Summary
Background
Left ventricular ejection fraction (LVEF) is an important indicator of left ventricular function and of the severity and prognosis of ischaemic heart disease. Assessment of regional function using the wall motion score index (WMSI) is an alternative means of evaluating left ventricular function.
Aim
We attempted to evaluate LVEF by a method using the WMSI with cardiac magnetic resonance imaging (MRI).
Methods
One hundred and twenty-two patients referred for evaluation of heart disease had rest WMSI evaluation by cardiac MRI. The WMSI was evaluated using the 16-segment model and score proposed by the American Society of Echocardiography. In our first group of 80 patients, a correlation between WMSI and cardiac MRI LVEF was established and a regression equation was derived. This regression equation was then used in 42 consecutive patients to compare WMSI LVEF with the gold standard MRI LVEF.
Results
In the first 80 patients, MRI LVEF and WMSI correlated very well ( r = 0.93). Similarly, in the second group of 42 patients, WMSI LVEF derived from the regression equation correlated very well with MRI LVEF ( r = 0.94).
Conclusion
An objective evaluation of LVEF can be easily made using the WMSI with cardiac MRI, which correlates very well with standard MRI planimetric methods.
Résumé
Contexte
La fraction d’éjection du ventricule gauche (FEVG) est un important indicateur de la fonction ventriculaire gauche, de la sévérité et du pronostic de la maladie cardiaque ischémique. L’évaluation de la fonction régionale du VG en utilisant le score de contractilité régionale ou “wall motion score index” (WMSI) permet une évaluation alternative de la fonction du VG.
Objectif
Évaluer la FEVG en utilisant le WMSI en résonance magnétique cardiaque (RMC).
Méthodes
Cent vingt-deux patients référés pour évaluation de cardiopathie ont eu une RMC de repos pour évaluer leur fonction VG. Le score de contractilité régionale (WMSI) a été évalué en utilisant le modèle de 16 segments proposé par l’American Society of Echocardiography. D’un premier groupe de 80 patients, une corrélation entre le WMSI et l’évaluation de la FEVG par planimétrie à la RMC a été effectuée. Une équation de régression en a été déduite et fut utilisée dans un second groupe de 42 patients consécutifs. Les résultats furent comparés au gold standard , soit le calcul de la FEVG par planimétrie en RMC.
Résultats
Chez les 80 premier patients, la FEVG par RMC et le WMSI avaient une excellente corrélation ( r = 0,93). Dans le second groupe de 42 patients, la FEVG dérivée de l’équation de régression était corrélé aussi très bien avec la FEVG par planimétrie à la RMC ( r = 0,94).
Conclusion
Une évaluation de la FEVG peut être facilement effectuée en utilisant le WMSI en RMC et corrèle très bien avec les méthodes de planimétrie en RMC.
Background
LV systolic function is a major determinant of cardiac performance and LVEF is widely used as an index of systolic function in the management of cardiac patients. Echocardiography and RNA are the more commonly used techniques for estimation of LVEF. Echocardiographic analysis can be performed by simple visual assessment or more quantitative methods. One semi quantitative method separately grades different LV segments to obtain a global score of LV function or WMSI. The relationship between echocardiography-derived WMSI and LVEF has been studied previously. The objective of this study was to derive a similar WMSI LVEF using cardiac MRI and to compare its accuracy in determining LVEF.
Methods
Study population
From April to July 2009, 122 patients referred for cardiac MRI were enrolled in the study. Stress testing with dipyridamole was performed in 56 patients. Patients had to have sufficient image quality (i.e. good endocardial definition) to allow evaluation of LV function. Patients with significant valvular disease, hypertrophic cardiomyopathy or congenital heart disease were excluded from the study because of the unusual LV morphology, which is inappropriate for the classical geometric formula used in the planimetric method. To see if a difference between the WMSI and MRI LVEF would cause a change in classification (i.e. moderate LV dysfunction classified as severe, or normal LV function classified as mildly abnormal), patients were separated into the following subgroups according to LVEF: severely abnormal LV function with LVEF ≤ 30%; moderately abnormal LV function with LVEF 31–44%; mildly abnormal LV function with LVEF 45–54%; and normal LV function with LVEF ≥ 55%.
Cardiac MRI technique
For the assessment of LV function, images were acquired during multiple breath-holds using a 1.5-T whole-body magnet (Magnetom Espree, Siemens, Erlangen, Germany). Sixteen-channel anterior and posterior phased-array coils were used for signal acquisition. We used an electrocardiogram-triggered segmented K-space SSFP cine MRI pulse sequence. After scout images were completed, a stack of three base-to-apex short-axis cross-sectional SSFP cine MRI scans were performed, one at the base, one at the mid-ventricular level and one at the apex of the left ventricle. Each slice was acquired during one short breath-hold (7 to 12 seconds each, depending on heart rate). Scanner settings were as follows: field of view typically in the range of 300–360 mm; slice thickness, 6 mm; TR, 3.1 ms; TE, 1.6 ms; flip angle, 60 degrees; and image matrix 256 × 160. Temporal resolution was typically between 30 and 40 ms.
Cardiac MRI study
We used three standard short-axis views from the short-axis stack for analysis: basal (mitral level), mid-ventricular (papillary muscle) and apical, as used in the echocardiographic WMSI method. We then analyze the entire short-axis stack offline with the Siemens computer analysis system for calculations of LVEF, by tracing the endocardial outline at end-systole and end-diastole. End-systole was defined as the frame with the smallest cavity area and end-diastole as the frame with the largest LV cavity area. Visual semi quantitative assessment of regional wall motion and thickening for WMSI was performed by an experienced cardiologist in a blinded fashion. We used the 16-segment model recommended by the ASE . The 17-segment model, recommended for perfusion by the ASE and the European Society of Cardiology , was not used because the 16-segment model is more appropriate for evaluation of wall motion abnormalities as the tip of the normal apex (segment 17) does not move. At the basal and mid-ventricular levels, the left ventricle was divided into six segments and at the apical level it was divided into four segments ( Fig. 1 ). The score for each segment was graded according to the following system: normal, 1; hypokinesia, 2; akinesia, 3; dyskinesia, 4. Adequate visualization of all 16-segments was required for assessment of WMSI. The total wall motion score (WMS) was obtained by adding the score for each segment. The WMSI was calculated by dividing the total wall motion score by 16, as shown in Fig. 1 .
Statistical analysis
Data obtained for WMSI and MRI LVEF were compared by linear regression analysis. Correlation was assessed using the Pearson correlation coefficient. Intraclass correlation was calculated to assess agreement between the two methods. The interobserver and intraobserver variabilities were assessed using linear regression analysis and by calculating average percentage differences.
Results
The study population was composed of 82 men and 40 women, with ages ranging from 38 to 89 years (mean 65 years). Most of the patients were referred for evaluation of chronic ischaemic heart disease (72%), evaluation of non-ischaemic cardiomyopathy (24%) or other pathologies (4%).
In the initial cohort of 80 subjects, we observed a linear correlation between WMSI and the MRI LVEF calculated offline. Using regression analysis, the correlation coefficient between cardiac MRI LVEF and WMSI was calculated to be r = 0.93. The formula derived from this regression equation (MRI LVEF = 0.879–[0.244 × WMSI]) was then validated in the second cohort of 42 patients. The correlation between the WMSI and MRI LVEF was excellent, with a correlation coefficient of 0.94.
The estimation of LVEF according to WMS and WMSI is shown in Table 1 . Table 2 shows WMSI LVEF by MRI and WMSI LVEF from two echocardiography studies. Table 3 shows the correlation between MRI LVEF and WMSI LVEF according to LVEF classification (mild, moderate or severe LV dysfunction and normal LV function). The correlation between MRI LVEF and WMSI is shown in Fig. 2 and the Bland-Altman analysis is shown in Fig. 3 .
| WMS (WMSI) | LVEF (%) | WMS (WMSI) | LVEF (%) | WMS (WMSI) | LVEF (%) |
|---|---|---|---|---|---|
| 16 (1.0) | 64 | 27 (1.7) | 46 | 38 (2.4) | 28 |
| 17 (1.1) | 62 | 28 (1.8) | 45 | 39 (2.4) | 27 |
| 18 (1.1) | 61 | 29 (1.8) | 43 | 40 (2.5) | 25 |
| 19 (1.2) | 59 | 30 (1.9) | 41 | 41 (2.6) | 23 |
| 20 (1.3) | 58 | 31 (1.9) | 40 | 42 (2.6) | 22 |
| 21 (1.3) | 56 | 32 (2.0) | 38 | 43 (2.7) | 20 |
| 22 (1.4) | 54 | 33 (2.1) | 36 | 44 (2.8) | 19 |
| 23 (1.4) | 53 | 34 (2.1) | 35 | 45 (2.8) | 17 |
| 24 (1.5) | 51 | 35 (2.2) | 33 | 46 (2.9) | 15 |
| 25 (1.6) | 49 | 36 (2.3) | 31 | 47 (2.9) | 14 |
| 26 (1.6) | 48 | 37 (2.3) | 30 | 48 (3.0) | 12 |
| WMSI | ECHO LVEF (Lebeau; n = 243) | ECHO LVEF (Moller; n = 767) | MRI LVEF ( n = 122) |
|---|---|---|---|
| 1.0 | 67 | 64 | 64 |
| 1.1 | 65 | 62 | 62 |
| 1.2 | 62 | 59 | 59 |
| 1.3 | 61 | 56 | 56 |
| 1.4 | 57 | 54 | 54 |
| 1.5 | 54 | 51 | 51 |
| 1.6 | 53 | 48 | 48 |
| 1.7 | 50 | 46 | 46 |
| 1.8 | 47 | 43 | 43 |
| 1.9 | 44 | 41 | 41 |
| 2.0 | 41 | 38 | 38 |
| 2.1 | 39 | 35 | 35 |
| 2.2 | 36 | 33 | 33 |
| 2.3 | 34 | 30 | 30 |
| 2.4 | 31 | 28 | 28 |
| 2.5 | 28 | 25 | 25 |
| 2.6 | 26 | 22 | 22 |
| 2.7 | 24 | 20 | 20 |
| 2.8 | 21 | 17 | 17 |
| 2.9 | 18 | 14 | 14 |
| 3.0 | 15 | 12 | 12 |
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