Evaluation of myocardial structure and function in hypertrophic obstructive cardiomyopathy via cardiovascular magnetic resonance: regional distribution and sex differences

Introduction

Hypertrophic obstructive cardiomyopathy (HOCM) is the most prevalent phenotype of hypertrophic cardiomyopathy (HCM), accounting for nearly 70% of cases, and is defined by asymmetric left ventricular (LV) hypertrophy accompanied by dynamic LV outflow tract obstruction (LVOTO) at rest or with provocation (1). This phenotype confers a heightened risk of heart failure and sudden cardiac death, particularly in younger populations (2-4). The underlying pathophysiology is multifactorial, involving structural remodeling, altered myocardial mechanics, and abnormal loading conditions. At the microscopic level, disorganized cardiomyocyte architecture, microvascular dysfunction, and interstitial fibrosis collectively contribute to progressive myocardial dysfunction and adverse clinical outcomes (2,5-7).

Compared to patients with non-obstructive HCM, those with HOCM more frequently require invasive interventions, such as surgical septal myectomy or alcohol septal ablation (5,7). Baseline myocardial function and its potential for reverse remodeling following intervention are critical determinants of prognosis in patients with HOCM (8,9). Recently, pharmacologic therapies such as mavacamten have shown promise in reducing LVOTO by modulating sarcomeric contractility; however, concerns remain regarding their impact on myocardial function (10). In this context, myocardial strain imaging has emerged as a sensitive marker of early myocardial dysfunction, capable of detecting subclinical abnormalities prior to changes in LV ejection fraction (LVEF) (7,11-13). Identifying detailed strain abnormalities patterns may improve risk stratification and therapeutic decision-making in this high-risk population.

Advances in multimodal cardiac imaging, particularly echocardiography speckle tracking and cardiovascular magnetic resonance feature tracking (CMR-FT), have clarified the structural determinants of myocardial deformation. Studies have demonstrated that increased LV mass is associated with global and regional strain impairment, highlighting the mechanical burden imposed by hypertrophy (14,15). Both myocardial hypertrophy and fibrosis are implicated in regional mechanical dysfunction; however, the independent contribution of myocardial fibrosis to contractile heterogeneity remains controversial (14,16,17). Furthermore, an accumulating body of evidence suggests that sex-specific differences in cardiac remodeling may influence functional impairment, with females exhibiting smaller LV cavity size and more severe diastolic dysfunction (18). Yet, the combined impact of regional hypertrophic distribution, myocardial fibrosis, and sex differences on the strain mechanics in HOCM has not been comprehensively evaluated.

Due to the high spatial resolution and superior tissue characterization capabilities of CMR techniques—including cine imaging for LV wall thickness (WT) assessment, CMR-FT for multidirectional myocardial deformation analysis, and late gadolinium enhancement (LGE) and extracellular volume (ECV) mapping for fibrosis quantification—CMR provides a uniquely comprehensive platform for elucidating the complex interplay between myocardial structure and function (19,20). The aim of this study was to systematically evaluate the global impact of myocardial hypertrophy and fibrosis on multidirectional myocardial strain in patients with HOCM. Specifically, we sought to delineate the independent contributions of hypertrophic patterns and fibrotic burden to myocardial dysfunction and to examine how these factors differentially affect strain across various LV regions and between sexes, thereby offering potential insights into the development of personalized diagnostic and therapeutic strategies. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-457/rc).

Methods

Study population

This retrospective study included patients who underwent CMR examination at Tongji Hospital between April 2022 and January 2024. Participants were enrolled if they met the diagnostic criteria for HCM according to the 2024 European Society of Cardiology (ESC) Guidelines (21). The other inclusion criteria were as follows: (I) HCM with a LVOT gradient ≥30 mmHg as assessed by Doppler echocardiography at resting or under provocation conditions; and (II) completion of a full CMR protocol, including cine imaging, T1 mapping, and LGE imaging. Meanwhile, the exclusion criteria were as follows: (I) suboptimal image quality to support the image analysis; (II) significant coronary artery disease (≥50% stenosis); (III) prior cardiac interventions (e.g., alcohol septal ablation and surgical myectomy); and (IV) metabolic cardiomyopathies such as Fabry disease. Baseline characteristics and CMR parameters were recorded. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Ethics Committee of Tongji Hospital (approval No. 2020, S155). The requirement for informed consent was waived due to the retrospective nature of the analysis.

CMR image acquisition

All CMR exams were performed with a 3-T system (MAGNETOM Skyra, Siemens Healthineers, Erlangen, Germany). The imaging protocol included cine imaging, T1 mapping (native and post-contrast), first-pass perfusion imaging, and LGE. Cine images in short- and long-axis views (two-, three-, and four-chamber) were acquired with electrocardiogram-gated breath-hold sequences under the bSSFP technique. The key imaging parameters were as follows: slice thickness =8 mm, section gap =2 mm, echo time (TE) =1.39 ms, repetition time (TR) =3.2 ms, field of view (FOV) =360×360 mm², matrix size =189×154, flip angle =46°, and temporal resolution =32 ms. T1 mapping involved modified Look-Locker inversion recovery (MOLLI) sequences, with native T1 values captured via a 5(3)3 scheme and post-contrast T1 via a 4(1)3(1)2 scheme. LGE imaging was performed 10 minutes after the intravenous administration of gadolinium-based contrast medium (0.2 mmol/kg of gadobutrol, Bayer, Leverkusen, Germany) under a breath-hold phase-sensitive inversion recovery (PSIR) gradient-echo sequence and the following parameters: TR =732 ms, TE =1.27 ms, flip angle =50°, and slice thickness =8 mm.

Parameter measurements and data analysis

Structural and functional analyses were performed using CVI 42 version 5.14.0 (Circle Cardiovascular Imaging Inc., Calgary, AB, Canada). LV contours were delineated semiautomatically on short-axis cine images with manual adjustments. WT was segmented into basal (segments 1–6), middle (segments 7–12), and apical (segments 13–16) regions according to the 16-segment American Heart Association (AHA) model (22). Key parameters such as LV end diastolic volume (LVEDV), LV end systolic volume (LVESV), LVEF, and LV mass (LVM) were derived from end-diastolic and end-systolic delineations. The indices for LVM (LVMi), LVEDV (LVEDVi), and LVESV (LVESVi) were calculated by indexing to body surface area (BSA). Left atrial (LA) end-diastolic volume (LAEDV), LA end-systolic volume (LAESV), and LA ejection fraction (LAEF) were measured from the two- and four-chamber views.

Hypertrophic wall distribution characteristics across the 16 segments were quantified via the following metrics: mean WT, maximum WT (max WT), WT variation, and hypertrophic segments count. Mean WT and max WT were defined as the average and thickest values among the 16 segments, respectively. WT variation was calculated as the standard deviation (SD) of WT divided by the mean thickness of the 16 segments. Segments with a WT ≥12.0 mm were defined as hypertrophic and added to the hypertrophic segments count.

Strain analysis was conducted with a tissue tracking module, which measured peak systolic LS, CS, and RS including global and regional (basal, middle, and apical) values. LGE percentage (LGE%) was calculated as the LGE volume relative to total myocardial volume and identified with a grayscale threshold of ≥5 SD above that of the normal myocardium. Native- and post-T1 values were measured across all LV short-axis slices. Extracellular volume fraction (ECV%) was calculated with a standard formula based on T1 relaxation times of the myocardium and blood as measured both pre- and post-contrast administration, along with the patient’s hematocrit (cellular volume fraction of blood) within 1 week (23).

To enhance the reliability of the analysis, all measurements were conducted in a blinded manner, ensuring independence from another other. Strain parameters were measured again in a randomly selected cohort of 30 patients after a 15-day interval by a radiologist (Y.B.) with 6 years of experience in CMR.

Statistical analysis

Continuous variables were presented as the mean ± SD or as the median and IQR based on their distribution and were compared between sexes via the independent t-test or Mann-Whitney test, as appropriate. Categorical variables were expressed as frequencies (%) and were compared via the Chi-squared or Fisher exact test. A P value <0.05 was considered statistically significant. The statistical analysis was conducted in three sequential steps. First, Pearson or Spearman correlation coefficients were computed based on data normality to evaluate the associations between myocardial hypertrophy parameters—including LVMi, mean WT, max WT, WT variation, and hypertrophic segment count—and fibrosis metrics (LGE%, ECV%, and native T1), with global myocardial strain indices including global longitudinal strain (GLS), global circumferential strain (GCS), and global radial strain (GRS). Second, variables that demonstrated statistically significant associations (P<0.05) in the univariate analysis were subsequently entered into multivariate linear regression (MLR) models to evaluate their independent effects on global strain parameters, with adjustments made for potential confounders such as sex and age. Multicollinearity among predictors was assessed and appropriately accounted for. Third, interaction terms were incorporated into the MLR models to examine whether the impact of myocardial hypertrophy on strain mechanics varied by regional location and sex. To facilitate the interpretation of significant interactions, interaction plots were generated to visually illustrate these differential effects.

Intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of continuous remeasurements in the 30 patients, with values >0.75 indicating good consistency. Statistical analyses were conducted with SPSS 24.0 (IBM Corp., Armonk, NY, USA) and Microsoft Excel 2016 (Microsoft Corp., Redmond, WA, USA).

Results

Out of 161 patients who met the inclusion criteria, 59 were excluded, as displayed in Figure 1. The reasons for exclusion were suboptimal image quality (11 with incomplete myocardial coverage or motion artifacts and 14 with the inconsistencies of heart rate in different sections leading to inaccurate strain analysis), prior cardiac interventions (14 with alcohol or radiofrequency ablation for myocardial reduction), severe coronary artery disease (n=15), and confirmed Fabry disease (n=5). Table 1 presents the demographic and baseline characteristics of the enrolled patients as stratified by sex. The cohort included individuals with New York Heart Association (NYHA) classifications I to IV and various HOCM phenotypes (including sigmoid, reverse, neutral, and apical). The majority of patients were referred for surgery, with a high mean peak LVOT gradient of 90.55±33.59 mmHg. Males, constituting 65.69% of the cohort, were significantly younger and had a larger BSA than did females (both P values <0.05). No significant sex-based differences were observed in peak LVOT gradients or mitral regurgitation severity. LVEDVi and LVESVi were also not significantly different between sexes (both P values >0.05). However, males demonstrated a higher hypertrophic burden, as evidenced by higher LVMi, LVM/EDV ratio, mean WT, max WT, and hypertrophic segment count. In addition, males demonstrated a higher LGE%, indicating more extensive focal fibrosis of the myocardium (all P values <0.05). In contrast, native T1 and ECV% were statistically similar between the sexes. Despite these structural differences, there were no significant sex differences in LVEF or the global strain metrics (GLS, GCS, and GRS) (all P values >0.05). Notably, females had a significantly lower LAEF compared to males (P<0.05).

Figure 1 Enrollment flowchart. CMR, cardiovascular magnetic resonance; HOCM, hypertrophic obstructive cardiomyopathy.

Correlation analysis revealed that key LV hypertrophy-related indices—LVMi, mean WT, max WT, hypertrophic segment count—as fibrosis-related parameters—LGE%, ECV%, and native T1—were significantly associated with all myocardial strain metrics, albeit to varying degrees (all P values <0.05). Among these variables, mean WT showed the strongest correlation with GLS (r=–0.72), while max WT was most closely correlated with GCS (r=–0.59). LGE% showed the strongest association with strain metrics among the fibrosis markers (GLS: r=–0.56; GCS: r=–0.55; GRS: r=0.51). In contrast, WT variation had no significant correlations with any of the strain metrics (all P values >0.05). ECV% exhibited the lowest correlation coefficients with strain metrics among the significant variables. Post-contrast T1 values did not significantly correlate with any strain metrics (all P values >0.05). Detailed absolute r values and significance are visualized in the bar charts in Figure 2. Additionally, LV functional metrics (LVESV and LVEF) correlated significantly with all strain metrics (all P values <0.001), with GRS showing the strongest associations (r=–0.41 and r=–0.62, respectively), followed by GCS (r=0.38 and r=–0.57, respectively) and GLS (r=0.31 and r=–0.39, respectively). There were no significant correlations of LVEDV or LA volume metrics (LAEDV, LAESV, and LAEF) with LV strain metrics (GLS, GCS, and GRS; all P values >0.05). Among the strain metrics, GRS and GCS were highly correlated with one another (r=–0.98; P<0.001), more so than with GLS (GRS: r=–0.70; GCS: r=0.74). The details of the correlations are presented in Figures S1,S2. In addition, age showed a modest but significant correlation with GCS (r=0.21; P=0.033) and a weak correlation with GRS (r=–0.17; P=0.082) and GLS (r=0.20; P=0.050).

Figure 2 Correlation between global myocardial strain and structural/fibrotic parameters in HOCM. Bar chart displaying the absolute correlation coefficients between global myocardial strain parameters—GLS, GCS, and GRS—and LV hypertrophy and fibrosis-related variables in patients with HOCM. Hypertrophy-related parameters include LVMi, mean WT, max WT, number of hypertrophic segments, and WT variation. Fibrosis-related parameters include LGE%, native T1, and ECV%. Correlation strengths are presented as absolute values. Statistical significance is denoted as follows: *, P<0.1; **, P<0.05; ***, P<0.001. ECV%, extracellular volume fraction; GCS, global circumferential strain; GLS, global longitudinal strain; GRS, global radial strain; HOCM, hypertrophic obstructive cardiomyopathy; LGE%, late gadolinium enhancement percentage; LV, left ventricular; LVMi, left ventricular mass index; max, maximum; WT, wall thickness.

Multivariate linear regression models, adjusted for sex and age, were used to identify the independent predictors of global strain metrics (GLS, GCS, and GRS), as shown in Table 2. Mean WT emerged as an independent predictor for all strain indices, including GLS (B=0.792), GCS (B=0.543), and GRS (B=–1.38) (all P values <0.001). ECV% was also independently associated with GLS (B=0.248; P<0.001) and GCS (B=0.162; P=0.018), while WT variation was associated with GCS (B=5.49; P=0.031). Meanwhile, hypertrophic segment count and LVMi were excluded during the model construction due to collinearity with other variables.

The interaction analysis results are summarized in Table 3. Sex significantly influenced global strain metrics, with strong interaction effects between sex and WT on GRS, GCS, and GLS (all interaction P values <0.001). Specifically, sex-WT interactions had standardized B values of –1.457, –1.588, and –1.892 for GRS, GCS, and GLS, respectively, highlighting distinct strain responses to WT between males and females. In regional strain analysis, WT showed no significant association with regional RS (B=0.226; P=0.701) or CS (B=0.05; P=0.816) and was non-significantly associated with regional LS (B=0.422; P=0.066). The myocardial region itself exerted a significant effect on all regional strain parameters (RS, CS, and LS), and the interaction between region and WT was statistically significant for all three strain types (all P values <0.05, suggesting that the effect of hypertrophy on regional myocardial mechanics varies across different cardiac regions. These findings indicate that the effect of myocardial hypertrophy on strain is modulated by both sex and regional myocardial location. Figure 3 indicates that an increased mean WT is associated with a significant reduction in global strain (absolute value reduction), particularly in females. In terms of region, the apex exhibited the most pronounced strain impairment with increasing mean WT. The scatter plots in Figure 4 demonstrate the associations across different LV regions and between sexes, revealing that strain impairment is most severe at the apex and more pronounced in females, as indicated by steeper regression slopes.

Figure 3 Sex- and region-specific associations between wall thickness and myocardial strain in patients with HOCM. Scatter plots illustrating the relationships between myocardial strain metrics and WT in patients with HOCM. Top row: global strain parameters—GRS, GCS, and GLS—plotted against mean WT and stratified by sex (blue for females and green for males). GRS declines more steeply with increasing WT in females, while GCS and GLS also showed greater impairment in females with a greater degree of hypertrophy. Bottom row: regional strain parameters—RS, CS, and LS—plotted against WT across left ventricular regions (blue for base, green for middle, and yellow for apex). Strain impairment was most pronounced at the apex, particularly for RS and LS, suggesting heightened regional vulnerability to hypertrophy. CS, circumferential strain; GCS, global circumferential strain; GLS, global longitudinal strain; GRS, global radial strain; HOCM, hypertrophic obstructive cardiomyopathy; LS, longitudinal strain; RS, radial strain; WT, wall thickness.

Figure 4 Sex-specific relationships between wall thickness across left ventricular regions. Scatter plots showing the associations between wall thickness (x-axis) and regional myocardial strain (y-axis) across basal (top row), midventricular (middle row), and apical (bottom row) segments. Columns correspond to LS, CS, and RS. Female and male patients are represented by blue and green circles, respectively, with corresponding linear regression lines. Strain impairment was most pronounced in the apical region, particularly among females, as reflected by steeper declines in absolute LS, CS, and RS values with increasing wall thickness. CS, circumferential strain; LS, longitudinal strain; RS, radial strain; WT, wall thickness.

The cases shown in Figure 5A,5B illustrate the differences in fibrotic burden (characterized by LGE and ECV mapping) across regions and sexes and indicate that females and apical regions exhibit significantly higher levels of fibrosis, potentially exacerbating strain impairment.

Figure 5 Regional and sex-specific variations in myocardial fibrosis among patients with HOCM and comparable wall thickness. (A) Short-axis LGE images from three representative patients with HOCM (rows) indicated that despite comparable wall thickness across basal (first column), middle (second column), and apical (third column) segments, apical regions consistently had more extensive fibrosis. The ECV maps from the third patient (fourth row) further revealed marked interstitial fibrosis in the apex, as indicated by intense red areas. These findings highlight the apex’s greater vulnerability to fibrotic remodeling. (B) Three-chamber LGE images in male (left) and female (right) cases (n=4). Despite similar wall thickness distribution, female patients exhibited a markedly greater fibrotic burden within hypertrophic regions. These findings suggest that female patients undergo more extensive myocardial remodeling, potentially exacerbating strain impairment due to the combined effects of hypertrophy and fibrosis. ECV, extracellular volume; HOCM, hypertrophic obstructive cardiomyopathy; LGE, late gadolinium enhancement.

The ICC analysis demonstrated good reproducibility for all the measurements, with ICC values ranging from 0.897 to 0.975 (Table S1).

Discussion

This study clarified the regional and sex-specific differences in the association between myocardial hypertrophy and strain impairment in patients with HOCM through use of advanced CMR techniques. All global strain metrics—GRS, GCS, and GLS—were significantly correlated with structural and fibrosis parameters, including WT distribution characteristics, LVMi, LGE%, ECV%, and native T1. Among these, mean WT, out of all hypertrophic distribution characteristics and fibrosis surrogates, emerged as the strongest independent predictor of global strain (GLS: B=0.792; GCS: B=0.543; GRS: B=–1.38; all P values <0.001). ECV% was independently associated with GLS (B=0.248) and GCS (B=0.162), while WT variation independently predicted GCS reduction (all P values <0.05). These results suggest the prominent role of hypertrophic burden, particularly mean WT, in determining global strain impairment. Additionally, we identified greater strain vulnerability in the apex and in female patients, evidenced by steeper regression slopes and higher fibrosis burden with a WT increment. Collectively, these findings highlight the importance of integrating quantitative phenotypic features and sex-specific patterns into individualized risk stratification and management in HOCM.

Contribution of hypertrophy and fibrosis to strain impairment in HOCM

Our findings underscore the central role of myocardial hypertrophy in mediating myocardial dysfunction in HOCM. Both WT and LVM were significantly correlated with global strain impairment, with mean WT emerging as the strongest independent predictor of GLS, GCS, and GRS. This aligns with prior two-dimensional (2D) and three-dimensional (3D) strain studies in broader HCM cohorts, where hypertrophy consistently predicted myocardial deformation abnormalities (14,16,17,24). Notably, among the various hypertrophic distribution metrics, mean WT—rather than max WT or WT variation—proved to be the most robust determinant of strain impairment across all three directional axes. Although max WT >30 mm has been linked to an elevated risk of sudden cardiac death, this relationship may be U-shaped (25,26). Our multivariate analysis further confirmed that mean WT independently correlates with all global strain indices, even after adjustments for fibrosis surrogates, highlighting the significance of total hypertrophic burden compared to other hypertrophic patterns. This potentially aligns with previous work reporting that extensive hypertrophy is linked to worse clinical outcomes in HCM (27). Moreover, regional variation in WT demonstrated an independent association with GCS (P<0.05) and a nonsignificant association with GRS (P=0.06), suggesting that segmental heterogeneity may influence myocardial deformation, particularly in circumferential and radial directions. These deformation components likely rely on more synchronized contractile forces across myocardial segments, rendering them more susceptible to disparities in WT than to longitudinal strain.

In terms of mechanism, myocardial hypertrophy disrupts the subendocardial longitudinal fibers that are primarily responsible for longitudinal shortening, which explains the heightened sensitivity of GLS to wall thickening (17,28). In contrast, RS has been reported to show weaker associations with WT, while CS may exhibit a biphasic trajectory—initially increasing during early compensatory hypertrophy and subsequently declining with disease progression (14). This trajectory suggests that CS is further and more greatly influenced by advanced histopathological changes than hypertrophy alone (17). All fibrosis markers (LGE%, ECV%, and native T1) were significantly associated with strain parameters in multiple directions. Among these, ECV% emerged as the only independent predictor of GLS and GCS, emphasizing the role of diffuse interstitial fibrosis in augmenting myocardial stiffness and limiting deformability (29,30). Although LGE% demonstrated moderately strong correlations with strain (r=0.51–0.56), its predictive power diminished after adjustment, likely due to its focal nature and collinearity with regional hypertrophy (20,31,32). Collectively, these findings support the centrality of hypertrophy in driving myocardial dysfunction and further indicate that strain impairment arises from a multifactorial interplay between structural remodeling and fibrotic burden.

Apical region and female sex as susceptibility factors

We observed that strain impairment varied by region, with the apex showing the greatest functional decline as WT increased. This suggests that the apex is particularly vulnerable to the effects of hypertrophy, likely due to its unique fiber orientation, heightened contractile demands, and sensitivity to pressure gradients (33,34). Apical hypertrophy may more severely limit deformation due to the region’s smaller capacity as compared to that of the basal and middle segments. Additionally, fibrosis may further impair apical function, which is consistent with its known susceptibility to fibrotic remodeling in advanced HCM (35), as exemplified by the representative cases shown in Figure 5A. This speculation is supported by a previous study in which apical HCM was associated with a significantly lower GLS as compared to other HCM phenotypes, such as sigmoid HCM (36), underscoring the substantial role of apical hypertrophy in global strain deterioration.

Furthermore, our study confirms and extends previous work demonstrating greater strain impairment in females. Although the enrolled male patients exhibited a greater hypertrophic burden as quantified by LVMi and LVM/EDV, the female patients had pronounced strain impairment for a given increase in WT. This suggests that myocardial strain in females is more susceptible to hypertrophic changes. Consistent with these findings, a previous study found that female patients tend to develop severer myocardial remodeling at the earlier stages of HCM, which may accelerate disease progression (37). This sex difference may be attributed to pathophysiological features unique to women, including greater interstitial fibrosis, cardiomyocyte disarray, and microvascular dysfunction (18,37,38). As illustrated in Figure 5B, several females with similar WT had a higher degree of fibrosis as compared to their male counterparts, possibly accelerating strain decline. Further stratified analysis revealed that female patients experienced especially significant impairment in apical strain as compared to males. Although apical twist mechanics were not directly assessed in this study, previous research has demonstrated that women tend to rely more on apical twist and untwisting to maintain stroke volume under conditions of reduced preload (39). This functional adaptation may chronically overload the apex, promoting fibrosis. The convergence of hypertrophy and fibrosis in this vulnerable region could thus exacerbate mechanical dysfunction. These findings may partly explain the increased risk of heart failure observed in female patients with HOCM, as previously reported (40). Age modestly correlated with GCS but did not independently predict strain impairment. We acknowledge that despite adjusting for age in our analysis, the higher prevalence of older age among female patients may partially explain their reduced compensatory capacity and greater functional impairment (41). Age-related factors, particularly the decline in estrogen levels during menopause, may synergistically contribute to the observed sex differences in strain impairment. Indeed, one study has suggested that estrogen exerts protective effects on myocardial remodeling and fibrosis; thus, reduced estrogen levels in postmenopausal women may exacerbate myocardial stiffening and functional decline (42). Larger-sample studies are needed to clarify the interactive effects of age and sex on myocardial hypertrophy and remodeling. Given the potential influence of menopause, future research incorporating hormonal profiles is also warranted. Notably, in real-world outpatient settings, women with HOCM are often diagnosed at an older age than are men (41), and thus our findings bear heightened clinical relevance and generalizability. The early identification and proactive management of women may be crucial to slowing disease progression and optimizing clinical outcomes.

Limitations

Our study involved several limitations that warrant discussion. First, the retrospective, single-center design may limit the generalizability of the findings. Second, we did not compare structural and functional differences between the HOCM and non-obstructive HCM cohorts, nor did we stratify patients with HOCM by anatomical subtype, which might have offered additional pathophysiological insights. Third, strain analysis was limited to CMR-derived parameters, with no validation against echocardiographic measures, potentially introducing modality-specific measurement bias. Additionally, fibrosis was assessed via imaging-based surrogates rather than histological validation, which might have reduced the accuracy of tissue characterization. Although age was adjusted for in the multivariate analyses, we acknowledge that the lack of age stratification is a limitation of this study. The absence of follow-up—both for longitudinal strain changes and posttreatment outcomes—precluded an evaluation of strain progression or its prognostic value. Future studies should incorporate prospective, multicenter designs with multimodal imaging and sex-specific diagnostic thresholds for WT hypertrophy in order to validate and expand upon these findings.

Conclusions

In this study, both global and regional myocardial dysfunction in HOCM were found to arise from a complex interplay of myocardial hypertrophy, fibrosis, and segmental structural heterogeneity. Among markers, mean WT emerged as the most robust and consistent determinant of multidirectional strain impairment. Notably, functional deterioration was most prominent in the apical regions and among female patients, indicating that these subgroups have heightened susceptibility to adverse remodeling. These findings emphasize the importance of phenotype-specific and sex-aware approaches in clinical evaluation. CMR-based multiparametric assessment offers a powerful, noninvasive tool for individualized risk stratification and may inform more targeted therapeutic strategies in the management of HOCM.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-457/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-457/dss

Funding: This work was supported by grants from the National Natural Science Foundation of China (No. 82272109).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-457/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Ethics Committee of Tongji Hospital (approval No. 2020, S155). The requirement for informed consent was waived due to the retrospective nature of the analysis.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Maron MS, Olivotto I, Zenovich AG, Link MS, Pandian NG, Kuvin JT, Nistri S, Cecchi F, Udelson JE, Maron BJ. Hypertrophic cardiomyopathy is predominantly a disease of left ventricular outflow tract obstruction. Circulation 2006;114:2232-9. [Crossref] [PubMed]
2. Veselka J, Anavekar NS, Charron P. Hypertrophic obstructive cardiomyopathy. Lancet 2017;389:1253-67. [Crossref] [PubMed]
3. Maron BJ, Desai MY, Nishimura RA, Spirito P, Rakowski H, Towbin JA, Rowin EJ, Maron MS, Sherrid MV. Diagnosis and Evaluation of Hypertrophic Cardiomyopathy: JACC State-of-the-Art Review. J Am Coll Cardiol 2022;79:372-89. [Crossref] [PubMed]
4. Palmisano V, Cossa S, Esposito A, Bassareo PP, Porcu M, Cau R, Pontone G, Suri JS, Saba L. Obstructive and Nonobstructive Hypertrophic Cardiomyopathy: Differences in Global and Segmental Myocardial Strain by Cardiac Magnetic Resonance Feature Tracking. J Thorac Imaging 2022;37:49-57. [Crossref] [PubMed]
5. Pelliccia F, Alfieri O, Calabrò P, Cecchi F, Ferrazzi P, Gragnano F, Kaski JP, Limongelli G, Maron M, Rapezzi C, Seggewiss H, Yacoub MH, Olivotto I. Multidisciplinary evaluation and management of obstructive hypertrophic cardiomyopathy in 2020: Towards the HCM Heart Team. Int J Cardiol 2020;304:86-92. [Crossref] [PubMed]
6. Nealy Z, Kramer C. Imaging in Hypertrophic Cardiomyopathy: Beyond Risk Stratification. Heart Fail Clin 2023;19:419-28. [Crossref] [PubMed]
7. Lebowitz S, Kowalewski M, Raffa GM, Chu D, Greco M, Gandolfo C, Mignosa C, Lorusso R, Suwalski P, Pilato M. Review of Contemporary Invasive Treatment Approaches and Critical Appraisal of Guidelines on Hypertrophic Obstructive Cardiomyopathy: State-of-the-Art Review. J Clin Med 2022;11:3405. [Crossref] [PubMed]
8. Cui H, Schaff HV, Nishimura RA, Geske JB, Dearani JA, Newman DB, Ommen SR. Preoperative left ventricular longitudinal strain predicts outcome of septal myectomy for obstructive hypertrophic cardiomyopathy. J Thorac Cardiovasc Surg 2023;166:492-500.e2. [Crossref] [PubMed]
9. Wang J, Sun X, Xiao M, Zhang M, Chen H, Zhu C, Wang S, Wang H. Regional Left Ventricular Reverse Remodeling After Myectomy in Hypertrophic Cardiomyopathy. Ann Thorac Surg 2016;102:124-31. [Crossref] [PubMed]
10. Braunwald E, Saberi S, Abraham TP, Elliott PM, Olivotto I. Mavacamten: a first-in-class myosin inhibitor for obstructive hypertrophic cardiomyopathy. Eur Heart J 2023;44:4622-33. [Crossref] [PubMed]
11. Yang S, Ji K, Chen X, Li F, Yang K, Yu S, Zheng Y, Song Y, Zhao K, Lu M, Wang S, Wang S, Zhao S. Left Ventricular Myocardial Remodeling and Prognostic Marker Derived from Postmyectomy Cardiac MRI Feature Tracking in Hypertrophic Obstructive Cardiomyopathy. Radiol Cardiothorac Imaging 2022;4:e210172. [Crossref] [PubMed]
12. Smiseth OA, Rider O, Cvijic M, Valkovič L, Remme EW, Voigt JU. Myocardial Strain Imaging: Theory, Current Practice, and the Future. JACC Cardiovasc Imaging 2025;18:340-81. [Crossref] [PubMed]
13. Smiseth OA, Torp H, Opdahl A, Haugaa KH, Urheim S. Myocardial strain imaging: how useful is it in clinical decision making? Eur Heart J 2016;37:1196-207. [Crossref] [PubMed]
14. Voilliot D, Huttin O, Hammache N, Filippetti L, Vaugrenard T, Aliot E, Sadoul N, Juillière Y, Selton-Suty C. Impact of Global and Segmental Hypertrophy on Two-Dimensional Strain Derived from Three-Dimensional Echocardiography in Hypertrophic Cardiomyopathy: Comparison with Healthy Subjects. J Am Soc Echocardiogr 2015;28:1093-102. [Crossref] [PubMed]
15. Kato S, Horita N, Utsunomiya D. Cardiac magnetic resonance-derived tissue tracking strain in patients with hypertrophic cardiomyopathy. Quant Imaging Med Surg 2023;13:1235-9. [Crossref] [PubMed]
16. Urbano-Moral JA, Rowin EJ, Maron MS, Crean A, Pandian NG. Investigation of global and regional myocardial mechanics with 3-dimensional speckle tracking echocardiography and relations to hypertrophy and fibrosis in hypertrophic cardiomyopathy. Circ Cardiovasc Imaging 2014;7:11-9. [Crossref] [PubMed]
17. Pagourelias ED, Mirea O, Vovas G, Duchenne J, Michalski B, Van Cleemput J, Bogaert J, Vassilikos VP, Voigt JU. Relation of regional myocardial structure and function in hypertrophic cardiomyopathy and amyloidois: a combined two-dimensional speckle tracking and cardiovascular magnetic resonance analysis. Eur Heart J Cardiovasc Imaging 2019;20:426-37. [Crossref] [PubMed]
18. Wasserstrum Y, Larranaga-Moreira JM, Lotan D, Fernandez-Fernandez X, Klempfner R, Sabbag A, Freimark D, Monserrat L, Arad M, Barriales-Villa R. Gender variability in the clinical phenotype of hypertrophic cardiomyopathy. European Heart Journal 2020;41:ehaa946.2089. Available online: https://doi.org/10.1093/ehjci/ehaa946.2089
19. Yang W, Xu J, Zhu L, Zhang Q, Wang Y, Zhao S, Lu M. Myocardial Strain Measurements Derived From MR Feature-Tracking: Influence of Sex, Age, Field Strength, and Vendor. JACC Cardiovasc Imaging 2024;17:364-79. [Crossref] [PubMed]
20. Nucifora G, Muser D, Gianfagna P, Morocutti G, Proclemer A. Systolic and diastolic myocardial mechanics in hypertrophic cardiomyopathy and their link to the extent of hypertrophy, replacement fibrosis and interstitial fibrosis. Int J Cardiovasc Imaging 2015;31:1603-10. [Crossref] [PubMed]
21. Ommen SR, Ho CY, Asif IM, Balaji S, Burke MA, Day SM, Dearani JA, Epps KC, Evanovich L, Ferrari VA, Joglar JA, Khan SS, Kim JJ, Kittleson MM, Krittanawong C, Martinez MW, Mital S, Naidu SS, Saberi S, Semsarian C, Times S, Waldman CB. AHA/ACC/AMSSM/HRS/PACES/SCMR Guideline for the Management of Hypertrophic Cardiomyopathy: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. Circulation 2024;2024:149.
22. Selvadurai BSN, Puntmann VO, Bluemke DA, Ferrari VA, Friedrich MG, Kramer CM, Kwong RY, Lombardi M, Prasad SK, Rademakers FE, Young AA, Kim RJ, Nagel E. Definition of Left Ventricular Segments for Cardiac Magnetic Resonance Imaging. JACC Cardiovasc Imaging 2018;11:926-8. [Crossref] [PubMed]
23. Messroghli DR, Moon JC, Ferreira VM, Grosse-Wortmann L, He T, Kellman P, Mascherbauer J, Nezafat R, Salerno M, Schelbert EB, Taylor AJ, Thompson R, Ugander M, van Heeswijk RB, Friedrich MG. Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imaging (EACVI). J Cardiovasc Magn Reson 2017;19:75. [Crossref] [PubMed]
24. Satriano A, Heydari B, Guron N, Fenwick K, Cheung M, Mikami Y, Merchant N, Lydell CP, Howarth AG, Fine NM, White JA. 3-Dimensional regional and global strain abnormalities in hypertrophic cardiomyopathy. Int J Cardiovasc Imaging 2019;35:1913-24. [Crossref] [PubMed]
25. Norrish G, Ding T, Field E, Cervi E, Ziółkowska L, Olivotto I, et al. Relationship Between Maximal Left Ventricular Wall Thickness and Sudden Cardiac Death in Childhood Onset Hypertrophic Cardiomyopathy. Circ Arrhythm Electrophysiol 2022;15:e010075. [Crossref] [PubMed]
26. O'Mahony C, Jichi F, Monserrat L, Ortiz-Genga M, Anastasakis A, Rapezzi C, Biagini E, Gimeno JR, Limongelli G, McKenna WJ, Omar RZ, Elliott PM. Inverted U-Shaped Relation Between the Risk of Sudden Cardiac Death and Maximal Left Ventricular Wall Thickness in Hypertrophic Cardiomyopathy. Circ Arrhythm Electrophysiol 2016;9:e003818. [Crossref] [PubMed]
