Right Ventricular Ejection Fraction with Cardiac Magnetic Resonance using a Wall Motion Score

Réal Lebeau, MD1, Maude Pagé, MD1, Karim Serri, MD1, Maxime Pichette, MD, MSc1, Maria Di

Lorenzo, MD1, Claude Sauvé, MD1, Alain Vinet, PhD2, Frédéric Poulin, MD, MSc1

1 Division of Cardiology, Department of Medicine, Hôpital du Sacré-Cœur de Montréal,

Université de Montréal, Montréal, Canada

2 Department of Pharmacology and Physiology, Hôpital du Sacré-Cœur de Montréal Research

Center, Université de Montréal, Montréal, Canada

Short title: RV wall motion for RVEF in CMR

Word count: 3800

Corresponding author

Dr. Frédéric Poulin, Hôpital du Sacré-Coeur de Montréal,

5400 Gouin Blvd W., Montreal, Quebec, Canada, H4J 1C5

Telephone: (514) 338-2222; Fax: (514) 338-2381

Email: f.poulin@umontreal.ca

ABSTRACT 

Purpose:

Volumetric method in cardiac magnetic resonance (CMR), the reference standard for right

ventricular ejection fraction (RVEF), requires expertise due to the complex RV geometry and

anatomical landmarks. The aim of our retrospective study was to describe a new method to

evaluate RVEF based on the wall motion score index (WMSI) in CMR.

Methods:

Visual assessment of wall motion was performed using an 8-segment model (normokinesia=1,

hypokinesia=2, akinesia=3). Correlation between the WMSI (WMS/8) with the reference CMR

volumetric-RVEF was analysed. A regression equation was derived to convert the WMSI into

RVEF. Accuracy of CMR WMSI-derived RVEF compared to volumetric-RVEF was evaluated using

Bland-Altman analysis.

Results:

In the 112 patients using the volumetric CMR method, the mean RVEF was 48±14%. Fifty-nine

patients had normal RV kinetics (WMSI = 1) which corresponded to a volumetric-RVEF of 56%

(SD 7%; range from 43 to 76%). The WMSI showed a very strong correlation with the CMR

volumetric-RVEF (r=-0.85). A regression equation was created: RVEF = 80 – 22 X WMSI. Overall,

the WMSI-RVEF resulted in good agreement with CMR (mean bias 3%). We describe a second

method to derive RVEF based on segmental kinetics and attributing a value of 7% to

normokinetic, 4% to hypokinetic and 2% to akinetic segments with equivalent correlation and

accuracy. In addition, using a WMSI cut-off of ≥ 1.5 was highly accurate (92%) to predict a

reference RVEF of ˂ 45%, an important prognostic indicator in CMR.

Conclusion:

Our results suggest that using the WMS in CMR (8-segment) to estimate RVEF is accurate and

correlates well to the volumetric method. A wall motion score index ≥ 1.5 is optimal to

categorize patients in the higher-risk subset of CMR-RVEF ˂ 45%.

KEYWORDS

Right ventricle, ejection fraction, cardiac magnetic resonance, wall motion score

INTRODUCTION

The technological refinement of imaging modalities and emergence of newer techniques(1, 2)

for the evaluation of the right ventricle (RV) have contributed to reinforce its important

prognostic role in cardiovascular diseases. Free of geometric assumptions(3), cardiac magnetic

resonance (CMR) is the most accurate method to measure RV ejection fraction (RVEF) which

translates into several validated implications in clinical decision-making. (4-11)

The CMR evaluation of RVEF done by volumetric analysis using short and long axis views (3) is

robust but is time-consuming and requires careful attention to details in the endocardial

tracings. For the left ventricular ejection fraction, the wall motion score (WMS) method is a

simpler alternative that has been well validated using echocardiography (12) and CMR.(13)

The aim of this retrospective study is to develop a RV wall motion score index (WMSI) in CMR to

calculate the RVEF and correlate it to the volumetric RVEF.

MATERIAL AND METHODS

Study population

From March 2016 to March 2019, 112 randomly selected patients referred for CMR were

enrolled in the study. Patients with poor diagnostic quality of CMR images and insufficient

endocardial definition to allow RV kinetic evaluation were excluded. The study was approved

by our institution Research Ethics Board and all participants provided written informed consent.

CMR acquisition technique

All evaluations were performed using a 1.5-T CMR scanner (Magnetom Avanto, Siemens,

Erlangen, Germany). Eighteen-channel anterior and posterior phased-array coils were used for

signal acquisition. Balanced steady-state free precession (bSSFP) cine CMR images were

acquired over a single breath-hold using the following imaging parameters: repetition time (TR) 

< 4 ms; echo time (TE) 1.5 ms; flip angle 60; slice thickness 8–10 mm; matrix 192 x 256; field of

view 300–400 mm; and temporal resolution 30-40 ms. The following cine views were acquired:

LV 2-chamber, 4-chamber, 3-chamber, biventricular short axis (including 9–12 contiguous

ventricular slices), and RV outflow tract (RVOT).

CMR RV assessment

Volumetric RVEF

The entire short-axis stack was analysed offline with a computer analysis system (Circle

Cardiovascular Imaging, Calgary, Canada) dedicated to CMR for the measurement of RVEF by

the volumetric method, by tracing the endocardial outline at end-systole and end-diastole, as

recommended.(14)

WMS RVEF

Three standard short axis views were analysed from the short axis stack: basal (mitral level),

mid-ventricular (papillary muscle) and apical, as in the echocardiographic WMSI method. From

the nine slices covering RV and LV base to apex, we selected the most representative slice of RV

base, mid and apex. Visual semi quantitative assessment of regional wall motion and thickening

for WMSI was performed by an experienced cardiologist (RL) in a blinded fashion using an 8-

segment model (Figure 1). At the basal and mid-ventricular levels, the RV was divided into 3

segments and at the apical level it was divided into two segments. Each segment was graded

according to the following score: normal= 1, hypokinesia= 2, and akinesia= 3. The global WMS

was obtained by adding the score for each segment and the WMSI was calculated by dividing

the WMS by 8 (Figure 1).

Intraobserver and interobserver variability

Twenty randomly selected studies were reanalysed by the same operator several months after

the initial analysis. A second experienced observer (MP), also blinded to previously obtained

data, analysed the same loops for the assessment of interobserver variability of the CMR-WMS.

Statistical analysis

Categorical variables are expressed in frequency and percentages. Normality of distribution of

continuous variables are assessed with the Shapiro-Wilk test. Continuous variables are

described as mean ± standard deviation (SD) if the distribution was normal, otherwise as

median and interquartile range (IQR) (25th-75th). CMR-WMSI and CMR volumetric RVEF were

compared by linear regression analysis and Bland-Altman analysis. Correlation was assessed by

the Pearson correlation coefficient. A regression equation was derived to convert the WMSI

into RVEF using the volumetric CMR method as the reference standard.

A simplified formula to easily derive RVEF from the segmental kinetic data was conceived. The

new formula consisted of attributing an individual ejection fraction (%) to each RV segment

based on the WMS and adding all 8 segmental EF into a global RVEF. The simplified formula

was:

Simplified segmental EF method = WNormokinesia NN + WHypokinesia NH + WAkinesia NA

In which W is the segmental EF and Nx is the number of segments of each class. The weights

(W) of the simplified segmental EF method were determined by least square optimisation of

the concordance with CMR-RVEF, which were afterward rounded to the nearest integer. Using

Bland-Altman analysis, we evaluated systematic bias (using mean differences between

methods), SD of inter-method difference, and precision (range within which are 95% of values

of differences between methods, i.e. ±1.96 SD of differences between methods).

Based on a RVEF cut-off of ˂ 45%, which is supported in the literature as a prognostically

important value (4, 6-10, 15), the classification performance of the WMSI (discrimination

between normal, CMR RVEF ≥ 45% and abnormal CMR RVEF< 45%) was assessed by the positive

predictive value.

The intra- and inter-observer variability were evaluated with the intraclass correlation

coefficient. All statistical analyses were conducted using SPSS, version 25 (SPSS Inc., Chicago IL).

RESULTS

Diagnostic quality data were obtained in 112 subjects (mean age 56, range from 19 to 82 years,

38% female) with a mean volumetric CMR-RVEF of 48±14% (IQR 43-57%; range from 5 to 76%).

Participants were referred for assessment of non-ischemic (57%; ˃15 different diagnoses) or

ischemic (21%) cardiomyopathy, valvular diseases (8%), and other diagnoses (14%).

We observed a very strong linear correlation between CMR-WMSI and the volumetric CMR-

RVEF (r=-0.85) (Figure 2). The regression equation to derive RVEF based on the WMSI is:

WMS-derived RVEF = 80 – 22 x WMSI (Figure 3)

The mean RVEF obtained by the regression equation was 51% (SD 12%; range from 16 to 58%).

The RVEF corresponding to each WMS and WMSI according to the regression equation are

shown in Table 1. In our cohort, 8/8 normal segments (WMSI =1) correspond to a RVEF of 58%,

8/8 hypokinetic segments (WMSI = 2) to a RVEF of 36% and 8/8 akinetic segments (WMSI = of

3) to a RVEF of 14%.

Among our 112 patients, 59 patients had normal CMR RV wall motion (WMSI = 1). In those

patients, the corresponding volumetric-RVEF was 56% (SD 7%; range from 43 to 76%).

Analysis of systematic bias

Bland-Altman analysis showed good agreement between the WMSI-RVEF and volumetric CMR-

RVEF (mean RVEF bias = -3%) (Figure 4 and Table 2).

Analysis of precision

The SDs of the distribution of inter-method differences between the WMSI-RVEF and

volumetric CMR were acceptable. The SD was ± 7.5% (± 16% of the median CMR-RVEF).

Consequently, the 95% confidence interval of inter-method difference (±1.96 SD i.e. precision)

was 29.4% (Figure 4 and Table 2).

Optimal pathologic threshold in WMSI

The optimal threshold in WMSI to discriminate normal from pathologic patients (volumetric

CMR RVEF < 45%) was 1.5 (which corresponds to 2 akinetic or 4 hypokinetic segments in the 8-

segment model). It has a sensibility of 77%, a specificity of 98% and a positive predictive value

of 92%.

Simplified segmental 7-4-2% RVEF method (Score 7-4-2)

Based on the results of the regression analysis, we calculated a simpler method to derive RVEF

by attributing an individual EF of 7% to each normokinetic segment (normal WMS-RVEF =

58%/8 segments ≈7%/ segment); of 4% to hypokinetic segments (hypokinetic WMS-RVEF =

36%/8 segments≈4%/segment), and of 2% to akinetic segments (akinetic WMS-RVEF = 14%/8

segments ≈2%/ segment). Segmental EFs are then added to obtain global RVEF (Figure 5).

RVEF by Score 7-4-2= 7 NN + 4 NH +2 NA

In which Nbx is the number of segments of each class. This simplified method also correlated

well with the CMR-RVEF (r=0.85) with similar precision (mean difference between methods 1.3

± 7.4%) than the WMSI-derived RVEF. (not shown)

Reproducibility

Analysis of intra- and inter-observer variability for the WMS demonstrated good agreement

between observations (intra-observer intraclass correlation coefficient=0.93; inter-observer

intraclass correlation coefficient=0.85).

DISCUSSION 

In this study of patients with a broad range of RVEF and cardiac pathologies, the assessment of

RVEF in CMR using a simple 8-segment WMS in short-axis, similar to the echocardiographic

WMS for LVEF, resulted in accurate and precise estimation of RVEF compared to the reference

standard. This is a novel application of the WMS that allows a quicker method to provide a

reliable estimation of RVEF in CMR. The 7-4-2 score simplifies the calculation of the RVEF based

on the regional kinetic and has a very strong correlation to the CMR volumetric RVEF.

Because of the complex shape of the RV and its wall trabeculations, it may require extensive

manual adjustment of the endocardial contouring in both diastole and systole when using the

volumetric method in CMR. Studies have shown that the reproducibility of the manual RV

contouring by short-axis cine-CMR is not optimal, especially in the infundibulum and tricuspid

areas (basal tomographic plane).(16-18) While CMR-volumetric quantification is facilitated by

automatically generated contours, they have to be carefully reviewed by an expert. As opposed

to the multiple and complex segmentation for RV CMR analysis found in the literature (16, 19)

the WMS proposed herein using short-axis views is a simpler reproducible method with

unambiguous anatomic landmarks.

Absence of Wall Motion Abnormality

In our study, the absence of wall motion abnormality (WMA) (WMS = 8), the most common

finding, corresponded to a certain range of volumetric-RVEF (56%±7%; from 43 to 76%). This is

not surprising since the normal range of CMR volumetric-RVEF and the lower limits vary widely

in studies of normal subjects.

In the large Framingham Heart Study adult cohort (N=1336, 64±9 years, 43% men) free of

prevalent cardiovascular and pulmonary disease and with normal LV systolic function, mean

CMR-RVEF was 68 ± 6% in women and 64 ± 7% in men. The lower limits of normal were 57 and

52%, respectively.(20) In a second large UK biobank of 804 healthy participants of Caucasian

ethnicity (59±7 years, 46% men), mean CMR-RVEF was 58 ± 6% in women and 54 ± 6% in men.

The lower limits of normal were 47 and 45%, respectively.(21) The multiethnic study of

atherosclerosis (MESA), a large study of RV morphology in participants without cardiovascular

disease (N=4123, 62±10 years, 48% men), mean CMR-RVEF was 62 ± 11% in women and 72 ±

13% in men. The lower limits of normal were 40 and 47%, respectively.(22) Thus, in our

derivation cohort, the range of volumetric CMR RVEF obtained when the WMSI = 1 is similar to

what has been previously published.

Clinically Relevant WMS Threshold

While the determination of a clinically significant threshold in CMR WMS was beyond the scope

of our study, it has been demonstrated that CMR-RVEF ≤ 45% carries adverse implications in a

variety of cardiovascular diseases.(4, 6-10, 15) In our cohort, CMR-RVEF ≤ 45% was equivalent

to a WMS of ≥ 1.5 corresponding to a validated prognostic indicator with a good positive

predictive value (92%).

Wall Motion Score in CMR

Studies of RV wall motion assessment in CMR are scarce. In 65 healthy individuals, Quick et al.

have noticed a surprisingly high incidence of non-pathological wall motion disorders (91%),

especially dyskinesia, involving 2 or more segments in 60% of patients.(23) These WMA were

visible in the horizontal long axis and transverse planes but rarely depicted in the short-axis

plane. These findings are also concordant with the report by Sievers et al. of regional WMA

present in 27/29 healthy subjects. (24) The extent of these abnormalities was small and located

mostly around the moderator band. In our cohort, the 57 patients with normal CMR-RVEF

(≥50%) had no (n=34, 60%) or minimal WMA (1 WMA in 13, 23%; 2 WMA in 7, 12%; and 3 WMA

in 3 patients, 5%). The basal or mid- anterior segments accounted for 69% of the WMA

observed (data not shown). Our lower incidence of WMA in healthy patients is probably related

to the fact that our method uses only short-axis views to assess RVEF.

We have previously demonstrated the correlation between the RV WMS by echocardiography

and radionuclide angiography RVEF. (25) This study is the first to demonstrate a similar

correlation between the standard wall motion grading (normal, hypokinesia, akinesia) in short-

axis CMR views, comparable to the one used in echocardiography, and the volumetric-CMR

RVEF.

Limitations

This is a small derivation cohort with biases inherent to its retrospective nature. A validation in

a different and larger patient population would reinforce the findings, including the proposed

threshold of WMS ≥ 1.5. While we acknowledge that estimation of the WMA can be subjective,

our interobserver variability was good. This model of WMS is not designed for the evaluation of

hyperkinetic states or aneurysmal and dyskinetic segments. The incidence of aneurysmal and

dyskinetic segments in our cohort was insufficient to develop a distinct WMS. Thus, this

method might not apply to diseases such as arrhythmogenic RV cardiomyopathy. Finally, this is

not surprising in an unselected cohort that more than 50% of patients had no WMA. The

significant range of reference RVEF associated with visually unimpaired segmental RV kinetic

(WMS=1) depicts the concept of variability in the so-called normal RVEF (important load

dependency).

CONCLUSIONS

Our results suggest that using the WMS in CMR (8-segment model) to estimate RVEF is accurate

and correlates strongly with the volumetric method. A WMS index ≥ 1.5 is optimal to

categorize patients in the higher-risk subset of CMR-RVEF ˂ 45%. While these results require

further validation, the intuitive RV segmentation in short-axis, easy kinetic grading (normal,

hypokinesia, akinesia), and good reproducibility argue for a wider application of this method.

Declarations

ACKNOWLEDGEMENTS: We gratefully acknowledge Sylvie Loranger for secretarial assistance and Dr Reginald Nadeau for the careful assistance with the preparation and review of the manuscript.

FUNDING: None.

CONFLICTS OF INTEREST: None.

ETHICAL STANDARDSThe study was approved by our institution Research Ethics Board and all participants provided written informed consent.

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FIGURE LEGENDS

Figure 1: RV segmentation used in the wall motion score.

Legend: The RV short-axis views (A-C, A=basal level; B=mid-ventricular level; C=apical level) are

divided in 8 segments (D).

Figure 2. Linear regression analysis between the RV wall motion score index vs. CMR

volumetric-RVEF.

Legend: RV, right ventricle; CMR, cardiac magnetic resonance; RVEF, right ventricular ejection

fraction.

Figure 3. Linear regression analysis between the RV WMSI-RVEF wall motion score index vs.

CMR volumetric-RVEF.

Legend: RV, right ventricle; WMSI, wall motion score index; CMR, cardiac magnetic resonance;

RVEF, right ventricular ejection fraction.

Figure 4. Comparison between volumetric RVEF vs. WMSI-derived RVEF in CMR

Legend: RVEF, right ventricular ejection fraction; CMR, cardiac magnetic resonance; WMSI, wall

motion score index, SD, standard deviation.

Figure 5. Simplified segmental 7-4-2% RVEF method. Calculation tool in a patient with wall

motion abnormalities in the right coronary artery territory.

Legend: Global RVEF is obtained by multiplying the number of segments by the segmental EF

based on the wall motion, as depicted. In this patient, CMR-volumetric RVEF was 44%.

Table 1. The conversion of CMR WMS and WMSI into CMR-volumetric RVEF by the regression model.

WMS WMSI RVEF WMS WMSI RVEF

8 1 58 16 2 36

9 1,1 55 17 2,1 33

10 1,3 53 18 2,3 31

11 1,4 50 19 2,4 28

12 1,5 47 20 2,5 25

13 1,6 44 21 2,6 22

14 1,8 42 22 2,8 20

15 1,9 39 23 2,9 17

16 2 36 24 3 14

RVEF: right ventricular ejection fraction by volumetric cardiac magnetic resonance; WMSI: wall motion score index. Regression equation for the 112 patients was: CMR RVEF = 80 – 22 x WMSI.

Table 2. Comparison between volumetric RVEF vs. WMSI-derived RVEF in CMR

Mean difference between methods ± SD, %

Precision, %

CMR volumetric RVEF vs. WMSI-derived RVEF

-3.0 ± 7.5 29.4

RVEF, right ventricular ejection fraction; CMR, cardiac magnetic resonance; WMSI, wall motion score index

Figure 1: RV segmentation used in the wall motion score.

Figure 2. Linear regression analysis between the RV wall motion score index vs. CMR

volumetric-RVEF.

Figure 3. Linear regression analysis between the RV WMSI-RVEF wall motion score index vs.

CMR volumetric-RVEF.

Figure 4. Comparison between volumetric RVEF vs. WMSI-derived RVEF in CMR

Figure 5. Simplified segmental 7-4-2% RVEF method. Calculation tool in a patient with wall

motion abnormalities in the right coronary artery territory.