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Updated: Mar 27, 2026

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging
Published on: May 24, 2021
Computer-based assessment of ventricular mechanical synchrony from magnetic resonance imaging
Insights
This study developed an automated method using cardiac MRI to assess ventricular synchrony in heart failure patients. This noninvasive technique may improve prediction of response to cardiac resynchronization therapy (CRT).
Area of Science:
- Cardiovascular Imaging and Diagnostics
- Heart Failure Management
- Biomedical Engineering
Background:
- Cardiac resynchronization therapy (CRT) significantly benefits patients with advanced heart failure (HF), improving clinical status in approximately 70%.
- Accurate prediction of CRT response is crucial for optimizing patient treatment and outcomes.
- Magnetic Resonance Imaging (MRI) is the gold standard for assessing cardiac structure and function.
Purpose of the Study:
- To develop an automated method for assessing left ventricular mechanical synchrony using cardiac MRI.
- To explore the potential of this novel method for predicting ventricular dyssynchrony in heart failure.
Main Methods:
- Prospective recruitment of 26 healthy volunteers (age 24-73) for standard MRI scans.
- Automated processing of MRI images to track atrioventricular junction (AVJ) motions.
- Derivation of myocardial velocities (Sm1, Sm2, Em, Am) and their timing (TSm1, TSm2, TEm, TAm).
- Calculation of ventricular synchrony indices (e.g., TSm1-SD-6) and correlation with age.
Main Results:
- The automated MRI analysis method has a computational time of approximately 5 minutes per dataset.
- No significant differences were found in the time to peak velocities across 6 segments (One-way ANOVA).
- No significant correlation was observed between TSm2-SD-6, TAm-SD-6, and age.
- A fair positive correlation was found between TSm1-SD-6, TEm-SD-6, and age.
Conclusions:
- Noninvasive ventricular synchrony assessment derived from standard MRI images is feasible.
- This novel method offers a potential tool for assessing ventricular mechanical dyssynchrony in heart failure patients.
- Further validation is needed to establish its clinical utility in predicting CRT response.
Abstract:
Cardiac resynchronization therapy (CRT) has revolutionized the care of a substantial portion of patients with advanced heart failure (HF). From current guideline (NYHA III or IV heart failure, left ventricular ejection fraction ≤35% and ECG QRS duration ≥ 120 ms), CRT improves clinical status in about 70% of those treated. Ideally, the ability to accurately predict likelihood of response will enhance the quality of treatment. This study aims to develop an automated method to assess left ventricular mechanical synchrony from magnetic resonance imaging (MRI), which has been considered as gold standard cardiac imaging for ventricular structure and function assessment. 26 healthy volunteers (age ranges from 24 years to 73 years) were prospectively recruited and underwent standard MRI scans. MRI images (e.g. 2-chamber, 3-chamber and 4-chamber views) were processed and atrioventricular junction (AVJ) motions were auto-tracked during cardiac cycle. The myocardial velocities Sm1 and Sm2 at systolic phase; Em and Am at early and late mitral filing phase, were derived respectively. The time to these measures (e.g., TSm1, TSm2, TEm and TAm) were determined and ventricular synchrony indices TSm1-SD-6, TSm2-SD-6, TEm-SD-6 and TAm-SD-6 (standard deviations of TSm1, TSm2, TEm and TAm for 6 AVJ points) were assessed and correlated with age. The computational time per dataset is approximately 5 minutes. One-way ANOVA analysis found that there were no significant differences in time to peak velocities in 6 segments. Second, linear regression analysis found that there were no significant correlation between TSm2-SD-6 and TAm-SD-6 with age, and fair positive correlation between TSm1-SD-6 and TEm-SD-6 with age. In this prospective study, noninvasive ventricular synchrony derived from typically acquired MRI images offers a novel method that may enable ventricular mechanical dyssynchrony assessment in heart failure.
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