This prospective study enrolled consecutive adult patients with HCM, seen in the dedicated cardiomyopathy clinics of Santa Marta Hospital (n=70) (Lisbon, Portugal) and Garcia de Orta Hospital (n=13) (Almada, Portugal). CMR studies were performed at the Heart Center, Hospital da Cruz Vermelha Portuguesa (Lisbon, Portugal). The diagnosis of HCM was established according to current guidelines.1,29 Obstructive HCM was defined according to a peak gradient of ≥30 mmHg in the left ventricular outflow tract (LVOT) at rest or after provocation, on echocardiographic assessment. Inclusion criteria, exclusion criteria and clinical evaluation including ECG and echocardiography occurred as previously published by Aguiar Rosa et al.23

The study followed the principles outlined in the Declaration of Helsinki. The institutional ethics committees approved the study protocol. All patients provided written informed consent.

All subjects underwent the same CMR protocol as previously described by Aguiar Rosa et al.23 In brief, CMR was performed on a 1.5-T magnetic resonance system (Sola, Siemens, Erlangen, Germany). Using compressed sensing-based techniques, cine images in three long-axis planes and sequential short axis slices were acquired. Pre-contrast short axis T1 maps were generated using a Modified Look Locker Inversion (MOLLI) sequence and pre-contrast short axis T2 maps were generated using a single shot balanced steady state free precession acquisition. Stress perfusion 90 seconds after hyperemia was induced by regadenoson (400 mcg bolus) using 0.05 mmol/kg of gadolinium (Gadovist, Bayer Schering Pharma AG, Berlin, Germany). LGE images were acquired 10-15 minutes after intravenous administration of additional 0.15 mmol/kg of gadolinium at end diastole, using a breath-held segmented inversion-recovery steady state free precession sequence after determining the optimal inversion time using a scout sequence.

CMR interpretation was performed using commercially available software (CMR42, Circle Cardiovascular Imaging, Calgary, Alberta, Canada). LV wall thickness, LV mass, end diastolic volume (EDV), end systolic volume (ESV) and LV ejection fraction (EF) were measured from short axis cine images excluding papillary muscles and trabeculations.

For perfusion assessment, the myocardium was divided into 32 subsegments (16 American Heart Association (AHA) segments subdivided into an endocardial and epicardial layer). Ischemic burden for each patient was calculated as the number of involved sub-segments, assigning 3% of myocardium to each subsegment. Each segment was analyzed for the presence or absence of perfusion defects. Perfusion defects sparing the subendocardium and coincident with LGE were not considered, as subendocardial involvement is mandatory for microvascular dysfunction defects. The LGE was analyzed per-segment basis using a signal threshold versus reference myocardium of ≥6 standard deviation.

Three-dimensional longitudinal, circumferential and radial strains were obtained by manually drawing epicardial and endocardial contours on the end diastolic frame of short axis and long-axis images (four-chamber, two-chamber and three-chamber views), using an automatic feature tracking algorithm from cine images.

For each patient, each of the 16 AHA segments was assessed for LV thickness (≤11 mm; 12-14 mm; ≥15 mm), presence of perfusion defect, T1 mapping, T2 mapping, ECV, presence of LGE, longitudinal strain, radial strain and circumferential strain.

Statistical analysis was performed using the Statistical Package for the Social Sciences, V.23.0 for Windows (SPSS). Point estimates and 95% confidence interval (CI) are described for all mean estimates.

Descriptive statistics are presented as absolute frequency (number) and relative frequency (percentage) for categorical variables and as the mean for continuous variables.

The Kolmogorov-Smirnov test was used to test normality assumptions.

A segment-by-segment analysis was performed to assess the correlation between ischemia, LV hypertrophy, tissue characteristics and myocardial deformation parameters, calculated with univariable logistic and linear regressions. Subsequently multivariable analyses, adjusted for potential confounders, were performed. Whenever statistical hypothesis testing was used, a significance level of α=5% was considered.

The results of univariable regression analysis for potential factors associated with T1 mapping, T2 mapping, LGE and ECV are presented in Supplementary Table 1. Subsequently, a multivariable regression analysis, adjusted for potential confounders, was performed (Table 2).

Perfusion defects were associated with changes in tissue characteristics, independently of LV wall thickness (Figure 3). Segments with perfusion defect had a higher native T1 than those without (β-estimate 30.28, 95% CI 24.60-35.96, p<0.001), as well as a significantly higher ECV (β-estimate 1.50, 95% CI 0.81-2.11, p<0.001). T2 values were also higher in segments with perfusion defect (β-estimate 0.73, 95% CI 0.32-1.14, p<0.001) (Table 2 and Figure 3).

Figure 3.

Tissue characterization (T1 mapping, extracellular volume, T2 mapping) features, according to the presence or absence of perfusion defects.

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Furthermore, regardless of the wall thickness, segments with a perfusion defect more frequently had LGE (OR 4.16, 95% CI 3.19-5.41, p<0.001) (Figure 2). Among the 424 segments with perfusion defect, 115 segments (27.1%) did not present LGE.

Besides perfusion defects, wall thickness and obstructive HCM were features associated with tissue abnormalities (Table 2).

Univariable regression analyses for longitudinal strain, radial strain and circumferential strain are shown in Supplementary Table 2 and the multivariable analyses are described below.

