Identification of viable but dysfunctional myocardium after myocardial infarction is important for management, including the decision for revascularization. Assessment of infarct transmurality (TRM) by late contrast enhancement on magnetic resonance imaging (MRI) is frequently used for this task but has several limitations, particularly its availability. The goal of this study was to compare the value of several simple echocardiographic parameters measured at rest at the bedside for the identification of three degrees of infarct TRM, with contrast-enhanced MRI as the gold standard.
In a prospective, single-center study, 41 patients (33 men; mean age, 62 ± 10 years; 32 with ST-segment elevation infarctions) underwent resting echocardiography and contrast-enhanced MRI <5 days after infarction. Wall motion score, preejection velocity by tissue Doppler, and longitudinal, circumferential, and radial peak systolic strain by speckle-tracking-based strain imaging were assessed, and the findings were compared with infarct TRM stratified by contrast-enhanced MRI (no scar, 0% TRM; nontransmural scar, 1%–50% TRM; and transmural scar, 51%–100% TRM).
Four hundred segments showed no scar, 125 showed nontransmural scar, and 213 showed transmural scar on contrast-enhanced MRI. The sensitivity and specificity of visual wall motion scoring to detect any scar versus no scar were 71% and 81%, respectively, similar to values for circumferential strain (sensitivity and specificity both 81% with a cutoff of −14.5%). Longitudinal and radial strain performed less well, and the presence of preejection velocity performed distinctly worse (45% and 90%, respectively). The sensitivity and specificity for identifying nontransmural versus transmural infarction was better for circumferential strain (78% and 75%, respectively, with a cutoff of −10.5%) than for the other strain types, preejection velocity (52% and 67%, respectively), or visual wall motion scoring (50% and 81%, respectively, for a score > 2).
Visual wall motion analysis alone is able to detect infarcted myocardium but cannot differentiate sufficiently between transmural and nontransmural infarction. This is best achieved at the bedside using speckle-tracking-based circumferential strain.
Myocardial infarction leads to loss of myocytes, with loss of contractile function and the generation of a fibrous scar. The extent of scar transmurality has been shown to influence the degree of contractile dysfunction and to further predict the likelihood of regional contractile recovery either spontaneously or after revascularization. Scar transmurality is measurable on gadolinium-enhanced magnetic resonance images, but this technique is costly, is not readily available everywhere (in particular not at the bedside), and has limitations or contraindications in patients with arrhythmias, pacemakers or implanted internal cardioverter-defibrillators, or with advanced renal failure. Therefore, a bedside method to determine the chances of functional recovery of dyssynergic myocardium continues to be desirable. Stress echocardiography using pharmacologic or low-level exercise stress has been validated for this task, but it is time consuming and requires a high degree of expertise to interpret. In recent years, tissue velocity and deformation parameters measured using echocardiography have been correlated with myocardial scar transmurality by several groups. With the development of multidirectional strain analysis using speckle-tracking modalities, additional insights into regional deformation are available. Another recently proposed echocardiographic parameter for the assessment of the reversibility of regional contractile dysfunction is the myocardial preejection tissue velocity.
In this study, we compared the conventional wall motion score (WMS) by two-dimensional (2D) echocardiography, the presence of regional preejection tissue velocities by tissue Doppler, and regional myocardial deformation in the longitudinal, circumferential, and radial directions by speckle-tracking with scar transmurality by contrast-enhanced magnetic resonance imaging (MRI) as the surrogate reference standard for myocardial viability.
In a prospective, single-center study, 54 consecutive patients with acute myocardial infarctions with clearly present wall motion abnormalities on preliminary echocardiography who were sufficiently stable were examined. The diagnosis of myocardial infarction was made by clinical presentation, electrocardiographic findings, and troponin and creatine kinase elevations. All patients underwent successful acute primary percutaneous intervention with recanalization of the infarct-related coronary artery. Echocardiography was performed during the first 72 hours and MRI on days 3 to 5 after infarction. All patients were in stable sinus rhythm. All patients gave informed consent for the study. Thirteen patients were excluded from further analysis: in six patients, echocardiographic image quality was too poor for further analysis, four patients had contraindications to MRI (severe renal insufficiency, pacemaker), and MRI was terminated in three patients because of claustrophobia. Of the remaining 41 patients, 34 had ST-segment elevation infarctions, and seven had non–ST-segment elevation infarctions. Further characteristics of the patients are given in Table 1 .
