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Updated: Jun 6, 2026
Echocardiographic Assessment of Cardiac Anatomy and Function in Adult Rats
Published on: December 13, 2019
Automated left ventricular diastolic function evaluation from phase-contrast cardiovascular magnetic resonance and
Emilie Bollache1, Alban Redheuil, Stéphanie Clément-Guinaudeau
1INSERM U678/UPMC Université Paris 6, Paris, France. emilie.bollache@imed.jussieu.fr
Insights
This study developed an automated method using phase-contrast cardiovascular magnetic resonance (PC-CMR) to assess diastolic dysfunction. The technique reliably measures diastolic parameters, aiding in early heart failure detection.
Area of Science:
- Cardiovascular Imaging
- Medical Physics
- Diagnostic Technology
Background:
- Early detection of diastolic dysfunction is critical for managing incipient heart failure.
- Current evaluation using phase-contrast (PC) cardiovascular magnetic resonance (CMR) is limited by manual post-processing.
- Automating parameter estimation from PC-CMR data is needed for clinical routine.
Purpose of the Study:
- To develop a robust automated process for estimating diastolic parameters from PC-CMR data.
- To assess the consistency of these parameters against echocardiography.
- To evaluate the ability of these parameters to characterize left ventricular (LV) diastolic dysfunction.
Main Methods:
- Studied 35 controls and 18 patients with severe aortic valve stenosis.
- Utilized custom software for semi-automated extraction of diastolic parameters from PC-CMR.
- Assessed inter-operator reproducibility of flow pattern segmentation and functional parameters.
Main Results:
- High inter-operator reproducibility for flow pattern segmentation (99.7 ± 1.6%) and functional parameters (<1.96 ± 2.95%).
- Significant differences in diastolic parameters between patients and controls (p < 0.0002).
- PC-CMR parameters showed good correlation with echocardiography (r > 0.71) and accurately differentiated patients from controls (accuracy > 0.85).
Conclusions:
- A fast, reproducible technique for PC-CMR data analysis was developed.
- The technique reliably extracts velocity and flow rate-related diastolic parameters.
- This automated method enhances CMR's utility in evaluating and managing diastolic dysfunction.
Background:
Early 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.
Results:
We 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.
Conclusions:
A 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.
