Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/ou_press/myocardial-fibrosis-as-an-early-feature-in-phospholamban-p-arg14del-PkN03Dmx16
- Publisher
- Oxford University Press
- Copyright
- Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com.
- ISSN
- 2047-2404
- DOI
- 10.1093/ehjci/jey047
- Publisher site
- See Article on Publisher Site
Abstract
Abstract Aims The p.Arg14del founder mutation in the gene encoding phospholamban (PLN) is associated with an increased risk of malignant ventricular arrhythmia (VA) and heart failure. It has been shown to lead to calcium overload, cardiomyocyte damage, and eventually to myocardial fibrosis. This study sought to investigate ventricular function, the extent and localization of myocardial fibrosis and the associations with ECG features and VA in PLN p.Arg14del mutation carriers. Methods and results Cardiovascular magnetic resonance (CMR) data of 150 mutation carriers were analysed retrospectively. Left ventricular (LV) and right ventricular (RV) volumes, mass, and ejection fraction were measured. The extent of late gadolinium enhancement (LGE) was expressed as a percentage of myocardial mass. All standard ECG parameters were measured. Occurrence of VA was analysed on ambulatory 24-h and/or exercise electrocardiography, if available. Mean age was 40 ± 15 years, 42% males, and 7% were index patients while 93% were pre-symptomatic carriers identified after family cascade screening. Mean LV ejection fraction (LVEF) and RV ejection fraction were 58 ± 9% and 55 ± 9%, respectively. LV-LGE was present in 91% of mutation carriers with reduced LVEF (<45%) and in 30% of carriers with preserved LVEF. In carriers with positive LV-LGE, its median extent was 5.9% (interquartile range 3.2–12.7). LGE was mainly observed in the inferolateral wall. Carriers with inverted T-waves in the lateral ECG leads more often had LV-LGE (P < 0.01) than carriers without. Finally, the presence of LV-LGE, but not attenuated R-waves and inverted lateral T-waves, was independently associated with VA. Conclusion LV myocardial fibrosis is present in many PLN p.Arg14del mutation carriers, and who still have a preserved LVEF. It is seen predominantly in the LV inferolateral wall and corresponds with electrocardiographic repolarization abnormalities. Although preliminary, myocardial fibrosis was found to be independently associated with VA. Our findings support the use of CMR with LGE early in the diagnostic work-up. arrhythmogenic cardiomyopathy , phospholamban , fibrosis , cardiovascular magnetic resonance , electrocardiogram , ventricular arrhythmia Introduction The pathogenic c.40_42delAGA (p.Arg14del) founder mutation in the phospholamban gene (PLN; locus 6q22.31; OMIM gene description number 172405) has been identified in 10–15% of patients diagnosed with dilated cardiomyopathy (DCM) and/or arrhythmogenic cardiomyopathy (ACM) in the Netherlands.1–3 It has also been found in several other European countries, Canada, and the USA. PLN is a transmembrane sarcoplasmic reticulum (SR) phosphoprotein that regulates SR Ca2+-ATPase (SERCA) activity and the p.Arg14del mutation has been shown to lead to calcium overload and consequent cardiomyocyte damage, and eventually to myocardial fibrosis.4,5 Indeed, examination of 20 whole heart specimens (autopsies and explants) of PLN p.Arg14del mutation carriers revealed extensive myocardial fibrosis in all cases.6,7 A striking clinical manifestation of PLN p.Arg14del mutation-related cardiomyopathy is the development of low-amplitude QRS complexes on the surface ECG,1,8 and it is likely that this is a reflection of underlying fibrosis, although this has not been proven. In addition, repolarization changes on the ECG, particularly of negative T-waves in the lateral leads, are an early manifestation in mutation carriers. Late gadolinium-enhanced (LGE) cardiovascular magnetic resonance (CMR) imaging has become the gold standard for non-invasive in vivo assessment of ventricular myocardial fibrosis; it allows the early identification and evaluation of both the extent and localization of myocardial fibrosis in different forms of cardiomyopathy.9–11 Importantly, LGE has consistently been shown to be a strong risk factor for sudden cardiac death (SCD) and overall mortality in a wide range of cardiomyopathies, e.g. DCM.12–16 In this study, we formulated three hypotheses based on the previous electrocardiographic and histopathological findings: (i) that LGE is present in a distinct subgroup of PLN p.Arg14del mutation carriers, (ii) that the ECG changes reflect fibrosis, and (iii) that, assuming that fibrosis is a substrate for ventricular arrhythmia (VA) in mutation carriers, the presence of LGE is associated with VA. We investigated CMR- and ECG parameters, and VA occurrence, in a large cohort of 150 mutation carriers to test these hypotheses. In particular, we analysed the extent and localization of CMR LGE together with ECG parameters to investigate whether the development of low-voltage QRS amplitude and/or repolarization changes are associated with left ventricular (LV) LGE. We also investigated whether these findings are associated with VA. Methods Source population Adult (>18 years old) PLN p.Arg14del mutation carriers who had undergone CMR imaging were selected from the PHORECAST registry (PHOspholamban RElated CArdiomyopathy STudy; http://www.phorecast.nl). Demographic and clinical parameters at the time of CMR were collected retrospectively in three Dutch hospitals (University Medical Center Groningen, Academic Medical Center Amsterdam, and Antonius Hospital Sneek). Our group included both index patients and their relatives referred to a cardiogenetics outpatient clinic for family cascade screening. Index patients in the cohort were not known to be related to each other. Cardiovascular magnetic resonance imaging protocol CMR imaging studies in all three centres were performed on a 1.5 T whole-body CMR scanner (Magnetom Avanto, Siemens Healthcare GmbH, Erlangen, Germany) using a phased-array cardiac receiver coil. Then ECG-gated cine, steady-state free-precession (True FISP) sequences were acquired during repeated breath holds in contiguous short-axis slices (6 or 8 mm per slice) covering the entire left ventricle and right ventricle. The following scan parameters were used: TE 1.1 ms, TR 42 ms, and flip angle 55°; matrix 192 × 192, voxel size 1.82 × 1.82 × (6 or 8) mm. Using identical slice locations, LGE images were acquired 10 min after intravenous administration of 0.2 mmol/kg gadolinium-based contrast agent (Dotarem, Gorinchem, the Netherlands; 0.2 mmol/kg) with a single-shot 2D phase-sensitive inversion recovery sequence [TE 3.2 ms, TR 700 ms, flip angle 25°; matrix 360 × 360 mm, voxel size 1.4 × 1.4 × (6 or 8) mm]. The inversion time was set individually to null the signal of normal myocardium. All procedures were performed according to the standardized protocols recommended by the Society for Cardiovascular Magnetic Resonance.17 CMR imaging analysis All CMR imaging analyses were performed using QMass 7.6 (Medis medical imaging systems BV, Leiden, the Netherlands). The endo- and epicardial contours of the left ventricle and right ventricle were manually traced on the short-axis slices in the end-diastolic and end-systolic phases by a single experienced observer (T.M.G.), who was blinded for the patients’ clinical data. Papillary muscle and trabeculae were included in the blood volume. End-diastolic and end-systolic volumes were calculated using the summation of slice multiplied by slice thickness method, indexed to body surface area, and compared to reference values.18 LV volume was dichotomized based on reference values18 into ‘non-dilated’ or ‘dilated’ (>112 mL/m2 for males and >99 mL/m2 for females). For LGE imaging, first the presence of delayed-enhanced signal intensity was visually determined by two experienced independent observers (by agreement), who were blinded for patients’ clinical data (T.M.G.: >5 years experience in CMR; and T.P.W.: >15 years experience in CMR, Level 3 certified cardiovascular radiologist). Subsequently, the extent of LV-LGE was quantified by one observer (T.M.G.) using the full-width at half-maximum method, by defining the enhanced area using 50% of the maximum signal found within the enhanced area as previously described.19 LV-LGE size was expressed as a percentage of total LV mass. LV-LGE location was determined using the 17-segment model.20 The amount of right ventricular (RV) LGE was quantified using the 12-segment model of the right ventricle and classified as small (≤4 segments involved) or large (>4 segments involved).21 ECG analysis Standard 12-lead resting ECGs, recorded around the time of CMR [median time span between CMR and ECG: 35 days; interquartile range (IQR) 1–100], were analysed after digitalization using ImageJ (http://rsb.info.nih.gov/ij/). Each ECG was time-calibrated and conduction and repolarization parameters during sinus rhythm were determined. Measurements of time-related parameters (heart rate, PQ-interval, QRS-duration, and QT-interval) were performed manually on-screen, in lead II whenever possible. Parameters were averaged from up to three consecutive beats with similar preceding RR-intervals. For the QT- and heart-rate corrected QT-interval, we used the tangent method with Bazett’s correction.22 R-waves of all 12 leads were summed and dichotomized based on the median value (5.3 mm) into ‘normal voltage’ or ‘low voltage’. Inverted T-waves were determined and considered present if inverted in the right precordial leads (V1 as well as V2) and/or in at least in two adjacent lateral leads (V4, V5, or V6). ECGs were not analysed if there was a left- or right-bundle branch block or bifascicular block. Ventricular arrhythmia To determine the association between ECG parameters, fibrosis and VA, the occurrence of VA [non-sustained or sustained ventricular tachycardia (VT)] was analysed on ambulatory 24-h (Holter) and/or exercise ECG. The indication was at the discretion of the attending physician, and ambulatory 24-h and/or exercise electrocardiography were therefore not available for every mutation carrier. Non-sustained VT was defined as at least three consecutive ventricular complexes at a heart rate >100 b.p.m. with a duration of less than 30 s. Sustained VT was defined as an arrhythmia at a heart rate >100 b.p.m. that lasted ≥30 s and/or required termination because of haemodynamic compromise in <30 s. Statistical analysis Statistical analyses, including bootstrapping, were performed using SPSS software, version 24.0 (SPSS for Windows, 2016 release 24.0.0.0, Chicago, IL, USA). Continuous variables are presented as a mean with standard deviation and compared with the unpaired t-test for a normal distribution, or presented as the median with an IQR for a skewed distribution, as determined by the Kolmogorov–Smirnov Goodness-of-Fit test. Categorical variables are presented as frequencies with percentages and analysed using the Fisher’s exact test. The Pearson’s correlation test was used for correlation analysis. Associations between demographic-, ECG- and CMR-variables were initially analysed using univariable regression. All variables that were statistically significantly associated with LV-LGE presence in the univariable analysis were then included in a multivariable regression model. Bootstrapping, using 1000 bootstrap samples, was used to evaluate the performance of the model. Bootstrapping is the most efficient validation procedure as all aspects of the model development, including variable selection, are validated.23 The association with VA was also analysed, for this analysis only the mutation carriers where ambulatory and/or exercise ECG data were available were included in the analysis. Due to the low prevalence of VA, we had to limit our selection of variables for the corresponding multivariable analysis. The selection was based on clinical relevance and prevalence and included: low voltage, inverted lateral T-waves, left ventricular ejection fraction (LVEF), and LV-LGE. Odds ratios and 95% confidence intervals were calculated. A P-value <0.05 was considered to be statistically significant. Results Patient characteristics We identified 194 mutation carriers who had undergone CMR imaging in the three centres. For 28 patients, there were no clinical, ECG data and/or CMR LGE available and LGE could not be evaluated in six patients due to insufficient image quality. Ten patients were excluded based on their ECG (three bifascicular blocks, four right bundle branch blocks, one left bundle branch block, one atrial fibrillation, and one Wolff–Parkinson–White syndrome). Our final study group consisted of 150 mutation carriers (Table 1). Their mean age was 40 ± 15 years and 42% were male. Ten (7%) carriers were index patients (mean age 44 ± 10 years), while the other 140 participants were relatives identified by family cascade screening (mean age 40 ± 15 years). The vast majority (93%) of participants were in New York Heart Association functional class I and did not take heart failure medication. The number of prescriptions for beta-blockers, renin-angiotensin system inhibitors, aldosterone-blocking agents (spironolactone or eplerenone), and diuretics were significantly higher (P < 0.05) in the index patients. Table 1 Clinical characteristics (n = 150) Patient characteristics All patients Index (n = 10) Relative (n = 140) Age (years) 40 ± 15 44 ± 10 40 ± 15 Sex Male 63 (42%) 5 (50%) 58 (41%) Female 87 (58%) 5 (50%) 82 (59%) BSA (m2) 1.92 ± 0.16 1.99 ± 0.26 1.91 ± 0.17 NYHA functional class I 139 (93%) 8 (80%) 131 (94%) II 11 (7%) 2 (20%) 9 (6%) III/IV 0 (0%) 0 (0%) 0 (0%) Ventricular arrhythmia 23 (15%) 6 (60%) 17 (12%)* ECG parameters PR interval (ms) 150 ± 21 151 ± 10 150 ± 21 QRS width (ms) 85 ± 11 91 ± 15 85 ± 11 QTc (ms) 408 ± 23 411 ± 29 409 ± 23 R-wave amplitude (mV; median) 5.3 (1.4–17.0) 3.4 (1.6–6.1) 5.5 (1.4–17.0)* Inverted right precordial T-waves (V1 and V2) 17 (11%) 0 (0%) 17 (12%) Inverted lateral T-waves (V4, V5, or V6) 43 (23%) 8 (80%) 35 (25%)* Medication Anti-arrhythmic 6 (4%) 2 (20%) 4 (3%) Beta-blocker 22 (15%) 7 (70%) 15 (11%)* RAAS inhibitors 15 (10%) 6 (60%) 9 (7%)* Spironolactone/eplerenone 2 (1%) 2 (20%) 0 (0%)* Diuretics 9 (6%) 4 (10%) 5 (4%)* Anti-coagulant 7 (5%) 2 (20%) 5 (4%) Anti-platelet therapy 4 (3%) 1 (10%) 3 (2%) Patient characteristics All patients Index (n = 10) Relative (n = 140) Age (years) 40 ± 15 44 ± 10 40 ± 15 Sex Male 63 (42%) 5 (50%) 58 (41%) Female 87 (58%) 5 (50%) 82 (59%) BSA (m2) 1.92 ± 0.16 1.99 ± 0.26 1.91 ± 0.17 NYHA functional class I 139 (93%) 8 (80%) 131 (94%) II 11 (7%) 2 (20%) 9 (6%) III/IV 0 (0%) 0 (0%) 0 (0%) Ventricular arrhythmia 23 (15%) 6 (60%) 17 (12%)* ECG parameters PR interval (ms) 150 ± 21 151 ± 10 150 ± 21 QRS width (ms) 85 ± 11 91 ± 15 85 ± 11 QTc (ms) 408 ± 23 411 ± 29 409 ± 23 R-wave amplitude (mV; median) 5.3 (1.4–17.0) 3.4 (1.6–6.1) 5.5 (1.4–17.0)* Inverted right precordial T-waves (V1 and V2) 17 (11%) 0 (0%) 17 (12%) Inverted lateral T-waves (V4, V5, or V6) 43 (23%) 8 (80%) 35 (25%)* Medication Anti-arrhythmic 6 (4%) 2 (20%) 4 (3%) Beta-blocker 22 (15%) 7 (70%) 15 (11%)* RAAS inhibitors 15 (10%) 6 (60%) 9 (7%)* Spironolactone/eplerenone 2 (1%) 2 (20%) 0 (0%)* Diuretics 9 (6%) 4 (10%) 5 (4%)* Anti-coagulant 7 (5%) 2 (20%) 5 (4%) Anti-platelet therapy 4 (3%) 1 (10%) 3 (2%) BSA, body surface area; NYHA, New York Heart Association; ECG, electrocardiogram; RAAS, renin-angiotensin system; QTc, corrected QT-interval. * P < 0.05. Table 1 Clinical characteristics (n = 150) Patient characteristics All patients Index (n = 10) Relative (n = 140) Age (years) 40 ± 15 44 ± 10 40 ± 15 Sex Male 63 (42%) 5 (50%) 58 (41%) Female 87 (58%) 5 (50%) 82 (59%) BSA (m2) 1.92 ± 0.16 1.99 ± 0.26 1.91 ± 0.17 NYHA functional class I 139 (93%) 8 (80%) 131 (94%) II 11 (7%) 2 (20%) 9 (6%) III/IV 0 (0%) 0 (0%) 0 (0%) Ventricular arrhythmia 23 (15%) 6 (60%) 17 (12%)* ECG parameters PR interval (ms) 150 ± 21 151 ± 10 150 ± 21 QRS width (ms) 85 ± 11 91 ± 15 85 ± 11 QTc (ms) 408 ± 23 411 ± 29 409 ± 23 R-wave amplitude (mV; median) 5.3 (1.4–17.0) 3.4 (1.6–6.1) 5.5 (1.4–17.0)* Inverted right precordial T-waves (V1 and V2) 17 (11%) 0 (0%) 17 (12%) Inverted lateral T-waves (V4, V5, or V6) 43 (23%) 8 (80%) 35 (25%)* Medication Anti-arrhythmic 6 (4%) 2 (20%) 4 (3%) Beta-blocker 22 (15%) 7 (70%) 15 (11%)* RAAS inhibitors 15 (10%) 6 (60%) 9 (7%)* Spironolactone/eplerenone 2 (1%) 2 (20%) 0 (0%)* Diuretics 9 (6%) 4 (10%) 5 (4%)* Anti-coagulant 7 (5%) 2 (20%) 5 (4%) Anti-platelet therapy 4 (3%) 1 (10%) 3 (2%) Patient characteristics All patients Index (n = 10) Relative (n = 140) Age (years) 40 ± 15 44 ± 10 40 ± 15 Sex Male 63 (42%) 5 (50%) 58 (41%) Female 87 (58%) 5 (50%) 82 (59%) BSA (m2) 1.92 ± 0.16 1.99 ± 0.26 1.91 ± 0.17 NYHA functional class I 139 (93%) 8 (80%) 131 (94%) II 11 (7%) 2 (20%) 9 (6%) III/IV 0 (0%) 0 (0%) 0 (0%) Ventricular arrhythmia 23 (15%) 6 (60%) 17 (12%)* ECG parameters PR interval (ms) 150 ± 21 151 ± 10 150 ± 21 QRS width (ms) 85 ± 11 91 ± 15 85 ± 11 QTc (ms) 408 ± 23 411 ± 29 409 ± 23 R-wave amplitude (mV; median) 5.3 (1.4–17.0) 3.4 (1.6–6.1) 5.5 (1.4–17.0)* Inverted right precordial T-waves (V1 and V2) 17 (11%) 0 (0%) 17 (12%) Inverted lateral T-waves (V4, V5, or V6) 43 (23%) 8 (80%) 35 (25%)* Medication Anti-arrhythmic 6 (4%) 2 (20%) 4 (3%) Beta-blocker 22 (15%) 7 (70%) 15 (11%)* RAAS inhibitors 15 (10%) 6 (60%) 9 (7%)* Spironolactone/eplerenone 2 (1%) 2 (20%) 0 (0%)* Diuretics 9 (6%) 4 (10%) 5 (4%)* Anti-coagulant 7 (5%) 2 (20%) 5 (4%) Anti-platelet therapy 4 (3%) 1 (10%) 3 (2%) BSA, body surface area; NYHA, New York Heart Association; ECG, electrocardiogram; RAAS, renin-angiotensin system; QTc, corrected QT-interval. * P < 0.05. CMR findings Mean end-diastolic LV and RV volumes, LVEF and right ventricular ejection fraction (RVEF) were normal, but we observed significant differences between index patients and their relatives for LV end-diastolic volume (240 ± 105 vs. 174 ± 35 mL, P < 0.05), LV end-diastolic volume index (119 ± 43 vs. 91 ± 15 mL/m2, P < 0.05), LV end-diastolic mass (125 ± 47 vs. 92 ± 22 g, P < 0.05), LV end-diastolic mass index (62 ± 17 vs. 48 ± 9 mL/m2, P < 0.05), LVEF (40 ± 14 vs. 59 ± 7%, P < 0.05), and RVEF (45 ± 11 vs. 56 ± 9%, P < 0.05) (Table 2). Eleven (7%) mutation carriers had reduced LVEF (i.e. <45%), five of these were index patients (index patients 5/10 vs. relatives 6/140, P < 0.05). There was a significant correlation between LVEF and RVEF (r = 0.78, P < 0.001) (Figure 1). Table 2 Cardiac magnetic resonance imaging parameters (n = 150) All patients Index (n = 10) Relative (n = 140) Left ventricle LVEDV (mL) 179 ± 46 240 ± 105 174 ± 35* LVEDVi (mL/m2) 93 ± 19 119 ± 43 91 ± 15* LVEDM (g) 95 ± 25 125 ± 47 92 ± 22* LVEDMi (g/m2) 49 ± 10 62 ± 17 48 ± 9* LVEF (%) 58 ± 9 40 ± 14 59 ± 7* LVEF <45% 11 (7%) 5 (50%) 6 (4%)* LV-LGE present (%) 50 (33%) 9 (90%) 41 (29%)* LGE % LV mass (median), if present 5.9 (3.2–12.7) 18 (8.1–30.2) 4.6 (3.0–8.3)* Right ventricle RVEDV (mL) 186 ± 42 203 ± 78 185 ± 38 RVEDVi (mL/m2) 97 ± 17 100 ± 28 97 ± 16 RVEF (%) 55 ± 8 45 ± 11 56 ± 9* RV-LGE present (%) 8 (5%) 2 (20%) 6 (4%)* All patients Index (n = 10) Relative (n = 140) Left ventricle LVEDV (mL) 179 ± 46 240 ± 105 174 ± 35* LVEDVi (mL/m2) 93 ± 19 119 ± 43 91 ± 15* LVEDM (g) 95 ± 25 125 ± 47 92 ± 22* LVEDMi (g/m2) 49 ± 10 62 ± 17 48 ± 9* LVEF (%) 58 ± 9 40 ± 14 59 ± 7* LVEF <45% 11 (7%) 5 (50%) 6 (4%)* LV-LGE present (%) 50 (33%) 9 (90%) 41 (29%)* LGE % LV mass (median), if present 5.9 (3.2–12.7) 18 (8.1–30.2) 4.6 (3.0–8.3)* Right ventricle RVEDV (mL) 186 ± 42 203 ± 78 185 ± 38 RVEDVi (mL/m2) 97 ± 17 100 ± 28 97 ± 16 RVEF (%) 55 ± 8 45 ± 11 56 ± 9* RV-LGE present (%) 8 (5%) 2 (20%) 6 (4%)* LGE, late gadolinium enhancement; LVEDV, left ventricular end-diastolic volume; LVEDVi, left ventricular end-diastolic volume index; LVEDM, left ventricular end-diastolic mass; LVEDMi, left ventricular end-diastolic mass index; LVEF, left ventricular ejection fraction; RVEDV, right ventricular end-diastolic volume; RVEDDi, right ventricular end-diastolic volume index; RVEF, right ventricular ejection fraction. * P < 0.05. Table 2 Cardiac magnetic resonance imaging parameters (n = 150) All patients Index (n = 10) Relative (n = 140) Left ventricle LVEDV (mL) 179 ± 46 240 ± 105 174 ± 35* LVEDVi (mL/m2) 93 ± 19 119 ± 43 91 ± 15* LVEDM (g) 95 ± 25 125 ± 47 92 ± 22* LVEDMi (g/m2) 49 ± 10 62 ± 17 48 ± 9* LVEF (%) 58 ± 9 40 ± 14 59 ± 7* LVEF <45% 11 (7%) 5 (50%) 6 (4%)* LV-LGE present (%) 50 (33%) 9 (90%) 41 (29%)* LGE % LV mass (median), if present 5.9 (3.2–12.7) 18 (8.1–30.2) 4.6 (3.0–8.3)* Right ventricle RVEDV (mL) 186 ± 42 203 ± 78 185 ± 38 RVEDVi (mL/m2) 97 ± 17 100 ± 28 97 ± 16 RVEF (%) 55 ± 8 45 ± 11 56 ± 9* RV-LGE present (%) 8 (5%) 2 (20%) 6 (4%)* All patients Index (n = 10) Relative (n = 140) Left ventricle LVEDV (mL) 179 ± 46 240 ± 105 174 ± 35* LVEDVi (mL/m2) 93 ± 19 119 ± 43 91 ± 15* LVEDM (g) 95 ± 25 125 ± 47 92 ± 22* LVEDMi (g/m2) 49 ± 10 62 ± 17 48 ± 9* LVEF (%) 58 ± 9 40 ± 14 59 ± 7* LVEF <45% 11 (7%) 5 (50%) 6 (4%)* LV-LGE present (%) 50 (33%) 9 (90%) 41 (29%)* LGE % LV mass (median), if present 5.9 (3.2–12.7) 18 (8.1–30.2) 4.6 (3.0–8.3)* Right ventricle RVEDV (mL) 186 ± 42 203 ± 78 185 ± 38 RVEDVi (mL/m2) 97 ± 17 100 ± 28 97 ± 16 RVEF (%) 55 ± 8 45 ± 11 56 ± 9* RV-LGE present (%) 8 (5%) 2 (20%) 6 (4%)* LGE, late gadolinium enhancement; LVEDV, left ventricular end-diastolic volume; LVEDVi, left ventricular end-diastolic volume index; LVEDM, left ventricular end-diastolic mass; LVEDMi, left ventricular end-diastolic mass index; LVEF, left ventricular ejection fraction; RVEDV, right ventricular end-diastolic volume; RVEDDi, right ventricular end-diastolic volume index; RVEF, right ventricular ejection fraction. * P < 0.05. Figure 1 View largeDownload slide Scatter plot depicting the relationship between LVEF and RVEF in PLN p.Arg14del mutation carriers (n = 150; P < 0.01). Figure 1 View largeDownload slide Scatter plot depicting the relationship between LVEF and RVEF in PLN p.Arg14del mutation carriers (n = 150; P < 0.01). LV-LGE was seen in 50 mutation carriers (index patients 9/10 vs. relatives 41/140, P < 0.05). Mutation carriers with LV-LGE were significantly older (47 ± 15 vs. 36 ± 14 years, P < 0.01) than those without LV-LGE. Almost all mutation-carriers with reduced LVEF (10/11; 91%) also had LV-LGE, while it was also present in 29% (40/139) of mutation carriers with preserved LVEF (Figure 2). In carriers with LV-LGE, the median volume of enhanced LV myocardium was 5.9% (3.2–12.7), with index patients showing higher volumes than relatives [18.0% (8.1–30.2) vs. 4.6% (3.0–8.3), P < 0.05]. Delayed enhancement was mainly present in the basal inferolateral wall of the left ventricle (most abundant in segments 5 and 11), whereas segments 1–3, 7–9, and 14 were least affected (Figure 3). In one case, we were able to examine the explanted heart to compare it with LV-LGE CMR findings, showing extensive interstitial fibrosis in the area of LGE (Figure 4). Figure 2 View largeDownload slide Scatter plot depicting the relationship between the amount of LV myocardial fibrosis (%) and LVEF (%) in PLN p.Arg14del mutation carriers (n = 150; P < 0.01). The dotted line represents an LVEF of 45%. Figure 2 View largeDownload slide Scatter plot depicting the relationship between the amount of LV myocardial fibrosis (%) and LVEF (%) in PLN p.Arg14del mutation carriers (n = 150; P < 0.01). The dotted line represents an LVEF of 45%. Figure 3 View largeDownload slide Bull’s eye plot (17 left ventricular segments model) depicting the presence and localization of myocardial fibrosis in PLN p.Arg14del mutation carriers (n = 150; % per segment represents the percentage of mutation carriers with CMR LGE in that segment). Figure 3 View largeDownload slide Bull’s eye plot (17 left ventricular segments model) depicting the presence and localization of myocardial fibrosis in PLN p.Arg14del mutation carriers (n = 150; % per segment represents the percentage of mutation carriers with CMR LGE in that segment). Figure 4 View largeDownload slide Clinico-pathological correlation between late gadolinium-enhanced CMR- and histopathological findings in a PLN p.Arg14del mutation carrier. Coronary angiography revealed no coronary artery disease. (A) Short-axis delayed enhancement image of a mutation carrier showing inferolateral wall thinning and extensive LGE (arrow) of the inferolateral wall of the LV. The observed subendocardial LGE pattern is probably due to wall thinning in this mutation carriers, as also observed in some other cases. (B) Mid-ventricular cross-section of the explanted heart (gross examination) of the same mutation carrier showing macroscopically visible fibro-fatty replacement of the RV wall (arrow) and limited fibro-fatty alteration in the LV wall. (C) Microscopic analysis of Masson trichrome-stained LV free wall sample from the same explanted heart showing extensive interstitial fibrosis. Figure 4 View largeDownload slide Clinico-pathological correlation between late gadolinium-enhanced CMR- and histopathological findings in a PLN p.Arg14del mutation carrier. Coronary angiography revealed no coronary artery disease. (A) Short-axis delayed enhancement image of a mutation carrier showing inferolateral wall thinning and extensive LGE (arrow) of the inferolateral wall of the LV. The observed subendocardial LGE pattern is probably due to wall thinning in this mutation carriers, as also observed in some other cases. (B) Mid-ventricular cross-section of the explanted heart (gross examination) of the same mutation carrier showing macroscopically visible fibro-fatty replacement of the RV wall (arrow) and limited fibro-fatty alteration in the LV wall. (C) Microscopic analysis of Masson trichrome-stained LV free wall sample from the same explanted heart showing extensive interstitial fibrosis. In the right ventricle, we observed LGE in only 8 (5%) mutation carriers (index patients 2/10 vs. relatives 6/140, P < 0.05). RVEF was significantly lower in mutation carriers with RV-LGE than in those without RV-LGE (43 ± 8 vs. 56 ± 7%, P < 0.05). ECG findings and VA occurrence ECG conduction and repolarization parameters were, on average, within the normal range (Table 1). The median R-wave amplitude was 5.3 mV (index 3.4 mV vs. relatives 5.5 mV, P < 0.05). Carriers with low voltage (mean R-value below median) were significantly older than carriers with normal voltage (44 ± 15 vs. 36 ± 14 years, P < 0.01). Inverted T-waves in the right precordial leads were seen in 17 (11%) carriers and inverted T-waves in the lateral leads were seen in 43 (29%) carriers (index 8/10 vs. relatives 36/140, P < 0.05). A representative example of electrocardiographic and CMR findings in a PLN mutation carrier is shown in Figure 5. Figure 5 View largeDownload slide (A) Typical cine CMR images in a PLN p.Arg14del mutation carrier showing left lateral delayed contrast enhancement (arrow). (B) Twelve-lead ECG of the same mutation carrier showing normal sinus rhythm with low voltages in all leads (<0.5 mV) and flattened or inverted T-waves in all precordial leads and inferolateral limb leads. Figure 5 View largeDownload slide (A) Typical cine CMR images in a PLN p.Arg14del mutation carrier showing left lateral delayed contrast enhancement (arrow). (B) Twelve-lead ECG of the same mutation carrier showing normal sinus rhythm with low voltages in all leads (<0.5 mV) and flattened or inverted T-waves in all precordial leads and inferolateral limb leads. In 23/150 (15%) carriers, either sustained or non-sustained VT was documented (index patients 6/10 vs. relatives 17/140, P < 0.05). Association between ECG findings and CMR LV-LGE In univariable analysis, the presence of low voltage on the surface ECG was associated with the presence of CMR LGE [odds ratio (OR) = 3.06, P < 0.01] (Table 3). If the surface ECG showed inverted T-waves in the lateral leads (V4–V6), then LV-LGE was also seen more often (OR = 8.48, P < 0.01). Table 3 Univariable and multivariable analysis of the association between demographic-, ECG-, and CMR-variables and the presence of LV-LGE LV-LGE (n = 50) No LV-LGE (n = 100) Univariable (OR 95% CI) Multivariable (OR 95% CI) Age (years) 47 ± 15 36 ± 14 1.04 (1.02–1.07), P < 0.05 1.05 (1.01–1.08), P < 0.01; B = 0.45 Sex Male 25 (50%) 38 (38%) 1.63 (0.82–3.24), P = 0.16 Female 25 (50%) 62 (62%) NYHA functional class (≥2) 6 (12%) 5 (5%) 2.59 (0.75–8.95), P = 0.13 Low voltage (present) 34 (68%) 41 (41%) 3.06 (1.50–6.25), P < 0.05 1.09 (0.45–2.62), P = 0.85; B = 0.85 Inverted lateral T-wave (present) 29 (58%) 14 (14%) 8.48 (3.83–18.8), P < 0.05 5.70 (2.28–14.26), P < 0.01; B = 1.74 LV dilatation (present) 16 (32%) 13 (13%) 3.15 (1.37–7.24), P < 0.05 2.51 (0.83–7.61), P = 0.10; B = 0.92 LVEF <45% (present) 10 (20%) 1 (1%) 24.8 (3.07–199), P < 0.05 5.34 (0.52 -54.8), P = 0.16; B = 1.67 RVEF <45% (present) 6 (12%) 1 (1%) 13.5 (1.58–116), P < 0.05 2.11 (0.12–37.59), P = 0.61; B = 0.75 LV-LGE (n = 50) No LV-LGE (n = 100) Univariable (OR 95% CI) Multivariable (OR 95% CI) Age (years) 47 ± 15 36 ± 14 1.04 (1.02–1.07), P < 0.05 1.05 (1.01–1.08), P < 0.01; B = 0.45 Sex Male 25 (50%) 38 (38%) 1.63 (0.82–3.24), P = 0.16 Female 25 (50%) 62 (62%) NYHA functional class (≥2) 6 (12%) 5 (5%) 2.59 (0.75–8.95), P = 0.13 Low voltage (present) 34 (68%) 41 (41%) 3.06 (1.50–6.25), P < 0.05 1.09 (0.45–2.62), P = 0.85; B = 0.85 Inverted lateral T-wave (present) 29 (58%) 14 (14%) 8.48 (3.83–18.8), P < 0.05 5.70 (2.28–14.26), P < 0.01; B = 1.74 LV dilatation (present) 16 (32%) 13 (13%) 3.15 (1.37–7.24), P < 0.05 2.51 (0.83–7.61), P = 0.10; B = 0.92 LVEF <45% (present) 10 (20%) 1 (1%) 24.8 (3.07–199), P < 0.05 5.34 (0.52 -54.8), P = 0.16; B = 1.67 RVEF <45% (present) 6 (12%) 1 (1%) 13.5 (1.58–116), P < 0.05 2.11 (0.12–37.59), P = 0.61; B = 0.75 LGE, late gadolinium enhancement; NYHA, New York Heart Association; LVEF, left ventricular ejection fraction; RVEF, right ventricular ejection fraction; B, regression coefficient; CI, confidence interval. Table 3 Univariable and multivariable analysis of the association between demographic-, ECG-, and CMR-variables and the presence of LV-LGE LV-LGE (n = 50) No LV-LGE (n = 100) Univariable (OR 95% CI) Multivariable (OR 95% CI) Age (years) 47 ± 15 36 ± 14 1.04 (1.02–1.07), P < 0.05 1.05 (1.01–1.08), P < 0.01; B = 0.45 Sex Male 25 (50%) 38 (38%) 1.63 (0.82–3.24), P = 0.16 Female 25 (50%) 62 (62%) NYHA functional class (≥2) 6 (12%) 5 (5%) 2.59 (0.75–8.95), P = 0.13 Low voltage (present) 34 (68%) 41 (41%) 3.06 (1.50–6.25), P < 0.05 1.09 (0.45–2.62), P = 0.85; B = 0.85 Inverted lateral T-wave (present) 29 (58%) 14 (14%) 8.48 (3.83–18.8), P < 0.05 5.70 (2.28–14.26), P < 0.01; B = 1.74 LV dilatation (present) 16 (32%) 13 (13%) 3.15 (1.37–7.24), P < 0.05 2.51 (0.83–7.61), P = 0.10; B = 0.92 LVEF <45% (present) 10 (20%) 1 (1%) 24.8 (3.07–199), P < 0.05 5.34 (0.52 -54.8), P = 0.16; B = 1.67 RVEF <45% (present) 6 (12%) 1 (1%) 13.5 (1.58–116), P < 0.05 2.11 (0.12–37.59), P = 0.61; B = 0.75 LV-LGE (n = 50) No LV-LGE (n = 100) Univariable (OR 95% CI) Multivariable (OR 95% CI) Age (years) 47 ± 15 36 ± 14 1.04 (1.02–1.07), P < 0.05 1.05 (1.01–1.08), P < 0.01; B = 0.45 Sex Male 25 (50%) 38 (38%) 1.63 (0.82–3.24), P = 0.16 Female 25 (50%) 62 (62%) NYHA functional class (≥2) 6 (12%) 5 (5%) 2.59 (0.75–8.95), P = 0.13 Low voltage (present) 34 (68%) 41 (41%) 3.06 (1.50–6.25), P < 0.05 1.09 (0.45–2.62), P = 0.85; B = 0.85 Inverted lateral T-wave (present) 29 (58%) 14 (14%) 8.48 (3.83–18.8), P < 0.05 5.70 (2.28–14.26), P < 0.01; B = 1.74 LV dilatation (present) 16 (32%) 13 (13%) 3.15 (1.37–7.24), P < 0.05 2.51 (0.83–7.61), P = 0.10; B = 0.92 LVEF <45% (present) 10 (20%) 1 (1%) 24.8 (3.07–199), P < 0.05 5.34 (0.52 -54.8), P = 0.16; B = 1.67 RVEF <45% (present) 6 (12%) 1 (1%) 13.5 (1.58–116), P < 0.05 2.11 (0.12–37.59), P = 0.61; B = 0.75 LGE, late gadolinium enhancement; NYHA, New York Heart Association; LVEF, left ventricular ejection fraction; RVEF, right ventricular ejection fraction; B, regression coefficient; CI, confidence interval. In a multivariable regression model including age, low-voltage, inverted lateral T-waves, LVEF, LV dilatation and RVEF (all P < 0.05 in univariable analysis), only two factors − age (OR = 1.05, P < 0.01) and inverted lateral T-waves (OR = 5.70, P < 0.01) − were independently associated with the presence of LV-LGE. Bootstrapping yielded comparable results in comparison with conventional computation. Association between ECG findings, CMR LV-LGE, and VA occurrence In the univariable analysis, inverted lateral T-waves, low voltage, and LVEF <45% were associated with the occurrence of VA (Table 4). We also found that the presence of CMR LV-LGE was significantly associated with the occurrence of VA (OR = 10.5, P < 0.01; Figure 6). Table 4 Univariable and multivariable analysis of the association between ECG- and CMR-variables and VA occurrence VA (n = 23) No VA (n = 110a) Univariable (OR 95% CI) Multivariable (OR 95% CI) Low voltage (present) 16 (70%) 50 (45%) 2.55 (0.97–6.68) P < 0.05 0.73 (0.20–2.59) P = 0.62; B = −0.32 Inverted lateral T-wave (present) 16 (70%) 26 (24%) 7.38 (2.74–19.89) P < 0.05 3.05 (0.85–10.91) P = 0.09; B = 1.11 LVEF<45% (present) 7 (30%) 3 (3%) 15.6 (3.66–66.58) P < 0.05 4.91 (0.95–25.47) P = 0.06; B = 1.59 LV-LGE (present) 18 (78%) 28 (25%) 10.5 (3.58–31.04) P < 0.05 5.52 (1.62–18.77) P < 0.01; B = 1.71 VA (n = 23) No VA (n = 110a) Univariable (OR 95% CI) Multivariable (OR 95% CI) Low voltage (present) 16 (70%) 50 (45%) 2.55 (0.97–6.68) P < 0.05 0.73 (0.20–2.59) P = 0.62; B = −0.32 Inverted lateral T-wave (present) 16 (70%) 26 (24%) 7.38 (2.74–19.89) P < 0.05 3.05 (0.85–10.91) P = 0.09; B = 1.11 LVEF<45% (present) 7 (30%) 3 (3%) 15.6 (3.66–66.58) P < 0.05 4.91 (0.95–25.47) P = 0.06; B = 1.59 LV-LGE (present) 18 (78%) 28 (25%) 10.5 (3.58–31.04) P < 0.05 5.52 (1.62–18.77) P < 0.01; B = 1.71 VA, ventricular arrhythmia; LVEF, left ventricular ejection fraction; LGE, late gadolinium enhancement; B, regression coefficient; CI, confidence interval. a Only the mutation carriers where ambulatory and/or exercise ECG data were available were included in this analysis. Table 4 Univariable and multivariable analysis of the association between ECG- and CMR-variables and VA occurrence VA (n = 23) No VA (n = 110a) Univariable (OR 95% CI) Multivariable (OR 95% CI) Low voltage (present) 16 (70%) 50 (45%) 2.55 (0.97–6.68) P < 0.05 0.73 (0.20–2.59) P = 0.62; B = −0.32 Inverted lateral T-wave (present) 16 (70%) 26 (24%) 7.38 (2.74–19.89) P < 0.05 3.05 (0.85–10.91) P = 0.09; B = 1.11 LVEF<45% (present) 7 (30%) 3 (3%) 15.6 (3.66–66.58) P < 0.05 4.91 (0.95–25.47) P = 0.06; B = 1.59 LV-LGE (present) 18 (78%) 28 (25%) 10.5 (3.58–31.04) P < 0.05 5.52 (1.62–18.77) P < 0.01; B = 1.71 VA (n = 23) No VA (n = 110a) Univariable (OR 95% CI) Multivariable (OR 95% CI) Low voltage (present) 16 (70%) 50 (45%) 2.55 (0.97–6.68) P < 0.05 0.73 (0.20–2.59) P = 0.62; B = −0.32 Inverted lateral T-wave (present) 16 (70%) 26 (24%) 7.38 (2.74–19.89) P < 0.05 3.05 (0.85–10.91) P = 0.09; B = 1.11 LVEF<45% (present) 7 (30%) 3 (3%) 15.6 (3.66–66.58) P < 0.05 4.91 (0.95–25.47) P = 0.06; B = 1.59 LV-LGE (present) 18 (78%) 28 (25%) 10.5 (3.58–31.04) P < 0.05 5.52 (1.62–18.77) P < 0.01; B = 1.71 VA, ventricular arrhythmia; LVEF, left ventricular ejection fraction; LGE, late gadolinium enhancement; B, regression coefficient; CI, confidence interval. a Only the mutation carriers where ambulatory and/or exercise ECG data were available were included in this analysis. Figure 6 View largeDownload slide Bull’s eye plot (17 LV segments model) showing localization of LGE (% per segment represents the mutation carriers with CMR LGE in that segment) in PLN p.Arg14del mutation carriers who experienced VA (n = 23; right panel) vs. no VA (n = 127; left panel). VA, ventricular arrhythmia. Figure 6 View largeDownload slide Bull’s eye plot (17 LV segments model) showing localization of LGE (% per segment represents the mutation carriers with CMR LGE in that segment) in PLN p.Arg14del mutation carriers who experienced VA (n = 23; right panel) vs. no VA (n = 127; left panel). VA, ventricular arrhythmia. The presence of LV-LGE (OR 5.52, P < 0.01) remained independently associated with the occurrence of VA, but low voltage, inverted T-waves and LVEF <45% were not independently associated with VA occurrence. Discussion PLN p.Arg14del cardiomyopathy is characterized by early low voltage and repolarization changes on the ECG1,8 and a high risk for VA,3 both likely a reflection of fibrosis although previously unproven. This study provides new insights into the association between these observations. As hypothesized, firstly, we found that LGE is present in a distinct subgroup of PLN p.Arg14del mutation carriers in this cohort. Index patients showed more extensive structural and functional evidence of disease progress but LV-LGE was also seen in many subjects with a preserved LV systolic function (LVEF >45%). This important finding suggests that fibrosis is an early feature in PLN p.Arg14del cardiomyopathy. Secondly, both the presence of low voltage and inverted lateral T-waves were associated with LV-LGE in PLN p.Arg14del mutation carriers. LV-LGE was most abundant in the LV inferolateral wall, where we observed a high prevalence of negative T-waves. Our findings strongly suggest that these ECG changes are a reflection of myocardial fibrosis. Thirdly, in line with these findings, we could demonstrate that LV-LGE is independently associated with the occurrence of VA, attesting to the clinical importance of fibrosis in this disease. Finally, in addition to previous clinical and histopathological findings,1,6,7 our current data support the notion of biventricular involvement in PLN p.Arg14del cardiomyopathy, given the strong correlation between LV and RV systolic function. The pathophysiological mechanisms responsible for these findings in PLN p.Arg14del cardiomyopathy are not fully understood, but it is likely that disturbed calcium homeostasis plays an important role. The mutation in the PLN gene leads to reduced SERCA activity, which causes calcium overload leading to cardiomyocyte damage and eventually myocardial fibrosis.7 We observed a specific predominance of this fibrosis in the inferolateral wall of the left ventricle, comparable to desmosomal ACM24 and specific other forms of cardiomyopathy, for example in Duchenne muscular dystrophy.25,26 It is unclear how a pathogenic mutation that presumably affects the heart in a diffuse manner may result in a segmental distribution of disease. Whether the inferolateral wall is more vulnerable due to regional molecular changes caused by the mutation, or whether this regional susceptibility results from exposure to higher mechanical stress has not yet been elucidated. Current guidelines for the primary prevention of SCD in patients with DCM generally recommend that a defibrillator be implanted in patients, who have NYHA functional class II/III and an LVEF of less than 35%.27–29 However, previous studies suggest that the presence of LV-LGE imaging is an extra independent risk factor in these patients.12–16 In our previous study on PLN p.Arg14del mutation carriers, we showed that an LVEF of less than 45% (rather than 35%) is an independent risk factor for VA.3 In this study, we refine this finding by showing that LV-LGE is an even stronger risk factor than LVEF. In fact, even in the setting of preserved LVEF, the mere presence of LV-LGE is associated with a higher risk of VA in PLN p.Arg14del mutation carriers. Taken together, these data strongly support the use of CMR with LGE in this patient group, and should include the pre-symptomatic carriers. Study considerations/limitations CMR imaging was only performed in PLN p.Arg14del mutation carriers without a pacemaker or implantable cardioverter defibrillator, leading to a preferential inclusion of patients with early-stage disease. Moreover, the majority were not index patients, but carriers identified after family cascade screening. However, these circumstances provided us with a unique opportunity to study early-stage disease. The main limitation of the LGE technique is the inability to evaluate diffuse myocardial fibrosis. The enhanced area is defined on the basis of the difference in signal intensity relative to that of the normal myocardium. If the myocardial fibrosis is diffuse instead of focal, no differences in signal intensity will be observed. T1 mapping, a CMR sequence to visualize and quantify diffuse myocardial interstitial fibrosis in the whole heart, better reflects the total myocardial fibrosis burden30 but has only recently become available at our centres. We speculate that the presence of RV myocardial fibrosis is underestimated in the present cohort. We believe the observed low prevalence of RV-LGE is mainly due to the thin wall of the right ventricle, which makes the right ventricle much harder to visualize. The occurrence of VA was determined on ambulatory 24-h (Holter) and/or (exercise) electrocardiography, which were not available for every patient Therefore, we have only included mutation carriers where ambulatory and/or exercise ECG data were available for the VA-analysis. This may have led to selection bias. Finally, this was a retrospective study with inherent limitations, in particular regarding the collection and analysis of our data. Although this does not negate our observed associations between ECG and CMR findings, caution is definitely warranted regarding the findings on prognostication. Conclusions This multi-centre CMR study is the largest carried out so far in a genetically homogeneous cardiomyopathy cohort worldwide. We observed LV myocardial fibrosis even in the presence of preserved LVEF, which suggests that the development of fibrosis occurs as an early phenomenon in PLN p.Arg14del mutation carriers. Myocardial fibrosis is mainly present in the LV inferolateral wall and corresponds with ECG repolarization abnormalities. Although preliminary, the presence of LV-LGE was found to be independently associated with VA. Based on our findings, we recommend integrating CMR findings into the diagnostic work-up for both symptomatic and pre-symptomatic mutation carriers. Declaration of Helsinki The study conformed to the principles of the Helsinki Declaration and the institutional medical ethics committees. The data were collected retrospectively and the clinical investigations were performed as part of routine patient care. Acknowledgements We thank Jackie Senior for carefully editing the manuscript. Conflict of interest: A.A.M.W. is a Member of the Scientific Advisory Board of LilaNova. P.L.v.H. became an employee of F.Hoffman-La Roche Ltd. in 2016. The authors report no further conflicts of interest or any relationships with industry. Funding This work was supported by the Netherlands Cardiovascular Research Initiative (CVON), an initiative supported by the Dutch Heart Foundation (the Hague, the Netherlands): CVON [grant number 2012-10] PREDICT, CVON [grant number 2014-40] DOSIS, and CVON [grant number 2015-12] eDETECT projects. W.P.t.R is supported by Young Talent Program (CVON PREDICT) grant 2017T001 - Dutch Heart Foundation. References 1 van der Zwaag PA , van Rijsingen IA , Asimaki A , Jongbloed JD , van Veldhuisen DJ , Wiesfeld AC et al. Phospholamban R14del mutation in patients diagnosed with dilated cardiomyopathy or arrhythmogenic right ventricular cardiomyopathy: evidence supporting the concept of arrhythmogenic cardiomyopathy . Eur J Heart Fail 2012 ; 14 : 1199 – 207 . Google Scholar Crossref Search ADS PubMed 2 van der Zwaag PA , van Rijsingen IA , de Ruiter R , Nannenberg EA , Groeneweg JA , Post JG et al. Recurrent and founder mutations in the Netherlands-Phospholamban p.Arg14del mutation causes arrhythmogenic cardiomyopathy . Neth Heart J 2013 ; 21 : 286 – 93 . Google Scholar Crossref Search ADS PubMed 3 van Rijsingen IA , van der Zwaag PA , Groeneweg JA , Nannenberg EA , Jongbloed JD , Zwinderman AH et al. Outcome in phospholamban R14del carriers: results of a large multicentre cohort study . Circ Cardiovasc Genet 2014 ; 7 : 455 – 65 . Google Scholar Crossref Search ADS PubMed 4 MacLennan DH , Kranias EG. Phospholamban: a crucial regulator of cardiac contractility . Nat Rev Mol Cell Biol 2003 ; 4 : 566 – 77 . Google Scholar Crossref Search ADS PubMed 5 Haghighi K , Kolokathis F , Gramolini AO , Waggoner JR , Pater L , Lynch RA et al. A mutation in the human phospholamban gene, deleting arginine 14, results in lethal, hereditary cardiomyopathy . Proc Natl Acad Sci USA 2006 ; 103 : 1388 – 93 . Google Scholar Crossref Search ADS PubMed 6 Gho JM , van Es R , Stathonikos N , Harakalova M , Te Rijdt WP , Suurmeijer AJ et al. High resolution systematic digital histological quantification of cardiac fibrosis and adipose tissue in phospholamban p.Arg14del mutation associated cardiomyopathy . PLoS One 2014 ; 9 : e94820 . Google Scholar Crossref Search ADS PubMed 7 Te Rijdt WP , van Tintelen JP , Vink A , van der Wal AC , de Boer RA , van den Berg MP et al. Phospholamban p.Arg14del cardiomyopathy is characterized by phospholamban aggregates, aggresomes, and autophagic degradation . Histopathology 2016 ; 69 : 542 – 50 . Google Scholar Crossref Search ADS PubMed 8 Posch MG , Perrot A , Geier C , Boldt LH , Schmidt G , Lehmkuhl HB et al. Genetic deletion of arginine 14 in phospholamban causes dilated cardiomyopathy with attenuated electrocardiographic R amplitudes . Heart Rhythm 2009 ; 6 : 480 – 6 . Google Scholar Crossref Search ADS PubMed 9 McCrohon JA , Moon JC , Prasad SK , McKenna WJ , Lorenz CH , Coats AJ et al. Differentiation of heart failure related to dilated cardiomyopathy and coronary artery disease using gadolinium-enhanced cardiovascular magnetic resonance . Circulation 2003 ; 108 : 54 – 9 . Google Scholar Crossref Search ADS PubMed 10 Holmstrom M , Kivisto S , Helio T , Jurkko R , Kaartinen M , Antila M et al. Late gadolinium enhanced cardiovascular magnetic resonance of lamin A/C gene mutation related dilated cardiomyopathy . J Cardiovasc Magn Reson 2011 ; 13 : 30. Google Scholar Crossref Search ADS PubMed 11 Almaas VM , Haugaa KH , Strom EH , Scott H , Smith HJ , Dahl CP et al. Noninvasive assessment of myocardial fibrosis in patients with obstructive hypertrophic cardiomyopathy . Heart 2014 ; 100 : 631 – 8 . Google Scholar Crossref Search ADS PubMed 12 Assomull RG , Prasad SK , Lyne J , Smith G , Burman ED , Khan M et al. Cardiovascular magnetic resonance, fibrosis, and prognosis in dilated cardiomyopathy . J Am Coll Cardiol 2006 ; 48 : 1977 – 85 . Google Scholar Crossref Search ADS PubMed 13 Wu KC , Weiss RG , Thiemann DR , Kitagawa K , Schmidt A , Dalal D et al. Late gadolinium enhancement by cardiovascular magnetic resonance heralds an adverse prognosis in nonischemic cardiomyopathy . J Am Coll Cardiol 2008 ; 51 : 2414 – 21 . Google Scholar Crossref Search ADS PubMed 14 Lehrke S , Lossnitzer D , Schob M , Steen H , Merten C , Kemmling H et al. Use of cardiovascular magnetic resonance for risk stratification in chronic heart failure: prognostic value of late gadolinium enhancement in patients with non-ischaemic dilated cardiomyopathy . Heart 2011 ; 97 : 727 – 32 . Google Scholar Crossref Search ADS PubMed 15 Gulati A , Jabbour A , Ismail TF , Guha K , Khwaja J , Raza S et al. Association of fibrosis with mortality and sudden cardiac death in patients with nonischemic dilated cardiomyopathy . JAMA 2013 ; 309 : 896 – 908 . Google Scholar Crossref Search ADS PubMed 16 Disertori M , Rigoni M , Pace N , Casolo G , Mase M , Gonzini L et al. Myocardial fibrosis assessment by LGE is a powerful predictor of ventricular tachyarrhythmias in ischemic and nonischemic LV dysfunction: a meta-analysis . JACC Cardiovasc Imaging 2016 ; 9 : 1046 – 55 . Google Scholar Crossref Search ADS PubMed 17 Kramer CM , Barkhausen J , Flamm SD , Kim RJ , Nagel E ; Society for Cardiovascular Magnetic Resonance Board of Trustees Task Force on Standardized Protocols . Standardized cardiovascular magnetic resonance (CMR) protocols 2013 update . J Cardiovasc Magn Reson 2013 ; 15 : 91 . Google Scholar Crossref Search ADS PubMed 18 Alfakih K , Plein S , Thiele H , Jones T , Ridgway JP , Sivananthan MU. Normal human left and right ventricular dimensions for MRI as assessed by turbo gradient echo and steady-state free precession imaging sequences . J Magn Reson Imaging 2003 ; 17 : 323 – 9 . Google Scholar Crossref Search ADS PubMed 19 Mikami Y , Kolman L , Joncas SX , Stirrat J , Scholl D , Rajchl M et al. Accuracy and reproducibility of semi-automated late gadolinium enhancement quantification techniques in patients with hypertrophic cardiomyopathy . J Cardiovasc Magn Reson 2014 ; 16 : 85. Google Scholar Crossref Search ADS PubMed 20 Cerqueira MD , Weissman NJ , Dilsizian V , Jacobs AK , Kaul S , Laskey WK et al. American Heart Association Writing Group on Myocardial Segmentation and Registration for Cardiac Imaging. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association . Circulation 2002 ; 105 : 539 – 42 . Google Scholar Crossref Search ADS PubMed 21 Kumar A , Abdel-Aty H , Kriedemann I , Schulz-Menger J , Gross CM , Dietz R et al. Contrast-enhanced cardiovascular magnetic resonance imaging of right ventricular infarction . J Am Coll Cardiol 2006 ; 48 : 1969 – 76 . Google Scholar Crossref Search ADS PubMed 22 Postema PG , De Jong JS , Van der Bilt IA , Wilde AA. Accurate electrocardiographic assessment of the QT interval: teach the tangent . Heart Rhythm 2008 ; 5 : 1015 – 8 . Google Scholar Crossref Search ADS PubMed 23 Harrell FE. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis . Berlin : Springer ; 2001 . 24 Te Riele AS , James CA , Philips B , Rastegar N , Bhonsale A , Groeneweg JA et al. Mutation-positive arrhythmogenic right ventricular dysplasia/cardiomyopathy: the triangle of dysplasia displaced . J Cardiovasc Electrophysiol 2013 ; 24 : 1311 – 20 . Google Scholar Crossref Search ADS PubMed 25 Verhaert D , Richards K , Rafael-Fortney JA , Raman SV. Cardiac involvement in patients with muscular dystrophies: magnetic resonance imaging phenotype and genotypic considerations . Circ Cardiovasc Imaging 2011 ; 4 : 67 – 76 . Google Scholar Crossref Search ADS PubMed 26 Frankel KA , Rosser RJ. The pathology of the heart in progressive muscular dystrophy: epimyocardial fibrosis . Hum Pathol 1976 ; 7 : 375 – 86 . Google Scholar Crossref Search ADS PubMed 27 Epstein AE , DiMarco JP , Ellenbogen KA , Estes NA 3rd , Freedman RA , Gettes LS et al. ; American College of Cardiology Foundation, American Heart Association Task Force on Practice G and Heart Rhythm Society . 2012 ACCF/AHA/HRS focused update incorporated into the ACCF/AHA/HRS 2008 guidelines for device-based therapy of cardiac rhythm abnormalities: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines and the Heart Rhythm Society . Circulation 2013 ; 127 : e283 – 352 . Google Scholar Crossref Search ADS PubMed 28 Priori SG , Blomstrom-Lundqvist C , Mazzanti A , Blom N , Borggrefe M , Camm J et al. ; Authors/Task Force Members and Document Reviewers . 2015 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: the Task Force for the Management of Patients with Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death of the European Society of Cardiology (ESC). Endorsed by: association for European Paediatric and Congenital Cardiology (AEPC) . Eur Heart J 2015 ; 36 : 2793 – 867 . Google Scholar Crossref Search ADS PubMed 29 Ponikowski P , Voors AA , Anker SD , Bueno H , Cleland JG , Coats AJ et al. ; ESC Scientific Document Group . 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC . Eur Heart J 2016 ; 37 : 2129 – 200 . Google Scholar Crossref Search ADS PubMed 30 Jellis CL , Kwon DH. Myocardial T1 mapping: modalities and clinical applications . Cardiovasc Diagn Ther 2014 ; 4 : 126 – 37 . Google Scholar PubMed Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
Journal
European Heart Journal – Cardiovascular Imaging – Oxford University Press
Published: Jan 1, 2019