The Concordance Rates between LV Hypertrophy and RV Hypertrophy in Patients with Hypertrophic Cardiomyopathy as Diagnosed by Cardiovascular MRI with Fibrosis Imaging ()
1. Introduction
Hypertrophic cardiomyopathy (
HCM
) is a genetically determined heart muscle disease most often (60 to 70 percent) caused by mutations in one of several sarcomere genes which encode components of the contractile apparatus [1] -[5] .
HCM
is characterized by left ventricular hypertrophy of various morphologies, with a wide array clinical manifestations and hemodynamic abnormalities [6] [7] . Infrequently, however, right ventricular (RV) involvement is described in reports of
HCM
. Other cardiac imaging modalities such as echocardiography and nuclear imaging have well known difficulties in assessment of the RV morphological abnormalities in
HCM
[8] - [10] . This has led to Cardiovascular
MRI
(CMR) becoming the leading modality to define the structural and functional as well as the clinical impact of
HCM
providing complete coverage of both ventricles with high spatial resolution Figures 1-3. Moreover, assessment of RV diseases, and specifically cardiomyopathies, is greatly
![]()
Figure 1. A 52 years old woman with SCD with CMR depicting SSFP images that demonstrate markedly thickened anterior wall to a maximum of 33 mm.
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Figure 2. A 52 years old woman (same in Figure 1) with SSFP images demonstrating markedly thickened septal wall to a maximum of 37 mm.
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Figure 3. A 32-years old female with SSFP image depicting markedly thin apex with relative hypertrophy of basal myocardium.
aided by the use of non-contrast CMR, which can be used to measure not only the thin-walled RV, providing mass estimations, but also provide volumetric information. Late gadolinium enhancement (
LGE
) adds the accurate identification of regions of myocardial fibrosis Figure 4, Figure 5. Via CMR; innumerable studies have established that LVH and
LGE
are the predominant phenotypic expressions of
HCM
. We hypothesize that there is significant right ventricular myocardial fibrosis as detected by CMR in
HCM
patients, which upon demonstration, would provide evidence for right ventricular involvement.
2. Methods
Images were obtained using a 1.5T General Electric whole body scanner (HD Excite version 12 GE Milwaukee WI). Subjects were imaged in the supine position and signal reception was accomplished using a 4-channel phased array cardiac coil. Sequences of interest included single shot Echo Planar Imaging, using a cardiac-trig- gered system with 40mT maximum gradient strength and 150 mT/m/ms maximum slew rate. The following parameters were used: repetition time (TR) = 9 ms, echo time (TE) = 4 ms, flip angle (FA) = 40 degrees, slice thickness = 8 mm, number of excitations (NEX) = 2 - 4, field of view = 380 - 420 mm, and matrix 128 × 128. Sagittal scout images were used to plan multiplanar steady state free-precession sequences (SSFP). Contrast
imaging/
LGE
was performed with gadolinium administration (0.15 mmol/kg, Post-injection 2/10 minutes).
LGE
images were obtained using breath-hold manual T1-weighted, inversion recovery preparations. Regions of myocardium with usually abnormal high signals were designated as fibrotic according to standard techniques. LV/RV mass indices (LVMI/RVMI), wall thickness and end-diastolic volumes were calculated after manually delineating the ventricular contours (epicardial and endocardial) during end-diastole. The ejection fraction was calculated by dividing LV stroke volume by end-diastolic volume. Fibrosis was semi-quantitatively assessed in both ventricles by an experienced clinician. A local IRB approved the research protocol.
3. Statistics
Data were reported as mean ± standard deviation for continuous variables and percentages for categorical variables. The independent samples t-test or the Mann-Whitney U test was used to determine differences between continuous variables. The chi-square test or Fisher’s Exact test was used to compare categorical variables. Data were examined for normality using the Kolmogrov-Smirnov test. Nonparametric tests were used to evaluate data that breaks parametric assumptions. A value of p < 0.05 on two-tailed testing was considered statistically significant. Statistical analyses were performed using
PASW
Statistics, version 18.0 (
IBM
-
SPSS
Inc., Chicago).
