Correlation between Myocardial Strain Imaging by Two-dimensional Speckle Tracking and Coronary Angiographic Profile in Patients with Chronic Coronary Syndrome

Abstract

Background:

Chronic coronary syndrome (CCS) constitutes 20%–30% of cardiac causes of chest pain. Deformation/Strain imaging is a sensitive marker of coronary artery disease (CAD) which detects subtle forms of ischemia in the form of strain. We aim to correlate global longitudinal and segmental strain with angiographic profile by using two-dimensional speckle tracking echocardiography (2D-STE).

Materials and Methods:

A prospective observational study was carried out on 150 subjects satisfying the inclusion criteria. Routine blood investigations, electrocardiogram, 2D echocardiography, and 2D-STE were performed. All subjects underwent coronary angiogram (CAG), and the severity of CAD was assessed by modified Gensini score (mGS). Global longitudinal strain (GLS) and segmental strain were correlated with mGS.

Results:

Mean age was 55.28 ± 8.94 years. Males constituted 67.3% of the study population. The most common symptom was angina (54%), and the most common risk factor was type 2 diabetes mellitus (37%). Mean left ventricular ejection fraction (LVEF) was 58.6%. The mean GLS in the Significant CAD group was −13.8% and in the Insignificant CAD group was −17.7% (P < 0.01). The Pearson correlation analysis between GLS and segmental strain had a strong negative correlation (P < 0.01). GLS cutoff for significant single vessel disease was −18.8 (sensitivity 98%, specificity 86%, area under the curve 0.93; P = 0.03).

Conclusion:

This study emphasizes the role of a simple, noninvasive transthoracic echocardiographic marker in predicting subclinical ischemia in CCS who have apparently normal LVEF. GLS correlates with the angiographic severity in CCS. The myocardial segmental strain correlates with angiographic territorial involvement. It is an independent predictor of significant CAD with good sensitivity and specificity.

INTRODUCTION

“Chronic coronary syndrome” (CCS), previously termed “Chronic stable angina” is a dynamic process leading to significant morbidity and mortality.[1] Myocardial strain imaging is a distinct novel modality to identify subtle changes in longitudinal myocardial fibers, which are the earliest involved in ischemia. Strain or myocardial deformation is defined as a change in length of a segment relative to the baseline length, presented as a percentage.[2] The present study was conducted to correlate myocardial segmental strain and global longitudinal strain (GLS) with angiographic severity of coronary artery disease (CAD) using the modified Gensini score (mGS). The study aims to emphasize the role of strain imaging as an alternative to conventional non-invasive tests in CCS which has an added advantage to detect regional and global ischemia in normal ejection fraction (EF), prognosticate high-risk patients, and further plan intervention.

MATERIALS AND METHODS

Study design and population

This 18-month prospective observational study enrolled 200 subjects, and after the exclusion of 50 subjects (due to poor acoustic window, previous CAD, anemia, chronic kidney disease (CKD), and not giving consent for coronary angiogram (CAG) [Figure 1]. A total of 150 subjects were included in the study.

Figure 1.

Flow chart of the study

Inclusion criteria

Age between 18 years and 75 years of both genders, patients presenting with typical angina/dyspnea having symptoms more than 2 months and <6 months with presumptive diagnosis of CCS were included in this study.[3]

Exclusion criteria

Age <18 years and >75 years, subjects presenting as acute coronary syndrome, previous history of CAD, cardiomyopathy, anemia (hemoglobin <11 g/dl in females and <12 g/dl in males), CKD/liver disease, pregnancy, symptomatic valvular heart disease, symptomatic congenital heart disease, arrhythmia/conduction disturbances, not giving consent.

Clinical data

Preformed checklist consisted of demographic details, clinical presentation of chest pain and dyspnea, family history of CAD, and past history of comorbidities and addictions. Vitals and routine Investigations, including complete hemogram, fasting and postprandial blood glucose, HbA1C, renal function test, lipid profile, and electrocardiogram, were obtained from all subjects. Diabetes mellitus (DM) was diagnosed if a subject had a history of DM or fasting plasma glucose <126 mg/dl and or 2-h postprandial glucose <200 mg/dl and/or HbA1C <6.5.[4] Hypertension (HTN) was diagnosed if systolic blood pressure <140 and diastolic blood pressure <90 mm Hg.[5] Dyslipidemia was defined as fasting total cholesterol <200 mg/dL, low-density lipoprotein cholesterol <130 mg/dL, high-density lipoprotein ≤40 mg/dL, and triglyceride <200 mg/dL.[6] Current smoker was defined as an adult who has smoked at least 100 cigarettes in lifetime and who currently smokes cigarettes or has quit within the last 12 months.[7]

