. Recently, complex flow features including the degree of helicity within the false lumen have been correlated with interval expansion rates.23 This suggests a clear role for 4D flow in identifying patients at risk for aortic expansion and rupture that may influence the timing of intervention.
Pulmonary hypertension is associated with substantial morbidity and mortality. The diagnosis has traditionally relied on invasive measurement of mean pulmonary arterial pressure. Pulmonary arterial size measurements alone as determined by CT and MRI are unreliable for identifying hypertension, necessitating the use of more advanced imaging approaches. Doppler echocardiography is commonly used; however, 2D cine PC-MRI has been shown to be more comparable to right heart catheterization than echocardiography in estimating pulmonary flow including pulmonary artery stroke volume and systolic pressure.56
The pulmonary artery stiffens with hypertension. This stiffness can be quantified with MRI using a range of measurements including pulsatility and compliance.57 The reduced vascular compliance along with pulmonary artery dilatation contributes to retrograde flow seen with pulmonary hypertension. Although a small amount of retrograde pulmonary flow is normal, it is substantially elevated with pulmonary hypertension and predictably occurs earlier in the cardiac cycle. The timing of retrograde flow can effectively identify pulmonary hypertension and estimate the mean pulmonary arterial pressure.58
4D flow can extend the analysis of pulmonary hypertension beyond vessel stiffness and the timing and extent of regurgitant flow. Abnormal and characteristic complex flow patterns have been demonstrated with pulmonary hypertension. Vortical flow in the main pulmonary artery is strongly correlated with manifest pulmonary hypertension, and the duration of vortical flow correlates with resting mean pulmonary artery pressure (Fig. 7).24 In addition, diastolic flow duration along the anterior main pulmonary artery after pulmonary valve closure has been reported to be significantly longer in manifest relative to latent pulmonary hypertension.24 With visualization and quantification of these flow features, serial 4D flow may be able to monitor patients and detect disease progression in a way not possible with other modalities. This could be useful for guiding medical therapy and assessing treatment response.
Intracardiac blood flow patterns are complex and interrelated with many factors including the cardiac valves, myocardium, thoracic vessels, and 3D chamber geometry. Altered flow patterns can be demonstrated by echocardiography and MRI. However, echocardiography is limited by acoustic windows and to the assessment of flow in a single dimension. 2D cine PC-MRI is limited to the plane of acquisition and does not do justice to 3D flow features. 4D flow affords a clear advantage in this regard and has shown promise for the evaluation of valvular regurgitation and stenosis and different forms of heart failure.
Conventional 2D cine PC-MRI assessment of the cardiac valves is challenging. The valves move considerably during the cardiac cycle, requiring correction for through-plane valve motion. This is particularly true of the mitral and tricuspid valves. Retrospective 3D valve-tracking using a volumetric 4D flow data set can mitigate the effects of this motion. Good accuracy has been demonstrated for mitral and tricuspid flow measurements, and evaluation of all 4 valves can be achieved with a single acquisition.12,25 Another approach for evaluation of valve regurgitation that inherently accounts for valve motion is assessment of the associated flow turbulence. For example, the elevated TKE seen in the left atrium with mitral regurgitation has been shown to be proportional to regurgitant volume.59
