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Magnetic Resonance in Medicine
Article . 2024 . Peer-reviewed
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PubMed Central
Other literature type . 2024
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Serveur académique lausannois
Article . 2025
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High on sparsity: Interbin compensation of cardiac motion for improved assessment of left‐ventricular function using 5D whole‐heart MRI

Authors: Jérôme Yerly; Christopher W. Roy; Bastien Milani; Katerina Eyre; Mozedin Javad Raifee; Matthias Stuber;

High on sparsity: Interbin compensation of cardiac motion for improved assessment of left‐ventricular function using 5D whole‐heart MRI

Abstract

AbstractPurposeCardiac magnetic resonance is the gold standard for evaluating left‐ventricular ejection fraction (LVEF). Standard protocols, however, can be inefficient, facing challenges due to significant operator and patient involvement. Although the free‐running framework (FRF) addresses these challenges, the potential of the extensive data it collects remains underutilized. Therefore, we propose to leverage the large amount of data collected by incorporating interbin cardiac motion compensation into FRF (FRF‐MC) to improve both image quality and LVEF measurement accuracy, while reducing the sensitivity to user‐defined regularization parameters.MethodsFRF‐MC consists of several steps: data acquisition, self‐gating signal extraction, deformation field estimations, and motion‐resolved reconstruction with interbin cardiac motion compensation. FRF‐MC was compared with the original 5D‐FRF method using LVEF and several image‐quality metrics. The cardiac regularization weight () was optimized for both methods by maximizing image quality without compromising LVEF measurement accuracy. Evaluations were performed in numerical simulations and in 9 healthy participants. In vivo images were assessed by blinded expert reviewers and compared with reference standard 2D‐cine images.ResultsBoth in silico and in vivo results revealed that FRF‐MC outperformed FRF in terms of image quality and LVEF accuracy. FRF‐MC reduced temporal blurring, preserving detailed anatomy even at higher cardiac regularization weights, and led to more accurate LVEF measurements. Optimized produced accurate LVEF for both methods compared with the 2D‐cine reference (FRF‐MC: 0.59% [−7.2%, 6.0%], p = 0.47; FRF: 0.86% [−8.5%, 6.7%], p = 0.36), but FRF‐MC resulted in superior image quality (FRF‐MC: 2.89 ± 0.58, FRF: 2.11 ± 0.47; p < 10−3).ConclusionIncorporating interbin cardiac motion compensation significantly improved image quality, supported higher cardiac regularization weights without compromising LVEF measurement accuracy, and reduced sensitivity to user‐defined regularization parameters.

Keywords

Male, Adult, Humans; Ventricular Function, Left/physiology; Heart/diagnostic imaging; Male; Algorithms; Magnetic Resonance Imaging/methods; Adult; Image Processing, Computer-Assisted/methods; Motion; Female; Stroke Volume/physiology; Computer Simulation; Reproducibility of Results; Image Interpretation, Computer-Assisted/methods; Heart Ventricles/diagnostic imaging; Healthy Volunteers; 3D radial trajectory; 5D whole‐heart MRI; accuracy; cardiac function; compressed sensing; ejection fraction; free‐running; left ventricle ejection fraction; motion compensation; motion fields; precision; radial MRI; self‐gating, Heart Ventricles, Reproducibility of Results, Heart, Stroke Volume, Imaging Methodology, Magnetic Resonance Imaging, Ventricular Function, Left, Healthy Volunteers, Motion, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, Humans, Female, Computer Simulation, Algorithms

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
Green
hybrid