Clinical Applications of Aortic 4D Flow Imaging

CARDIAC MAGNETIC RESONANCE (E NAGEL, SECTION EDITOR)

Clinical Applications of Aortic 4D Flow Imaging

Michael D. Hope & S. Jarrett Wrenn &

Petter Dyverfeldt

Published online: 17 January 2013# Springer Science+Business Media New York 2013

Abstract Quantitative aortic magnetic resonance (MR)blood flow imaging is a rapidly advancing technique thatis likely to impact clinical medicine in the near future. Theacquisition of comprehensive 4D velocity datasets is nowpossible in a clinically acceptable time frame. Unique andintuitive visualization methods are available. A number ofimportant hemodynamic biomarkers can be derived fromthe data, and exploited to help understand how abnormalflow is inter-related with aortic pathology. Initial data sug-gest that some of the derived biomarkers can refine theclinical assessment of aortic disease and predict diseaseprogression. We provide an overview of aortic imaging withemphasis on how flow imaging is currently used, discuss thefundamental technical aspects of multidimensional MR flowimaging, introduce key hemodynamic markers, and showhow this type of imaging may soon be used for the earlyidentification of patients at risk for the development ofpotentially devastating aortic complications.

Keywords Aorta . Magnetic resonance imaging . Phasecontrast MRI . Velocity-encodedMRI . 4D flow . Flowmeasurement . Eccentric flow . Hemodynamic imaging .

Biomarkers . Aneurysm . Aortic stenosis . Bicuspid aorticvalve . Aortic coarctation . Pulse wave velocity .

Turbulence . Pressure loss .Wall shear stress

Introduction

Imaging of the aorta is crucial for the diagnosis and man-agement of life-threatening diseases such as aneurysm anddissection. Magnetic resonance imaging (MRI) of bloodflow offers unique and valuable insights that complementconventional anatomic evaluation. This type of flow imag-ing has rapidly evolved in recent years. Here we reviewcurrent techniques and applications of quantitative MR aor-tic flow imaging, the hemodynamic biomarkers they cangenerate, and future prospects for the field.

As the largest artery in the body, the aorta experiencesextreme hemodynamic forces over each cardiac cycle, re-peatedly receiving and distributing the left ventricular sys-tolic impulse. Visualization of aortic blood flow (Fig. 1) andmeasurement of associated hemodynamic parameters arenow possible with advances in MRI scanner hardware, pulsesequences, and post-processing tools. These capabilities arestarting to be used clinically to better understand vascularhomeostasis and aortic disease states.

Overview of Aortic Imaging

Aortic aneurysms are common, accounting for over 13,000deaths yearly in the United States [1]. With the increasinguse of cross-sectional imaging, the number of patients diag-nosed with aortic aneurysm is increasing. Abdominal aorticaneurysms (AAA) are more common than thoracic aorticaneurysms. Risk factors for AAA include advanced age,smoking, hypertension, atherosclerosis, and male gender;in fact, they are found in up to 5 % of men over the age of65 [2]. Thoracic aortic aneurysms are more heterogeneousthan AAAs in patient demographics, etiologies, and diseaseprogression [3]. In both cases, patients are followed withserial imaging and risk-stratified by aortic dimensions.

Electronic supplementary material The online version of this article(doi:10.1007/s12410-012-9187-8) contains supplementary material,which is available to authorized users.

M. D. Hope (*) : S. J. Wrenn : P. DyverfeldtDepartment of Radiology, University of California,San Francisco, 505 Parnassus Avenue, Box 0628,San Francisco, CA 94143-0628, USAe-mail: [email protected]

Curr Cardiovasc Imaging Rep (2013) 6:128–139DOI 10.1007/s12410-012-9187-8

http://dx.doi.org/10.1007/s12410-012-9187-8

The guidelines that dictate management of these patientsare based upon the strategy of surveillance imaging withelective intervention when a threshold dimension or growthrate is observed [3, 4]. This threshold is met when the risk ofleaving an aneurysm untreated (ie, the risk of dissection andrupture) equals the risk of intervention. In the ascendingaorta, for example, a diameter of 5.5 cm or a growth rateof 0.5 cm/year prompts intervention in a typical patient.Unfortunately, significant aortic disease specific morbidityand mortality are seen in patients who do not meet theseanatomic thresholds [5–9], illustrating that vessel dimen-sions alone do not capture the complexity of aortic diseaseprogression.

