Lee_4Dflow

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Three-dimensional left atrial blood flow
characteristics in patients with atrial fibrillation
assessed by 4D flow CMR
Dan C. Lee1,2,3†, Michael Markl2,4*†, Jason Ng1,3, Maria Carr2, Brandon Benefield1,
James C. Carr2, and Jeffrey J. Goldberger1,3,5
1
Feinberg Cardiovascular Research Institute, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; 2
Department of Radiology, Northwestern University Feinberg
School of Medicine, 737 N. Michigan Avenue Suite 1600, Chicago, IL 60611, USA; 3
Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA;
4
Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA; and 5
Center for Cardiovascular Innovation, Department of
Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
Received 21 May 2015; accepted after revision 21 October 2015
Aims To apply 4D flow cardiac magnetic resonance (CMR) for the volumetric measurement of 3D left atrial (LA) blood flow
to evaluate its potential to detect altered LA flow in patients with atrial fibrillation (AF) and to investigate associations of
changes in systolic and diastolic LA flow with the current clinical risk score (CHA2DS2-VASc) used for the assessment of
thromboembolic risk in AF.
Methods
and results
4D flow CMR was performed in 40 patients with a history of AF (in sinus rhythm during CMR scan, age ¼ 61 + 11
years), 20 age-appropriate controls (59 + 7 years), and 10 young healthy volunteers (24 + 2 years) to measure
in vivo time-resolved 3D LA blood flow. LA velocities were characterized with respect to atrial function and timing
by calculating normalized LA flow velocity histograms during ventricular systole, early diastole, mid-late diastole, and
the entire cardiac cycle. Mean, median, and peak LA velocity steadily decreased when comparing young volunteers,
age-appropriate controls, and AF patients by 10–44% and 8–26% for early diastole and the entire cardiac cycle,
respectively (P , 0.01 for all comparisons except median velocity for young vs. older volunteers and peak velocity
for older volunteers and AF patients). There were moderate but significant inverse relationships between increased
CHA2DS2-VASc score and reduced mean LA velocity (early diastole: r ¼ 20.37, P , 0.001; entire RR-interval:
r ¼ 20.33, P ¼ 0.005), median LA velocity (r ¼ 20.33, P ¼ 0.003; r ¼ 20.25, P ¼ 0.017), and peak velocity
(r ¼ 20.36, P ¼ 0.001; r ¼ 20.45, P , 0.001). LA flow indices also correlated significantly with age and LA volume
(R2
¼ 0.44–0.62, P , 0.001), but not with left ventricular ejection fraction.
Conclusion Left atrial 4D flow CMR demonstrated significantly reduced LA blood flow velocities in patients with AF. Further study
is needed to determine whether these measures can improve upon the CHA2DS2-VASc score for stroke risk prediction
and enhance individual decisions on anticoagulation in patients with AF.
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Keywords atrial fibrillation † stroke † 4D flow CMR † cardiovascular MRI † flow
Introduction
Atrial fibrillation (AF) is the most common cardiac arrhythmia, af-
fecting 33.5 million patients worldwide.1
Among adults 40 years
or older, the lifetime risk of developing AF is 25%.2
A frequent
and serious complication from AF is stroke (15–20% of all strokes
occur in patients with AF), which is attributed to embolism of
thrombus from the left atrium (LA).3,4
Currently, clinicians use
risk models to estimate an AF patient’s annual stroke risk. The
most widely used algorithms in patients with AF have been the
CHADS2 score5
and more recently the CHA2DS2-VASc score
which is now recommended.6 – 9
However, these scores have lim-
ited predictive values for thromboembolism (C statistics 0.55–
0.67), as they are based on upstream clinical factors (age, gender,
* Corresponding author. Tel: +1 312 695 1799. E-mail: mmarkl@northwestern.edu
†
The first two authors contributed equally to this article and they both share first authorship of this article.
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2015. For permissions please email: journals.permissions@oup.com.
European Heart Journal – Cardiovascular Imaging
doi:10.1093/ehjci/jev304
European Heart Journal - Cardiovascular Imaging Advance Access published November 20, 2015
byguestonDecember11,2015Downloadedfrom

diabetes, etc.) rather than individual physiologic factors, such as sta-
sis, implicated in LA thrombus formation.6,10
Individualization of the factors associated with atrial thrombus
formation might thus help improve these population-based risk
scores. Virchow’s triad, consisting of endothelial/endocardial dam-
age or dysfunction, stasis or reduced flow, and hypercoagulability,
describes factors conducive to thrombogenesis. Although there is
evidence supporting the presence of all three factors in AF, reduced
left atrial appendage (LAA) flow velocity is thought to play a primary
role as demonstrated by previous Doppler transoesophageal echo-
cardiography (TEE) studies.11,12
In these studies, however, the as-
sessment of flow was based on 2D analysis planes and single
direction velocity measurement in the LAA which does not provide
complete evaluation of the complex 3D blood flow in the LA.
The aim of this study was therefore to apply 4D flow CMR for the
comprehensive quantification of time-resolved, three-directional
blood flow velocities with full volumetric coverage of the LA.13 –19
We hypothesized that the LA blood flow velocity distribution mea-
sured by 4D flow CMR is significantly altered in patients with a his-
tory of AF compared with controls. Furthermore, we hypothesized
that metrics of LA haemodynamics, in particular, reduced mean and
peak LA flow velocities, correlate with the CHA2DS2-VASc risk
score.
Methods
Study population
A total of 70 subjects underwent 4D flow CMR for quantification of LA
3D blood flow velocities: 40 patients with a history of AF who were in
sinus rhythm at the time of the CMR scan, 20 age-appropriate volun-
teers, and 10 healthy volunteers under age 30. Patients with documen-
ted history of atrial fibrillation—either paroxysmal or persistent—were
eligible for inclusion. Patients with implantable devices, significant renal
impairment, and either intolerance or contraindication to CMR were
excluded. None of the volunteers had a history of cardiovascular dis-
ease. All subjects for this HIPAA compliant study were included in the
study according to procedures approved by the Northwestern Univer-
sity Institutional Review Board
Magnetic resonance imaging
All patients in this study were in sinus rhythm during the CMR scan.
CMR examinations were performed on both 1.5 T and 3 T MR systems
(Espree, Aera, Avanto, and Skyra, Siemens, Erlangen, Germany). All
patients underwent standard-of-care CMR including the acquisition of
four-chamber, two-chamber, and short–axis, ECG-gated time-resolved
2D cine MR images using a steady-state free precession (SSFP) se-
quence. For the assessment of LA blood flow, time-resolved, 3D phase-
contrast CMR with three-directional velocity encoding (4D flow CMR)
was used to measure 3D blood flow velocities in the LA. The principle
advantage of 4D flow CMR is that during a single, free-breathing acqui-
sition, blood velocity can be measured in three orthogonal directions
with full volumetric coverage of the LA throughout the cardiac cycle.20
The data acquisition was synchronized with cardiac motion (prospective
ECG gating) and subject’s respiration by navigator gating of the
diaphragm motion as described previously.21
Further 4D flow CMR
pulse sequence parameters were as follows: flip angle ¼ 158, spatial
resolution ¼ 2.5–3.0 × 2.5–3.0 × 3.0–4.0 mm, temporal resolution ¼
37.6–41.6 ms, total acquisition time ¼ 10–20 min depending on heart
rate and navigator efficiency, velocity sensitivity ¼ 100–150 cm/s.
Data analysis
A schematic of the 4D flow analysis workflow is shown in Figure 1.
After noise filtering, Maxwell, and eddy current correction, 3D
PC-MR angiography (3D-PC MRA), or time-averaged magnitude
(tMag) data were derived from the 4D flow data.21
3D-PC MRA or
tMag data (depending on quality of atrial lumen contrast) were used
to guide manual definition of the LA endocardial surface using dedi-
cated 3D segmentation software (MIMIC’s Materialise 16.0, USA).
For each subject, the resulting 3D LA segmentation mask was used
to isolate the velocity data inside the segmented LA volume for all atrial
voxels. Next, velocity magnitudes for each subject were arranged in
histograms for cardiac time frames corresponding to ventricular sys-
tole (4D flow data within the first 300 ms after the R-wave), early dia-
stole, mid-to-late diastole (first and second 50% of the remainder of
the cardiac cycle), as well as the entire cardiac cycle. All histograms
were normalized by the total number of voxels in the atrium to pre-
vent overweighting data from patients with large atria and to allow
for the calculation of group-averaged LA velocity histograms and com-
parisons across subjects.
In addition, for each subject, we calculated LA volume (in mL), mean
velocity (in m/s), median velocity (in m/s), and peak velocity (in m/s) for
all analysed time periods (systole, early diastole, mid-to-late diastole, en-
tire cardiac cycle). A typical patient LA velocity histogram covering the
entire RR interval contained .50 000 velocities (3D volume + time
over the cardiac cycle). Peak velocity was calculated as the average of
the top 5% of all LA velocities. To evaluate inter-observer variability
of 4D flow-based LA flow analysis, a second independent observer,
blinded to the other’s results, independently analysed a subgroup of
17 subjects.
2D cine SSFP data were used to evaluate global cardiac function and
left ventricular ejection fraction (LVEF).
CHA2DS2-VASc Risk Score
The current guidelines for management of patients with AF recommend
the use of the CHA2DS2-VASc Risk Score for assessment of stroke
risk.6,7
Patient medical records documented prior to CMR acquisition
were examined to document clinical risk factors for stroke or thrombo-
embolism. Using the definitions described by Lip et al.,6
patients were
given one point for congestive heart failure/left ventricular dysfunction,
hypertension, aged 65–74, diabetes, vascular disease, sex category
female, and two points for age ≥75 and stroke/transient ischaemic
attack/thromboembolism.
Statistical analysis
All continuous data are presented as mean + standard deviation.
For each group (young volunteers, age-appropriate volunteers, and
AF patients), a Shapiro–Wilk test was used to determine whether
parameters were normally distributed. To compare parameters
among the three groups, one-way ANOVA (Gaussian distribution)
or Kruskal–Wallis (non-Gaussian distribution) was used. If these
tests determined that a parameter was significantly different between
groups (P , 0.05), multiple comparisons for all groups were
performed using independent sample t-tests (Gaussian distribution)
or Mann–Whitney U tests (non-Gaussian distribution). Bonferroni
correction was used to adjust for multiple comparisons, and differ-
ences were considered significant for P , 0.0167. All analysis was
performed using Matlab (version R2011a, The Mathworks, USA).
To identify relationships between LA volume, age, and metrics of
LA haemodynamics, linear regression was performed and Pearson’s
correlation coefficient was calculated; a correlation was considered
significant for P , 0.05.
D.C. Lee et al.Page 2 of 10

Results
Study population
Characteristics of the study population are described in Tables 1
and 2. The AF patients and age-appropriate controls were similar
in age (61.3+11.1 vs. 59.2 +7.4, P ¼ 0.45) and gender distribution
(68 vs. 65% male, P ¼ 0.70). Overall, LVEF was well preserved in all
groups with no difference between young (63.7 + 3.7%) and
age-appropriate volunteers (62.1 + 4.2%, P ¼ 0.31). Compared
with AF patients (58.1 + 8.1%), there was a trend towards higher
LVEF in age-appropriate volunteers (P ¼ 0.063) and a significantly
higher LVEF in young volunteers (P ¼ 0.016). Mean LA volume
steadily increased when comparing young controls, age-appropriate
controls, and AF patients (P , 0.01 for all comparisons). Heart rate
was similar among all groups.
Additional clinical information is provided for the AF patients
(n ¼ 40) in Table 3. Most AF patients previously underwent rhythm
control procedures: 13 underwent both cardioversion and AF abla-
tion, 10 only had prior cardioversion, 6 only had prior ablation, and
11 had no prior rhythm control procedures. Of the 19 patients
with prior ablation, 12 had prior catheter AF ablation, 3 had prior
surgical AF ablation, and 3 had both. The median time interval be-
tween rhythm control procedure and CMR was 184 days (349 +
429 days, range ¼ 12–1704 days). Only two (5%) patients under-
went CMR ,30 days after a rhythm control procedure. One patient
had cardioversion 13 days before CMR (mean LA velocity 0.13 m/s);
another had cardioversion 12 days before CMR (mean LA velocity
0.10 m/s). All patients received some thromboembolism prophy-
laxis: 8 (20%) aspirin only, 12 (30%) warfarin, and 20 (50%) novel
oral anticoagulant (NOAC). None of the patients had severe mitral
Figure 1 Atrial 4D flow CMR for two AF patients (both imaged while in sinus rhythm) with similar LA volume and low CHA2DS2-VASc scores
but different LA flow velocities. (A) Left atrial 3D blood flow visualization and a representative LA tomogram colour coded according to the vel-
ocity vector magnitude at a single time frame in diastole (B) 3D LA segmentation based on volumetric 3D PC-MRA data (grey-shaded iso-surface).
(C) Normalized velocity histograms quantify the LA velocity distribution inside the segmented LA geometry. Quantitative indices of LA flow—
mean, median, and peak LA velocity—are shown on the histograms. Note the reduced flow velocities in Subject no. 35 compared with Subject
#no. 51 despite similar clinical factors.
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Table 1 Demographics of study cohorts
n Age (years) LVEF (%) LA volume (mL) Heart rate (bpm)
Young volunteers 10 24+2 64+4 25+5 63+8
Older volunteers 20 59+7 62+1 37+12 68+11
AF patients in sinus 40 61+11 58+8 61+24 68+15
3-D LA blood flow characteristics in patients with AF Page 3 of 10

stenosis, and three patients had mild (n ¼ 2) and severe (n ¼ 1)
mitral regurgitation.
Left atrial 4D flow CMR examples
Figure 1 illustrates LA flow visualization (Figure 1A), LA segmentation
based on 3D PC-MRA data (Figure 1B), and resultant LA velocity his-
tograms (Figure 1C) for two AF patients with similar LA volumes and
low CHA2DS2-VASc scores but different LA velocities. LA blood
flow visualization (Figure 1A) showed overall higher blood flow
velocities for Subject no. 35 (top row) compared with Subject no.
51 (bottom row) as corroborated by the velocity histograms
(Figure 1C). Accordingly, quantitative indices of overall LA flow
(mean velocity, median velocity, and peak velocity based on velocity
data from entire cardiac cycle) were reduced by 38, 25, and 40%, re-
spectively, for Subject no. 51, indicating the potential of 4D flow
CMR to detect poor LA flow despite similar LA volume and low
CHA2DS2-VASc risk score.
LA velocities with respect to atrial
function and timing—group comparisons
All 4D flow CMR data were of sufficient quality for LA segmenta-
tion and velocity quantification. Group-averaged LA velocity his-
tograms during systole, early diastole, and mid-to-late diastole
for control groups and AF patients are shown in Figure 2 and
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Table 3 AF patient clinical information
Cardioversion Ablation Both CV and ABL None
Prior rhythm control procedures 10 (25.0%) 6 (15.0%) 13 (32.5%) 11 (27.5%)
Median (d) Range (d) Patients with ,30-day interval
Time from rhythm control procedure to CMR 184 12–1704 2 (5%)
Risk factors Antiarrhythmic medications
CHF/LV dysfunction 2 (5%) Class IA 0 (0%)
Hypertension 21 (52.5%) Class IC 9 (22.5%)
Aged 65–74 3 (7.5%) Class II (BB) 22 (55%)
Diabetes 3 (7.5%) Class III 14 (35%)
Stroke 6 (15%) Class IV (CCB) 8 (20%)
Vascular disease 8 (20%) Class V 6 (15%)
Aged 75 or over 3 (7.5%)
Sex category female 11 (27.5%) Thromboembolism prophylaxis
Aspirin only 8 (20%)
Hyperlipidaemia 22 (55%) Warfarin 12 (30%)
eGFR .60 27 (67.5%) NOAC 20 (50%)
eGFR 45–59 12 (30%)
eGFR 30–44 1 (2.5%) ACE/ARB 11 (27.5%)
eGFR ,30 0 (0%) Statin 20 (50%)
CV, cardioversion; ABL, ablation; CHF, congestive heart failure; LV, left ventricular; eGFR, estimated glomerular filtration rate; BB, b-blocker; NOAC, novel oral anticoagulant;
ACE, ACE inhibitor; ARB, angiotensin receptor blocker; CCB, calcium channel blocker.
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Table 2 Statistical analysis of differences between groups
Repeated measures Young controls vs.
age-appropriate controls
Young controls vs. AF
pts. in sinus
Age-appropriate controls
vs. AF pts. in sinus
Age ANOVA
P < 0.0001
P < 0.0001a
P < 0.0001a
P ¼ 0.4469a
LVEF Kruskal–Wallis
P 5 0.02
P ¼ 0.3068a
P 5 0.0161b
P ¼ 0.0625b
LA volume ANOVA
P < 0.0001
P 5 0.0049a
P < 0.0001a
P 5 0.0001a
Heart rate Kruskal–Wallis
P ¼ 0.40
N/A N/A N/A
Significant differences (after Bonferroni correction, P , 0.0167) between individual groups are indicated by bold type. N/A, multiple comparisons between groups were not
performed due to non-significant differences in repeated-measures test.
a
Two-sided t-test.
b
Mann–Whitney test.

illustrate overall lower LA velocities (more compact histogram
centred at lower velocities) in AF patients compared with con-
trols. Resulting LA flow metrics (mean, median, and peak LA
velocities) for all time periods and statistical differences between
groups are summarized in Table 4. For AF patients, all indices were
significantly reduced (P , 0.0167) compared with young and
Figure 2 Group-averaged left atrial velocity histograms for n ¼ 10 young healthy volunteers (A), n ¼ 20 older controls (B), and n ¼ 40 AF pa-
tients (C) during systole, early diastole, and late diastole. Mean, median, and peak left atrial velocities are marked on each panel.
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Table 4 Descriptive statistics of metrics of LA 3D blood flow for control cohorts and AF patients
Mean LA vel. (m/s) Median LA vel. (m/s) Peak velocity (m/s)
Entire RR interval
Young volunteers 0.18+0.02 0.15+0.01 0.43+0.02
Age-appropriate controls 0.16+0.02* 0.14+0.02 0.37+0.04*
AF patients in sinus 0.13+0.02#,+
0.12+0.02#,+
0.34+0.05#
Ventricular systole
Age-appropriate controls 0.14+0.03 0.13+0.03 0.34+0.05
AF patients 0.12+0.02#,+
0.11+0.02#,+
0.30+0.05#,+
Early diastole
Age-appropriate controls 0.16+0.03* 0.15+0.03* 0.36+0.05*
AF patients 0.14+0.03#+
0.12+0.03#+
0.32+0.07#
Mid-late diastole
Age-appropriate controls 0.17+0.04 0.15+0.04 0.38+0.06
AF patients 0.15+0.04 0.14+0.04 0.34+0.09
*Significant difference age-appropriate controls vs. young volunteers, P , 0.0167.
#
Significant difference AF patients vs. young volunteers, P , 0.0167.
+
Significant difference AF patients vs. age-appropriate controls, P , 0.0167.

age-appropriate controls during systole and early diastole (except
for peak LA velocity compared with age-appropriate controls).
Findings were most pronounced for the early diastolic time peri-
od. If LA velocity data over the entire cardiac cycle were taken into
account, all three measures of LA blood flow detected statistically
significant differences (P , 0.0167) between young volunteers,
older volunteers, and AF patients except median velocity for
young vs. older volunteers and peak velocity for older volunteers
vs. AF patients.
The distribution of individual patient LA flow metrics for time
periods with most pronounced changes in LA velocities (early dia-
stole, entire cardiac cycle) is illustrated in Figure 3. All three indices
steadily decreased when comparing young volunteers, age-
appropriate controls, and AF patients by 10–44% and 8–26% for
early diastole and the entire RR interval, respectively. However,
for both time periods, individual patient values illustrate a wide
distribution within each group.
Correlation with clinical factors
For all 70 subjects, scatter plots illustrating the relationship between
metrics of LA flow based on velocity data from entire cardiac cycle
and known clinical risk factors for stroke (age,22
LA volume,23
and
LVEF24
) are shown in Figure 4. Mean LA velocities correlated nega-
tively with age (R2
¼ 0.31, P , 0.0001) and LA volume (R2
¼ 0.30,
P , 0.0001). Similarly, reduced median LA velocities were sig-
nificantly associated with increased age (R2
¼ 0.19, P , 0.0001)
and increased LA volume (R2
¼ 0.28, P ¼ 0.0001). In addition, sig-
nificant inverse relationships were found for peak LA velocities
with age (R2
¼ 0.39, P , 0.0001) and with LA volume (R2
¼ 0.22,
P , 0.0001).
As summarized in Table 5, there were moderate significant (P ,
0.05) relationships between increased CHA2DS2-VASc score (i.e.
higher thromboembolic risk) and reduced mean LA velocity, median
LA velocity, and peak LA velocity during early diastole and based on
data from the entire cardiac cycle (Figure 5).
Inter-observer variability
Bland–Altman plots demonstrate high inter-observer agreement
for measurements of mean, median, and peak LA velocity (Figure 6).
Observer variability resulted in average inter-observer differences
of 5.5% for mean velocity, 5.9% for median velocity, and 6.8% for
peak velocity.
Discussion
The findings of this study demonstrate the feasibility of 4D flow
CMR for the comprehensive quantification of left atrial 3D blood
flow. 4D flow CMR detected significant changes in LA haemo-
dynamics and reduced LA velocities in patients with a history of
AF compared with young and age-appropriate control groups.
Moreover, reduction in LA velocities was monetary but significantly
associated with age and LA volume in the entire cohort, and there
was a significant relationship with the standard-of-care clinical
CHA2DS2-VASc risk score in patients with history of AF. These re-
sults indicate the potential of the technique for the evaluation of
changes in LA blood flow. Specifically, the correlation of LA flow
metrics with the CHA2DS2-VASc score (a population-based meas-
ure for thromboembolic risk) suggests that individual physiologic
LA flow measurements, as obtained by 4D flow CMR, may be sen-
sitive markers for stroke risk stratification in patients with AF.
Figure 3 Group-wise comparisons of LA mean (A), median (B), and peak velocities (C) representing LA flow dynamics over the entire cardiac
cycle (top row) and during early diastole (lower row). The individual box plots illustrate the median (central mark) and the 25th and 75th per-
centiles (edges), the whiskers extend to the most extreme data points not considered outliers, and outliers are plotted individually as ‘+’.

However, the observed correlation was moderate indicating the
potential added value of 4D flow-derived metrics of LA flow dy-
namics for the identification of patients with altered LA velocities.
In this context, our findings also demonstrated that AF patients can
express substantially different LA velocities despite similar CHA2-
DS2-VASc score as illustrated in the examples in Figure 1 and
Figure 4 Correlation analysis between metrics of LA flow (A: mean velocity, B: median velocity, C: peak velocity based on velocity data from
entire cardiac cycle) and LA volume, subject age, and LVEF for all n ¼ 70 subjects included in the study.

evident by the overlap in metrics of LA flow in Figures 3 and 5. We
speculate that a number of factors (including LA volume, age,
blood pressure, etc.) will influence LA flow and a direct measure-
ment of AF induced changes LA velocities may be the most optimal
method rather than relying on surrogate metrics or risk scores.
Currently, risk models such as the CHA2DS2-VASc score used in
this study are recommended to help clinicians weigh the benefit of
stroke reduction against the risk of bleeding. These models assign
points for each of several risk factors for stroke held by the patient
(e.g. age, hypertension, heart failure/reduced LVEF, and prior
thromboembolism), and the total point score corresponds to the
estimated stroke risk.6– 9
Risk models have played a vital role in help-
ing clinicians estimate stroke risk, to weigh the benefit of therapy
aimed at stroke risk reduction against the concomitant increased
risk of major bleeding. However, a comparison of these risk models,
including those from Atrial Fibrillation Investigators (AFI), Stroke
Prevention in Atrial Fibrillation Investigators (SPAF), Framingham
Heart Study, and the most commonly used CHADS2 and
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Table 5 Results of correlation analysis comparing metrics of LA flow with the clinical risk score for AF patients (n 5 40)
CHA2DS2-VASc score vs.
Mean LA vel. Median LA vel. Peak velocity
r P r P r P
Entire RR interval 20.331 0.005 20.255 0.017 20.446 ,0.001
Ventricular systole 20.133 NS 20.136 NS 20.124 NS
Early diastole 20.368 ,0.001 20.331 0.003 20.361 0.001
Mid-late diastole 20.214 0.038 20.174 NS 20.140 NS
NS, not significant.
Figure 5 Relationships between metrics of LA flow (mean, median, and peak LA velocity based on velocity data from entire cardiac cycle) with
stroke risk estimated by CHA2DS2-VASc score for n ¼ 40 AF patients.
Figure 6 Bland–Altman analysis of inter-observer variability in a subgroup of n ¼ 17 subjects with LA segmentation by two observers, blinded
to each other’s results.

CHA2DS2-VASc Risk Scores, demonstrated suboptimal C statistics
ranging from 0.55 to 0.67.6
A major limitation of risk scores is that they are based on up-
stream clinical factors that are associated with stroke on a popula-
tion basis. Predictive accuracy can potentially be improved by using
physiologic data that are specific to the individual patient. In this con-
text, studies utilizing TEE have shown that decreased LAA peak flow
velocities are independent risk factors for stroke in AF.11,25
Further-
more, the presence of spontaneous echo contrast, a marker of
reduced blood flow velocity or stasis, has been shown to be an
independent predictor for thromboembolism.12,26
In this study, we used 4D flow CMR for the assessment of LA
blood flow velocities, which has several potential advantages com-
pared with TEE including full volumetric coverage of the LA, quan-
tification of the complete time-resolved, three-directional velocity
field inside the LA, and no need for semi-invasive oesophageal intub-
ation. It should be noted that previous TEE studies focused only on
the assessment of LAA velocities, while our study was based on the
quantification of flow within the entire LA that limits the compar-
ability of findings from both modalities.
Using 4D flow CMR, we found significant differences in the LA
flow profiles of young volunteers, older volunteers, and patients
with a history of AF who were in sinus rhythm at the time of the
scan. LA velocities were significantly impaired in patients with a his-
tory of AF compared with older volunteers, while young volunteers
predictably demonstrated the most robust LA flow patterns. It is
notable that there was a wide spread in the LA flow metrics of indi-
vidual patients in each group. We speculate that based on LA flow
patterns, some of the AF patients may have stroke risk similar to
controls, while those with impaired LA flow may have higher stroke
risk.
Future longitudinal studies are needed to confirm this hypothesis
and investigate whether the combination of clinical scores (e.g.
CHA2DS2-VASc) with patient-specific 4D flow-derived LA flow vel-
ocities can provide improved stroke risk stratification. Indeed, we
found that LA flow metrics correlated with other known predictors
for the development of stroke and the CHA2DS2-VASc score. In the
population-based longitudinal Framingham Heart Study, age22
and
LA size23
were found to be significant risk factors for stroke. In
our study, all three indices of LA flow (mean, median, and peak
LA velocity) were associated with LA volume and age. LA velocities
did not correlate with LVEF; however, the correlation between im-
paired LV function and stroke risk in AF is not seen as consistently
across trials. In analysis of the Euro Heart Survey for AF8
(used to
derive the CHA2DS2-VASc score) and in the SPORTIF III/V trials,27
heart failure and LVEF ,40% were not significant univariate predic-
tors of thromboembolic events.
It should be noted that all 4D flow CMR data were acquired over
multiple heartbeats, and the resulting images represent a composite
of blood flow over the entire acquisition time. As all subjects with a
history of AF were in sinus rhythm at the time of CMR scan, the 4D
flow data can accurately capture the magnitude and timing of LA vel-
ocities over the cardiac cycle. Mitral regurgitation that could affect
LAvelocities was not analysed on our study cohort. However, mitral
regurgitation would result in high atrial velocities (as a result of a re-
gurgitant jet) and may thus result in generally elevated LA velocities
compared with subjects without regurgitation. Nevertheless, our
data show reduced LA velocities in AF patients during all cardiac
phases and thus indicate that, even in the presence of mitral regur-
gitation, LA velocities are still significantly lower in patient with AF
compared with age-appropriate controls. Furthermore, our study
evaluated blood flow velocities in the entire LA, while previous
TEE studies focused on the quantification of metrics of LAA flow.
Further studies are thus warranted to systematically evaluate blood
flow velocities in both the LA and LAA and assess the impact of the
mitral regurgitation on 4D flow data.
Our study has important limitations. The small size of our patient
cohort (n ¼ 40) underlines the feasibility nature of our study and
limits the conclusions regarding the diagnostic value of metrics of
LA flow dynamics that can be drawn from our findings. Specifically,
the heterogeneity of our study cohort (inclusion of patients with mi-
tral regurgitation or shortly after cardioversion and thus stunned at-
rium and mitral valve) may have additionally influenced LA flow and
velocities. It should be noted, however, that 4D flow data were ac-
quired with velocity sensitivities (venc) ranging from 100 to 150 cm/
s. As a result, blood flow velocities exceeding venc and the normal
range of atrial velocities (e.g. high regurgitant jet velocities in patients
with mitral regurgitation) will undergo velocity aliasing and are thus
mapped back into the range of +venc. The venc setting in 4D flow
CMR therefore acts as a low-pass filter for high blood flow veloci-
ties. We expect that even the presence of severe mitral regurgita-
tion and high regurgitant jet velocities will thus only moderately
impact LA velocity quantification. Nevertheless, future studies
should include larger cohorts and control for cardiovascular abnor-
malities that may additionally affect LA flow dynamics.
We did not have concurrent TEE data in these patients, preclud-
ing assessment of the correlation between peak LAA emptying vel-
ocity by TEE and 4D flow CMR metrics of LA flow. Analysis of
velocity data is based upon the composite velocity histograms for
each patient. More sophisticated analyses including residence
time, vorticity, and shear force may improve identification of pa-
tients with poor LA flow characteristics that increase risk of throm-
bus formation. Four-dimensional flow data were acquired at both
1.5 T and 3 T MRI systems which may have resulted in different im-
age quality (signal-to-noise levels). Future studies should include a
systematic comparison of image quality and flow metrics between
field strengths. We have previously investigated inter-study and
inter-observer reproducibility for flow and velocity measurements
using 4D flow CMR in the aorta and liver vasculature.28,29
Findings
from these studies have demonstrated good scan–rescan repeat-
ability. However, the evaluation of inter-study repeatability for LA
flow analysis was beyond the scope of this study and should be in-
vestigated in future studies. Finally, the assessment of atrial delayed
enhancement was not part of our study protocol but would be an
important addition for future studies.
Conclusions
Four-Dimensional flow CMR quantification of LA flow char-
acteristics demonstrated impaired LA flow in patients with a history
of atrial fibrillation compared with controls. Reduced LA mean, me-
dian, and peak LA velocities correlated with clinical predictors of
stroke, including age, LA volume, and CHA2DS2-VASc score. The
findings demonstrate the sensitivity of the technique to detect LA

flow abnormalities associated with AF. Further studies are war-
ranted to investigate whether the combination of clinical scores
(e.g. CHA2DS2-VASc) with patient-specific 4D flow-derived LA
flow velocities can provide improved stroke risk stratification.
Conflict of interest: None declared.
Funding
This work was supported by the American Heart Association
(12GRNT12080032) and the National Institutes of Health
(1R21HL113895-01A1).
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