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In vivo diffusion MRI of the human heart using a 300 mT/m gradient system

Maryam Afzali, Lars Mueller, Sam Coveney, Fabrizio Fasano, John R. Evans, Maria Engel, Filip Szczepankiewicz, Irvin Teh, Erica Dall’Armellina, Derek K. Jones, Jürgen E. Schneider

2024Magnetic Resonance in Medicine22 citationsDOIOpen Access PDF

Abstract

Abstract Purpose This work reports for the first time on the implementation and application of cardiac diffusion‐weighted MRI on a Connectom MR scanner with a maximum gradient strength of 300 mT/m. It evaluates the benefits of the increased gradient performance for the investigation of the myocardial microstructure. Methods Cardiac diffusion‐weighted imaging (DWI) experiments were performed on 10 healthy volunteers using a spin‐echo sequence with up to second‐ and third‐order motion compensation ( and ) and , and 1000 (twice the commonly used on clinical scanners). Mean diffusivity (MD), fractional anisotropy (FA), helix angle (HA), and secondary eigenvector angle (E2A) were calculated for b = [100, 450] and b = [100, 1000] for both and . Results The MD values with are slightly higher than with with for and for . A reduction in MD is observed by increasing the from 450 to 1000 ( for and for ). The difference between FA, E2A, and HA was not significant in different schemes (). Conclusion This work demonstrates cardiac DWI in vivo with higher b ‐value and higher order of motion compensated diffusion gradient waveforms than is commonly used. Increasing the motion compensation order from to and the maximum b ‐value from 450 to 1000 affected the MD values but FA and the angular metrics (HA and E2A) remained unchanged. Our work paves the way for cardiac DWI on the next‐generation MR scanners with high‐performance gradient systems.

Topics & Concepts

In vivoNuclear magnetic resonanceDiffusionDiffusion MRIHuman heartMagnetic resonance imagingBiomedical engineeringMedicinePhysicsRadiologyCardiologyBiologyThermodynamicsBiotechnologyAdvanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and ApplicationsMRI in cancer diagnosis
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