Dataset Information

Prognostic Cardiac Magnetic Resonance Markers of Left Ventricular Involvement in Arrhythmogenic Cardiomyopathy for Predicting Heart Failure Outcomes.

ABSTRACT: Background Left ventricular (LV) involvement is frequently observed in arrhythmogenic cardiomyopathy (ACM). We investigated the association of LV myocardial assessment using cardiac magnetic resonance (CMR) with clinical outcomes including heart failure (HF)-related events in ACM. Methods and Results We retrospectively analyzed 60 patients with ACM between 2005 and 2020 according to the 2010 Task Force Criteria and assessed HF-related events (HF hospitalization, heart transplantation, and cardiac death) and ventricular tachycardia events. We analyzed CMR findings including late gadolinium enhancement (LGE) in all subjects and obtained mapping values (native T1, extracellular volume, and T2) on 30 (50%) patients out of them. Among the study population (mean age 49 years, 77% male), 41 (68%) patients had LV LGE. During a median follow-up of 34 months, there were 13 (22%) HF-related events, and 20 (30%) ventricular tachycardia events. Kaplan-Meier survival analysis revealed that HF-related events occurred only in patients with LV LGE (+) (versus LV LGE (-), log-rank P=0.006), and the events were not significantly different regarding right ventricular LGE (log-rank P>0.999). When categorized by median value for each mapping parameter, HF-related events occurred more in patients with higher native T1 (versus lower native T1, log-rank P=0.002), and higher T2 (versus lower T2, log-rank P=0.002), higher extracellular volume (versus lower extracellular volume, log-rank P=0.002). However, regarding ventricular tachycardia events, there were no significant differences according to these CMR markers. Conclusions LV myocardial assessment using CMR with LGE imaging and native T1, T2, and extracellular volume markers were significantly associated with HF-related event risk in patients with ACM.

SUBMITTER: Chun KH

PROVIDER: S-EPMC9075293 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:AimsPeripartum cardiomyopathy (PPCM) is a major cause of acute heart failure in the peripartum period and considered potentially life threatening. While many aspects of its clinical profiles have been frequently reported, functional analysis, in particular of the right ventricle, and tissue characterization by cardiovascular magnetic resonance (CMR) imaging have been only sporadically described. The aim of the present study was to analyse pathological alterations and their prognostic relevance found in CMR imaging of patients newly diagnosed with PPCM.Methods and resultsIn this multicenter study 34 patients with confirmed PPCM underwent CMR imaging at the time of diagnosis and at 5 ± 1 months follow-up. Cine imaging of PPCM patients showed moderate to severe reduction of systolic left ventricular (LV) function (mean LVEF: 29.7 ± 12.8%). In 35% of the patients right ventricular (RV) systolic function was also reduced with a mean RVEF of 42.9 ± 13.9%. Dilatation of the LV was observed in 91% (mean LV-EDV/BSA 128.5 ± 32.1 mL/m2), and dilatation of the RV was present in 24% (mean RV-EDV/BSA 87.4 ± 18.5 mL/m2) of the patients. Focal non-ischemic late gadolinium enhancement (LGE) was visible in 71%, and regional wall motion abnormalities were evident in 88% of the patients. LGE and wall motion abnormalities were predominantly located in the anteroseptal and basal to midventricular segments. RV dysfunction at baseline was associated with reduced probability of full cardiac recovery at 5 ± 1 months follow-up.ConclusionsBesides LV systolic dysfunction, RV dysfunction and dilatation are observed in about one third of PPCM patients at the time of diagnosis. RV dysfunction is associated with unfavourable outcome. A distinct pattern of LV wall motion abnormalities and myocardial scar is evident in most PPCM patients. The present study may help to establish a set of CMR criteria suitable for diagnosis in patients with suspected PPCM and may add further knowledge to the pathology of the disease.

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.

Project description:AimsOur previous studies suggested that the complement system was critical in the prognosis of arrhythmogenic right ventricular cardiomyopathy (ARVC). The acylation-stimulating protein (ASP), generated through the alternate complement pathway, was reported to regulate lipogenesis and triglyceride storage. This study aimed to investigate the role of ASP in predicting adverse cardiac events in an ARVC cohort.Methods and resultsWe enrolled 111 ARVC patients and 106 healthy volunteers, and measured their plasma ASP levels using enzyme-linked immunosorbent assays. Plasma ASP levels were significantly higher in the ARVC patients than in the healthy controls (2325.22 ± 20.08 vs. 2189.75 ± 15.55, P < 0.001), with a similar trend observed in the myocardial explant assay. Spearman correlation analysis indicated plasma ASP level associated with cardiac structural (right ventricular internal dimension, P = 0.006) and functional remodelling (left ventricular ejection fraction, P = 0.002) in ARVC patients. The ARVC patients were followed up for an average of 17.79 ± 1.09 months. Heart failure-associated events (HFAEs) were defined as heart transplantation, on a cardiac transplant list, or death due to end-stage heart failure. Plasma ASP levels in patients with HFAEs were significantly higher than in those without clinical events (2486.03 ± 26.70 vs. 2268.83 ± 23.51, P < 0.001) or those with malignant arrhythmic events (2486.03 ± 26.70 vs. 2297.80 ± 60.46, P = 0.008). LASSO (least absolute shrinkage and selection operator) and multivariable Cox regression analyses showed the ASP level (HR = 1.004, 95% CI [1.002,1.006], P = 0.002) was an independent predictor for adverse HFAEs in ARVC patients. The spline-fitting procedure was applied to illustrate the HFAE-free probabilities at different time points.ConclusionsOur results suggest that plasma ASP may be a useful biomarker in prediction of adverse HF-associated events in ARVC patients.

Dataset Information

Prognostic Cardiac Magnetic Resonance Markers of Left Ventricular Involvement in Arrhythmogenic Cardiomyopathy for Predicting Heart Failure Outcomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets