Double pulsed field gradient diffusion MRI to assess skeletal muscle microstructure
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Magnetic_Resonance_in_Med_2023 ...
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Affiliation
Department of Biomedical Engineering, University of ArizonaDepartment of Medical Imaging, University of Arizona
Issue Date
2023-07-01Keywords
diffusion anisotropydiffusion tensor imaging (DTI)
diffusion tensor subspace imaging (DiTSI)
double pulsed field gradient
skeletal muscle
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John Wiley and Sons IncCitation
Berry DB, Galinsky VL, Hutchinson EB, Galons JP, Ward SR, Frank LR. Double pulsed field gradient diffusion MRI to assess skeletal muscle microstructure. Magn Reson Med. 2023; 90(4): 1582-1593. doi: 10.1002/mrm.29751Journal
Magnetic Resonance in MedicineRights
© 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Purpose: Preliminary study to determine whether double pulsed field gradient (PFG) diffusion MRI is sensitive to key features of muscle microstructure related to function. Methods: The restricted diffusion profile of molecules in models of muscle microstructure derived from histology were systematically simulated using a numerical simulation approach. Diffusion tensor subspace imaging analysis of the diffusion signal was performed, and spherical anisotropy (SA) was calculated for each model. Linear regression was used to determine the predictive capacity of SA on the fiber area, fiber diameter, and surface area to volume ratio of the models. Additionally, a rat model of muscle hypertrophy was scanned using a single PFG and a double PFG pulse sequence, and the restricted diffusion measurements were compared with histological measurements of microstructure. Results: Excellent agreement between SA and muscle fiber area (r2 = 0.71; p < 0.0001), fiber diameter (r2 = 0.83; p < 0.0001), and surface area to volume ratio (r2 = 0.97; p < 0.0001) in simulated models was found. In a scanned rat leg, the distribution of these microstructural features measured from histology was broad and demonstrated that there is a wide variance in the microstructural features observed, similar to the SA distributions. However, the distribution of fractional anisotropy measurements in the same tissue was narrow. Conclusions: This study demonstrates that SA—a scalar value from diffusion tensor subspace imaging analysis—is highly sensitive to muscle microstructural features predictive of function. Furthermore, these techniques and analysis tools can be translated to real experiments in skeletal muscle. The increased dynamic range of SA compared with fractional anisotropy in the same tissue suggests increased sensitivity to detecting changes in tissue microstructure. © 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.Note
Open access articleISSN
0740-3194PubMed ID
37392410Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1002/mrm.29751
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Except where otherwise noted, this item's license is described as © 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License.
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