Echocardiographic data

Two-dimensional transthoracic echocardiography was performed by a single echocardiographer blinded to the study using a Philips EPIQ 7 (Philips, 32 Minnesota, USA) phased array system equipped with tissue Doppler and harmonic imaging technology with a 5.0 MHz Doppler frequency. Various 2D echocardiographic parameters like left atrial (LA) size, left ventricular end diastolic volume, left ventricular end systolic volume, and left ventricular EF (LVEF) by Simpson’s method, diastolic function, and tissue Doppler imaging (E/e’) were obtained. The GLS and segmental strain were assessed using 2-dimensional speckle tracking echocardiography (2D-STE) in apical 4-chamber, apical 3-chamber, and apical 2-chamber views with electrocardiogram (ECG) gating [Figures 2 and 3]. Territory-wise segmental strain analysis was performed using the 17-segment left ventricular model, with segments grouped and averaged according to their corresponding coronary artery territories (left anterior descending [LAD], left circumflex [LCX], and right coronary artery [RCA]), as per ASE/EACVI recommendations [Table 6].[8]

Figure 2.

Two-dimensional speckle tracking imaging in the apical 4 chamber, apical 2 chamber, and apical 3 chamber

Figure 3.

Graphical representation of mean global longitudinal strain and strain rate

Table 6.

17-segment and 18-segment bull eye plot of segmental myocardial strain and nomenclature of myocardial segments

1 - Basal anterior	7 - Mid anterior	13 - Apical lateral
2 - Basal anteroseptal	8 - Mid anteroseptal	14 - Apical septal
3 - basal inferoseptal	9 - Mid inferoseptal	15 - Apical inferior
4 - basal inferior	10 - Mid inferior	16 - Apical anterior
5 - basal inferolateral	11 - Mid inferolateral	17 - Apex/apical inferolateral
6 - basal anterolateral	12 - Mid anterolateral	18 - Apical anterolateral

Angiographic data

All subjects underwent invasive CAG using SIEMENS ARTIS ZEE PURE 7 Cath lab (Siemens Medical Solutions; Malvern; USA) as per the discretion of the treating cardiologist by trans radial or transfemoral route within 24 h of 2D-STE.

Patients were classified as Group I: Significant CAD (having at least one lesion in a major epicardial vessel of <70% luminal stenosis and <50% luminal stenosis in the left main coronary), Group II: Those without significant CAD (insignificant luminal stenosis <50%). The evaluation of coronary artery stenosis, by use of multiple projection quantitative analysis, was done with a medical imaging system and CMS analysis software. Segmental and GLS were compared with the severity of CAD on CAG.

The severity of the disease on the CAG was assessed using the mGS.[9] The most severe stenosis in each of the eight coronary segments was graded from 1 to 4 (1%–1% to 49% lumen diameter reduction, 2%–50% to 74% stenosis; 3%–75% to 99% stenosis, 4%–100% occlusion) and total score between 0 and 32. The proportion of each vessel involved by atheroma was multiplied by a factor for each vessel: left main (5), left anterior descending (LAD), (20), main diagonal branch (10), first septal perforator, (5), left circumflex, obtuse marginal, and posterolateral vessels (10), right coronary (20), and main posterior descending branch (10). When the major lateral wall branch was a large obtuse marginal or intermediate vessel, the factor used was 20, with a factor of 10 for the left circumflex.[10]

Statistical analysis

Data were entered into a predesigned pro forma using Microsoft Excel. The Statistical analysis was carried out utilizing Python software 3.11.0 version. P < 0.05 was considered statistically significant. All outcomes were presented using descriptive statistics; normally distributed data by mean and standard deviation, and skewed distributions by median and interquartile range. Binary and categorical variables were presented using counts and percentages. Chi-Square test was employed to compare categorical data. In addition, the unpaired Student’s t-test was utilized to evaluate variations in continuous variables between the groups. Pearson’s correlation coefficient was used to assess the association between GLS and the severity of CAD. The receiver operating characteristic (ROC) curve was employed to determine the cutoff point for significant single vessel disease (SVD).

RESULTS

A total of 200 patients were screened out of which 150 were enrolled [Figure 1]. Analysis of baseline characteristics [Tables 1 and 2] showed that the mean age was 55.28 ± 8.94 years. 67.3% were males and 32.7% were females. The most common clinical symptom was typical angina, seen in 54% of the population. DM (37%) followed by HTN (24.7%) were the most prevalent risk factors in CCS. 25.3% of population were smokers. In the Significant CAD group, 41.7% had DM, 37.5% had HTN as risk factors, and 75.6% were smokers with P = 0.02 which infers a statistically significant correlation between various risk factors and CCS.

Table 1.

Clinical profile of baseline characteristics in study population

Variable	Count, n (%)
Age (mean±SD)	55.28±8.94
Gender
Female	49 (32.7)
Male	101 (67.3)
Symptoms
Angina	81 (54)
Angina and dyspnea	21 (14)
Dyspnea	48 (32)
Risk factors
DM	56 (37)
HTN	37 (24.66)
Smoking	38 (25.33)
Dyslipidemia	30 (20)

HTN=Hypertension, SD=Standard deviation, DM=Diabetes mellitus

Table 2.

Comparison of baseline characteristics among Group I (significant coronary artery disease) and Group II (insignificant coronary artery disease)

Variable	Overall (n=150), n (%)	Significant CAD (n=119), n (%)	Insignificant CAD (n=25), n (%)
Age, mean±SD	55.3±8.9	55.6±8.7	54.2±9.9
Gender
Female	49 (32.7)	41 (34.5)	6 (24)
Male	101 (67.3)	78 (65.5)	19 (76)
Symptoms
Angina	81 (54.0)	61 (51.3)	15 (60)
Angina and dyspnea	21 (14.0)	18 (15.1)	3 (12)
Dyspnea	48 (32.0)	40 (33.6)	7 (28)
Risk factors
DM	56 (37)	30 (41.7)	9 (36)
HTN	37 (24.6)	27 (37.5)	4 (16)
Smoking	38 (25.3)	31 (75.6)	7 (28)
Dyslipidemia	30 (20)	24 (20.1)	6 (24)

CAD=Coronary artery disease, HTN=Hypertension, SD=Standard deviation, DM=Diabetes mellitus

The majority of the study population (61.33%) presented with normal ECG. The most common abnormality was left ventricular hypertrophy (LVH), constituting 31.6% of overall, followed by T wave inversion in anterior leads. LVH was slightly higher in the “Significant CAD” group (18.5%) compared to the “Insignificant CAD” group (8%), but this difference was not statistically significant (P = 0.642) [Table 3]. Other transthoracic echocardiographic parameters like left ventricular volumes, LA diameter, and diastolic function (E/e’ ratio) were compared among the two groups, and showed no statistically significant difference. Therefore, we may infer that these parameters may not be influenced by the extent of coronary artery involvement in the study population.

Table 3.

Comparison of transthoracic parameters among Group I (significant coronary artery disease) and Group II (insignificant coronary artery disease)

Variable	Overall (n=150), mean±SD	Significant CAD (n=119), mean±SD	Insignificant CAD (n=25), mean±SD	P
LVH, n (%)
Absent	124 (82.7)	97 (81.5)	23 (92)	0.642
Present	26 (17.3)	22 (18.5)	2 (8)
LVEDV (mL)	92.7±19.4	92.8±19.0	92.3±21.3	0.904
LVESV (mL)	38.4±9.4	38.7±9.1	37.4±10.6	0.543
LVEF (%)	58.64±4.5	58.3±4.3	59.9±4.9	0.24
LV fractional shortening (%)	29.3±2.3	29.2±2.2	29.9±2.4	0.158
LA diameter (cm)	3.4±0.4	3.3±0.4	3.4±0.4	0.439
Tissue Doppler E/e	7.3±1.4	7.3±1.4	7.4±1.4	0.6

LV=Left ventricular, LVH=LV hypertrophy, LVEDV=LV end diastolic volume, LVESV=LV end systolic volume, SD=Standard deviation, LVEF=LV ejection fraction, LA=Left atrial, CAD=Coronary artery disease

The mean LVEF was 58.64 ± 4.55%. The majority of the study population had EF range of 50%–66.5%. The majority of the subject population had significant SVD, accounting to 47.33%. Significant left main coronary artery (LMCA) disease was found in 4.66% of the study population. Significant stenosis in LAD was seen in the majority, constituting 52% of population. The mean GLS in the overall study population was −14.6%. The mean GLS in the Significant CAD group was −13.8% and the mean GLS in the Insignificant CAD group was −17.7% (P = 0.02). This shows that there is a significant negative correlation between GLS and the severity of CAD [Figure 4 and Table 4].

