Dataset Information

Characterization of Left Ventricular Non-Compaction Cardiomyopathy.

ABSTRACT: Left ventricle non-compaction cardiomyopathy (LVNC) has gained great interest in recent years, being one of the most controversial cardiomyopathies. There are several open debates, not only about its genetic heterogeneity, or about the possibility to be an acquired cardiomyopathy, but also about its possible overdiagnosis based on imaging techniques. In order to better understand this entity, we identified 38 LVNC patients diagnosed by cardiac MRI (CMRI) or anatomopathological study that could underwent NGS-sequencing and clinical study. Anatomopathological exam was performed in eight available LVNC hearts. The genetic yield was 34.2%. Patients with negative genetic testing had better left ventricular ejection fraction (LVEF) or it showed a tendency to improve in follow-up, and a possible trigger factor for LVNC was identified in 1/3 of them. Nonetheless, cerebrovascular accidents occurred in similar proportions in both groups. We conclude that in LVNC there seem to be different ways to achieve the same final phenotype. Genetic testing has a good genetic yield and provides valuable information. LVNC without an underlying genetic cause may have a better prognosis in terms of LVEF evolution. However, anticoagulation to prevent cerebrovascular accident (CVA) should be carefully evaluated in all patients. Larger series with pathologic examination are needed to help better understand this entity.

SUBMITTER: Lorca R

PROVIDER: S-EPMC7464545 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Characterization of Left Ventricular Non-Compaction Cardiomyopathy.

Lorca Rebeca R Martín María M Pascual Isaac I Astudillo Aurora A Díaz Molina Beatriz B Cigarrán Helena H Cuesta-Llavona Elías E Avanzas Pablo P Rodríguez Reguero José Julían JJ Coto Eliecer E Morís César C Gómez Juan J

Journal of clinical medicine 20200805 8

Left ventricle non-compaction cardiomyopathy (LVNC) has gained great interest in recent years, being one of the most controversial cardiomyopathies. There are several open debates, not only about its genetic heterogeneity, or about the possibility to be an acquired cardiomyopathy, but also about its possible overdiagnosis based on imaging techniques. In order to better understand this entity, we identified 38 LVNC patients diagnosed by cardiac MRI (CMRI) or anatomopathological study that could u ...[more]

PMID: 32764337

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Project description:AimsLeft ventricular non-compaction cardiomyopathy (LVNC) is a poorly understood entity resulting in heart failure. Whether it is a distinct form of cardiomyopathy or an anatomical phenotype is a subject of discussion. The current diagnosis is based on morphologic findings by comparing the compacted to non-compacted myocardium. The study aimed to compare demographic and prognostic variables of patients with dilated cardiomyopathy (DCM) and LVNC. Emphasis was given to cardiac magnetic resonance (CMR) imaging analysis. Data on survival were also assessed.Methods and resultsWe retrospectively evaluated the characteristics and outcomes of 262 non-ischaemic cardiomyopathy patients with LVNC and DCM phenotypes. Petersen's CMR criteria of non-compacted to the compacted myocardial ratio 2.3 were used to diagnose LVNC. The primary endpoint was a composite endpoint of major adverse cardiovascular events comprising cardiovascular-related death, left ventricular assisted device implantation, or heart transplantation. A total of 262 patients with CMR data were included in the study. One hundred fifty-five patients who fulfilled CMR criteria were diagnosed as LVNC. CMR findings revealed that LVNC patients had higher left ventricular end-diastolic (137.2 ± 51.6, 116.8 ± 44.6, P = 0.002) and systolic volume index (98.4 ± 49.5, 85.9 ± 42.7, P = 0.049). Cardiac haemodynamics, cardiac output (5.61 ± 2.03, 4.96 ± 1.83; P = 0.010), stroke volume (73.9 ± 28.8, 65.1 ± 25.1; P = 0.013), and cardiac index (2.85 ± 1.0, 2.37 ± 0.72; P < 0.0001), were higher in LVNC patients. Of all the 249 patients, 102 (40.9%) patients demonstrated late gadolinium enhancement (LGE). According to Petersen's criteria, the Kaplan-Meier survival outcome did not reveal significant differences (hazard ratio [HR]: 1.53, 95% confidence interval [CI]: [0.89-2.63], P = 0.11). The presence or pattern of LGE did not show significant importance for endpoint-free survival. Most of the sub-epicardial LGE pattern was found in LVNC patients (94.4%). When receiver operator characteristics analysis was applied to NC/C ratio to discriminate the primary endpoint, a higher NC/C ratio of 2.57 was associated with adverse events (HR: 1.90, 95% CI: [1.12-3.24], P = 0.016).ConclusionsOur study questions the criteria being used for the diagnosis of LVNC. Further evaluation of CMR variables and association of these findings with demographic variables and survival is mandatory.

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

Characterization of Left Ventricular Non-Compaction Cardiomyopathy.

Publications

Characterization of Left Ventricular Non-Compaction Cardiomyopathy.

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