Higher values of longitudinal strain (reflecting lower deformation) were found in segments with wall thickness ≥15 mm (β-estimate 2.28, 95% CI 0.87-3.69, p=0.002) compared with non-hypertrophied segments (Table 3). No association was found between perfusion defects and longitudinal strain in this segmental analysis. Higher values of circumferential strain (lower deformation) were found in segments with wall thickness 12-14 mm (β-estimate 2.31, 95% CI 1.35-3.26, p<0.001), wall thickness ≥15 mm (β-estimate 5.14, 95% CI 4.32-5.97, p<0.001) versus segments with normal wall thickness, in segments with perfusion defect (β-estimate 2.76, 95% CI 2.01-3.50, p<0.001) and in segments with LGE (β-estimate 2.30, 95% CI 1.57-3.02, p<0.001). Lower radial strain values (reflecting lower myocardial deformation) were found in segments with wall thickness 12-14 mm (β-estimate -9.90, 95% CI -13.19–-6.59, p<0.001) and wall thickness ≥15 mm (β-estimate -19.78, 95% CI -22.48–-17.09, p<0.001) in contrast to non-hypertrophied segments, segments with perfusion defect (β-estimate -10.39, 95% CI -12.83–-7.95, p<0.001) and with LGE (β-estimate -9.84, 95% CI -12.19–-7.48, p<0.001) (Table 3).

No association was found between T1 and T2 mapping values, ECV and tissue tracking analysis.

As a hallmark of the disease, severity of wall thickness was expectedly associated with tissue abnormalities. However, segments with only mild hypertrophy also showed the presence of increased T1 mapping and of LGE, displaying tissue abnormalities even in the absence of overt LV hypertrophy.

Regardless of the severity of hypertrophy, CMD was consistently related to tissue abnormalities in this study. Segments with perfusion defects were linked to both increased ECV and LGE, indicating the presence of both diffuse tissue abnormalities and replacement fibrosis.17,18 Hypertrophied myocytes are arranged in disarray, with increased extracellular matrix accumulation. While reduced ECV can be seen in cellular hypertrophy32 and in healthy athletes,33 ECV has been demonstrated to be increased in HCM in the context of focal or diffuse fibrosis,34 albeit with considerable heterogeneity among HCM patients.32 Moreover, while LGE may not accurately reveal the presence of abnormal tissue in the setting of less severe or more diffuse fibrosis, ECV has shown to be a surrogate for the presence of fibrosis in a significantly higher percentage of cardiac segments compared to LGE.35

Histologically, the severity of the abnormalities in intramural small vessels was previously found to be co-localized with fibrotic scars.17,18 By CMR stress perfusion, higher ischemic burden and lower stress myocardial blood flow were found to be linked to the presence of LGE.25,36 This suggests that replacement fibrosis may be partially secondary to microvascular dysfunction and ischemia.30,37,38 However, while LGE burden is a recognized prognostic factor particularly in advanced stages, it is tempting to speculate that ECV may detect earlier pathophysiological changes in HCM. Similarly, CMD is a pathological feature that seems to have an impact from an early stage of the disease, and thus may be a useful marker of disease progression and prognosis.13,39

Native T1 mapping reflects diffuse abnormalities in both the intracellular and extracellular spaces.40 In HCM, native T1 may be affected by the intracellular compartment where altered calcium cycling and sarcomeric calcium sensitivity, disturbed biomechanical stress sensing and impaired cardiac energy homeostasis have been detected.41 In our cohort, higher native T1 levels correlated with myocardial ischemia. This finding suggests that CMD may be associated not only with increased diffuse fibrosis but also with intracellular compartment abnormalities.

T2-weighted imaging, a tissue characterization technique mainly used to identify edema, can be elevated in HCM,42 both in hypertrophied and non-hypertrophied segments, despite normal wall thickness and preserved contractile function, which suggests that tissue abnormalities may precede morphological and functional remodeling in HCM.43 Furthermore, higher T2 values were previously correlated with higher brain natriuretic peptide levels, higher LGE extension and nonsustained ventricular tachycardia and have, therefore, been suggested as a possible marker for arrhythmogenicity.44 In our cohort, segments with higher T2 values were associated with greater LGE extent as well as with ischemia. To our knowledge, this is the first evidence of correlation between higher T2 and ischemia.

Speckle tracking parameters for systolic function are often impaired in HCM, such as longitudinal, circumferential and radial strain. Changes in these parameters vary widely between segments, reflecting the asymmetric nature of the disease. They are more prominent in segments with significant hypertrophy and fibrosis.45–47 In line with previous data,48 and using a per-segment analysis, we found a relationship between wall thickness and LGE and impaired LV myocardial deformation parameters.

Furthermore, hypoperfused segments showed worse circumferential and radial strain, independently of wall thickness or fibrosis, which is a novel - although probably expected - finding.

As LV performance is determined by several factors other than ischemia, such as wall thickness and extent of replacement fibrosis, with considerable heterogeneity among patients and within the left ventricle,46 in this study we did not find a correlation between impaired longitudinal strain and perfusion defects.

One limitation of our study is the relatively small population. Six patients were in AF during the scan, which may have influenced parametric mapping values. CMR assessment of tissue characteristics was not validated with histological samples. Perfusion defects, a surrogate for myocardial ischemia, were assessed using a semiquantitative visual analysis of ischemia in 32 segments, as used in previous studies comparing stress CMR with invasive evaluation of fractional flow reserve.14 While the adopted method is readily available and easily applicable, it relies on visual assessment and the total of LV assessed is 96% (3% for each segment).