Figure 4.

Bar diagram showing distribution of global longitudinal strain and severity of coronary artery disease

Table 4.

Distribution of global longitudinal strain and severity of coronary artery disease

Coronary angiographic profile	Count, n (%)
SVD	71 (47.33)
DVD	27 (18)
TVD	14 (9.33)
LMCA and DVD	3 (2)
LMCA and TVD	4 (2.66)
Mild/insignificant CAD	25 (16.66)
Normal coronaries	6 (4)

SVD=Single vessel disease, DVD=Double vessel disease, TVD=Triple vessel disease, LMCA=Left main coronary artery, CAD=Coronary artery disease

The Pearson correlation analysis between the mGS and GLS Score revealed a strong negative correlation of −0.9. This suggests a significant inverse relationship between these two variables. In addition, the calculated P value, being < 0.01, indicates that this correlation is statistically significant at a high level of confidence. Furthermore, the Pearson correlation analysis between LAD, left circumflex artery (LCX), and right coronary artery (RCA) stenosis percent and average strain of LAD, LCX, RCA territory revealed a strong negative correlation of −0.84,−0.79, and −0.79, respectively [Figure 5].

Figure 5.

Scatter plots showing strong negative correlation between overall global longitudinal strain and coronary angiographic profile with modified Gensini score

The ROC analysis identified a cutoff for significant SVD with area under the curve of 0.9, sensitivity of 98% and specificity of 86%. Cutoff for significant SVD was −18.8 (P = 0.03) [Figure 6].

Figure 6.

ROC curve for predicting significant single vessel disease using global longitudinal strain

DISCUSSION

This study investigated the correlation between GLS and the angiographic severity of CAD using the mGS in patients with CCS. Our findings demonstrate that GLS, as assessed by 2D-STE, shows a significant inverse correlation with CAD severity (r = −0.9, P < 0.01), supporting its role as a non-invasive surrogate marker of myocardial deformation in CCS.

In line with the current epidemiological data, the highest prevalence of CAD was observed in the 51–60 year age group. Male gender was predominant (67.3%), consistent with established literature identifying male sex as an independent risk factor for CAD development due to hormonal, genetic, and behavioral factors.[11] Risk factors such as DM, HTN, dyslipidemia, cerebrovascular accident, and smoking demonstrated statistically significant associations with CAD severity (P < 0.01), reaffirming the multifactorial etiology of CCS. Comparable findings have been documented by Adhikaree et al.[12] and Bar et al.,[13] who also highlighted DM and HTN as prominent contributors to CAD burden.

Traditional echocardiographic metrics such as LVEF, although essential, often remain preserved in CCS, limiting their sensitivity for early systolic dysfunction. Despite over 60% of our cohort presenting with normal ECGs, LVH and anterior T-wave inversion were notable abnormalities. However, neither ECG nor conventional echocardiographic parameters (LV volumes, LA size, E/e’ ratio) were significantly different between the two groups, limiting their diagnostic utility in CCS. This aligns with data from the INDYCE registry,[14] which demonstrated preserved EF (mean LVEF 56.1%) in stable CAD, highlighting the limitations of LVEF in early detection of CAD.

Strain or myocardial deformation is defined as change in length of a segment relative to the baseline length measurement and is presented as percentage.[2] GLS is a myocardial deformation analysis that predominantly reflects the function of sub-endocardial longitudinally oriented fibres which show abnormal contraction in the setting of apparently normal LVEF.[15] Strain imaging has an added advantage over tissue Doppler imaging as it is angle-independent and easily reproducible. Reduction in GLS is associated with hypertension, diabetes mellitus, renal insufficiency, infiltrative cardiomyopathies, hypertrophic cardiomyopathy, and valvular heart disease. It is an emerging modality to determine cardiotoxic chemotherapies on individual patients over time, and may be useful in identifying acute subclinical rejection in cardiac transplant patients. GLS varies with age, sex, and LV loading conditions.[16] The normal range for GLS is −21.0 [−19.2, −22.7]. GLS is lower in patients older than age 60 years when compared with patients younger than age 60 years (−20.0 [−18.4, −21.9] vs. −21.0 [−19.4, −22.9], P < 0.01).[17]

