In vivo demonstration of microscopic anisotropy in the human kidney using multidimensional diffusion MRI
(2019) In Magnetic Resonance in Medicine 82(6). p.2160-2168- Abstract
Purpose: To demonstrate the feasibility of multidimensional diffusion MRI to probe and quantify microscopic fractional anisotropy (µFA) in human kidneys in vivo. Methods: Linear tensor encoded (LTE) and spherical tensor encoded (STE) renal diffusion MRI scans were performed in 10 healthy volunteers. Respiratory triggering and image registration were used to minimize motion artefacts during the acquisition. Kidney cortex–medulla were semi-automatically segmented based on fractional anisotropy (FA) values. A model-free analysis of LTE and STE signal dependence on b-value in the renal cortex and medulla was performed. Subsequently, µFA was estimated using a single-shell approach. Finally, a comparison of conventional FA and µFA is shown.... (More)
Purpose: To demonstrate the feasibility of multidimensional diffusion MRI to probe and quantify microscopic fractional anisotropy (µFA) in human kidneys in vivo. Methods: Linear tensor encoded (LTE) and spherical tensor encoded (STE) renal diffusion MRI scans were performed in 10 healthy volunteers. Respiratory triggering and image registration were used to minimize motion artefacts during the acquisition. Kidney cortex–medulla were semi-automatically segmented based on fractional anisotropy (FA) values. A model-free analysis of LTE and STE signal dependence on b-value in the renal cortex and medulla was performed. Subsequently, µFA was estimated using a single-shell approach. Finally, a comparison of conventional FA and µFA is shown. Results: The hallmark effect of µFA (divergence of LTE and STE signal with increasing b-value) was observed in all subjects. A statistically significant difference between LTE and STE signal was found in the cortex and medulla, starting from b = 750 s/mm2 and b = 500 s/mm2, respectively. This difference was maximal at the highest b-value sampled (b = 1000 s/mm2) which suggests that relatively high b-values are required for µFA mapping in the kidney compared to conventional FA. Cortical and medullary µFA were, respectively, 0.53 ± 0.09 and 0.65 ± 0.05, both respectively higher than conventional FA (0.19 ± 0.02 and 0.40 ± 0.02). Conclusion: The feasibility of combining LTE and STE diffusion MRI to probe and quantify µFA in human kidneys is demonstrated for the first time. By doing so, we show that novel microstructure information—not accessible by conventional diffusion encoding—can be probed by multidimensional diffusion MRI. We also identify relevant technical limitations that warrant further development of the technique for body MRI.
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- author
- Nery, Fabio ; Szczepankiewicz, Filip LU ; Kerkelä, Leevi ; Hall, Matt G. ; Kaden, Enrico ; Gordon, Isky ; Thomas, David L. and Clark, Chris A.
- organization
- publishing date
- 2019-06-26
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- diffusion, fractional anisotropy, kidney, microscopic anisotropy, spherical tensor encoding, tensor-valued diffusion encoding
- in
- Magnetic Resonance in Medicine
- volume
- 82
- issue
- 6
- pages
- 2160 - 2168
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- pmid:31243814
- scopus:85068368866
- ISSN
- 0740-3194
- DOI
- 10.1002/mrm.27869
- language
- English
- LU publication?
- yes
- id
- 68af28de-3ecf-4606-966c-6a8583c115e5
- date added to LUP
- 2019-07-19 14:11:10
- date last changed
- 2024-09-18 07:13:09
@article{68af28de-3ecf-4606-966c-6a8583c115e5, abstract = {{<p>Purpose: To demonstrate the feasibility of multidimensional diffusion MRI to probe and quantify microscopic fractional anisotropy (µFA) in human kidneys in vivo. Methods: Linear tensor encoded (LTE) and spherical tensor encoded (STE) renal diffusion MRI scans were performed in 10 healthy volunteers. Respiratory triggering and image registration were used to minimize motion artefacts during the acquisition. Kidney cortex–medulla were semi-automatically segmented based on fractional anisotropy (FA) values. A model-free analysis of LTE and STE signal dependence on b-value in the renal cortex and medulla was performed. Subsequently, µFA was estimated using a single-shell approach. Finally, a comparison of conventional FA and µFA is shown. Results: The hallmark effect of µFA (divergence of LTE and STE signal with increasing b-value) was observed in all subjects. A statistically significant difference between LTE and STE signal was found in the cortex and medulla, starting from b = 750 s/mm<sup>2</sup> and b = 500 s/mm<sup>2</sup>, respectively. This difference was maximal at the highest b-value sampled (b = 1000 s/mm<sup>2</sup>) which suggests that relatively high b-values are required for µFA mapping in the kidney compared to conventional FA. Cortical and medullary µFA were, respectively, 0.53 ± 0.09 and 0.65 ± 0.05, both respectively higher than conventional FA (0.19 ± 0.02 and 0.40 ± 0.02). Conclusion: The feasibility of combining LTE and STE diffusion MRI to probe and quantify µFA in human kidneys is demonstrated for the first time. By doing so, we show that novel microstructure information—not accessible by conventional diffusion encoding—can be probed by multidimensional diffusion MRI. We also identify relevant technical limitations that warrant further development of the technique for body MRI.</p>}}, author = {{Nery, Fabio and Szczepankiewicz, Filip and Kerkelä, Leevi and Hall, Matt G. and Kaden, Enrico and Gordon, Isky and Thomas, David L. and Clark, Chris A.}}, issn = {{0740-3194}}, keywords = {{diffusion; fractional anisotropy; kidney; microscopic anisotropy; spherical tensor encoding; tensor-valued diffusion encoding}}, language = {{eng}}, month = {{06}}, number = {{6}}, pages = {{2160--2168}}, publisher = {{John Wiley & Sons Inc.}}, series = {{Magnetic Resonance in Medicine}}, title = {{In vivo demonstration of microscopic anisotropy in the human kidney using multidimensional diffusion MRI}}, url = {{http://dx.doi.org/10.1002/mrm.27869}}, doi = {{10.1002/mrm.27869}}, volume = {{82}}, year = {{2019}}, }