Myocardial T1 mapping and extracellular volume quantification in patients with left ventricular non-compaction cardiomyopathy

Araujo-Filho, José A B; Assunção, Antonildes Nascimento; Melo, Marcelo Dantas Tavares de; Bière, Loïc; Lima, Cárita Portilho de; Dantas, Roberto Nery; Nomura, César Higa; Salemi, Vera Maria Cury; Jerosch‐Herold, Michael; Filho, José Rodrigues

doi:10.1093/ehjci/jey022

Cited by 40 publications

(26 citation statements)

References 41 publications

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“…10 Recently, the importance of extracellular volume quantification as a CMRI parameter in predicting ventricular arrhythmias in patients with LVNC has been demonstrated, showing the interstitial fibrosis as a predisposing factor in ventricular arrhythmias, even in patients with low LGE. 33 Another piece of interesting data in our sample is that almost 30% of patients with MACE had normal diastolic function patterns on echo. Thus, 14.8% of the LVNC patients had normal systolic and diastolic LV functions, no LGE, and still had adverse outcomes, which showed the severity of Table 4 Cardiac magnetic resonance imaging parameters in non-compaction cardiomyopathy patients with/without major adverse cardiovascular events…”

Section: Discussionmentioning

confidence: 72%

Biventricular imaging markers to predict outcomes in non‐compaction cardiomyopathy: a machine learning study

et al. 2020

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Aims Left ventricular non-compaction cardiomyopathy (LVNC) is a genetic heart disease, with heart failure, arrhythmias, and embolic events as main clinical manifestations. The goal of this study was to analyse a large set of echocardiographic (echo) and cardiac magnetic resonance imaging (CMRI) parameters using machine learning (ML) techniques to find imaging predictors of clinical outcomes in a long-term follow-up of LVNC patients. Methods and results Patients with echo and/or CMRI criteria of LVNC, followed from January 2011 to December 2017 in the heart failure section of a tertiary referral cardiologic hospital, were enrolled in a retrospective study. Two-dimensional colour Doppler echocardiography and subsequent CMRI were carried out. Twenty-four hour Holter monitoring was also performed in all patients. Death, cardiac transplantation, heart failure hospitalization, aborted sudden cardiac death, complex ventricular arrhythmias (sustained and non-sustained ventricular tachycardia), and embolisms (i.e. stroke, pulmonary thromboembolism and/or peripheral arterial embolism) were registered and were referred to as major adverse cardiovascular events (MACEs) in this study. Recruited for the study were 108 LVNC patients, aged 38.3 ± 15.5 years, 48.1% men, diagnosed by echo and CMRI criteria. They were followed for 5.8 ± 3.9 years, and MACEs were registered. CMRI and echo parameters were analysed via a supervised ML methodology. Forty-seven (43.5%) patients had at least one MACE. The best performance of imaging variables was achieved by combining four parameters: left ventricular (LV) ejection fraction (by CMRI), right ventricular (RV) end-systolic volume (by CMRI), RV systolic dysfunction (by echo), and RV lower diameter (by CMRI) with accuracy, sensitivity, and specificity rates of 75.5%, 77%, 75%, respectively. Conclusions Our findings show the importance of biventricular assessment to detect the severity of this cardiomyopathy and to plan for early clinical intervention. In addition, this study shows that even patients with normal LV function and negative late gadolinium enhancement had MACE. ML is a promising tool for analysing a large set of parameters to stratify and predict prognosis in LVNC patients.

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Section: Discussionmentioning

confidence: 72%

Biventricular imaging markers to predict outcomes in non‐compaction cardiomyopathy: a machine learning study

et al. 2020

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“…Increased native T1 values at the ventricular insertion points (Fig. 13), which are closely related to the frequently observed focal patterns of LE in patients with right heart pressure overload [86,87], could represent a potential non-contrast diagnostic marker in patients with suspicion of pulmonary hypertension [88,92].…”

Section: Eccentric Left Ventricular Hypertrophymentioning

confidence: 69%

“…2). Of interest, ECV in non-compaction CMP was found to be associated with LV dysfunction and ventricular arrhythmia, but not with the extent of non-compacted myocardium [87].…”

Section: Eccentric Left Ventricular Hypertrophymentioning

confidence: 94%

Cardiac magnetic resonance T1 mapping. Part 2: Diagnostic potential and applications

Reiter

Kräuter

et al. 2018

European Journal of Radiology

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Non-invasive identification and differentiation of myocardial diseases represents the primary objectives of cardiac magnetic resonance (CMR) longitudinal relaxation time (T1) and extracellular volume (ECV) mapping. Given the fact that myocardial T1 and ECV values overlap throughout and within left ventricular phenotypes, a central issue to be addressed is whether and to what extent myocardial T1 and ECV mapping provides additional or superior diagnostic information to standard CMR imaging, and whether native T1 mapping could be employed as a non-contrast alternative to late gadolinium enhancement (LE) imaging. The present review aims to summarize physiological and pathophysiological alterations in native T1 and ECV values and summarized myocardial T1 and ECV alterations associated with cardiac diseases to support the translation of research findings into routine CMR imaging.

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“…As our study concentrated on the analysis of the CMR imaging, we did not relate our results to adverse clinical outcomes but the established parameters of the LV function, such as EF or EDV, as they are considered possible good prognostic factors of adverse outcomes in cardiomyopathies [1,4]. Focusing mainly on LV morphology, we did not perform any LGE or T1-mapping analysis [24].…”

Section: Discussionmentioning

confidence: 99%

Influence of observer-dependency on left ventricular hypertrabeculation mass measurement and its relationship with left ventricular volume and ejection fraction – comparison between manual and semiautomatic CMR image analysis methods

et al. 2020

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Background Recent studies concerning left ventricular noncompaction (LVNC) suggest that the extent of left ventricular (LV) hypertrabeculation has no impact on prognosis. The variety of methods of LV noncompacted myocardial mass (NCM) assessment may influence the results. Hence, we compared two methods of NCM estimation: largely observer-independent Hautvast's (H) computed algorithm-based approach and commonly used Jacquier's (J) method, and their associations with LV end-diastolic volume (EDV) and ejection fraction (EF). Methods Cardiac magnetic resonance images of 77 persons (45±17yo)-42 LVNC, 15 non-ischemic dilative cardiomyopathy, 20 control group were analyzed. LVNC patients were divided into the subgroup with normal (LVNC N) and high EDV (LVNC DCM). NCM and total left ventricular mass (LVM) were estimated by Hautvast's [excluding intertrabecular blood (ITB) and including papillary muscles (PMs) into NCM] and Jacquier's approach (including ITB and PMs, if unclearly distinguished, into NCM). Results The cutoff value of NCM for LVNC diagnosis was 22% (AUC 0.933) for NCM H /LVM H and 26% (AUC 0.883) for NCM J /LVM J. Inter-and intra-observer variability (estimated by

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Myocardial T1 mapping and extracellular volume quantification in patients with left ventricular non-compaction cardiomyopathy

Cited by 40 publications

References 41 publications

Biventricular imaging markers to predict outcomes in non‐compaction cardiomyopathy: a machine learning study

Biventricular imaging markers to predict outcomes in non‐compaction cardiomyopathy: a machine learning study

Cardiac magnetic resonance T1 mapping. Part 2: Diagnostic potential and applications

Influence of observer-dependency on left ventricular hypertrabeculation mass measurement and its relationship with left ventricular volume and ejection fraction – comparison between manual and semiautomatic CMR image analysis methods

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