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In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI

Johnson, Jessica T.E. ; Irfanoglu, M. Okan ; Manninen, Eppu ; Ross, Thomas J. ; Yang, Yihong ; Laun, Frederik B. ; Martin, Jan LU ; Topgaard, Daniel LU and Benjamini, Dan LU (2024) In Human Brain Mapping 45(7).
Abstract

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, (Formula presented.), in addition to the diffusion tensor, (Formula presented.), and relaxation, (Formula presented.), (Formula presented.),... (More)

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, (Formula presented.), in addition to the diffusion tensor, (Formula presented.), and relaxation, (Formula presented.), (Formula presented.), correlations. A (Formula presented.) clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their (Formula presented.) distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
denoising, diffusion tensor distribution, diffusion time dependency, diffusion-relaxation, human brain
in
Human Brain Mapping
volume
45
issue
7
article number
e26697
publisher
Wiley-Blackwell
external identifiers
  • scopus:85192813944
  • pmid:38726888
ISSN
1065-9471
DOI
10.1002/hbm.26697
language
English
LU publication?
yes
id
ce69bb6a-2c46-4f43-afc3-54167e9c1c06
date added to LUP
2024-05-23 11:37:25
date last changed
2024-06-06 12:35:15
@article{ce69bb6a-2c46-4f43-afc3-54167e9c1c06,
  abstract     = {{<p>Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, (Formula presented.), in addition to the diffusion tensor, (Formula presented.), and relaxation, (Formula presented.), (Formula presented.), correlations. A (Formula presented.) clinical imaging protocol was then introduced, with limited brain coverage and 3 mm<sup>3</sup> voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm<sup>3</sup> voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their (Formula presented.) distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.</p>}},
  author       = {{Johnson, Jessica T.E. and Irfanoglu, M. Okan and Manninen, Eppu and Ross, Thomas J. and Yang, Yihong and Laun, Frederik B. and Martin, Jan and Topgaard, Daniel and Benjamini, Dan}},
  issn         = {{1065-9471}},
  keywords     = {{denoising; diffusion tensor distribution; diffusion time dependency; diffusion-relaxation; human brain}},
  language     = {{eng}},
  number       = {{7}},
  publisher    = {{Wiley-Blackwell}},
  series       = {{Human Brain Mapping}},
  title        = {{In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI}},
  url          = {{http://dx.doi.org/10.1002/hbm.26697}},
  doi          = {{10.1002/hbm.26697}},
  volume       = {{45}},
  year         = {{2024}},
}