Dataset Information

Left ventricular non-compaction cardiomyopathy in children: characterisation of clinical status using tissue Doppler-derived indices of left ventricular diastolic relaxation.

ABSTRACT:

Background

Left ventricular non-compaction (LVNC) may manifest an undulating phenotype ranging from dilated to hypertrophic appearance. It is unknown whether tissue Doppler (TD) velocities can predict adverse clinical outcomes including death and need for transplantation in children with LVNC.

Methods and results

56 children (median age 4.5 years, median follow-up 26 months) with LVNC evaluated at one hospital from January 1999 to May 2004 were compared with 56 age/sex-matched controls. Children with LVNC had significantly decreased early diastolic TD velocities (Ea) at the lateral mitral (11.0 vs 17.0 cm/s) and septal (8.9 vs 11.0 cm/s) annuli compared with normal controls (p<0.001 for each comparison). Using receiver operator characteristic curves, the lateral mitral Ea velocity proved the most sensitive and specific predictor for meeting the primary end point (PEP) at 1 year after diagnosis (area under the curve = 0.888, SE = 0.048, 95% CI 0.775 to 0.956). A lateral mitral Ea cut-off velocity of 7.8 cm/s had a sensitivity of 87% and a specificity of 79% for the PEP. Freedom from death or transplantation was 85% at 1 year and 77% at 2 years.

Conclusions

TD velocities are significantly reduced in patients with LVNC compared with normal controls. Reduced lateral mitral Ea velocity helps predict children with LVNC who are at risk of adverse clinical outcomes including death and need for cardiac transplantation.

SUBMITTER: McMahon CJ

PROVIDER: S-EPMC1955174 | biostudies-literature | 2007 Jun

REPOSITORIES: biostudies-literature

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Publications

Left ventricular non-compaction cardiomyopathy in children: characterisation of clinical status using tissue Doppler-derived indices of left ventricular diastolic relaxation.

McMahon Colin J CJ Pignatelli Ricardo H RH Nagueh Sherif F SF Lee Vei-Vei VV Vaughn William W Valdes Santiago O SO Kovalchin John P JP Jefferies John L JL Dreyer William J WJ Denfield Susan W SW Clunie Sarah S Towbin Jeffrey A JA Eidem Benjamin W BW

Heart (British Cardiac Society) 20061129 6

<h4>Background</h4>Left ventricular non-compaction (LVNC) may manifest an undulating phenotype ranging from dilated to hypertrophic appearance. It is unknown whether tissue Doppler (TD) velocities can predict adverse clinical outcomes including death and need for transplantation in children with LVNC.<h4>Methods and results</h4>56 children (median age 4.5 years, median follow-up 26 months) with LVNC evaluated at one hospital from January 1999 to May 2004 were compared with 56 age/sex-matched con ...[more]

PMID: 17135224

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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:BackgroundEarly detection of diastolic dysfunction is crucial for patients with incipient heart failure. Although this evaluation could be performed from phase-contrast (PC) cardiovascular magnetic resonance (CMR) data, its usefulness in clinical routine is not yet established, mainly because the interpretation of such data remains mostly based on manual post-processing. Accordingly, our goal was to develop a robust process to automatically estimate velocity and flow rate-related diastolic parameters from PC-CMR data and to test the consistency of these parameters against echocardiography as well as their ability to characterize left ventricular (LV) diastolic dysfunction.ResultsWe studied 35 controls and 18 patients with severe aortic valve stenosis and preserved LV ejection fraction who had PC-CMR and Doppler echocardiography exams on the same day. PC-CMR mitral flow and myocardial velocity data were analyzed using custom software for semi-automated extraction of diastolic parameters. Inter-operator reproducibility of flow pattern segmentation and functional parameters was assessed on a sub-group of 30 subjects. The mean percentage of overlap between the transmitral flow segmentations performed by two independent operators was 99.7 ± 1.6%, resulting in a small variability (<1.96 ± 2.95%) in functional parameter measurement. For maximal myocardial longitudinal velocities, the inter-operator variability was 4.25 ± 5.89%. The MR diastolic parameters varied significantly in patients as opposed to controls (p < 0.0002). Both velocity and flow rate diastolic parameters were consistent with echocardiographic values (r > 0.71) and receiver operating characteristic (ROC) analysis revealed their ability to separate patients from controls, with sensitivity > 0.80, specificity > 0.80 and accuracy > 0.85. Slight superiority in terms of correlation with echocardiography (r = 0.81) and accuracy to detect LV abnormalities (sensitivity > 0.83, specificity > 0.91 and accuracy > 0.89) was found for the PC-CMR flow-rate related parameters.ConclusionsA fast and reproducible technique for flow and myocardial PC-CMR data analysis was successfully used on controls and patients to extract consistent velocity-related diastolic parameters, as well as flow rate-related parameters. This technique provides a valuable addition to established CMR tools in the evaluation and the management of patients with diastolic dysfunction.

Dataset Information

Left ventricular non-compaction cardiomyopathy in children: characterisation of clinical status using tissue Doppler-derived indices of left ventricular diastolic relaxation.

Background

Methods and results

Conclusions

Publications

Left ventricular non-compaction cardiomyopathy in children: characterisation of clinical status using tissue Doppler-derived indices of left ventricular diastolic relaxation.

Similar Datasets

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