Clinical assessment of valve stenosis also relies heavily on hemodynamic assessment. For aortic stenosis, maximum velocity, transvalvular pressure gradient, and continuity equation estimation of the valve area are routinely studied with echocardiography. MRI has proven useful for estimation of the effective orifice area. A jet shear layer detection method using MRI velocity data obviates the need for stroke volume measurements and has been shown to be less variable than other approaches for effective orifice area estimation.60 The pressure loss caused by a stenotic valve is typically estimated using the modified Bernoulli equation and the peak measured poststenotic velocity. MRI compares well with echocardiography in this regard.61 However, the modified Bernoulli equation is designed to estimate the peak pressure gradient rather than the true irreversible pressure loss. Consequently, it often misclassifies the true hemodynamic severity of a stenosis. MRI-measured TKE has been shown to correlate with irreversible pressure loss in aortic stenosis and may represent the most direct means of measuring the true hemodynamic impact of a stenotic lesion.11
Heart failure is a broad term that refers to the condition in which the heart is unable to pump sufficient blood to meet the body’s needs. It is associated with abnormal intracardiac blood flow.26,62,63 Quantitative analysis of intracardiac flow abnormalities can be achieved with 4D flow. Such analysis may help fine-tune the identification and monitoring of these patients and direct efforts to restore efficient flow. For example, the blood that transits the left ventricle or right ventricle can be separated into 4 different functional components (Fig. 8): (1) the direct flow, which enters and exits during a single heartbeat; (2) the retained inflow, which enters but does not exit; (3) the delayed ejection flow, which starts inside and exits on the subsequent heartbeat; and (4) the residual volume that resides in the ventricle for at least 2 cardiac cycles.8,41,64 Investigation of the relative percentages of these flow components, as well as the kinetic energy and momentum of the components, may allow for a refined analysis of the dynamics of ventricular filling and ejection.65
Application of this analysis in patients with compensated heart failure has shown that 4D flow can identify flow differences not seen with conventional hemodynamic assessment. Not only is the direct flow percentage diminished, but also the kinetic energy of the direct flow at end diastole is reduced. As a consequence, an increased workload is placed on the left ventricle to eject the same stroke volume.26 These unique 4D flow markers of inefficient intracardiac flow may add to the early identification and monitoring of cardiac dysfunction. They could also influence pacing strategies or target heart rates in cases in which diastolic-systolic coupling is diminished. Furthermore, analysis of the residual volume including its size and degree of stasis may be helpful in the risk stratification of intrachamber thrombus formation.
Isolated diastolic dysfunction is another promising target for 4D flow. In ischemic disease, diastolic ventricular relaxation is impaired before loss of systolic function. In fact, up to half of the patients with heart failure have normal left ventricular ejection fractions.66 Invasive means of diagnosing diastolic dysfunction are impractical, and echocardiography is limited by the variables discussed above. 2D cine PC-MRI can assess diastolic function by measuring transmitral inflow (including E/A wave peak ratio) and deceleration time, as well as pulmonary vein flow.67
4D flow may extend this analysis by detecting other flow features indicative of diastolic dysfunction. 2D MRI flow studies have demonstrated identification of impairment of the inflow jet before the ventricular apex with diastolic dysfunction.68 Studies with animal models suggest additional flow aberrations with more severe ventricular dysfunction. A combination of pressure field calculation and pathline visualizations has been used to demonstrate disruption of the normal apical pressure gradient and diminished apically directed flow in animals with ventricular infarcts.69 Detecting such flow alterations with 4D flow may help to better identify early ventricular dysfunction.
CHD imaging is challenging because of complex anatomy and physiology. Imaging after surgical repair is even more difficult and requires a level of familiarity with the surgical technique. In this section, we will discuss a few of the more common types of complex CHD for which flow evaluation is useful: single ventricle physiology with Fontan palliation, anomalous pulmonary venous return, and Tetralogy of Fallot (TOF).
Imaging CHD often requires a multimodality approach. Catheter angiography is often required but is invasive and requires iodinated contrast and ionizing radiation. Echocardiography is almost universally used but is restricted to available acoustic windows and has limited quantitative abilities compared with MRI. CT provides excellent anatomic assessment at the expense of radiation but offers limited functional information. MRI is often used for complex cases for its combination of anatomic and functional assessment. Flow quantification with conventional 2D cine PC-MRI typically requires multiple acquisition planes, which can be challenging and time-consuming. 4D flow can comprehensively resolve complex blood flow in a single acquisition, allowing the visualization and retrospective characterization of hemodynamic flow patterns otherwise not possible.70 Capturing all flow data in a single acquisition has been shown to be faster than conventional 2D cine PC-MRI for the measurement of flow volumes in complex heart disease.27 Furthermore, the 3D visualization of cardiac and vascular anatomy and its relationship with thoracic structures may have benefits in surgical planning and follow-up.71
In cases of complex CHD in which only 1 functional ventricle exists, a Fontan palliation is often performed. The single functional ventricle is used to pump systemically, and systemic venous return is shunted directly to the pulmonary arteries through a total cavopulmonary connection. Without the coordinated pumping of the right ventricle to deliver blood to the pulmonary arteries, some very complex flow patterns can develop. 4D flow has proven very useful for visualizing the Fontan circulation. Variable flow patterns are seen and correlate with the specific surgical technique used.7,70,72,73
4D flow offers a comprehensive method for the evaluation and surveillance imaging of patients with Fontan anatomy (Fig. 10). Fontan circulation is dynamic, changing over the life of the patient. Those with suboptimal Fontan hemodynamics demonstrate decreased inferior vena cava and progressively increased superior vena cava flow.74 The major potential of 4D flow may lie in the assessment of differential pulmonary arterial flow. Determination of superior and inferior caval contribution of flow to each pulmonary artery can be achieved by quantitative pathline analysis (Fig. 9).7 Unequal distribution of blood flow is associated with pulmonary arteriovenous malformations in the lung that receives little flow from the inferior vena cava.76 Automated quantification of the caval contribution of flow could augment the postsurgical evaluation of Fontan patients.
Shunts and Anomalous Pulmonary Venous Return
Echocardiography is commonly the first-line investigation for shunts, with PC-MRI being used as an adjunct modality for certain shunts that are difficult to detect by echocardiography and also because of its quantitative abilities. PC-MRI evaluation of flow dynamics commonly involves the calculation of pulmonary to systemic shunt ratios (Qp/Qs). A shunt ratio >1.5 usually requires intervention.
4D flow has been shown to identify intracardiac shunts with accuracy equal to that of echocardiography and better than that of 2D cine PC-MRI.77 Extracardiac shunts can also be identified with sensitivity equal to that of echocardiography.77 4D flow may have a unique role in the evaluation of complex, multilevel shunts. Quantification of each individual component of flow has been described with 4D flow in the setting of anomalous pulmonary venous return and atrial septal defect.78 Total and partial anomalous pulmonary venous return can be identified by MRI with depiction of both anatomic detail and shunt quantification. Compared with conventional MRI, 4D flow allows for anomalous venous distinction from adjacent vessels without contrast and provides characterization of flow patterns and standard anatomic and shunt information.79
TOF is the most common cyanotic congenital cardiac defect. MRI is routinely used for monitoring patients after surgical repair. Analysis includes assessment of right ventricular volumes and function and quantification of pulmonary stenosis and regurgitation. In addition, asymmetric pulmonary flow can be quantified and may prompt endovascular intervention for pulmonary stenoses. 4D flow has been used to characterize abnormal flow patterns throughout the right ventricular outflow tract and pulmonary circulation after surgical repair.80,81 Even in patients without residual pulmonary stenosis after repair, elevated peak systolic velocity and abnormal vortex flow in the main pulmonary artery have been demonstrated.80 Given the previously demonstrated correlation between vortex flow and pulmonary hypertension, the presence of vortex flow in the TOF repair may offer a new risk stratification parameter beyond right ventricular function.
SUMMARY OF FUTURE PROSPECTS
4D flow MRI is a rapidly advancing technique with tremendous clinical potential. New acceleration techniques allow for data acquisition in ≤15 minutes. Complex flow visualization is evolving, with consensus emerging on the best ways to characterize abnormal flow features. A range of quantitative hemodynamic markers can be calculated that extend the diagnostic possibilities of the technique. Focused clinical applications are being explored, with encouraging preliminary results. 4D flow evaluation of intracardiac flow may aid the diagnosis of diastolic dysfunction and early systolic heart failure. Valve-related aortic disease is another area of potential application, with the degree of eccentric systolic flow shown to correlate with progressive aortic dilation in patients with BAV. Larger studies are needed to convincingly demonstrate the unique abilities of 4D flow. One goal is to refine the assessment of cardiovascular disease so as to better identify responders to specific medical or surgical therapies. Another goal is to identify cardiovascular disease processes early in their course so that preemptive treatment can be undertaken.
1. Hsiao A, Lustig M, Alley MT, et al..Rapid pediatric cardiac assessment of flow and ventricular volume with compressed sensing parallel imaging volumetric cine phase-contrast MRI.Am J Roentgenol.2012;198:W250–W259.
2. Knobloch V, Boesiger P, Kozerke S.Sparsity transform k-t principal component analysis for accelerating cine three-dimensional flow measurements.Magn Reson Med.2012(In press). doi: 10.1002/mrm.24431.
3. Sigfridsson A, Petersson S, Carlhall CJ, et al..Four-dimensional flow MRI using spiral acquisition.Magn Reson Med.2012;68:1065–1073.
4. Gu T, Korosec FR, Block WF, et al..PC VIPR: a high-speed 3D phase-contrast method for flow quantification and high-resolution angiography.Am J Neuroradiol.2005;26:743–749.
5. Buonocore MH.Visualizing blood flow patterns using streamlines, arrows, and particle paths.Magn Reson Med.1998;40:210–226.
6. Wigstrom L, Ebbers T, Fyrenius A, et al..Particle trace visualization of intracardiac flow using time-resolved 3D phase contrast MRI.Magn Reson Med.1999;41:793–799.
7. Bächler P, Valverde I, Pinochet N, et al..Caval blood flow distribution in patients with Fontan circulation: quantification by using particle traces from 4D flow MR imaging.Radiology.2013;267:67–75.
8. Eriksson J, Carlhall CJ, Dyverfeldt P, et al..Semi-automatic quantification of 4D left ventricular blood flow.J Cardiovasc Magn Reson.2010;12:9doi: 10.1186/1532-429X-12-9.
9. Toger J, Carlsson M, Soderlind G, et al..Volume tracking: a new method for quantitative assessment and visualization of intracardiac blood flow from three-dimensional, time-resolved, three-component magnetic resonance velocity mapping.BMC Med Imaging.2011;11:10doi: 10.1186/1471-2342-11-10.
10. Heiberg E, Ebbers T, Wigstrom L, et al..Three-dimensional flow characterization using vector pattern matching.IEEE Trans Vis Comput Graph.2003;9:313–319.
11. Dyverfeldt P, Hope MD, Tseng EE, et al..Noninvasive magnetic resonance measurement of turbulent kinetic energy for the estimation of irreversible pressure loss in aortic stenosis.JACC Cardiovasc Imaging.2013;6:64–71.
12. Westenberg JJ, Danilouchkine MG, Doornbos J, et al..Accurate and reproducible mitral valvular blood flow measurement with three-directional velocity-encoded magnetic resonance imaging.J Cardiovasc Magn Reson.2004;6:767–776.
13. den Reijer PM, Sallee D III, van der Velden P, et al..Hemodynamic predictors of aortic dilatation in bicuspid aortic valve by velocity-encoded cardiovascular magnetic resonance.J Cardiovasc Magn Reson.2010;12:4.
14. Sigovan M, Hope MD, Dyverfeldt P, et al..Comparison of four-dimensional flow parameters for quantification of flow eccentricity in the ascending aorta.J Magn Reson Imaging.2011;34:1226–1230.
15. Markl M, Wallis W, Brendecke S, et al..Estimation of global aortic pulse wave velocity by flow-sensitive 4D MRI.Magn Reson Med.2010;63:1575–1582.
16. Tyszka JM, Laidlaw DH, Asa JW, et al..Three-dimensional, time-resolved (4D) relative pressure mapping using magnetic resonance imaging.J Magn Reson Imaging.2000;12:321–329.
17. Ebbers T, Farneback G.Improving computation of cardiovascular relative pressure fields from velocity MRI.J Magn Reson Imaging.2009;30:54–61.
18. Dyverfeldt P, Sigfridsson A, Kvitting JP, et al..Quantification of intravoxel velocity standard deviation and turbulence intensity by generalizing phase-contrast MRI.Magn Reson Med.2006;56:850–858.
19. Stalder AF, Russe MF, Frydrychowicz A, et al..Quantitative 2D and 3D phase contrast MRI: optimized analysis of blood flow and vessel wall parameters.Magn Reson Med.2008;60:1218–1231.
20. Markl M, Draney MT, Miller DC, et al..Time-resolved three-dimensional magnetic resonance velocity mapping of aortic flow in healthy volunteers and patients after valve-sparing aortic root replacement.J Thorac Cardiovasc Surg.2005;130:456–463.
21. Hope MD, Meadows AK, Hope TA, et al..Clinical evaluation of aortic coarctation with 4D flow MR imaging.J Magn Reson Imaging.2010;31:711–718.
22. Hope MD, Wrenn J, Sigovan M, et al..Imaging biomarkers of aortic disease: increased growth rates with eccentric systolic flow.J Am Coll Cardiol.2012;60:356–357.
23. Clough RE, Waltham M, Giese D, et al..A new imaging method for assessment of aortic dissection using four-dimensional phase contrast magnetic resonance imaging.J Vasc Surg.2012;55:914–923.
24. Reiter G, Reiter U, Kovacs G, et al..Magnetic resonance–derived 3-dimensional blood flow patterns in the main pulmonary artery as a marker of pulmonary hypertension and a measure of elevated mean pulmonary arterial pressure/clinical perspective.Circ Cardiovasc Imaging.2008;1:23–30.
25. Roes SD, Hammer S, van der Geest RJ, et al..Flow assessment through four heart valves simultaneously using 3-dimensional 3-directional velocity-encoded magnetic resonance imaging with retrospective valve tracking in healthy volunteers and patients with valvular regurgitation.Invest Radiol.2009;44:669–675.
26. Eriksson J, Bolger AF, Ebbers T, et al..Four-dimensional blood flow-specific markers of LV dysfunction in dilated cardiomyopathy.Eur Heart J Cardiovasc Imaging.2012[Epub ahead of print].
27. Valverde I, Nordmeyer S, Uribe S, et al..Systemic-to-pulmonary collateral flow in patients with palliated univentricular heart physiology: measurement using cardiovascular magnetic resonance 4D velocity acquisition.J Cardiovasc Magn Reson.2012;14:25doi: 10.1186/1532-429X-14-25.
28. Mohiaddin RH, Firmin DN, Longmore DB.Age-related changes of human aortic flow wave velocity measured noninvasively by magnetic resonance imaging.J Appl Physiol.1993;74:492–497.
29. Wentland AL, Wieben O, Francois CJ, et al..Aortic pulse wave velocity measurements with undersampled 4D flow-sensitive MRI: comparison with 2D and algorithm determination.J Magn Reson Imaging.2013;37:853–859.
30. Laurent S, Cockcroft J, Van Bortel L, et al..Expert consensus document on arterial stiffness: methodological issues and clinical applications.Eur Heart J.2006;27:2588–2605.
31. Nollen GJ, Groenink M, Tijssen JG, et al..Aortic stiffness and diameter predict progressive aortic dilatation in patients with Marfan syndrome.Eur Heart J.2004;25:1146–1152.
