Dataset Information

Myocardial deformation pattern in left ventricular non-compaction: Comparison with dilated cardiomyopathy.

ABSTRACT: Left ventricular (LV) systolic dysfunction is the most frequent initial presentation of patient with LV noncompaction (NC). Our objectives were to evaluate myocardial contraction properties in patients with LVNC and the relationship of non-compacted segments with the degree of global and regional systolic deformation.We included 50 LVNC with an echocardiography and speckle imaging calculation of peak longitudinal strain (PLS). Each of the 16 LV myocardial segments was defined as NC (ratio NC/compacted layer > 2), borderline (NC/C 0-2) and compacted (NC/C = 0). Basal, median and apical strain values were calculated as the average of segmental strain values. For comparison a group of 50 patients with dilated cardiomyopathy (DCM) underwent the same measurements.There was no statistical difference between the 2 groups for any conventional LV systolic parameters. A characteristic deformation pattern was observed in LVNC with higher strain values in the LV apical segments (- 12.8 ± 5.9 vs - 10.7 ± 5.7) and an apical-basal ratio (1.52 ± 0.73 vs 1.12 ± 0.42; p < 0.001). There was no correlation between LV function and the degree of NC. Among 726 segments, compacta thickness was thinner in NC vs C segments (6.4 ± 1.4 vs 7.7 ± 1.8 mm; p < 0.05). There was no difference in WMS but regional strain values were significantly higher in NC compared to C segments (- 13.1 ± 6.1 vs - 10.2 ± 6.3; p < 0.05).Compared to DCM, LVNC presented with relatively preserved apical deformation as compared to basal segments. Lower regional deformation values in compacted segments confirm the concept that LVNC is a phenotypic marker of an underlying diffuse cardiomyopathy involving both C and NC myocardium.

SUBMITTER: Huttin O

PROVIDER: S-EPMC5497160 | biostudies-other | 2014 Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

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

Myocardial deformation pattern in left ventricular non-compaction: Comparison with dilated cardiomyopathy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets