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Updated: Mar 31, 2026
Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging
Published on: May 24, 2021
Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets
Sandro Queirós1, Daniel Barbosa2, Jan Engvall3
1Lab on Cardiovascular Imaging and Dynamics, KU Leuven, Leuven, Belgium ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães Portugal Algoritmi Center, School of Engineering, University of Minho, Guimarães, Portugal sandroqueiros@ecsaude.uminho.pt.
Insights
A new automated framework accurately quantifies left ventricular function from cardiac MRI (CMR) images. This method is significantly faster than manual analysis, improving efficiency in clinical cardiology.
Area of Science:
- Cardiovascular Imaging
- Medical Image Analysis
- Computational Cardiology
Background:
- Quantitative analysis of cine cardiac magnetic resonance (CMR) images for left ventricular morphology and function is standard in cardiology.
- Current manual analysis is time-consuming and prone to observer variability.
Purpose of the Study:
- To validate a novel framework for automatic quantification of left ventricular global function in a clinical setting.
- To assess the feasibility, accuracy, and time efficiency of this automated approach.
Main Methods:
- Automated analysis of 318 cine CMR studies from the DOPPLER-CIP trial.
- Comparison of automated results with manual measurements and intra-/inter-observer variability.
- Evaluation of time efficiency for automated versus manual contouring.
Main Results:
- The automated analysis was feasible in 95% of cases (302/318).
- Good agreement was observed between automated and manual measurements for key parameters like end-diastolic volume, end-systolic volume, and ejection fraction.
- Automated analysis was approximately 150 times faster than manual contouring (5.61s vs. 14 min).
Conclusions:
- The proposed automatic framework offers a fast, robust, and accurate method for quantifying left ventricular indices.
- This automated approach is suitable for 'real-world' cine CMR images in clinical practice.
Aims:
Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.
Methods And Results:
Analyses of 318 CMR studies, acquired at the enrolment of patients in a multi-centre imaging trial (DOPPLER-CIP), were performed automatically, as well as manually. For comparative purposes, intra- and inter-observer variability was also assessed in a subset of patients. The extracted morphological and functional parameters were compared between both analyses, and time efficiency was evaluated. The automatic analysis was feasible in 95% of the cases (302/318) and showed a good agreement with manually derived reference measurements, with small biases and narrow limits of agreement particularly for end-diastolic volume (-4.08 ± 8.98 mL), end-systolic volume (1.18 ± 9.74 mL), and ejection fraction (-1.53 ± 4.93%). These results were comparable with the agreement between two independent observers. A complete automatic analysis took 5.61 ± 1.22 s, which is nearly 150 times faster than manual contouring (14 ± 2 min, P < 0.05).
Conclusion:
The proposed automatic framework provides a fast, robust, and accurate quantification of relevant left ventricular clinical indices in 'real-world' cine CMR images.
