MILD RHEUMATIC VALVULAR HEART DISEASE IS ASSOCIATED WITH INTERSTITIAL MYOCARDIAL FIBROSIS: A T1 MAPPING STUDY

Introduction: Aortic stenosis (AS) and aortic regurgitation (AR) patients develop both myocardial hypertrophia and fibrosis. B-type natriuretic peptide (BNP) and troponin are biomarkers whose value in aortic valvular heart disease (VHD) remains controversial. Cardiac magnetic resonance (CMR) imaging can detect replacement myocardial fibrosis (MF) by using late gadolinium enhancement (LGE), and diffuse MF by using extracellular volume (ECV) based measures (relative - ECV fraction - and absolute - indexed ECV) calculated from T1 mapping. Data evaluating the relationship of these biomarkers with both types of MF are scarce in AS, and are missing in AR patients. Hypothesis: There is an association between preoperative BNP and troponin and preoperative MF measures in severe aortic VHD patients. Methods: Patients with isolated severe AS or AR were prospectively recruited to be submitted to CMR before surgery, including LGE and ECV measures quantifications. They also collected blood samples for quantification of BNP and high sensitivity T troponin. The relationship between biomarkers and MF parameters was evaluated using linear regression and nonparametric conventional tests. Results: The study population included 99 patients, 67 with AS and 32 with AR. BNP median was 63 (39-103) pg/mL and troponin median was 17 (5-34) ng/L, no difference between AS and AR (p=0.31 and p=0.88, respectively). BNP and troponin were associated with presence of LGE. BNP median was 47 (32-87) pg/mL without LGE vs. 87 (47-190) pg/mL with LGE (p=0.002). Troponin median was 13 (5-25) ng/L without LGE vs. 30 (10-71) ng/L with LGE (p=0.001). Regarding ECV measures, patients with ECV fraction higher than 28.25% had higher BNP levels (p<0.001) and patients with indexed ECV higher than 24.21mL/m 2 had higher troponin levels (p=0.015) (Figure 1). Conclusions: BNP and troponin are associated with quantity of MF in patients with severe aortic VHD with indication of intervention.

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Abstract 16762: Post-Operative Prognostic Prediction of Different Myocardial Fibrosis Measures in Severe Aortic Valvular Heart Disease

Circulation ◽

10.1161/circ.142.suppl_3.16762 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Lucas J Pires ◽

Vitor E Rosa ◽

THAMARA C MORAIS ◽

Antonio S de Santis ◽

Joao Ricardo C Fernandes ◽

...

Keyword(s):

Heart Disease ◽

Clinical Outcomes ◽

Myocardial Fibrosis ◽

Valvular Heart Disease ◽

Cox Regression ◽

Extracellular Volume ◽

Functional Class ◽

Diffuse Myocardial Fibrosis ◽

Class Iii

Introduction: Aortic stenosis (AS) and aortic regurgitation (AR) patients develop myocardial remodeling characterized by hypertrophia and fibrosis. Cardiac magnetic resonance (CMR) imaging can detect the presence of replacement myocardial fibrosis, by using late gadolinium enhancement (LGE), and diffuse myocardial fibrosis, by using extracellular volume (ECV) based measures (relative - ECV fraction - and absolute - indexed ECV) calculated from T1 mapping. There are only few studies with AS patients and scarce data with AR patients showing an association between fibrosis and post-operative clinical outcomes. Hypothesis: There is an association between preoperative myocardial fibrosis measures and post-operative clinical outcomes in severe aortic valvular heart disease (VHD) patients submitted to surgical intervention. Methods: Patients with isolated severe AS or AR were prospectively recruited to be submitted to CMR before indicated surgery, including LGE and ECV measures quantifications. All patients were submitted to conventional surgery and were followed during post-operative period. Results: The study population included 99 patients, 67 with AS and 32 with AR. After a median post-operative follow up of 12.3 (3.2-24.4) months, the presence of LGE areas, found in 32 patients (32.3%), independently predicted post-operative combined events (global mortality or STS morbidity events or persistent NYHA functional class III-IV) during follow up in univariate and multivariate Cox regression analyses (HR 3.96, 95%CI 1.76-8.91, p<0.01). Kaplan-Meier curve is presented in Figure 1. ECV fraction (HR 1.02, 95%CI 0.96-1.09, p=0.55) or indexed ECV (HR 1.00, 95%CI 0.97-1.03, p=0.86) did not predict post-operative combined events. Conclusions: Presence of replacement myocardial fibrosis, but not diffuse myocardial fibrosis, in preoperative CMR predicts post-operative combined clinical events in severe VHD patients submitted to surgery.

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P852Impact of ischemic and valvular heart disease on atrial excitation: a high-resolution epicardial mapping study

EP Europace ◽

10.1093/ehjci/eux151.034 ◽

2017 ◽

Vol 19 (suppl_3) ◽

pp. iii158-iii158

Author(s):

E M J P Mouws ◽

EAH Lanters ◽

CP. Teuwen ◽

JME Van Der Does ◽

C. Kik ◽

...

Keyword(s):

Heart Disease ◽

High Resolution ◽

Valvular Heart Disease ◽

Epicardial Mapping ◽

Mapping Study ◽

Atrial Excitation

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1004Impact of ischemic and valvular heart disease on atrial excitation: a high-resolution epicardial mapping study

EP Europace ◽

10.1093/europace/euy015.553 ◽

2018 ◽

Vol 20 (suppl_1) ◽

pp. i191-i191

Author(s):

E M J P Mouws ◽

EAH Lanters ◽

C P Teuwen ◽

JME Van Der Does ◽

C Kik ◽

...

Keyword(s):

Heart Disease ◽

High Resolution ◽

Valvular Heart Disease ◽

Epicardial Mapping ◽

Mapping Study ◽

Atrial Excitation

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Abstract 15154: T1-mapping and Outcomes in Non-ischemic Cardiomyopathies- An Investigator-led Multicenter Observational Longitudinal Study

Circulation ◽

10.1161/circ.132.suppl_3.15154 ◽

2015 ◽

Vol 132 (suppl_3) ◽

Author(s):

Valentina O Puntmann ◽

Gerry Carr-White ◽

Andrew Jabbour ◽

Chung-Yao Yu ◽

Rolf Gebker ◽

...

Keyword(s):

Longitudinal Study ◽

Risk Stratification ◽

Myocardial Fibrosis ◽

T1 Mapping ◽

Independent Predictor ◽

Reference Ranges ◽

Non Invasive ◽

Native T1 ◽

All Cause Mortality ◽

Interstitial Myocardial Fibrosis

Introduction: Nonischemic cardiomyopathy (NICM) is a recognised cause of poor clinical outcome. NICM is characterised by intrinsic myocardial impairment, which is driven by interstitial myocardial fibrosis in a considerable majority of NICM. The lack of accurate and noninvasive characterisation of interstitial myocardial fibrosis limits recognition of disease and effective clinical management in NICM. Hypothesis: T1 mapping by CMR is a novel non-invasive imaging application with a recognized potential to significantly improve the management of patients with NICM, supporting characterization of interstitial myocardial disease, assessment of severity of disease, risk stratification as well as development of targeted therapies. Comparative prognostic relevance of T1-mapping parameters in subjects with NICM for adverse outcome is unknown. Methods: an investigator-led multicenter observational longitudinal study in patients with NICM. We standardized imaging acquisition based on the modified Look-Locker sequence (MOLLI) (3(3)3(3)5) and post-processing approach of T1 mapping, and transferred the methodology to several other centres. We determined reference ranges for T1 mapping values and provided proof of concept studies in NICM in discrimination between health and disease. The primary endpoint was all-cause mortality. Results: 805 consecutive patients (mean age (years) 50±16; males: n=499, 62%) with NICM underwent contrast-enhanced CMR with T1-mapping. During a median follow-up period of 17 months (range 36 months), we observed a total of 26 deaths (18 cardiac). Native T1, ECV and extent of LGE were strongly associated with an increased likelihood of all-cause mortality (p<0.001). In multivariate analyses, native T1 was the sole independent predictor of all-cause and cardiac mortality, over and above ECV and LGE. Native T1 was also superior in correctly classifying subjects and adverse events over a 17-months period. Conclusions. In patients with NICM, non-invasive measures of interstitial myocardial fibrosis are useful in prediction of outcome. Native T1 is an independent predictor over and above conventional markers of risk, providing a basis for a novel algorithm of risk stratification in NICM.

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