32. Cavalcante JL, Lima JA, Redheuil A, et al..Aortic stiffness: current understanding and future directions.J Am Coll Cardiol.2011;57:1511–1522.
33. Dyverfeldt P, Kvitting JP, Sigfridsson A, et al..Assessment of fluctuating velocities in disturbed cardiovascular blood flow: in vivo feasibility of generalized phase-contrast MRI.J Magn Reson Imaging.2008;28:655–663.
34. Dyverfeldt P, Sigfridsson A, Knutsson H, et al..A novel MRI framework for the quantification of any moment of arbitrary velocity distributions.Magn Reson Med.2011;65:725–731.
35. Petersson S, Dyverfeldt P, Gardhagen R, et al..Simulation of phase contrast MRI of turbulent flow.Magn Reson Med.2010;64:1039–1046.
36. Petersson S, Dyverfeldt P, Ebbers T.Assessment of the accuracy of MRI wall shear stress estimation using numerical simulations.J Magn Reson Imaging.2012;36:128–138.
37. Hope MD, Hope TA, Crook SE, et al..4D flow CMR in assessment of valve-related ascending aortic disease.J Am Coll Cardiol Cardiovasc Imaging.2011;4:781–787.
38. Hope MD, Hope TA, Meadows AK, et al..Bicuspid aortic valve: four-dimensional MR evaluation of ascending aortic systolic flow patterns.Radiology.2010;255:53–61.
39. Cheng C, Tempel D, van Haperen R, et al..Atherosclerotic lesion size and vulnerability are determined by patterns of fluid shear stress.Circulation.2006;113:2744–2753.
40. Malek AM, Alper SL, Izumo S.Hemodynamic shear stress and its role in atherosclerosis.JAMA.1999;282:2035–2042.
41. Bolger AF, Heiberg E, Karlsson M, et al..Transit of blood flow through the human left ventricle mapped by cardiovascular magnetic resonance.J Cardiovasc Magn Reson.2007;9:741–747.
42. Siu SC, Silversides CK.Bicuspid aortic valve disease.J Am Coll Cardiol.2010;55:2789–2800.
43. Lu MT, Thadani SR, Hope MD.Quantitative assessment of asymmetric aortic dilation with valve-related aortic disease.Acad Radiol.2013;20:10–15.
44. Barker AJ, Markl M, Bürk J, et al..Bicuspid aortic valve is associated with altered wall shear stress in the ascending aorta/clinical perspective.Circ Cardiovasc Imaging.2012;5:457–466.
45. Hope MD, Dyverfeldt P, Acevedo-Bolton G, et al..Post-stenotic dilation: evaluation of ascending aortic dilation with 4D flow MR imaging.Int J Cardiol.2012;156:e40–e42.
46. Steffens JC, Bourne MW, Sakuma H, et al..Quantification of collateral blood flow in coarctation of the aorta by velocity encoded cine magnetic resonance imaging.Circulation.1994;90:937–943.
47. Muzzarelli S, Ordovas KG, Hope MD, et al..Diagnostic value of the flow profile in the distal descending aorta by phase-contrast magnetic resonance for predicting severe coarctation of the aorta.J Magn Reson Imaging.2011;33:1440–1446.
48. Muzzarelli S, Meadows AK, Ordovas KG, et al..Prediction of hemodynamic severity of coarctation by magnetic resonance imaging.Am J Cardiol.2011;108:1335–1340.
49. Frydrychowicz A, Markl M, Hirtler D, et al..Aortic hemodynamics in patients with and without repair of aortic coarctation: in vivo analysis by 4D flow-sensitive magnetic resonance imaging.Invest Radiol.2011;46:317–325.
50. Ou P, Mousseaux E, Celermajer DS, et al..Aortic arch shape deformation after coarctation surgery: effect on blood pressure response.J Thorac Cardiovasc Surg.2006;132:1105–1111.
