Quantification of Tissue Microstructure Using Tensor-Valued Diffusion Encoding: Brain and Body
(2022) In Frontiers in Physics 10.- Abstract
- Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive technique to probe tissue microstructure. Conventional Stejskal–Tanner diffusion encoding (i.e., encoding along a single axis), is unable to disentangle different microstructural features within a voxel; If a voxel contains microcompartments that vary in more than one attribute (e.g., size, shape, orientation), it can be difficult to quantify one of those attributes in isolation using Stejskal–Tanner diffusion encoding. Multidimensional diffusion encoding, in which the water diffusion is encoded along multiple directions in q-space (characterized by the so-called “b-tensor”) has been proposed previously to solve this problem. The shape of the b-tensor can be used as... (More)
- Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive technique to probe tissue microstructure. Conventional Stejskal–Tanner diffusion encoding (i.e., encoding along a single axis), is unable to disentangle different microstructural features within a voxel; If a voxel contains microcompartments that vary in more than one attribute (e.g., size, shape, orientation), it can be difficult to quantify one of those attributes in isolation using Stejskal–Tanner diffusion encoding. Multidimensional diffusion encoding, in which the water diffusion is encoded along multiple directions in q-space (characterized by the so-called “b-tensor”) has been proposed previously to solve this problem. The shape of the b-tensor can be used as an additional encoding dimension and provides sensitivity to microscopic anisotropy. This has been applied in multiple organs, including brain, heart, breast, kidney and prostate. In this work, we discuss the advantages of using b-tensor encoding in different organs. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/b0bdebc7-838c-4ce6-b811-bcf0fbfa7fd7
- author
- Afzali, Maryam ; Mueller, Lars ; Szczepankiewicz, Filip LU ; Jones, Derek K. and Schneider, Jürgen E.
- organization
- publishing date
- 2022
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Frontiers in Physics
- volume
- 10
- article number
- 809133
- publisher
- Frontiers Media S. A.
- external identifiers
-
- scopus:85125219384
- ISSN
- 2296-424X
- DOI
- 10.3389/fphy.2022.809133
- language
- English
- LU publication?
- yes
- id
- b0bdebc7-838c-4ce6-b811-bcf0fbfa7fd7
- alternative location
- https://www.frontiersin.org/articles/10.3389/fphy.2022.809133/full
- date added to LUP
- 2022-04-04 12:47:56
- date last changed
- 2023-09-18 11:14:06
@article{b0bdebc7-838c-4ce6-b811-bcf0fbfa7fd7, abstract = {{Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive technique to probe tissue microstructure. Conventional Stejskal–Tanner diffusion encoding (i.e., encoding along a single axis), is unable to disentangle different microstructural features within a voxel; If a voxel contains microcompartments that vary in more than one attribute (e.g., size, shape, orientation), it can be difficult to quantify one of those attributes in isolation using Stejskal–Tanner diffusion encoding. Multidimensional diffusion encoding, in which the water diffusion is encoded along multiple directions in q-space (characterized by the so-called “b-tensor”) has been proposed previously to solve this problem. The shape of the b-tensor can be used as an additional encoding dimension and provides sensitivity to microscopic anisotropy. This has been applied in multiple organs, including brain, heart, breast, kidney and prostate. In this work, we discuss the advantages of using b-tensor encoding in different organs.}}, author = {{Afzali, Maryam and Mueller, Lars and Szczepankiewicz, Filip and Jones, Derek K. and Schneider, Jürgen E.}}, issn = {{2296-424X}}, language = {{eng}}, publisher = {{Frontiers Media S. A.}}, series = {{Frontiers in Physics}}, title = {{Quantification of Tissue Microstructure Using Tensor-Valued Diffusion Encoding: Brain and Body}}, url = {{http://dx.doi.org/10.3389/fphy.2022.809133}}, doi = {{10.3389/fphy.2022.809133}}, volume = {{10}}, year = {{2022}}, }