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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 29  |  Issue : 4  |  Page : 156-164

Transmural extent in relation to clinical scoring in non-ST elevation myocardial infarction patients: Speckle-tracking echocardiographic study


Department of Cardiovascular, Faculty of Medicine, Zagazig University, Zagazig, Egypt

Date of Web Publication27-Jan-2020

Correspondence Address:
Hanan Ibrahim Radwan
Department of Cardiovascular, Faculty of Medicine, Zagazig University, Sharkia Governorate, Zagazig
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jcecho.jcecho_54_19

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  Abstract 


Background: To assess the extent of transmurality in non-ST elevation myocardial infarction (NSTEMI) patients using speckle-tracking echocardiography (STE) in relation to their risk categorization to improve the risk stratification of NSTEMI patients through detecting the presence of transmural infarction. Patients and Methods: It included 96 patients with NSTEMI. All patients were subjected to GRACE score (GS) calculation, transthoracic and speckle-tracking echocardiography (STE): To detect left ventricular ejection fraction and myocardial global longitudinal strain [GLS]and circumferential strain [CS]. Results: As compared to low-GS group; high-risk group was older with the increased prevalence of hypertension (HTN), diabetes, and smoking. There was no significant difference between both groups regarding LS and CS of all 17 segments except for apex where longitudinal strain (LS) was significantly decreased in low-risk group (−17.2 ± 1.1) as compared to high-risk group (−18.6 ± 1.4). GLS was significantly decreased in high-risk group (15.4 ± 0.6) as compared to low-risk group (16 ± 0.8), P = 0.02 with no significant difference in the global CS (P = 0.8). Transmural infarction constitutes 37.5% of all patients. The prevalence of transmural infarction was increased in the low-risk group without significant difference. GS showed a positive correlation with age, male, HTN, diabetes, and smoking and negative correlation with GLS. There was no significant correlation between GS and global CS. Age, GS, and LS were significantly related to transmural infarction. None was found to predict the occurrence of transmural infarction. Conclusion: Transmural extent as detected by STE had been found in a relatively substantial number of patients with NSTEMI, and it may serve as a tool in conjunction with risk stratification scores for the selection of high-risk patients.

Keywords: GRACE score, non-ST elevation myocardial infarction, speckle-tracking echocardiography, transmural extent


How to cite this article:
Radwan HI, Hussein EM, Shaker A. Transmural extent in relation to clinical scoring in non-ST elevation myocardial infarction patients: Speckle-tracking echocardiographic study. J Cardiovasc Echography 2019;29:156-64

How to cite this URL:
Radwan HI, Hussein EM, Shaker A. Transmural extent in relation to clinical scoring in non-ST elevation myocardial infarction patients: Speckle-tracking echocardiographic study. J Cardiovasc Echography [serial online] 2019 [cited 2020 Nov 28];29:156-64. Available from: https://www.jcecho.org/text.asp?2019/29/4/156/276899




  Introduction Top


There was a general perception, that ST-elevation myocardial infarction (STEMI) is associated with transmural ischemia, while non-ST elevation myocardial infarction (NSTEMI) is associated with nontransmural subendocardial ischemia. However, STEMI/NSTEMI based on the electrocardiographic classification had shown to characterize the total size of myocardial infarction (MI) rather than the transmural extent (TME) as assessed by cardiac magnetic resonance.[1] Transmural MI without invasive treatment is strongly linked to adverse long-term outcomes in NSTEMI patients.[2] On the other hand, as NSTEMI patients constitute a nonhomogeneous problem, the American Heart Association/American College of Cardiology and European Society of Cardiology guidelines support the invasive approach in high-risk NSTEMI patients and the conservative strategy for low-risk NSTEMI patients.[3] Myocardial deformation (strain) imaging either derived from color-coded tissue Doppler imaging or from two-dimensional (2D) speckle-tracking echocardiography (STE) offers enhanced quantification of global as well as segmental function. The main advantage of STE over the Doppler-based technique is its lack of dependence on the ultrasound insonation angle.[4] Transmural and subendocardial infarct segments were found to have similar radial and longitudinal strain (LS), while transmural infarct segments had lower circumferential strain than subendocardial infarcts.[5] Our objective is to assess the extent of transmurality in NSTEMI patients using STE in relation to their risk categorization to improve the risk stratification of NSTEMI patients through detecting the presence of transmural infarction in such patients, thus optimizing their management.


  Patients and Methods Top


Patients

The cross-sectional study carried out in the Cardiology Department, Zagazig University Hospitals, from February 2016 to September 2017. It included 96 patients with NSTEMI. NSTEMI was defined as elevation in cardiac markers without ST-segment elevation in patients presenting with ischemic chest pain.[6] Patients with previous revascularization, history of old MI, rheumatic heart disease, heart muscle disease, rhythm disturbance, conduction defect, and poor echogenic window were excluded from the study. Our study included 96 patients with NSTEMI who were classified into two groups according to GRACE score (GS); high-risk group (GS >140) which included 30 patients (31%) and low-intermediate group (GS <140) which included 66 patients (69%).

Methods

All patients were subjected to the following: complete history taking with special emphasis to coronary artery disease (CAD) risk factors such as hypertension (HTN), diabetes mellitus, dyslipidemia, smoking, and family history of ischemic heart disease or sudden cardiac death. Also history of chest pain or dyspnea or hemodynamic instability. Electrocardiogram (ECG): To detect ST-segment depression or T wave inversion and detect its site. Laboratory investigations: with special emphasis to cardiac markers (Troponin, CK-MB). GS was detected for each patient [Figure 1]. Transthoracic echocardiography: Examination was done by using General Electric VIVID 9 with M4S transducer, with a frequency of 1.5–4.3 MHz and high frame rate (60–90 frame/s), examinations included measurements of cardiac dimensions and left ventricular (LV) ejection fraction. Speckle-tracking echocardiography: Three-dimensional grayscale images were acquired in the apical four-chamber, apical two-chamber, apical long-axis, and mid-ventricular short-axis views. Echo was done during hospital admission within 3–4 days after admission. Digital storage of cardiac cycles triggered to the QRS complex was saved for offline analysis. The left ventricle was analyzed using a 17-segment model. The endocardial borders were traced at the end-systolic frame from the three apical views and mid-ventricular short-axis views, and an automated tracking algorithm outlined the myocardium in successive frames throughout the cardiac cycle. After the tracking, quality was verified for each segment (with subsequent manual adjustment of the region of interest [ROI] if necessary), myocardial motion was analyzed by speckle-tracking within the ROI bounded by endocardial and epicardial borders [Figure 2]. Myocardial longitudinal, circumferential, and radial strain and strain-rate profiles were obtained and both peak systolic strain and strain-rate values were measured[7] [Figure 3].
Figure 1: Online calculation of GRACE score, assessment the risk of 1 year, 3 years mortality, and 1 year death or myocardial infarction (http://gracescore.org)

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Figure 2: Segmentation of the region of interest in apical views

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Figure 3: Different components of left ventricular myocardial deformation that can be measured by speckle-tracking echocardiography (Dandel et al., 2009)

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How to obtain strain parameters

Image acquisition

Images for speckle-tracking echocardiographic analysis, currently performed offline, are obtained and recorded by using conventional 2D grayscale echocardiography during breath holding with stable electrocardiographic tracing. Care must be taken to obtain true apical and short-axis images using standard anatomic landmarks in each view and to avoid foreshortening of the analyzed myocardial structure, thus allowing a more reliable delineation of the endocardial border. The optimal frame rate for the 2D image acquisition is set between 60 and 110 frames per se cond.[8],[9] These settings are recommended to combine high temporal resolution with acceptable spatial definition and to enhance the feasibility of the frame-to-frame tracking technique. We begin with an apical long-axis-chamber view for speckle-tracking analysis to select the frame corresponding to the aortic valve closure, which is a useful reference for the subsequent analysis. Apical four- and two-chamber view acquisitions are necessary for LS analysis. Short-axis recordings, useful for radial strain, circumferential strain, and rotation analysis, are obtained from a standard parasternal probe position for the basal plane and from a more distal anterior or anterolateral position for the apical plane. To standardize acquisitions, the basal plane is identified as the plane, including the tips of the mitral leaflets, whereas the apical plane is identified distally to the papillary muscles as the plane just proximal to the level at which LV cavity end-systolic obliteration occurs.[10]

Offline analysis

Recordings are processed using specific acoustic-tracking software usually available on dedicated workstations, allowing for an offline semi-automated analysis of speckle-based strain. The endocardial surface of the myocardial segment analyzed is manually traced in apical and/or short-axis views by a point-and-click approach. An epicardial surface tracing is then automatically generated by the system, thus creating a ROI. After manual adjustment of the ROI width and shape, the software automatically divides the ROI into six segments, and the resulting tracking quality for each segment is automatically scored as either acceptable or unacceptable, with the possibility of further manual correction. Segments for which no adequate image quality can be obtained are rejected by the software and excluded from the analysis. Finally, once the ROI is optimized, the software generates strain curves for each selected myocardial segment. From these curves, the operator can obtain regional and global (by averaging values observed in all segments) peak and time-to-peak values [Figure 3] and [Figure 4]. If the LS analysis is performed in all three apical views, the software automatically generates a topographic representation of all 17 analyzed segments. With a simple input, the operator can also obtain the LS time to peak and the postsystolic index (i.e., the percentage of the postsystolic strain value compared to the maximum strain peak of the evaluated segment), both shown to be useful in preliminary studies for the analysis and detection of potentially ischemic or dyssynchronous myocardial areas.[11] Interpretation: The normal global longitudinal strain (GLS) is usually in the range of −17%–−18% or more (i.e., more negative). The circumferential strain is usually greater than the LS with average values in excess of − 20%.[12] Transmural infarct segments had lower circumferential strain <20% and lower LS <−17%. While subendocardial (nontransmural) infarct segments had only lower LS <−16% with normal circumferential strain >20%.[5]
Figure 4: Speckle-tracking echocardiography, measurement of longitudinal strain (a) The endocardial border is manually traced in the end-systolic frame. The automated software creates a region-of-interest that includes the entire myocardial thickness. (b) The operator is prompted to review and approve the adequacy of tracking for each segment (c) The final strain curves. Color-coded curves depict segmental strain whereas the dotted white curve depicts the average strain. The lower left corner shows the parametric image, displaying the timing and the magnitude of segmental longitudinal strain.[12]

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Ethics

Human rights statements and informed consent: All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1964 and later revisions. Informed consent was obtained from all the patients for being included in the study.

Statistical analysis

The collected data were revised, coded, tabulated, and introduced to a PC using Statistical Package for the Social Science (SPSS 15.0.1 for Windows; SPSS Inc., Chicago, IL, USA, 2001). Data were presented and suitable analysis was done according to the type of data obtained for each parameter. Continuous variables were expressed as mean ± standard deviation; categorical variables were expressed as percentages. Independent t-test was used to compare means. Chi-square test was used to compare percentages. Correlation analysis (using Pearson's method and Spearman's method): Multivariate analysis investigated parameters were entered into a logistic regression model to determine which of these factors is considered as a significant risk factor and identify its risk estimate (odds ratio and 95% confidence interval). P < 0.05 was considered statistically significant and P < 0.001 was considered highly significant.


  Results Top


Baseline characteristics of the studied population [Table 1] showed male preponderance of the studied population (66.7%) with the increased prevalence of dyslipidemia (69%), diabetes (65%), smoking (56%), and HTN (52%) in order. The prevalence of transmural infarction constitutes 37.5% of the studied population, and the prevalence of nontransmural infarction constitutes 62.5% of the studied population. GLS ranged from −14.21 to −17.87 with mean −15.8 ± 0.83. Global Circumferential strain ranged from −25.65 to −33.93 with mean −31.2 ± 1.9. Our NSTEMI patients were classified into two groups according to GS to predict in-hospital mortality; high-risk group (GS >140) which included 30 patients (31%) and low-intermediate group (GS <140) which included 66 patients (69%).
Table 1: Sociodemographic characteristics of the studied population

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Sociodemographic characteristics of the studied groups

As compared to low-intermediate group, high-risk group were older (60.0 ± 5.6 vs. 53.4 ± 9, P = 0.002); with increased prevalence of HTN (86.7% vs. 39.4%, P = 0.009), diabetes (86.7% vs. 54.5%, P = 0.03), and smoking (80% vs. 45.5%, P = 0.02). There was no significant difference between both groups regarding sex distribution and dyslipidemia prevalence (P > 0.05) [Table 2].
Table 2: Sociodemographic characteristics of the studied groups

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Longitudinal and circumferential strain derived by speckle-tracking echocardiography

The high-risk group showed significant decrease of LS of mid anterior, basal inferior, mid inferior, and apical inferior, while the low-intermediate-risk group showed significant decrease of LS of mid anterolateral, apical lateral, and apex. Overall, the GLS was statistically significantly (P = 0.02) decreased in high-risk group (15.4 ± 0.6) as compared to low-intermediate-risk group (16± 0.8). On the other hand, the high-risk group showed significant decrease of chondroitin sulfate (CS) of mid anterior, while there was no significant difference between both groups regarding the global CS (31.3 ± 1.6 and 31.2 ± 2.0, P = 0.8). The prevalence of transmural infarction was increased in the low-intermediate-risk group without achieving significant difference as compared to the high-risk group (P = 0.09). Hence, we found insignificant increase of transmural infarction and insignificant difference of global CS between both groups, while LS was significantly decreased in high-risk group as compared to low-intermediate-risk group, suggesting increased nontransmural infarction in high-risk group and comparable the prevalence of transmural and nontransmural infarction in low-intermediate group [Table 3], [Table 4] and [Figure 5], [Figure 6].
Table 3: Apical three-chamber view and two-chamber view speckle-tracking echocardiography segmental longitudinal and circumferential strain of the studied patients

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Table 4: Apical four-chamber view and global speckle-tracking echocardiography global longitudinal and circumferential strain of the studied patients

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Figure 5: Speckle tracking echocardiography in pt with high GRACE score (251), right panel: Measurement of longitudinal strain: bull's eye. Impaired longitudinal strain in all segments. Left panel: Measurement of circumferential strain: bull's eye. Impaired circumferential strain in all segments

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Figure 6: Speckle-tracking echocardiography of pt with low GRACE score (111), Right panel: Measurement of global longitudinal strain, bull's eye. Left panel: Measurement of circumferential strain: bull's eye. Normal circumferential strain in all segments

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Correlation between GRACE score and other variables

GS showed a positive correlation with age (r = 0.466, P = 0.001), male gender (r = 0.359, P = 0.012), HTN (r = 0.405, P = 0.004), diabetes (r = 0.388, P = 0.006), and smoking (r = 0.420, P = 0.003). GS showed significant negative correlation with the GLS (r = −0.547, P = 0.000). There was no significant correlation between GS and global CS (r = 0.036, P = 0.8) [Table 5] and [Figure 7] and [Figure 8].
Table 5: Correlation between GRACE score and other variables

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Figure 7: Negative correlation between GRACE score and LS (r = −0.55, P = 0.000)

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Figure 8: Positive correlation between GRACE score and age, smoking, hypertension, and diabetes

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Univariate and multivariate analysis to predict transmural infarction

Age, GS, and LS were significantly related to transmural infarction (P = 0.002, 0.001, and 0.03, respectively). None was found to predict the occurrence of transmural infarction by multivariate analysis [Table 6] and [Table 7].
Table 6: Univariate analysis to predict transmural infarction

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Table 7: Logistic regression for predicators of transmural infraction

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  Discussion Top


Transmural and nontransmural are morphologic terms used widely to distinguish patients with MI; the identification of TME of MI is clinically implicated in both management and prognosis. TME is associated with a poor prognosis and more adverse cardiac events which necessitate early invasive intervention. Thanavaro et al.[13] found that patients with nontransmural infarction had a significantly lower mortality (3% vs. 11%) and a lower prevalence of premature ventricular complexes (81% vs. 88%). It was found that the extent of the infarction correlates with an increasing risk of events.[2]

In STEMI, the lack of ST-segment elevation reduction is accompanied with more extensive myocardial injury and more transmural infarction which results in worse prognosis.[14] Unfortunately, in non-ST-segment MI, no such marker is known.

A recent study had provided an evidence for a similar long-term prognosis in patients with STEMI and NSTEMI.[15] This could be attributed to the fact of the presence TME in both groups of patients. It is conceivable, that the extent of irreversible injured myocardium in NSTEMI is related to prognosis.

An accurate classification system that allows the physician to target intensive treatments to the highest-risk patients is required. The GRACE risk scores were developed from the Global Registry of Acute Coronary Events to provide a risk score for all forms of acute coronary syndrome (with or without ST elevation). The GS is an easily applicable and validated tool for triage decision-making in patients with NSTEMI.[16],[17],[18] In short, as GS being lower in NSTEMI patients, a less aggressive diagnostic approach can be followed. Hence, only 28% of the patients with NSTEMI admitted in the GRACE study received a percutaneous coronary intervention and 10% received coronary artery bypass grafting.[19] The GRACE study, unfortunately, lacks data on the outcome per NSTEMI patients with or without transmural infarction.

A previous study had observed a difference between the observed and expected mortality for the GRACE risk groups where the GS was not appropriate enough to estimate the absolute risk in NSTEMI patients.[20]

The current study was concerned to detect TME in NSTEMI patients. As detection of TME in such patient will allow a more accurate stratification, thus offering the opportunity to add some data regarding this challenging complication and hence optimizing their management.

The classic risk factors – HTN, hypercholesterolemia, diabetes mellitus, advancing age, and smoking – are well recognized to predict risk of cardiovascular disease,[21] so it was not surprising that these traditional risk factors were more prevalent in our high-risk group.

Magnetic resonance imaging (MRI) is the gold standard for identification of TME, as it has high spatial resolution and ability to directly visualize the scar extent in the form of delayed contrast enhancement, but its routine use is limited by its high costs, poor availability, relative complexity of acquisitions, and time-consuming image analysis.[22],[23]

STE is a relatively new tool used in clinical practice for evaluating and measuring global and regional strain. It provides non-Doppler, angle-independent, and objective quantification of myocardial deformation and LV systolic and diastolic dynamics. This technique quantifies contraction in the longitudinal direction as well as the circumferential direction. The longitudinal vector primarily represents subendocardial contraction, and the circumferential vector represents the deformation of subepicardial layers.[24]

Subendocardial infarction was found to be associated with a significant reduction in LS, whereas transmural infarction is associated with a reduction of circumferential strain.[5] Chan et al.[5] suggest that a significant decrease in circumferential strain is observed when infarction transmurality is more than 75%. Therefore, decreased circumferential strain may be an independent cardiovascular risk factor providing more important value than LS.[25],[26]

LS did not differentiate between nontransmural and transmural infarctions. The subendocardial layer of the myocardium contains predominantly longitudinal fibers, and the LS tracks motions parallel to the ultrasound beam, in contrary to the motion in the subepicardial layer where circumferential fibers are predominantly found. This factor explains why the deterioration of LS is not more pronounced in segments with transmural necrosis.[27] Sjøli et al.[28] demonstrated in a clinical study involving patients with first time MI that circumferential strain better separated between subendocardial necrosis and transmural necrosis on a segmental level than LS. Based on the previous studies, our study had used STE-derived LG and CS regionally and global to detect TME in NSTEMI patients. Against the old perception that transmural infarction is found only in patients with STEMI, while patients with NSTEMI had only subendocardial infarction, recent studies using contrast-enhanced MRI (Ce-MRI) showed that a percent of patients with NSTEMI had transmural infarction.[1],[27] Transmural myocardial involvement in NSTEMI patients was also detected using multidetector computed tomography.[2] Our study showed that the infarction in NSTEMI is predominantly subendocardial, but it was interesting that transmural infarction was found in 37.5% of our NSTEMI patients on contrary to a known notion that the presence of NSTEMI suggests nontransmural necrosis. Our results go hand in hand with the study of Sarafoff, et al.,[1] who studied the transmurality and size of MI using Ce-MRI where they found that 27% of patients presented with NSTEMI had transmural infarction. Furthermore, Loutfi et al.[27] studied thirty patients with NSTEMI for identification of high-risk patients through detection of LV systolic function, infarct size, and transmurality of infarction using strain Doppler echocardiography and Ce-MRI. They found that 30% of patients had transmural infarction, while 70% had subendocardial infarction. Another study was done by Kühl et al.,[2] who studied 396 patients with NSTEMI by multidetector computed tomography to assess the extent of the infarction and its effect on long-term outcomes. Patients with severe hypoperfusion defect (>50%, i.e., transmural) were found to be 18%.

We also found insignificant increase of transmural infarction and insignificant difference of global CS between both groups, while LS was significantly decreased in high-risk group as compared to low-intermediate-risk group, suggesting increased nontransmural infarction in high-risk group and comparable prevalence of transmural and nontransmural infarction in low-intermediate group.


  Conclusion Top


TME as detected by STE had been found in a relatively substantial number of patients with acute NSTEMI, and it may serve as a tool in conjunction with risk stratification scores for the selection of high-risk NSTEMI patients. Whether the TME detection, especially in low-intermediate NSTEMI patients, would translate into to better management and hence outcome has to be determined by further prospective studies.

Clinical implications

STE can be a useful noninvasive tool for more accurate risk stratification of NSTEMI patients, thus optimizing their management. Measuring TME in NSTEMI may assist the clinical decision pathway and risk stratification of the patient beyond current knowledge. The findings of this study may be relevant for choosing high-risk patients for more aggressive medical therapy or additive therapeutic strategies to promote infarct repair.

Limitations

Poor echocardiographic quality interferes with STE-derived strain as STE requires adequate echocardiographic views to obtain correct endocardial border delineation. Suboptimal image quality affecting strain measurements may have occurred in the current study, as in all studies that used the STE method. The sample size was relatively small, larger studies are needed to confirm our results.

Acknowledgment

The author would like to thank the staff of the cardiovascular department of Zagazig University Hospital for their expert input and detailed evaluations as well as our patients who participated in the study.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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Sjøli B, Ørn S, Grenne B, Ihlen H, Edvardsen T, Brunvand H. Diagnostic capability and reproducibility of strain by Doppler and by speckle tracking in patients with acute myocardial infarction. JACC Cardiovasc Imaging 2009;2:24-33.  Back to cited text no. 28
    


    Figures

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