51. Ahimastos AA, Aggarwal A, D’Orsa KM, et al..Effect of perindopril on large artery stiffness and aortic root diameter in patients with Marfan syndrome: a randomized controlled trial.JAMA.2007;298:1539–1547.
52. Groenink M, de Roos A, Mulder BJ, et al..Changes in aortic distensibility and pulse wave velocity assessed with magnetic resonance imaging following beta-blocker therapy in the Marfan syndrome.Am J Cardiol.1998;82:203–208.
53. Shores J, Berger KR, Murphy EA, et al..Progression of aortic dilatation and the benefit of long-term beta-adrenergic blockade in Marfan’s syndrome.N Engl J Med.1994;330:1335–1341.
54. Geiger J, Markl M, Herzer L, et al..Aortic flow patterns in patients with Marfan syndrome assessed by flow-sensitive four-dimensional MRI.J Magn Reson Imaging.2012;35:594–600.
55. Tsai TT, Evangelista A, Nienaber CA, et al..Partial thrombosis of the false lumen in patients with acute type B aortic dissection.N Engl J Med.2007;357:349–359.
56. Nogami M, Ohno Y, Koyama H, et al..Utility of phase contrast MR imaging for assessment of pulmonary flow and pressure estimation in patients with pulmonary hypertension: comparison with right heart catheterization and echocardiography.J Magn Reson Imaging.2009;30:973–980.
57. Sanz J, Kariisa M, Dellegrottaglie S, et al..Evaluation of pulmonary artery stiffness in pulmonary hypertension with cardiac magnetic resonance.J Am Coll Cardiol Cardiovasc Imaging.2009;2:286–295.
58. Helderman F, Mauritz GJ, Andringa KE, et al..Early onset of retrograde flow in the main pulmonary artery is a characteristic of pulmonary arterial hypertension.J Magn Reson Imaging.2011;33:1362–1368.
59. Dyverfeldt P, Kvitting JP, Carlhall CJ, et al..Hemodynamic aspects of mitral regurgitation assessed by generalized phase-contrast MRI.J Magn Reson Imaging.2011;33:582–588.
60. Garcia J, Marrufo OR, Rodriguez AO, et al..Cardiovascular magnetic resonance evaluation of aortic stenosis severity using single plane measurement of effective orifice area.J Cardiovasc Magn Reson.2012;14:23doi: 10.1186/1532-429X-14-23.
61. Kilner PJ, Manzara CC, Mohiaddin RH, et al..Magnetic resonance jet velocity mapping in mitral and aortic valve stenosis.Circulation.1993;87:1239–1248.
62. Hong G-R, Pedrizzetti G, Tonti G, et al..Characterization and quantification of vortex flow in the human left ventricle by contrast echocardiography using vector particle image velocimetry.J Am Coll Cardiol Cardiovasc Imaging.2008;1:705–717.
63. Carlhall CJ, Bolger A.Passing strange: flow in the failing ventricle.Circ Heart Fail.2010;3:326–331.
64. Fredriksson AG, Zajac J, Eriksson J, et al..4-D blood flow in the human right ventricle.Am J Physiol Heart Circ Physiol.2011;301:H2344–H2350.
65. Eriksson J, Dyverfeldt P, Engvall J, et al..Quantification of presystolic blood flow organization and energetics in the human left ventricle.Am J Physiol Heart Circ Physiol.2011;300:H2135–H2141.
66. Moller JE, Pellikka PA, Hillis GS, et al..Prognostic importance of diastolic function and filling pressure in patients with acute myocardial infarction.Circulation.2006;114:438–444.
67. Westenberg JJ.CMR for assessment of diastolic function.Curr Cardiovasc Imaging Rep.2011;4:149–158.
68. Kumar R, Charonko J, Hundley WG, et al..Assessment of left ventricular diastolic function using 4-dimensional phase-contrast cardiac magnetic resonance.J Comput Assist Tomogr.2011;35:108–112.