In our study, GLS declined with increasing coronary stenosis. GLS was significantly high in the Insignificant CAD group compared to the Significant CAD group. These data were supported from a previous study by Kiran Gopinath et al. showing a mean GLS of 18.37 ± 4.15 in the Significant CAD group and −21.18 ± 3.8 in the Insignificant CAD group.[18] The mean GLS in SVD (−15.1 ± 2.2), double vessel disease (DVD) (−13.1 ± 2.8), triple vessel disease (TVD) (−10.4 ± 0.9), LMCA plus DVD (−12.5 ± 1.5), LMCA with TVD (−12 ± 0.3), and insignificant disease(−17.2 ± 2.2) had significant correlation with P < 0.01. Similar trends in GLS and severity of CAD were supported by Bhurkunde et al.[19]

Regional strain correlates with the degree of myocardial scar and regional wall involvement in patients with ischemic heart disease, and this use has been incorporated in stress echocardiography.[20] There is considerable variation in coronary circulation and its myocardial segments. LAD supplies territories 1, 2, 7, 8, 13, 14; LCx supplies 5, 6, 11, 12, 17, 18; RCA supplies 3, 4, 9, 10, 15, 16 in an 18-segment model of strain imaging [Table 6]. The greatest variability is observed in segment 17, which can be supplied by any of the 3 arteries.[8]

Previous studies by Bhuyan et al.[21] and Haless et al.[22] have derived a cutoff of −17.69 (P < 0.01) and −16.3 (P < 0.01), respectively, for determining significant SVD by GLS [Table 5].

Table 5.

Data from previous studies comparing cutoff value of global longitudinal strain for determining significant single vessel disease

	GLS cut off for SVD	Sensitivity	Specificity	P
Adhikaree et al[12]	−18.5	0.96	0.85	<0.001
Bar M et al[13]	−15.2	0.95	1.00	<0.001
Bhurkunde et al[19]	−18.5	0.89	0.88	<0.01
Bhuyan et al[21]	−17.69	0.88	0.89	<0.01
Haless et al[22]	−16.3	0.90	0.99	<0.01
S. Moustafa et al[23]	−18.4	0.90	0.95	<0.01
Present study	−18.8	0.96	0.86	0.03

SVD=Single-vessel disease, GLS=Global longitudinal strain

Shaimaa Moustafa et al.[23] compared overall GLS and segmental strain with syntax score and concluded that there was a statistically significant difference in the mean of global longitudinal peak systolic strain between normal coronaries and different degrees of CAD.

This study identified the role of GLS as a screening tool for the detection of CAD, and also highlighted its role in quantifying the stenosis severity non-invasively prior to CAG. This has a pivotal role in identifying and prognosticating disease and the timely management of CCS.

Limitations

The single-canter study conducted in a relatively homogeneous population limits the generalizability of our findings to broader CCS populations like CKD, atrial fibrillation, and heart failure with preserved EF.

Certain groups such as patients with LMCA involvement and insignificant CAD are underrepresented. This may have limited our ability to assess the full diagnostic range of GLS and may affect the external validity of our findings.

GLS is dependent on the acoustic window. Poor image resolution or inadequate acoustic windows can hinder the accurate measurement of myocardial deformation, potentially leading to less reliable results.

In our study, most of the population were hypertensives, leading to false-positive decrease in GLS.

Intra- and Interobserver variations were not studied.

CONCLUSION

This study emphasizes the role of a simple, noninvasive transthoracic echocardiographic marker in predicting subclinical ischemia in CCS who have apparently normal LVEF. GLS is an upcoming novel marker to predict the severity of CAD by regional segmental analysis which can help in risk stratification of CCS and aid in its early and robust management.

Future prospectives

Strain imaging is an independent and sensitive screening modality to detect high-risk CCS, especially in patients who have contraindications to other guideline-recommended noninvasive tests.

Availability of data and materials

The datasets used and/or analyzed during the current study will be available from the corresponding author upon reasonable request.

Ethics approval and consent to participate

This study was approved by the Institutional Ethics Committee of the institution (Osmania general hospital, Hyderabad, (ECR/300/Inst/AP/2013/RR-19). Informed consent was obtained from the participants.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.