Clinico-imaging profile and correlations of global longitudinal strain abnormalities in Indian hypertrophic cardiomyopathy patients

Abstract

Background

Hypertrophic cardiomyopathy (HCM) is a prevalent genetic cardiac disorder with variable clinical expression. While global data are available, phenotypic characterization of Indian HCM patients remains limited. Speckle-tracking echocardiography (STE)-derived global longitudinal strain (GLS) may serve as a surrogate marker of myocardial fibrosis in settings with limited access to cardiac magnetic resonance (CMR).

Objectives

To characterize the clinical and imaging features of Indian patients with HCM and evaluate the correlation of GLS with CMR-derived late gadolinium enhancement (LGE) and electrocardiographic abnormalities.

Methods

This cross-sectional study enrolled 150 consecutive adult HCM patients at a tertiary care center in North India. All patients underwent detailed clinical evaluation, standard transthoracic echocardiography including STE-derived GLS, electrocardiography, and 24-h Holter monitoring. CMR was performed in 74 patients based on physician discretion. GLS was quantified using vendor-specific semi-automated software. LGE was quantified as a percentage of total left ventricular mass. Correlations were assessed using Spearman's coefficient (ρ).

Results

The mean age of the cohort was 46.7 ± 13.5 years, with 80 % males. Asymmetric septal hypertrophy (76 %) and obstructive HCM (53 %) were the predominant phenotypes. GLS was reduced (<−20 %) in 89 % of patients (mean GLS: −12.1 % ± 4.1 %). CMR revealed LGE in 92 % of patients, with ≥15 % LGE in 40 %. Peak GLS showed a strong positive correlation with percent LGE (ρ = 0.739). GLS was significantly lower in patients with CMR-detected perfusion deficits (p = 0.04), but not significantly associated with non-sustained ventricular tachycardia (p = 0.18). Modest inverse correlations were noted between GLS and tissue doppler indices (medial e’: −0.55; lateral e’: −0.60).

Conclusion

Indian HCM patients exhibit a distinct clinical profile with high fibrosis burden. STE-derived GLS correlates strongly with myocardial fibrosis on CMR and may serve as a practical risk stratification tool in resource-limited settings. Further multicentric studies are needed to validate these findings.

1. Introduction

Hypertrophic cardiomyopathy (HCM) is among the most prevalent genetic cardiac disorders, with an estimated prevalence of 1 in 200–500 in the general population.¹ The underlying defect is a mutation in one of the genes encoding cardiac sarcomeric proteins.² The clinical phenotype of HCM is quite heterogenous, ranging from asymptomatic presentations to heart failure, ventricular arrhythmias, and sudden cardiac death (SCD).³ While large registries from North America and Europe have delineated the natural history and risk stratification paradigms in HCM, population-specific variations exist.^4,5 For instance, a Japanese cohort demonstrated a higher prevalence of apical HCM (18 %) and lower rates of obstructive HCM (14 %) compared to Western populations.⁶ Data on the phenotypic expression of HCM in Indian patients remain scarce.

Echocardiography and cardiac magnetic resonance (CMR) imaging are pivotal for diagnosing HCM and stratifying SCD risk.⁷ Established risk markers include maximal left ventricular (LV) wall thickness >30 mm, LV systolic dysfunction, apical aneurysm, non-sustained ventricular tachycardia (NSVT), syncope, and malignant family history.⁸ CMR-derived late gadolinium enhancement (LGE) quantifies myocardial fibrosis, with extensive LGE independently predicting SCD.^9,10 Consequently, current European and U.S. guidelines incorporate LGE for implantable cardioverter-defibrillator (ICD) decision-making (Class IIb).^7,8 Speckle-tracking echocardiography (STE) provides sensitive detection of subclinical LV dysfunction via global longitudinal strain (GLS), which correlates with LGE burden.11, 12, 13, 14, 15, 16 Abnormal GLS also predicts adverse clinical outcomes in HCM patients including heart failure, atrial fibrillation and ventricular arrhythmias.¹⁷ Given CMR's cost and limited availability, GLS may serve as a pragmatic alternative for fibrosis detection and risk stratification.

This study aimed to.

• 1.Characterize the clinical and imaging profile of Indian HCM patients.
• 2.Evaluate the correlation of STE-derived GLS with CMR-quantified LGE and electrocardiographic abnormalities.

2. Methods

Study design and Population: This cross-sectional study was conducted at a tertiary care cardiology center in North India between February 2022 and July 2023. The study protocol was approved by the institutional ethics committee, and written informed consent was obtained from all participants. Consecutive adult patients (age ≥18 years) diagnosed with HCM—defined as a maximal end-diastolic LV wall thickness ≥15 mm on echocardiography, in the absence of other causes of hypertrophy—were enrolled.^7,8 Exclusion criteria included LV ejection fraction (LVEF) < 50 % or concomitant coronary artery disease (CAD), which may confound GLS analysis.

Study protocol: All participants underwent detailed clinical evaluation, 12-lead electrocardiography (ECG), 24-h Holter monitoring and standard transthoracic echocardiography (TTE) with STE for GLS (using Philips EPIQ CVx). CMR was performed selectively based on the treating cardiologist's discretion. The study protocol is depicted in Fig. 1.

Fig. 1.

Study protocol.

Obstructive HCM (HOCM) was defined by a resting or provoked LV outflow tract (LVOT) or mid-cavitary gradient ≥30 mmHg. GLS was acquired using apical 4-, 2-, and 3-chamber views with optimized endocardial border delineation and vendor-specific software (Philips EPIQ CVx). The semi-automated algorithm tracked myocardial speckles frame-by-frame, generating strain curves and a global bull's-eye plot (Supplemental Fig. 1). GLS values less negative than −20 % were considered abnormal, as per guideline recommendations.¹⁸

CMR was performed on Siemens Aera (1.5T) using a standard protocol as recommended by Society for Cardiovascular Magnetic Resonance (SCMR) guidelines.¹⁹ End-diastolic wall thickness was evaluated in all segments (AHA 17-segment model). LGE quantification was done using the “tissue characterization” module by drawing endocardial and epicardial contours and defining normal reference myocardium.

Data recording and analysis: Data were entered in a Microsoft Excel 2019 (Microsoft, Redmond, WA, USA) database and analysed using STATA 14.0 version (Stata Corp, Texas, USA). Continuous variables were tested for normality using Shapiro–Wilk tests and visual inspection of Q–Q plots, with normally distributed data reported as mean ± standard deviation (SD) and non-normal data as median (interquartile range, IQR); categorical variables were expressed as frequencies (percentages). Group comparisons utilized independent samples t-tests (normal data) or Mann–Whitney U tests (non-normal data) for continuous variables, and Chi-square/Fisher's exact tests for categorical variables. Correlations between global longitudinal strain (GLS) and late gadolinium enhancement (LGE) percentage (non-normal distributions) were assessed using Spearman's rank correlation coefficient (ρ), with strength interpreted as weak (0–0.3), moderate (0.3–0.7), or strong (>0.7); similar analyses were applied to GLS and tissue Doppler indices (medial/lateral e’). Subgroup comparisons (e.g., GLS in patients with vs. without perfusion deficits) employed two-sided t-tests or Mann–Whitney U tests, as appropriate. A two-sided p-value <0.05 was considered statistically significant.

3. Results

3.1. Clinical characteristics

A total of 150 patients with HCM (mean age 46.7 ± 13.8 years; 80 % male) were enrolled. Clinical characteristics are summarized in Table 1. Dyspnea was the most common presenting symptom (72 %), followed by angina (48 %) and syncope (21 %). Atrial fibrillation was present in 11.3 %, and NSVT was documented in 14 %. Only 10.6 % reported a family history of HCM or SCD.

Table 1.

Clinical profile and electrocardiographic abnormalities of 150 hypertrophic cardiomyopathy patients.

Variable	Mean/n (%)
Age (mean)	46.7 years
Male gender (percent)	80 %
Age at symptom onset (mean)	44.6 years
Dyspnea	72 %
Angina	48 %
Syncope	21 %
NYHA Class
I	28 (18.6 %)
II	105 (70 %)
III	17 (11.3 %)
Positive family history	16 (10.6 %)
Left Bundle Branch Block	4 (2.7 %)
Right Bundle Branch Block	3 (2 %)
Premature ventricular contraction	18 (12 %)
Atrial Fibrillation	17 (11.3 %)
NSVT	21 (14 %)
Ectopic atrial tachycardia	3 (2 %)
Accessory pathway mediated SVT	3 (2 %)

HCM: hypertrophic cardiomyopathy; NYHA: New York Heart Association functional classification; NSVT: non sustained ventricular tachycardia; SVT: supraventricular tachycardia.

3.2. Imaging characteristics

Detailed imaging findings are summarized in Table 2. Asymmetric septal hypertrophy and apical HCM were predominant phenotypes, diagnosed in 114 (76 %) and 19 (12.7 %) patients, respectively. Obstructive HCM (LVOT gradient ≥30 mmHg at rest or with provocation) was present in 79 (53 %) patients. Systolic anterior motion of anterior mitral leaflet (AML) was present in 90 (60 %) cases. Mitral regurgitation (MR) was present in 80 (53.3 %) of the cases and was mild in majority. One patient had severe MR caused by infective endocarditis (vegetation on AML) who underwent surgery (vegetectomy and septal myectomy). Tissue Doppler imaging (data from 136 participants) revealed reduced medial e′ (<7 cm/s) in 126 (92.6 %) and reduced lateral e′ (<10 cm/s) in 130 (95.6 %) patients. STE-derived GLS was available in 126 patients; 112 (89 %) had abnormal GLS (<−20 %), with a mean GLS of −12.1 % ± 4.1 %. No significant difference in GLS was observed between obstructive (−11.4 %) and non-obstructive (−12.7 %) subgroups (p = 0.08). The mean anteroposterior left atrial (LA) diameter (measured in parasternal long axis view) was 38.4 ± 4.2 mm (range: 28–49 mm). Mild to moderate LA enlargement was common, reflecting elevated filling pressures. Among patients with atrial fibrillation (n = 17), the mean LA diameter was 41.2 ± 4.7 mm, significantly greater than those without AF (38.1 ± 4.0 mm, p = 0.02). LA diameter showed a modest negative correlation with medial e’ velocity (Spearman's ρ = −0.41, p < 0.001), supporting its role as an indirect marker of diastolic dysfunction in this population.

Table 2.

Imaging characteristics of 150 Indian Hypertrophic Cardiomyopathy patients.

Imaging parameter	Mean/n (%)
Echocardiography
IVS thickness (mean)	20.2 mm (Range 13–32 mm)
Asymmetric septal hypertrophy	114 (76 %)
Concentric hypertrophy	16 (10.6 %)
Apical HCM	19 (12.7 %)
Biventricular hypertrophy	2 (1.3 %)
Non obstructive	71 (47 %)
Obstructive	79 (53 %)
Mean LVEF	64 %
Mean LA AP diameter	38.4 mm (range 28–49 mm)
Medial e’ (mean)	4.9 m/s
Lateral e’ (mean)	6.6 m/s
Average peak GLS	−12.1 % (Range - 4 % to - 24 %)
Systolic anterior motion of AML	90 (60 %)
Mitral regurgitation	80 (53.3 %)
Mild	70 (46.7 %)
Moderate	9 (6 %)
Cardiac Magnetic Resonance (n = 74)a
Indexed LV myocardial mass (g/m2)	109.5 (range 78–165)
Any LGE	68 (92 %)
LGE ≥5 %	59 (80 %)
LGE ≥15 %	30 (40 %)
% LGE of LV Mass	14 % (range 1 %–48 %)
Perfusion deficit in hypertrophied segment(s)	19 (25.6 %)

IVS: interventricular septum; LVEF: left ventricular ejection fraction; LA: left atrium; AML: anterior mitral leaflet; LGE: late gadolinium enhancement; CMR: cardiac magnetic resonance.

^aCMR was performed only in 74 patients based on physician discretion.

CMR data was available in 74 (49.3 %) patients. The mean LV myocardial mass indexed to body surface area was 109.5 ± 22.6 g/m² (range: 78–165 g/m²). The absolute LV myocardial mass was 191.3 ± 39.7 g. The site of maximal hypertrophy was basal septum in 34 (45.9 %) patients, mid septum in 25 (33.8 %) patients, basal anterior in 10 (13.5 %) patients and apical in 5 (6.6 %) patients. Perfusion deficit was noted in hypertrophied segments in 19 (25.6 %) cases. Myocardial fibrosis was quantified using late gadolinium enhancement (LGE) imaging. LGE was present in 68 (92 %) patients, with a mean percentage of LV mass involved of 14 ± 12 %. Extensive fibrosis (defined as LGE ≥15 % of LV mass) was present in 30 patients (40.5 %). Patients with extensive LGE had significantly lower peak GLS values (−10.1 ± 2.5 % vs. −13.7 ± 3.9 %, p < 0.001) and higher indexed LV mass (116.4 ± 18.9 g/m² vs. 104.6 ± 22.4 g/m², p = 0.02), suggesting a relationship between myocardial hypertrophy, fibrosis burden, and subclinical dysfunction.

3.3. Correlations of abnormal global longitudinal strain (GLS)

• •GLS and LGE: There was a significant positive correlation of peak GLS with percent LGE on CMR with a Spearman's correlation coefficient (ρ) of 0.739 (Fig. 2). An illustrative case is shown in Fig. 3, highlighting segmental concordance between GLS impairment and LGE.
• •GLS and Perfusion deficits: Patients with perfusion deficits had significantly lower GLS (−9.84 %) compared to those without deficits (−12.2 %; p = 0.04).
• •GLS and Arrhythmias: There was no significant association of GLS with electrocardiographic abnormalities like non-sustained VT (p = 0.18) or premature ventricular complexes (p = 0.35).
• •GLS and tissue doppler abnormalities: There was a modest negative correlation of peak GLS with medial e’ (correlation coefficient – 0.55) and lateral e’ (correlation coefficient −0.60) (Fig. 4).

Fig. 2.

Scatter plot depicting significant positive correlation between abnormal peak global longitudinal strain (GLS on y-axis) and percentage late gadolinium enhancement (%LGE on x-axis).

Fig. 3.

Cardiac magnetic resonance (CMR) imaging showing extensive late gadolinium enhancement (LGE) in hypertrophied segments and the corresponding peak GLS image (right) depicting abnormal strain values in these segments.

Fig. 4.

Scatter plot depicting modest negative correlation between tissue doppler derived medial and lateral e’ with abnormal peak GLS.

4. Discussion

This study presents one of the first comprehensive characterizations of Indian patients with HCM, revealing a unique clinical and imaging phenotype. The mean age at presentation (46.7 years) is comparable to international registries such as SHaRe (45.8 years) and EORP (47 years)^4,5 However, a striking male predominance (80 %) and lower familial history (10.6 %) distinguish our cohort. Indian patients exhibited a higher symptom burden, with dyspnea and angina reported in over two-thirds of the cohort, significantly more than Western registries. The lower prevalence of atrial fibrillation (11.3 %) may be attributed to the cross-sectional design and lack of long-term monitoring. NSVT runs were detected in 14 % of patients, similar to another large registry.²⁰ Around 80 % patients were either on beta-blocker and/or calcium channel blocker therapy.

The most common phenotype in this HCM cohort was asymmetric septal hypertrophy (76 %), and resting or provoked LVOT or mid-cavitary obstruction was detected in 53 % cases, similar to above mentioned registries. The mean value of peak GLS was - 12.1 %. Therefore, LV strain was reduced in the patients despite having normal LVEF. CMR detected myocardial fibrosis as LGE in the majority (92 %) of patients who underwent the test. This is higher than what is reported in previous studies like 75 % in study by Saito et al, and 66 % in study by Ismail et al,.^21,22 Importantly, those with extensive fibrosis (≥15 % LGE) had higher indexed LV mass and significantly impaired GLS, underlining the interrelation between hypertrophy, fibrosis, and subclinical dysfunction.

We also noted a strong correlation between STE-derived GLS and CMR-derived percent LGE (correlation coefficient,ρ = 0.739). This aligns with the prior studies by Klettas et al (ρ = 0.615), Almaas et al (ρ = 0.50), and Saito et al (ρ = 0.62) and supports STE's role in identifying fibrosis when CMR is unavailable.^15,22,23 Notably, perfusion deficits on CMR predicted abnormal GLS, reinforcing the interplay between microvascular dysfunction and contractile impairment.

While STE-derived GLS offers valuable insights into subclinical myocardial dysfunction and correlates well with CMR-derived LGE, several limitations warrant consideration. First, GLS measurements are highly vendor-dependent, with inter-vendor variability in tracking algorithms and strain values, which can affect reproducibility across different echocardiography platforms.24, 25, 26 Second, image quality and adequate endocardial border delineation are crucial; patients with poor acoustic windows (e.g., obesity, lung disease) may yield suboptimal strain analyses.²⁷ Third, load dependency of GLS can confound interpretation—strain values may be affected by changes in preload or afterload, limiting their specificity for intrinsic myocardial dysfunction.²⁶ Lastly, there is a lack of universally accepted strain cut-offs for risk stratification in HCM, which complicates clinical decision-making.

The strengths of our study include: The first of its kind study in India and therefore it presents to us the clinical and imaging data of Indian HCM patients which as highlighted above is different. We had a good sample size for our correlation of LGE and GLS, comparable or better than other studies answering this question. Limitations of our study include single-centre design, smaller sample size than the usual HCM registries and the lack of longitudinal long term follow up data of key clinical events.

5. Conclusions

Indian HCM patients exhibit distinct clinical and imaging features, including high LGE prevalence. GLS strongly correlates with myocardial fibrosis, offering a feasible alternative to CMR for risk assessment. Larger multicentre studies are warranted to validate these findings.

Ethics

Ethical clearance obtained from institutional ethics committee of All India Institute of Medical Sciences, New Delhi (Reference number: IECPG-619/28.10.2021, RT-27/25.11.2021)

Funding

This research did not receive any specific funding or grant.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Professor Rakesh Yadav and Professor Nitish Naik are members of editorial board of Indian heart journal. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following is the supplementary data to this article:

figs1.