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Evaluation of non‐Gaussian diffusion in cardiac MRI
Author(s) -
McClymont Darryl,
Teh Irvin,
Carruth Eric,
Omens Jeffrey,
McCulloch Andrew,
Whittington Hannah J.,
Kohl Peter,
Grau Vicente,
Schneider Jürgen E.
Publication year - 2017
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26466
Subject(s) - kurtosis , diffusion mri , gaussian , akaike information criterion , diffusion , magnetic resonance imaging , gaussian network model , nuclear magnetic resonance , medicine , physics , mathematics , statistics , radiology , quantum mechanics , thermodynamics
Purpose The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non‐Gaussian modeling. The aim of this study was to investigate non‐Gaussian diffusion in healthy and hypertrophic hearts. Methods Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion‐weighted images were acquired at b‐values up to 10,000 s/mm 2 . Models of diffusion were fit to the data and ranked based on the Akaike information criterion. Results The diffusion tensor was ranked best at b‐values up to 2000 s/mm 2 but reflected the signal poorly in the high b‐value regime, in which the best model was a non‐Gaussian “beta distribution” model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet‐normal directions. Conclusion Non‐Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174–1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine.