ArticleNMR in biomedicine2025
Decontrasted Image Registration Improves Quantification of Extracellular Volume and Fractional Myocardial Blood Volume.
Article in NMR in biomedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Accurate quantification of extracellular volume (ECV) and fractional myocardial blood volume (fMBV) in cardiac magnetic resonance (CMR) relies on precise alignment between precontrast and postcontrast images. Variable image contrast often undermines conventional motion correction, causing misalignment due to respiration or cardiac motion. Herein, we present a registration approach that accounts for varying image contrast levels and cardiac motion to achieve more precise and high-quality quantitative cardiac mapping. Patients with suspected myocardial diseases underwent cardiac MRI with Gadavist (0.1 mmol/kg, n = 11) and ferumoxytol (4.0 mg/kg cumulative, n = 9) enhancement for ECV and fMBV measurements, respectively. T1 maps were generated using the MOLLI sequence. To remove contrast variations across different inversion times and contrast doses, precontrast and postcontrast MOLLI images were grouped and processed using correlation-weighted representations based on the myocardium and blood pool signals. Groupwise registration is performed based on the maximization of mutual information. The image registration accuracy and mapping precision of the proposed method were assessed relative to those of conventional methods. ResultsCompared with the conventional groupwise registration approach, the proposed decontrasted approach showed superior alignment between images of different contrasts, as evidenced by the higher Dice scores (mean 0.77 vs. 0.69, p < 0.001). It also eliminated artifacts commonly observed owing to image misalignment (all 11 cases showed improvement). Improved myocardial mapping precision was observed for both ECV (median coefficient of variation, 0.14 vs. 0.27; p < 0.001) and fMBV (median coefficient of variation, 0.59 vs. 0.71; p < 0.001). It also reduced individual myocardial segmental variations in the ECV (5.8 to 3.58, p < 0.001) and fMBV maps (9.86 to 7.93, p < 0.001). Overall, decontrasted image registration improves the precision of contrast-enhanced myocardial parametric mapping by reducing the misalignment between multicontrast images. This framework may be extended to other postprocessing tasks in cardiac MRI that involve variable image contrasts.
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