4. Results
Via 72 patients referred for
HCM
, presenting to Allegheny General Hospital (Pittsburgh, Pennsylvania) Cardiac
![]()
Figure 4. The same patient in Figures 1-3, late gadolinium en- hancement (
LGE
) imaging showing the lacy pattern of fibrosis without infarct. The patient had a wall thickness >30 mm.
![]()
Figure 5. A 52 years old woman (same in Figure 1 & Figure 2) with
LGE
images demonstrating anteroseptal hypertrophy and extensive mid septal post-gadolinium enhancement consistent with marked fibrosis and/or infarct likely outstripping the vascular supply.
MRI
Center from 2007-2013, 52 (72%) were CMR confirmed but five were excluded due to poor image quality (demographics are shown in Table 1). The mean LVMI for the remaining 47 patients was 108 ± 44g/m2 while the mean RVMI was 30 ± 2 g/m2. All patients met formal LVH criteria while 34/47 (72%) met RVH criteria. As well, 34/47 (72%) had evidence of LV fibrosis while 24/47 (51%) had evidence for RV fibrosis. Of the RVH positive patients, 26/34 (76%) patients were LV
LGE
positive and over half of the patients, specifically 18/34 (52%) were RV
LGE
positive. Only 2 patients with RV fibrosis had absent LV fibrosis (see Table 2). In order to ascertain whether fibrosis drove cardiac function, further parameters were performed.
Relating the presence of
LGE
, there was no statistical difference in LVEF% between LV
LGE
positive and LV
LGE
negative patients (p = NS). Mean LVEF% was similar between groups (LV ? DHE, Mean = 66.6, SD = 9.5, Median = 69.0 vs. LV
LGE
+, Mean = 67.5, SD = 10.5, Median = 69.5). As well, there was no statistical difference in LVEF% between RV
LGE
− and RV
LGE
+ patients (p = NS). Mean LVEF% was similar between groups (RV
LGE
−, Mean = 67.5, SD = 12.6, Median = 70.0 vs. RV
LGE −
, Mean = 67.0, SD = 7.4, Median = 68.0). Similarly, there was no statistical difference in RVEF% between LV
LGE
− and LV
LGE
+ patients (p = NS). Mean RVEF% was similar between groups (LV
LGE
−, Mean = 58.1, SD = 5.3, Median = 60.0 vs. LV
LGE
+, Mean = 57.6, SD = 8.8, Median = 58.5).
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Table 1. Demographics and cardiac
MRI
data for patients with
HCM
(N = 47).
![]()
Table 2. Demographics and cardiac
MRI
data for patients with RV
LGE
+ (N = 24) and RV
LGE
− (N = 23).
p = NS for all comparisons.
5. Discussion
Imaging modalities such as echocardiography and nuclear imaging help to detect various prognostic indicators in
HCM
such as LV mass, function and associated microvascular obstruction [11] Figure 6, Figure 7. Cardiovascular Magnetic Resonance (CMR) has become an established imaging modality which provides often unique information on a wide range of cardiovascular diseases. High resolution, absence of foreshortening and ability to perform three-dimensional (3D) imaging quickly in addition to the reliability and reproducibility has placed CMR at the forefront as the gold standard for LV/RV functional and structural assessment. The evaluation of RV is classically difficult because of its inability to conform easily to any standard geometric formulae. Assessment of RV diseases, and specifically cardiomyopathies, is greatly aided by the use of non-contrast CMR that can be used to measure not only the thin-walled RV, providing mass estimations, but also provide volumetric information. Recently, using
LGE
imaging, myocardial areas that demonstrate increased contrast enhancement typically correspond to areas of greatest hypertrophy, greatest myofibrillar disarray and areas of greatest collagen deposition in the exteracellular matrix Figure 8. Early evidence from several investigators has demonstrated that those presenting with a positive
LGE
signal within the myocardium, with specific focus on LV
LGE
,
![]()
Figure 6. The same patient in Figure 3 with a parasternal long axis view that reveals the asymmetric septal hypertrophy of the left ventricle.
![]()
Figure 7. The same patient in Figure 3 with a 5-chamber-view via echocardiography demonstrating a similar pattern, albeit less definitive of apical thinning with relative basal hypertrophy.
![]()
Figure 8. A 48 years old woman with documented HCM and LGE demonstrating diffuse global fibrosis indicative of gross LV fibrosis.
possess an adverse cardiovascular outcome.
Four single-center studies focused on the use of
LGE
as a prognostic factor for
HCM
to predict ventricular tachyarrhythmia, atrial fibrillation, heart failure and sudden cardiac death demonstrated variable predictive power for VT/VF and SCD dependent on presence or absence of
LGE
[12] - [15] . More recently, a meta-analysis done by Green et al. incorporating these four studies in 2012 showed that there are significant predictable relationships between
LGE
and cardiovascular mortality, heart failure death, and all-cause mortality in
HCM
16. We had performed an earlier systematic review demonstrating similar finding in which
LGE
, for the first time in 1064 patients did predict SCD with χ2 of 6.6 and an odds ratio of 3.3 [17] . To date, however, minimal focus has been concentrated on the RV fibrosis and
LGE
(in only one autopsy-based
HCM
report in the form of increased wall thickness) [8] . The significant high concordance rates between LV hypertrophy and RV hypertrophy in patients with
HCM
was previously described in an interesting study, conducted by Maron et al. in 2007, to evaluate RV wall thickness and mass indices via high spatial resolution CMR [18] . This group concluded that diffuse RV wall hypertrophy was present in high number of patients with
HCM
(54%) while only one subject had CMR evidence of RV fibrosis Figures 9-11. Herein we demonstrate with high sensitivity detection, a high incidence of the RV fibrosis (52%) in
HCM
patients referred to a tertiary referral center using standard
LGE
techniques. Our results provide support for and emphasize the hypothesis that the genetic cardiomyopathic pathology
![]()
Figure 9. Late gadolinium enhancement (
LGE
) demonstrating diffuse enhancement of the LV and RV. Note, more RV outflow tract LGE is present than LV LGE in a proven HCM patient.
![]()
Figure 10. LGE of both ventricles is more evident in a near transmural but irregular RV free wall enhancement pattern from a young man with a father as the HCM proband.
![]()
Figure 11. LGE showing irregular, diffuse biventricular enhancement indicative of diffuse fibrosis consistent with the clinical history of HCM.
in
HCM
is more diffuse involving a biventricular process (our study focused on the myocardial fibrotic changes) and bring attention to reconsidering the AHA definition for the
HCM
that focuses only on the LV pathology [19] .
The frequency of RVH and RV fibrosis in the setting of
HCM
is surprising in that this phenomenon is rarely described [20] - [22] . However, given the genetic abnormalities, there is no reason to expect that the phenotypic expression should be limited to the LV. Interestingly, as for the LV, the presence or absence of RV fibrosis had little predictive power towards the systolic function based on our study results. Finally, our study raises a question: “Do
HCM
patients with evidence of combined RV and LV myocardial fibrosis have worse outcomes or higher mortality rates compared to
HCM
patients with LV or RV fibrosis alone?” We believe that further prospective clinical studies are needed to answer this question.
6. Conclusion
Classically,
HCM
has been assumed to be purely LV pathology. Via CMR, over half of tertiary referral population was shown via
LGE
fibrosis imaging to have not only RVH but RV fibrosis. This finding provides further insight into the biventricular nature of
HCM
pathophysiology and raises further questions as an additional adverse prognostic factor.
Acknowledgements
Participated in the research design: Biederman, Grant. Participated in writing of the manuscript: Amin, Biederman. Participated in the performance of the research: Amin, Grant, Biederman, Shah. Participated in data analysis: Thompson, Doyle, Biederman. Contributed new analytic tools: Yamrozik, Williams, Grant.
Disclosures
All authors listed have no conflicts of interest to disclose and none of the authors have received any funding from any resource.
NOTES
*Corresponding author.