69. Zhang Z, Friedman D, Dione DP, et al..Assessment of left ventricular 2D flow pathlines during early diastole using spatial modulation of magnetization with polarity alternating velocity encoding: a study in normal volunteers and canine animals with myocardial infarction.Magn Reson Med.2012[Epub ahead of print]. doi: 10.1002/mrm.24517.
70. Markl M, Geiger J, Kilner PJ, et al..Time-resolved three-dimensional magnetic resonance velocity mapping of cardiovascular flow paths in volunteers and patients with Fontan circulation.Eur J Cardiothorac Surg.2011;39:206–212.
71. Floemer F, Ulmer HE, Brockmeier K.Images in congenital heart disease. Use of 3D volume rendered magnetic resonance angiography to demonstrate a cervical aortic arch.Cardiol Young.2000;10:423–424.
72. Sundareswaran KS, Haggerty CM, de Zelicourt D, et al..Visualization of flow structures in Fontan patients using 3-dimensional phase contrast magnetic resonance imaging.J Thorac Cardiovasc Surg.2012;143:1108–1116.
73. Markl M, Geiger J, Stiller B, et al..Impaired continuity of flow in congenital heart disease with single ventricle physiology.Interact Cardiovasc Thorac Surg.2011;12:87–90.
74. Ovroutski S, Nordmeyer S, Miera O, et al..Caval flow reflects Fontan hemodynamics: quantification by magnetic resonance imaging.Clin Res Cardiol.2012;101:133–138.
75. Bächler P, et al..Quantification of caval flow contribution to the lungs in vivo after total cavopulmonary connection with 4-dimensional flow magnetic resonance imaging.J Thorac Cardiovasc Surg.2012;143:742–743.
76. Srivastava D, Preminger T, Lock JE, et al..Hepatic venous blood and the development of pulmonary arteriovenous malformations in congenital heart disease.Circulation.1995;92:1217–1222.
77. Hsiao A, Lustig M, Alley MT, et al..Evaluation of valvular insufficiency and shunts with parallel-imaging compressed-sensing 4D Phase-contrast MR imaging with stereoscopic 3D velocity-fusion volume-rendered visualization.Radiology.2012;265:87–95.
78. Valverde I, Simpson J, Schaeffter T, et al..4D phase-contrast flow cardiovascular magnetic resonance: comprehensive quantification and visualization of flow dynamics in atrial septal defect and partial anomalous pulmonary venous return.Pediatr Cardiol.2010;31:1244–1248.
79. Nordmeyer S, Riesenkampff E, Crelier G, et al..Flow-sensitive four-dimensional cine magnetic resonance imaging for offline blood flow quantification in multiple vessels: a validation study.J Magn Reson Imaging.2010;32:677–683.
80. Geiger J, Markl M, Jung B, et al..4D-MR flow analysis in patients after repair for tetralogy of Fallot.Eur Radiol.2011;21:1651–1657.
81. Francois CJ, Srinivasan S, Schiebler ML, et al..4D cardiovascular magnetic resonance velocity mapping of alterations of right heart flow patterns and main pulmonary artery hemodynamics in tetralogy of Fallot.J Cardiovasc Magn Reson.2012;14:16doi: 10.1186/1532-429X-14-16.
flow imaging; 4-dimensional flow; hemodynamics; aorta; heart failure
© 2013 by Lippincott Williams & Wilkins
What does "Remember me" mean?
By checking this box, you'll stay logged in until you logout. You'll get easier access to your articles, collections,
media, and all your other content, even if you close your browser or shut down your
To protect your most sensitive data and activities (like changing your password),
we'll ask you to re-enter your password when you access these services.
What if I'm on a computer that I share with others?
If you're using a public computer or you share this computer with others, we recommend
that you uncheck the "Remember me" box.
Highlight selected keywords in the article text.
Data is temporarily unavailable. Please try again soon.
Readers Of this Article Also Read