|Age (y)||62 ± 10|
|Infarct type (STEMI/NSTEMI)||7 (17%)/34 (83%)|
|Maximal creatine kinase (U/L)||2,483 ± 2,146|
|Maximal troponin I (ng/mL)||64 ± 38|
|Ejection fraction (echocardiography) (%)||46 ± 16|
|Family history of myocardial infarction||15 (37%)|
|3-vessel disease||15 (37%)|
|2-vessel disease||11 (26%)|
|1-vessel disease||15 (37%)|
|Previous myocardial infarction (all in regions remote from index infarction)||9 (22%)|
Follow-up to ascertain survival was obtained by telephone calls to practitioners caring for the patients or to the patients themselves.
Transthoracic echocardiography was performed using a Vivid 7 system (GE Healthcare, Solingen, Germany) with patients in the left lateral decubitus position. A 4-MHz center frequency transducer (M4S) was used. The frame rate was between 70 and 100 frames/sec. Electrocardiographically triggered digital loops, each with three consecutive cardiac cycles and acquired during an end-expiratory breath-hold, were stored at the original frame rate in proprietary image storage and analysis software (EchoPAC; GE Healthcare). The three standard apical views and three short-axis views of the left ventricle (basal, midpapillary, and apical) were recorded in 2D and tissue color Doppler modes, the latter with frame rates > 120 frames/sec. Using the EchoPAC Dimension 06 software, the data were processed and analyzed offline. On the basis of an 18-segment model of the left ventricle (six basal, six middle, and six apical segments), we first assessed segmental left ventricular function visually by determining a WMS for each segment (1 = normokinetic, 2 = hypokinetic, 3 = akinetic, and 4 = dyskinetic).
Strain Imaging by Speckle-Tracking
Each of the 18 segments was analyzed for regional deformation (“2D strain”) using speckle-tracking analysis: longitudinal strain (LS) was measured in the three apical views. Radial strain (RS) and circumferential strain (CS) were measured in a basal, midpapillary, and apical parasternal view. The software automatically marked myocardial segments that were not evaluable, and the curves were checked by an experienced examiner for plausibility. All segments that were not evaluable were excluded from further analysis. Peak systolic strain was measured separately from each curve by the investigator, who was blinded to the MRI results.
Preejection velocity (PEV) is a short-lived positive myocardial tissue velocity during the isovolumetric contraction phase before ejection. Aortic valve opening determined by continuous-wave Doppler was used to define the beginning of the ejection, and PEV was defined as any positive longitudinal tissue velocity above the noise level during the time interval from the beginning of the QRS complex on the electrocardiogram to the time point of aortic valve opening. Each of the 18 segments in the apical tissue Doppler cine-loops was investigated with regard to the presence of PEV.
MRI was performed using a 1.5-T Avanto system (Siemens Healthcare, Erlangen, Germany) as a reference standard for scar transmurality. For detection of late enhancement, a gadolinium contrast agent was used. MRI analysis was performed by a second, blinded investigator who used the same 18-segment model of the left ventricle as used in the echocardiographic analysis, with corresponding short-axis cross-sections. Segments were divided into three groups according to the fraction of wall thickness occupied on average in each segment by late enhancement: none (0%), nontransmural (1%–50%), or transmural (51%–100%).
Peak systolic strain values were correlated with the transmural extent of myocardial scar by late enhancement on MRI, stratified into the described three subgroups. The presence of PEV was rated as none or nontransmural infarction, and the absence of PEV was rated as transmural scar. Concerning wall motion, a normokinetic wall was rated as a segment without infarction, a hypokinetic wall as nontransmural infarction, and an akinetic or a dyskinetic wall as transmural infarction. All data are expressed as means ± SD. The statistical analysis was performed using SPSS Statistics version 19 (IBM, Armonk, NY) and Excel 2010 (Microsoft Corporation, Redmond, WA). P values < .05 were considered significant. Bonferroni’s correction was used to correct for multiple comparisons. Receiver operating characteristic curves were constructed and areas under the curves compared to analyze how well strain data classified segments as transmurally or nontransmurally scarred on MRI, and optimal cutoffs were determined. To determine whether the results of the strain analyses differed by left ventricular wall, we calculated receiver operating characteristic curves for each wall (septal, anteroseptal, anterior, lateral, posterior, and inferior) and each level (basal, middle, and apical) separately. All comparisons were performed by segments, not patients. Furthermore, we calculated the category-free net reclassification improvement for the addition of CS to WMS to predict infarct transmurality.
By 2D echocardiography, WMS could be determined in all 738 segments. Four hundred ten segments were normokinetic, 190 segments were hypokinetic, 116 segments were akinetic, and 22 segments were dyskinetic. Measurement of LS was possible in 699 segments, of RS in 613 segments, and of CS in 659 segments. PEV was assessable in 734 segments; it was present in 538 segments and absent in 196 segments.
By MRI, all 738 segments were evaluable for late enhancement: 400 had no late enhancement (normal), 125 showed delayed enhancement of 1% to 50% transmurality, and 213 segments showed 51% to 100% transmurality.
Comparison of Echocardiography and MRI
A representative example of corresponding echocardiographic and MRI data is presented in Figure 1 . The relation of visual wall motion analysis to the three categories of scar transmurality by MRI is shown in Figure 2 . The relations of longitudinal, radial, and circumferential peak systolic strain values to the three categories of scar transmurality by MRI are shown in Figure 3 . The relation of PEV to MRI-based scar transmurality is shown in Figure 4 .
The ability of the different echocardiographic parameters to discriminate among 0% (no scar at all) versus 1% to 100% MRI transmurality (any scar), 1% to 50% (nontransmural scar) versus 51% to 100% MRI transmurality (transmural scar), and 0% (no scar at all) versus 51% to 100% MRI transmurality (transmural scar) was analyzed using receiver operating characteristic curves and characterized by their areas under the curves and best cutoffs of the respective parameters for discrimination.
Table 2 shows the discriminatory ability of the three types of myocardial strain for separating nontransmural from transmural scar, separated for left ventricular walls as well as ( Table 3 ) for the apical, middle, and basal segmental levels. Note that we use the inequality operators with regard to the absolute strain values, regardless of sign.
|LS||0.68 (.08)||0.72 (.05)||0.68 (.07)||0.74 (.01)||0.74 (.00)||0.72 (.02)|
|RS||0.59 (.38)||0.66 (.17)||0.66 (.11)||0.70 (.02)||0.63 (.09)||0.57 (.49)|
|CS||0.66 (.12)||0.77 (.02)||0.73 (.02)||0.89 (.001)||0.77 (.00)||0.73 (.02)|
|LS||0.65 (.03)||0.64 (.02)||0.77 (.001)|
|RS||0.60 (.15)||0.65 (.01)||0.70 (.001)|
|CS||0.82 (.001)||0.79 (.001)||0.81 (.001)|
Table 4 shows the discriminatory ability of each echocardiographic parameter to separate no scar at all from any scar (1%–100% transmurality). Table 5 shows the discriminatory ability of each echocardiographic parameter to separate nontransmural scar (1%–50% transmurality) from transmural scar (51%–100% transmurality), and Table 6 displays the discriminatory ability of each echocardiographic parameter to separate no scar from transmural (51%–100% transmurality) scar. For all of these predictions, CS showed the highest area under the curve, although differences from other parameters were not always significant (see Tables 4–6 ).
|Variable||AUC||Cutoff||Sensitivity (%) (95% CI)||Specificity (%) (95% CI)|
|LS||0.81 ± 0.02||−13.5%||71 (66–76)||75 (71–79)|
|RS||0.77 ± 0.02||27.5%||71 (66–77)||66 (61–71)|
|CS||0.86 ± 0.01||−14.5%||81 (78–84)||81 (78–84)|
|WMS||0.82 ± 0.02||>1||77 (72–81)||81 (77–85)|
|PEV (−)||0.67 ± 0.02||Presence||45 (40–50)||90 (87–93)|