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Left ventricular non-compaction: clinical features and cardiovascular magnetic resonance imaging.

ABSTRACT: BACKGROUND: It is apparent that despite lack of family history, patients with the morphological characteristics of left ventricular non-compaction develop arrhythmias, thrombo-embolism and left ventricular dysfunction. METHODS: Forty two patients, aged 48.7 +/- 2.3 yrs (mean +/- SEM) underwent cardiovascular magnetic resonance (CMR) for the quantification of left ventricular volumes and extent of non-compacted (NC) myocardium. The latter was quantified using planimetry on the two-chamber long axis LV view (NC area). The patients included those referred specifically for CMR to investigate suspected cardiomyopathy, and as such is represents a selected group of patients. RESULTS: At presentation, 50% had dyspnoea, 19% chest pain, 14% palpitations and 5% stroke. Pulmonary embolism had occurred in 7% and brachial artery embolism in 2%. The ECG was abnormal in 81% and atrial fibrillation occurred in 29%. Transthoracic echocardiograms showed features of NC in only 10%. On CMR, patients who presented with dyspnoea had greater left ventricular volumes (both p < 0.0001) and a lower left ventricular ejection fraction (LVEF) (p < 0.0001) than age-matched, healthy controls. In patients without dyspnoea (n = 21), NC area correlated positively with end-diastolic volume (r = 0.52, p = 0.0184) and end-systolic volume (r = 0.56, p = 0.0095), and negatively with EF (r = -0.72, p = 0.0001). CONCLUSION: Left ventricular non-compaction is associated with dysrrhythmias, thromboembolic events, chest pain and LV dysfunction. The inverse correlation between NC area and EF suggests that NC contributes to left ventricular dysfunction.

SUBMITTER: Yousef ZR

PROVIDER: S-EPMC2743643 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Left ventricular non-compaction: clinical features and cardiovascular magnetic resonance imaging.

Yousef Zaheer R ZR Foley Paul W X PW Khadjooi Kayvan K Chalil Shajil S Sandman Harald H Mohammed Noor U H NU Leyva Francisco F

BMC cardiovascular disorders 20090809

<h4>Background</h4>It is apparent that despite lack of family history, patients with the morphological characteristics of left ventricular non-compaction develop arrhythmias, thrombo-embolism and left ventricular dysfunction.<h4>Methods</h4>Forty two patients, aged 48.7 +/- 2.3 yrs (mean +/- SEM) underwent cardiovascular magnetic resonance (CMR) for the quantification of left ventricular volumes and extent of non-compacted (NC) myocardium. The latter was quantified using planimetry on the two-ch ...[more]

PMID: 19664240

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Project description:BACKGROUND:Investigation of the myocardial strain characteristics of the left ventricular non-compaction (LVNC) phenotype with cardiovascular magnetic resonance (CMR) feature tracking. METHODS:CMR cine balanced steady-state free precession data sets of 59 retrospectively identified LVNC phenotype patients (40?years, IQR: 28-50?years; 51% male) and 36 healthy subjects (39?years, IQR: 30-47?years; 44% male) were evaluated for LV volumes, systolic function and mass. Hypertrabeculation in patients and healthy subjects was evaluated against established CMR diagnostic criteria. Global circumferential strain (GCS), global radial strain (GRS) and global longitudinal strain (GLS) were evaluated with feature-tracking software. Subgroup analyses were performed in patients (n =?25) and healthy subjects (n =?34) with normal LV volumetrics, and with healthy subjects (n =?18) meeting at least one LVNC diagnostic criteria. RESULTS:All LVNC phenotype patients, as well as a significant proportion of healthy subjects, met morphology-based CMR diagnostic criteria: non-compacted (NC): compacted myocardial diameter ratio?>?2.3 (100% vs. 19.4%), NC mass?>?20% (100% vs. 44.4%) and?>?25% (100% vs. 13.9%), and NC mass indexed to body surface area?>?15?g/m2 (100% vs. 41.7%). LVNC phenotype patients demonstrated reduced GRS (26.4% vs. 37.1%; p <?0.001), GCS (-?16.5% vs. -20.5%; p <?0.001) and GLS (-?14.6% vs. -17.1%; p <?0.001) compared to healthy subjects, with statistically significant differences persisting on subgroup comparisons of LVNC phenotype patients with healthy subjects meeting diagnostic criteria. GCS also demonstrated independent and incremental diagnostic value beyond each of the morphology-based CMR diagnostic criteria. CONCLUSIONS:LVNC phenotype patients demonstrate impaired strain by CMR feature tracking, also present on comparison of subjects with normal LV volumetrics meeting diagnostic criteria. The high proportion of healthy subjects meeting morphology-based CMR diagnostic criteria emphasizes the important potential complementary diagnostic value of strain in differentiating LVNC from physiologic hypertrabeculation.

Project description:Left Ventricular (LV) Non-compaction (LVNC), Hypertrophic Cardiomyopathy (HCM), and Dilated Cardiomyopathy (DCM) share morphological and functional traits that increase the diagnosis complexity. Additional clinical information, besides imaging data such as cardiovascular magnetic resonance (CMR), is usually required to reach a definitive diagnosis, including electrocardiography (ECG), family history, and genetics. Alternatively, indices of hypertrabeculation have been introduced, but they require tedious and time-consuming delineations of the trabeculae on the CMR images. In this paper, we propose a radiomics approach to automatically encode differences in the underlying shape, gray-scale and textural information in the myocardium and its trabeculae, which may enhance the capacity to differentiate between these overlapping conditions. A total of 118 subjects, including 35 patients with LVNC, 25 with HCM, 37 with DCM, as well as 21 healthy volunteers (NOR), underwent CMR imaging. A comprehensive radiomics characterization was applied to LV short-axis images to quantify shape, first-order, co-occurrence matrix, run-length matrix, and local binary patterns. Conventional CMR indices (LV volumes, mass, wall thickness, LV ejection fraction-LVEF-), as well as hypertrabeculation indices by Petersen and Jacquier, were also analyzed. State-of-the-art Machine Learning (ML) models (one-vs.-rest Support Vector Machine-SVM-, Logistic Regression-LR-, and Random Forest Classifier-RF-) were used for one-vs.-rest classification tasks. The use of radiomics models for the automated diagnosis of LVNC, HCM, and DCM resulted in excellent one-vs.-rest ROC-AUC values of 0.95 while generating these results without the need for the delineation of the trabeculae. First-order and texture features resulted to be among the most discriminative features in the obtained radiomics signatures, indicating their added value for quantifying relevant tissue patterns in cardiomyopathy differential diagnosis.

Dataset Information

Left ventricular non-compaction: clinical features and cardiovascular magnetic resonance imaging.

Publications

Left ventricular non-compaction: clinical features and cardiovascular magnetic resonance imaging.

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