Dataset Information

The Indices of Cardiovascular Magnetic Resonance Derived Atrial Dynamics May Improve the Contemporary Risk Stratification Algorithms in Children with Hypertrophic Cardiomyopathy.

ABSTRACT:

Introduction

The most efficient risk stratification algorithms are expected to deliver robust and indefectible identification of high-risk children with hypertrophic cardiomyopathy (HCM). Here we compare algorithms for risk stratification in primary prevention in HCM children and investigate whether novel indices of biatrial performance improve these algorithms.

Methods and results

The endpoints were defined as sudden cardiac death, resuscitated cardiac arrest, or appropriate implantable cardioverter-defibrillator discharge. We examined the prognostic utility of classic American College of Cardiology/American Heart Association (ACC/AHA) risk factors, the novel HCM Risk-Kids score and the combination of these with indices of biatrial dynamics. The study consisted of 55 HCM children (mean age 12.5 ± 4.6 years, 69.1% males); seven had endpoints (four deaths, three appropriate ICD discharges). A strong trend (DeLong p = 0.08) was observed towards better endpoint identification performance of the HCM Risk-Kids Model compared to the ACC/AHA strategy. Adding the atrial conduit function component significantly improved the prediction capabilities of the AHA/ACC Model (DeLong p = 0.01) and HCM Risk-Kids algorithm (DeLong p = 0.04).

Conclusions

The new HCM Risk-Kids individualised algorithm and score was capable of identifying high-risk children with very good accuracy. The inclusion of one of the atrial dynamic indices improved both risk stratification strategies.

SUBMITTER: Ziolkowska L

PROVIDER: S-EPMC7915130 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

The Indices of Cardiovascular Magnetic Resonance Derived Atrial Dynamics May Improve the Contemporary Risk Stratification Algorithms in Children with Hypertrophic Cardiomyopathy.

Ziółkowska Lidia L Mazurkiewicz Łukasz Ł Petryka Joanna J Kowalczyk-Domagała Monika M Boruc Agnieszka A Bieganowska Katarzyna K Ciara Elżbieta E Piekutowska-Abramczuk Dorota D Śpiewak Mateusz M Miśko Jolanta J Marczak Magdalena M Brzezińska-Rajszys Grażyna G

Journal of clinical medicine 20210208 4

<h4>Introduction</h4>The most efficient risk stratification algorithms are expected to deliver robust and indefectible identification of high-risk children with hypertrophic cardiomyopathy (HCM). Here we compare algorithms for risk stratification in primary prevention in HCM children and investigate whether novel indices of biatrial performance improve these algorithms.<h4>Methods and results</h4>The endpoints were defined as sudden cardiac death, resuscitated cardiac arrest, or appropriate impl ...[more]

PMID: 33567718

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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:BackgroundAngina is common in hypertrophic cardiomyopathy (HCM) and is associated with abnormal myocardial perfusion. Wave intensity analysis improves the understanding of the mechanics of myocardial ischemia.ObjectivesWave intensity analysis was used to describe the mechanisms underlying perfusion abnormalities in patients with HCM.MethodsSimultaneous pressure and flow were measured in the proximal left anterior descending artery in 33 patients with HCM and 20 control patients at rest and during hyperemia, allowing calculation of wave intensity. Patients also underwent quantitative first-pass perfusion cardiac magnetic resonance to measure myocardial perfusion reserve.ResultsPatients with HCM had a lower coronary flow reserve than control subjects (1.9 ± 0.8 vs. 2.7 ± 0.9; p = 0.01). Coronary hemodynamics in HCM were characterized by a very large backward compression wave during systole (38 ± 11% vs. 21 ± 6%; p < 0.001) and a proportionately smaller backward expansion wave (27% ± 8% vs. 33 ± 6%; p = 0.006) compared with control subjects. Patients with severe left ventricular outflow tract obstruction had a bisferiens pressure waveform resulting in an additional proximally originating deceleration wave during systole. The proportion of waves acting to accelerate coronary flow increased with hyperemia, and the magnitude of change was proportional to the myocardial perfusion reserve (rho = 0.53; p < 0.01).ConclusionsCoronary flow in patients with HCM is deranged. Distally, compressive deformation of intramyocardial blood vessels during systole results in an abnormally large backward compression wave, whereas proximally, severe left ventricular outflow tract obstruction is associated with an additional deceleration wave. Perfusion abnormalities in HCM are not simply a consequence of supply/demand mismatch or remodeling of the intramyocardial blood vessels; they represent a dynamic interaction with the mechanics of myocardial ischemia that may be amenable to treatment.

Dataset Information

The Indices of Cardiovascular Magnetic Resonance Derived Atrial Dynamics May Improve the Contemporary Risk Stratification Algorithms in Children with Hypertrophic Cardiomyopathy.

Introduction

Methods and results

Conclusions

Publications

The Indices of Cardiovascular Magnetic Resonance Derived Atrial Dynamics May Improve the Contemporary Risk Stratification Algorithms in Children with Hypertrophic Cardiomyopathy.

Similar Datasets

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