Two important considerations that play a role in aorticdisease progression are overlooked with a purely anatomy-based approach to aortic surveillance: (1) the structuralintegrity of the aortic wall, and (2) aortic hemodynamics.The former relates to inflammatory states, the expression ofextracellular matrix proteins, and other processes, many ofwhich can now be imaged using molecular strategies [10,11]. Hemodynamics are known to play an important role invascular disease pathogenesis and progression. For exam-ple, vessel stenoses are linked to downstream post-stenoticaneurysmal dilation, low wall shear stress promotes thedevelopment of atherosclerosis, and flow-stagnation hasbeen linked to intraluminal thrombus formation [6, 12–15].

Fig. 1 Systolic aortic bloodflow in a young man with abicuspid aortic valve and aorticcoarctation. Magnitude data a,in an oblique-sagittal orienta-tion demonstrates the coarcta-tion (arrow) and mild dilationof the ascending aorta (openarrow). Peak systolic flow isvisualized with short stream-lines generated throughout theaorta (red) and pulmonary ar-tery (blue) b. Focused flowevaluation of the thoracic aortain the same orientation (c) andin an oblique-coronal orienta-tion d, reveals eccentric veloci-ty distributions in both theascending aorta and about thecoarctation

Curr Cardiovasc Imaging Rep (2013) 6:128–139 129

Quantitative assessment of these parameters using MR flowimaging is now possible, and will provide valuable insightinto aortic disease in both research and clinical settings.

Current Clinical Flow Imaging Applications

MR blood flow imaging is routinely employed in a fewclinical scenarios. Typically, 2-dimensional (2D) cinephase-contrast (PC) MRI is used. Measurements are madewithin a plane that is prescribed according to the vessel orvalve of interest. Through-plane analysis allows for accurateflow volume quantification, but may miss peak velocitiesthat are better interrogated with analysis in the plane of avessel, or with 3-dimensional (3D) approaches. MR bloodflow imaging is commonly applied in the evaluation ofvalvular stenoses and regurgitation, cardiac output, shuntquantification, vessel stenoses, and coronary flow reserve.Here we will briefly discuss aortic valve disease and aorticcoarctation to illustrate how flow imaging is currently usedin the clinical evaluation of patients.

Aortic Valve Disease

Initial evaluation of aortic valve disease typically involvesechocardiography. MRI does offers some distinct advantagehowever, and is well accepted [16]. While MRI-derivedassessment of aortic stenosis can sometimes be limited dueto underestimation of peak velocities, the quantification ofregurgitation is accurate and not as prone to technical vari-ability as echocardiography [17]. In addition, quantitativeand reproducible measures of left ventricular size, functionand mass are obtained with MRI.

Aortic Regurgitation

Aortic regurgitation is evaluated with 2D cine PC-MRI byprescribing a plane perpendicular to the aorta in the tubularascending portion of the vessel. At multiple time pointsduring the cardiac cycle, the vessel lumen area is defined,and the measured flow through the segmented area yieldsflow volumes. The ratio of backward to forward flow is theregurgitant fraction.

Aortic Stenosis

Maximum velocity, transvalvular pressure gradient, andvalve area are routinely used for clinical evaluation of aorticstenosis. MRI permits estimation of both the anatomical andeffective orifice area (EOA), and has been shown to be lessvariable than other approaches for EOA estimation [18, 19].Estimation of the aortic valve gradient with stenosis usingMRI is performed with the modified Bernoulli equation in a

similar fashion to that employed in Doppler echocardiogra-phy, with good correlation reported [20]. The approachdiffers from flow quantification in that planes can be pre-scribed either parallel or perpendicular to the vessel in orderto identify maximal velocities. If the maximal flow veloci-ties in the vena contracta are not present in the interrogatedplanes, an underestimation of the degree of stenosis results.3D imaging techniques can avoid this problem. It shouldalso be noted that the limited temporal resolution of MRIcompared with echocardiography can also lead to underes-timation of pressure gradients.

Aortic Coarctation

Aortic coarctation refers to aortic narrowing at or near theligamentum arteriosum that restricts flow. MRI has becomethe imaging modality of choice for anatomic and hemody-namic interrogation of coarctation [21–23]. Anatomy isdelineated via high-resolution contrast-enhanced 3D-MRangiography (MRA). Hemodynamics are assessed withMR blood flow imaging. This evaluation includes (1) esti-mation of the degree of vessel stenosis, (2) quantification ofcollateral flow, and (3) assessment of dynamic flow profilesin the descending aorta. The degree of stenosis is assessed ina fashion similar to that used for aortic valve stenosis, wherepressure gradients are derived from peak velocities, andsuffers from the same limitations.

Collateral arterial flow develops as a means of bypassingthe hemodynamically significant aortic narrowing.Typically flow is measured at planes perpendicular to theaorta just beyond the coarctation and at the diaphragm.Normal flow drops over this interval [24]. However, withcollateral flow, the diaphragmatic flow is higher than thatnear the coarctation. The percentage increase can provide aquantitative measure of collateral flow [24, 25].

The hemodynamic significance of aortic coarctation isalso reflected in the flow profile of the descending aorta[21]. With significant coarctation, a slow systolic upstrokeand delayed return to baseline is seen, leading to diastolicflow persistence. This can be assessed with MR flow imag-ing in the descending aorta, including at the level of thediaphragm, where turbulence, aliasing, and stent-relatedartifact are noncontributory [26].

4D Flow

Multidimensional MR flow imaging permits the assessmentof cardiovascular hemodynamics well beyond the measure-ment of velocities through a 2D plane. It is a rapidly grow-ing field of research with a more than 10-fold increase inpublications in the last 5 years. Such attention stems fromthe numerous advantages the technique offers over 2D

130 Curr Cardiovasc Imaging Rep (2013) 6:128–139

methods: the capture of volumetric velocity data, completecoverage of the cardiovascular structures of interest, noconfinement to prospectively prescribed imaging planes,continuous breathing, and unique visualization and quanti-fication strategies.

Multidimensional MR flow imaging terminology can beconfusing. Here we will concentrate on 3D, time-resolved(cine), 3-directional PC-MRI, which is referred to as 4DFlow. The 4D component refers to 3D plus time, while“Flow” refers to the flow field information resulting from3-directional PC-MRI (Fig. 2).

Data Acquisition and Reconstruction

4D Flow acquisitions are synchronized to the cardiac cycleto obtain a cine series of images. The acquisition of acomplete data set requires many cardiac cycles (eg, 750heart beats); the reconstructed cardiac cycle thus representsan average of those cycles. The measurement of 3-directional velocities is achieved by applying motion-sensitivity in multiple directions (Fig. 2) [27]. Without ac-celeration of data acquisition, aortic 4D Flow scan time isabout an hour. However, many advances have been made toreduce scan time, with a typical Cartesian data acquisitionnow requiring 10 to 20 minutes. Data acquisition is typicallyperformed using an oblique-sagittal slab to encompass theentire thoracic aorta with spatial resolution in the 2–3 mm

range (Table 1). Further scan time reductions and improvedspatiotemporal resolution can be expected in the near future[28••, 29••, 30, 31•].

Flow Visualization

4D Flow imaging allows for unique and appealing visuali-zation of blood flow. Important abnormal flow character-istics may be revealed (Fig. 3, Movies 1 and 2) [32]. Vectorplots or particle trace methods including streamlines andpathlines can be used to visualize flow data [33]. Vectorplots allow for direct visualization of velocity fields.Streamlines represent instantaneous tangents to velocityvectors at a given time, and can reveal 3D flow patternssuch as vortices. Pathlines are calculated by integrating thevector field over time and represent actual trajectories thatparticles might take through the flow field. These visualiza-tion strategies offer a screening method for both data qualityand irregular flow patterns. However, visualization can betime-consuming and often requires considerable user-interaction. Automated approaches to standardize flow vi-sualization are needed.

Several new lines of investigation have resulted fromrecognizing global alterations in flow based on visualiza-tions: previously unsuspected pathways for arterial emboli[34•]; blood flow compartmentalization in the left ventricle[35]; altered hemodynamics in ascending aortic aneurysms

Fig. 2 Acquisition and reconstruction of aortic 4D Flow data. A 3Dimaging volume in a sagittal-oblique orientation covers the thoracicaorta a. Respiratory motion artifacts are suppressed by triggering dataacquisition only for cardiac cycles that occur during end expiration b.Data acquisition is synchronized to the cardiac cycle by ECG gating tocreate a cine series of images b. After Fourier transformation, 4complex-valued flow-encoding (FE) segments are obtained c. Onereference FEs acquired with zero first-gradient moment (FE0) and 3

FEs with motion-encoding in 3 perpendicular directions. The averageamplitude of the FEs provides a magnitude image used for anatomy d.Phase subtraction between the reference and motion-encoded segmentsprovides 3-directional velocity information. The intravoxel velocitystandard deviation (IVSD, σ) in 3 directions is obtained from theamplitude of the complex-valued FEs. Flow visualization and deriva-tion of hemodynamic biomarkers can be achieved by processing of thevelocity and IVSD data e


Table 1 Key aortic 4D flow imaging parameters

Parameter Typical Setting Comment

Orientation Sagittal-oblique In plane of aorta, or “candy-cane” view.

3D field-of-view (FOV, mm3) 320×320×70 Coverage in the readout, phase, and slice encoding directions.Adjusted to encompass the aorta.

3D matrix size, Nx × Ny × Nz 128×128×30 Number of frequency, phase, and slice encoding steps.

Velocity encoding range (VENC, cm/s) 150–300 Defines maximum measurable velocity. Velocities thatexceed the VENC are aliased.

Spatial resolution (mm3) 2.5×2.5×2.5 Size of the image voxels.

K-space segmentation (Nk) 2–3 k-space lines acquired per cardiac cycle. Enables a trade-offbetween temporal resolution and scan time.

Temporal resolution (ms) 35–45 (4 × TR) / Nk, where 4 is the number of encodings needed forphase reference (1) + 3-directional velocity encoding (3).

Respiratory efficiency, Reff 60 %–80 % Highly dependent on patient breathing.

parallel imaging acceleration factor 2 Degree of data undersampling. Non-acquired data is recoveredwith parallel imaging reconstruction methods.

Total scan time (min) 11–24 (HR 75 bpm) (Ny × Nz) / (Nk × Rnet × Reff × HR)

Fig. 3 4D flow visualization.a, Sagittal MRA image from ayoung female with bicuspidaortic valve and aorticcoarctation (open arrow).White bar denotes the levelthrough which cross-sectionswere obtained in panels b and c.b, Systolic velocity vector fieldthrough a cross-section of theascending aorta, illustrating aneccentric distribution of veloci-ties. c, Short streamlines at thesame level. d, Systolic stream-lines generated from a 3D gridthat spans the thoracic aortashow a helical systolic velocityfield pattern in the ascendingaorta (modified color scheme,see legend). See Movies 1 and 2for visualization of blood flowwith pathlines.


[36]; entry tears and resulting helical flow in chronic aorticdissection [37••]; and the relationship between eccentricflow and valve-related aortic disease [14, 38•].

Data Fidelity

Acquired 4D Flow data is representative of a specific heartrate, subject position (typically supine), and respiratory phase(typically end expiration). Flow visualization and derivedhemodynamic information should be interpreted in that phys-iologic context. The level of accuracy required of 4D Flow isapplication specific. Likewise, optimal approaches for dataprocessing and correction of known artifacts depend on theapplication in question [39•].

Validation of 4D Flow methods relies on in vitro, insilico, and animal model systems, as non-invasive methodsfor obtaining comprehensive hemodynamic parameters arelimited [40, 41]. However, due to long scan times (duringwhich subject position might change) and the fact that thereis not a standard way to correct for known artifacts, evenwell-validated 4D Flow protocols can produce low qualitydata sets. Identifying such data sets is often not trivial orstraightforward. We advocate the implementation of stan-dardized approaches to data quality control. This can beachieved by evaluation of the internal consistency of 4DFlow data. For example, pulmonary artery flow (Qp) andaortic flow (Qs) should be similar in non-shunt systems, andcan be easily extracted from the datasets and serve as acontrol for data quality. Pathline visualization can also beuseful for data validation. As pathlines are integrated overtime, they accumulate error and thus poor quality data canresult in pathlines extending beyond the vessel confines.Conservation-of-mass principles can be applied to pathlinesthrough a specified region of interest as a robust and inclu-sive method of validation [42•].

Quantitative Hemodynamic Markers

Comprehensive flow data can be used to calculate a numberof quantitative parameters referred to as hemodynamicmarkers. Although several can also be obtained from tradi-tional 2D cine PC-MRI data, all can be generated from asingle dataset with 4D Flow. We believe that the true clinicalvalue of aortic 4D Flow is likely to stem from the prognosticvalue of these markers for refined evaluation of aortic dis-ease and prediction of disease progression, rather than fromflow visualization.

Flow

In current clinical practice, flow is the most commonlymeasured hemodynamic parameter. As described above, this

is typically done with 2D cine PC-MRI through prescribedplanes. However, the 3D datasets obtained with 4D Flowprovide a unique advantage for these measurements becauseflow can be retrospectively calculated at any location in theimaging volume. This can be particularly useful in cases ofcongenital heart disease when flow measurement throughmultiple vessels is needed. Prescribing multiple imagingplanes while the patient is in the scanner is challengingand time consuming. An additional advantage of volumetriccoverage is the possibility of performing retrospective track-ing of heart valves to account for their motion during thecardiac cycle. This has been reported to enable accuratequantification of net flow volume through all heart valves[43]. Good correlation between 2D cine PC-MRI and 4DFlow has been demonstrated for aortic coarctation, correctedcomplex congenital heart disease and in the setting of type Baortic dissection [37••, 44••, 45••].

Fig. 4 Visualization of turbulence intensity with aortic stenosis. Sys-tolic flow in the ascending aorta (AA) and descending aorta (DA) for anormal subject a, and 3 patients with aortic stenosis and ascendingaortic dilation: peak/mean gradients in mm Hg of 56/30 b, 90/46 c, and75/43 d. Short streamlines (blue) generated throughout the ascendingaorta provide an overview of the systolic velocity field. Volume ren-dering of turbulent kinetic energy (TKE, red-yellow) reveal uniqueregions of elevated turbulence intensity


Pulse Wave Velocity

Pulse wave velocity (PWV) refers to the speed at which thesystolic impulse travels through the cardiovascular system.PWV is a measure of vascular stiffness, and has shown to bean important clinical biomarker. For example, carotid-femoral PWV is an independent predictor of mortality inthe general population and in subgroups of patients withcommon chronic illnesses [46]. PVW is also known tocorrelate well with aortic disease [46, 47] and has beenuseful in predicting progression [48] and evaluating treat-ment response [49, 50] in Marfan syndrome.

PC-MRI can measure PWV in an accurate and reproduc-ible way using transit time methods, whereby velocity-timeprofiles are measured at 2 or more locations in the vessel ofinterest [51]. The temporal differences between specific fea-tures of the flow versus time curve (eg, foot, half-maximum,or peak) are used to estimate pulse wave travel time. Thetravel distance can be reliably estimated from angiographicrepresentations of 3D MRI data. Another approach for esti-mating travel time involves using cross-correlation to estimatetime shifts between waveforms, which takes into consider-ation the entire pulse waveform [52]. This approach hasrecently been demonstrated with 4D Flow [53•]. An

Fig. 5 Abnormal systolic flow with post-stenotic aortic dilation. a,Normal blood flow in a healthy volunteer. From left to right, magneticresonance angiography (MRA), systolic streamlines in the ascendingaorta and cross-sectional analysis at the plane depicted in the proximalascending aorta are provided; this same sequence is found in eachimage panel presented. The MRA shows normal aortic geometry, thestreamlines normal laminar systolic flow, and the cross-sectional anal-ysis central fast flow and an even distribution of wall shear stress(WSS) around the aortic lumen; the green bars represent the relativemagnitude of WSS. b, A man with severe aortic stenosis and

aneurysmal dilation of the ascending aorta to 5.3 cm. Systolic flow iseccentric with streamlines that course through the ascending aorta in aright-handed helix. The cross-sectional analysis shows that flow ismarginalized to the right-anterior quadrant where WSS is focallyelevated. c, A young woman with BAV, aortic stenosis and dilation ofthe ascending aorta to 4.6 cm. Similar eccentric flow with a right-handed helix of systolic streamlines is demonstrated. WSS is againfocally elevated where flow is marginalized against the aortic wall.(With permission, Hope MD et al. Int J Cardiol. 2012;156(2):e40–42.)


advantage of MRI is the ability to perform focused, regionalassessment of individual vessels, which may prove moreclinically relevant than global evaluation [48].

Pressure

Pressure gradients are key to assessing the severity of ste-noses. They are routinely estimated from echocardiographyor MR velocity data using the modified Bernoulli equation.But the velocity fields acquired with 4D Flow can be ma-nipulated in more advanced ways. Pressure gradients can beintegrated along arbitrary lines, allowing the estimation ofpressure differences between selected points [54]. 3D pres-sure maps can also be calculated [55–57], but many chal-lenges exist and care must be taken to avoid systematic error[58]. A limitation of current MR pressure field mapping isthe assumption of non-turbulent flow. This is reasonable forintracardiac blood flow, but problematic for stenoses wheresignificant turbulence effects exist.

Turbulence

A hallmark of turbulent flow and related non-laminar typesof flow (eg, “transitional” or “disturbed”) is the presence ofapparently random velocity fluctuations. The standard devi-ation of the velocity fluctuations around the mean velocity isa common definition of turbulence intensity. Turbulenceintensity can be estimated by exploiting the effects of ve-locity fluctuations on the amplitude of the PC-MRI signal(Fig. 2) [59]. The turbulent kinetic energy (TKE) describesthe kinetic energy of the fluctuating velocity field, and canbe calculated from 4D Flow data [60] with good agreementwith reference methods [41, 59, 61, 62]. Application tovascular stenoses and valvular lesions has demonstratedthe potential of this extension of 4D Flow for revealingimportant information on the spatiotemporal dynamics ofdisturbed cardiovascular flows (Fig. 4) [60].

Dissipation of TKE is the primary cause of pressure lossacross stenoses, and thus may play an important role inevaluating their true hemodynamic significance. Recent datawith aortic stenosis indicate that a MR measured TKE maybe useful for the estimation of and irreversible pressure loss[63••]. Turbulence is also related to other relevant clinicalfactors including endothelial cell turnover, hemolysis andplatelet activation [64–66]. MR turbulence mappingexpands research possibilities in these areas.

Wall Shear Stress

Wall shear stress (WSS) is the frictional force exerted on avessel wall by flowing blood. 4D Flow can be used toestimate WSS and is widely applied [14, 67–69].Limitations of the method, including poor lumen-wall

contrast and partial volume effects of near wall velocitymeasurements have been addressed by combining lumenwall segmentations with line or plane fitting of velocitiesin multiple voxels [70]. Nevertheless, WSS estimates de-rived from PC-MRI underestimate true WSS in a non-linear,voxel-size dependent manner [70, 71•]. However, 4D Flowcan be used to identify areas of abnormally high or lowWSS, which may be clinically useful [14, 68, 72].

WSS is important for vascular homeostasis. Low and os-cillatory WSS is known to promote atherosclerosis by induc-ing atherogenic states of endothelial cells [12]. Goodcorrelation has been shown between aortic atherosclerosisand lowWSS observed by 4D Flow [73, 74]. WSS evaluationof abdominal aortic aneurysms, however, is often not possiblebecause of the presence of intraluminal thrombus [75].

The effect of high WSS on vessels is less well studiedthan low WSS, but has been linked to vessel remodeling[12]. High WSS can also lead to endothelial injury andweakening [76]. This has also been incorporated into alow then high WSS theory of atherosclerotic plaque rupture:low WSS leads to plaque formation and luminal narrowing,leading to elevated WSS at the upstream edge of the plaque;elevated WSS causes smooth muscle apoptosis and extra-cellular matrix degradation, weakening the vessel and pre-disposing to rupture [77]. Based on recent cell culture data,WSS gradients might be more important than absolute WSSvalues for driving aneurysm growth [78].

4D Flow has been used to evaluate WSS throughout thethoracic aorta [68, 79]. Focally elevated WSS has beencorrelated with typical areas of postoperative aneurysm

Table 2 Quantitative hemodynamic biomarkers

Hemodynamicbiomarker

Clinical Significance

Flow volume * Valve regurgitation

* Shunt quantification

* Collateral flow with aortic coarctation

Pulse wave velocity(PWV)

* Vascular stiffness

* Correlates well with disease states

* Independent predictor of mortality

Relative pressure * Driving force of blood flow

* Pressure loss across stenosis (along withturbulence)

Turbulence * Energy loss across stenosis

* Blood trauma

* Platelet activation

Wall shear stress(WSS)

* Regulator of endothelial cell function

* Low WSS promotes atherosclerosis

* High WSS linked to aortic growth

Eccentricity * Growth of aortic aneurysms

* Potential surrogate for wall shear stress


formation and aneurysm rupture [80, 81]. Valve-relatedaortic disease has been increasingly studied with 4D Flow,revealing distinctly abnormal hemodynamics that may un-derlie post-stenotic dilatation [67, 82–84]. For example,focally elevated WSS has been observed at the convexityof the ascending aorta in patients with bicuspid aortic valves(BAV) [14, 72], the same site where valve-related asymmet-ric aortic dilatation typically occurs in these patients (Fig. 5)[85–87] and where extracellular matrix changes have beenobserved in surgical specimens [88].

Flow Eccentricity

Normal flow in the ascending aorta is characterized by anapproximately parabolic velocity profile, where the highestvelocities are seen centrally. 4D Flow evaluation of patientswith aortic valve disease and/or aortic dilation, however,commonly demonstrates eccentric flow with highly skewedvelocity profiles. As a result, asymmetric near-wall velocitygradients are present, leading to areas of relatively highWSS. This eccentricity is well visualized and quantifiedwith 4D Flow. One approach is to calculate the angle be-tween the flow jet and the axis of the left ventricular outflowtract [89]. An alternate strategy involves calculating thedisplacement of flow from the aortic centerline [38•].

Capturing the asymmetric hemodynamics of eccentricflow with a simple, quantitative parameter such as flowdisplacement could prove clinically useful. Recently, linksbetween eccentric flow and ascending aorta growth has beenuncovered. Restricted aortic leaflet motion (which presum-ably results in flow eccentricity) was shown to correlatestrongly with increased aortic growth rate in a subset ofpatients with BAV [90•]. In a similar population of patients,4D Flow demonstrated good correlation between increasedaortic growth rates and flow displacement [91••]. Flowdisplacement is a simple parameter that is very reproducibleand better correlates with interval aortic growth than WSS(Hope MD, unpublished data, 2012). For these reasons, webelieve that eccentricity is one of the more promising he-modynamic markers for risk-stratifying patients for progres-sive valve-related aortic disease.

Conclusion

Quantitative aortic MR blood flow imaging is a rapidlyadvancing technique that is likely to impact clinical medi-cine in the near future. The acquisition of comprehensive 4Dvelocity datasets is now possible in a clinically practicaltime frame, with further scan reduction expected in the nearfuture. Unique and intuitive visualization methods are avail-able. A number of important hemodynamic markers can bederived from the data, and exploited to help understand how

abnormal flow promotes aortic pathology (Table 2). Initialdata suggest that some of the derived biomarkers can refinethe clinical assessment of aortic disease and predict aorticdisease progression. Larger, prospective studies are war-ranted to assess the potential of MR flow imaging for theearly identification of patients at risk for the development ofpotentially devastating aortic complications.

Acknowledgment Funding: Radiological Society of North AmericaResearch Scholar Grant (MDH). Swedish Heart-Lung Foundation(PD), Swedish Brain Foundation (PD), Fulbright Commission (PD).

Disclosure No potential conflicts of interest relevant to this articlewere reported.

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Clinical Applications of Aortic 4D Flow Imaging