27. Neubauer S, Kolm P, Ho CY, Kwong RY, Desai MY, Dolman SF, et al. Distinct Subgroups in Hypertrophic Cardiomyopathy in the NHLBI HCM Registry. J Am Coll Cardiol 2019;74:2333-45. [Crossref] [PubMed]
28. Funabashi N, Takaoka H, Ozawa K, Kobayashi Y. Endocardial Fibrotic Lesions Have a Greater Effect on Peak Longitudinal Strain than Epicardial Fibrotic Lesions in Hypertrophic Cardiomyopathy Patients. Int Heart J 2018;59:347-53. [Crossref] [PubMed]
29. Topriceanu CC, Captur G. Aberrant Myocardial Dynamics in Subclinical Hypertrophic Cardiomyopathy. Circ Cardiovasc Imaging 2024;17:e016572. [Crossref] [PubMed]
30. Jin C, Weber J, Singh H, Gliganic K, Cao JJ. The association of reduced left ventricular strains with increased extracellular volume and their collective impact on clinical outcomes. J Cardiovasc Magn Reson 2021;23:93. [Crossref] [PubMed]
31. Holtackers RJ, Emrich T, Botnar RM, Kooi ME, Wildberger JE, Kreitner KF. Late Gadolinium Enhancement Cardiac Magnetic Resonance Imaging: From Basic Concepts to Emerging Methods. Rofo 2022;194:491-504. [Crossref] [PubMed]
32. Jimenez Juan L, Crean AM, Wintersperger BJ. Late gadolinium enhancement imaging in assessment of myocardial viability: techniques and clinical applications. Radiol Clin North Am 2015;53:397-411. [Crossref] [PubMed]
33. Piro M, Della Bona R, Abbate A, Biasucci LM, Crea F. Sex-related differences in myocardial remodeling. J Am Coll Cardiol 2010;55:1057-65. [Crossref] [PubMed]
34. Wu EX, Wu Y, Tang H, Wang J, Yang J, Ng MC, Yang ES, Chan CW, Zhu S, Lau CP, Tse HF. Study of myocardial fiber pathway using magnetic resonance diffusion tensor imaging. Magn Reson Imaging 2007;25:1048-57. [Crossref] [PubMed]
35. Galati G, Leone O, Pasquale F, Olivotto I, Biagini E, Grigioni F, Pilato E, Lorenzini M, Corti B, Foà A, Agostini V, Cecchi F, Rapezzi C. Histological and Histometric Characterization of Myocardial Fibrosis in End-Stage Hypertrophic Cardiomyopathy: A Clinical-Pathological Study of 30 Explanted Hearts. Circ Heart Fail 2016;9:e003090. [Crossref] [PubMed]
36. Vergé MP, Cochet H, Reynaud A, Morlon L, Peyrou J, Vincent C, Rooryck C, Ritter P, Lafitte S, Réant P. Characterization of hypertrophic cardiomyopathy according to global, regional, and multi-layer longitudinal strain analysis, and prediction of sudden cardiac death. Int J Cardiovasc Imaging 2018;34:1091-8. [Crossref] [PubMed]
37. Nijenkamp LLAM, Bollen IAE, Niessen HWM, Dos Remedios CG, Michels M, Poggesi C, Ho CY, Kuster DWD, van der Velden J. Sex-specific cardiac remodeling in early and advanced stages of hypertrophic cardiomyopathy. PLoS One 2020;15:e0232427. [Crossref] [PubMed]
38. Güçlü A, Happé C, Eren S, Korkmaz IH, Niessen HW, Klein P, van Slegtenhorst M, Schinkel AF, Michels M, van Rossum AC, Germans T, van der Velden J. Left ventricular outflow tract gradient is associated with reduced capillary density in hypertrophic cardiomyopathy irrespective of genotype. Eur J Clin Invest 2015;45:1252-9. [Crossref] [PubMed]
39. Williams AM, Shave RE, Stembridge M, Eves ND. Females have greater left ventricular twist mechanics than males during acute reductions to preload. Am J Physiol Heart Circ Physiol 2016;311:H76-84. [Crossref] [PubMed]
40. Geske JB, Ong KC, Siontis KC, Hebl VB, Ackerman MJ, Hodge DO, Miller VM, Nishimura RA, Oh JK, Schaff HV, Gersh BJ, Ommen SR. Women with hypertrophic cardiomyopathy have worse survival. Eur Heart J 2017;38:3434-40. [Crossref] [PubMed]
41. Nijenkamp LLAM, Bollen IAE, van Velzen HG, Regan JA, van Slegtenhorst M, Niessen HWM, Schinkel AFL, Krüger M, Poggesi C, Ho CY, Kuster DWD, Michels M, van der Velden J. Sex Differences at the Time of Myectomy in Hypertrophic Cardiomyopathy. Circ Heart Fail 2018;11:e004133. [Crossref] [PubMed]
42. El Hajj MC, Ninh VK, El Hajj EC, Bradley JM, Gardner JD. Estrogen receptor antagonism exacerbates cardiac structural and functional remodeling in female rats. Am J Physiol Heart Circ Physiol 2017;312:H98-H105. [Crossref] [PubMed]