Estimation of Extracellular Volume from Regularized Multi-shell Diffusion MRI
Open accessAbstract
Diffusion MRI measures micron scale displacement of water molecules, providing unique insight into microstructural tissue architecture. However, current practical image resolution is in the millimeter scale, and thus diffusivities from many tissue compartments are averaged in each voxel, reducing the sensitivity and specificity of the measurement to subtle pathologies. Recent studies have pointed out that eliminating the contribution of extracellular water increases the sensitivity of the diffusion measures to tissue architecture. Moreover, in brain imaging, estimation of the extracellular volume appears to indicate pathological processes such as atrophy, edema and neuroinflammation. Here we study the free-water method, which assumes a bi-tensor model. We add low b-value shells to a regular DTI acquisition and present methods to improve the estimation of the model parameters using the extra information. In addition, we define a Laplace-Beltrami regularization operator that further stabilizes the multi-shell estimation.
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More advanced microstructural measures include inter- and intra-cellular signal fractions derived from DKI, Free Water modeling, NODDI, SMT, or AFD.
“More advanced measures include those reflecting inter- and intra-cellular signal fractions derived from Diffusion Kurtosis Imaging (DKI) (Jensen and Helpern, 2010), Free Water modeling (Pasternak et al., 2012; 2009), Neurite Orientation Dispersion and Density Imaging (NODDI) (Zhang et al., 2012), Spherical Mean Technique (SMT) (Kaden et al., 2016), or Apparent Fiber Density (AFD) (Raffelt et al.,”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Pasternak et al., 2012
The Free-Water Model section describes separate free-water and tissue signal contributions and identifies free water as extracellular. It does not identify the tissue contribution as an intra-cellular fraction, so the citation supports the Free Water example but not that more specific characterization. (LLM, conf=0.86)
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Cites
Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review
Assaf, Y., & Pasternak, O. (2008) · Journal of Molecular Neuroscience · doi:10.1007/s12031-007-0029-0 · Cited by 1,537 · see citing works
Self-citationTwenty‐five pitfalls in the analysis of diffusion MRI data
Jones, D. K., & Cercignani, M. (2010) · NMR in Biomedicine · doi:10.1002/nbm.1543 · Cited by 827 · see citing works
How and how not to correct for CSF-contamination in diffusion MRI
Metzler-Baddeley, C., O'Sullivan, M. J., Bells, S., Pasternak, O., & Jones, D. K. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.043 · Cited by 291 · see citing works
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Research works printed but not linked: 6
- [2]Vos SB Jones DK Viergever MA Leemans A Partial volume effect as a hidden covariate in DTI analyses Neuroimage 55 4 2011 1566 76 21262366
- [4]Pasternak O Sochen N Gur Y Intrator N Assaf Y Free water elimination and mapping from diffusion MRI Magn, Reson Med 62 3 2009 19623619
- [6]Wang Y Wang Q Haldar JP Yeh FC Xie M Sun P Tu TW Trinkaus K Klein RS Cross AH Song SK Quantification of increased cellularity during inflammatory demyelination Brain 134 12 2011 3590 601 22171354 PMC3235568
- [7]Metzler-Baddeley C Jones D Belaroussi B Aggleton J O’Sullivan M Frontotemporal connections in episodic memory and aging: A diffusion MRI tractography study J Neurosci 31 37 2011 13236 13245 21917806 PMC6623273
- [10]Mulkern RV Haker SJ Maier SE On high b diffusion imaging in the human brain: ruminations and experimental insights Magn Reson Imaging 27 8 2009 1151 62 19520535 PMC2894527
- [12]Pasternak O Sochen N Basser PJ The effect of metric selection on the analysis of diffusion tensor MRI data Neuroimage 49 3 2010 2190 2204 19879947 PMC2975386
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Zhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R. E., Yeh, C.-H., Zhao, T., & O’Donnell, L. J. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2021.118870 · Cited by 302 · see citing works
“This includes tissue microstructure or biophysical models such as Neurite Orientation Dispersion and Density Imaging (NODDI) [590] and Free Water (FW) [363, 362], as well as diffusion signal representations that include the diffusion tensor [36],”
MethodWhite-matter free-water diffusion MRI in schizophrenia: A systematic review and meta-analysis
Carreira Figueiredo, I., Borgan, F., Pasternak, O., Turkheimer, F. E., & Howes, O. D. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-022-01272-x · Cited by 65 · see citing works
Self-citationGong, S., Zhang, F., Norton, I., Essayed, W. I., Unadkat, P., Rigolo, L., Pasternak, O., Rathi, Y., Hou, L., Golby, A. J., et al. (2018) · PLOS ONE · doi:10.1371/journal.pone.0197056 · Cited by 51 · see citing works
Self-citationNakaya, M., Sato, N., Matsuda, H., Maikusa, N., Shigemoto, Y., Sone, D., Yamao, T., Ogawa, M., Kimura, Y., Chiba, E., et al. (2022) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1002/trc2.12356 · Cited by 41 · see citing works
- Authors
- Pasternak, O., Shenton, M. E., & Westin, C.-F.
- Affiliations
- Brigham and Women's Hospital (US)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2012
- Volume
- 15
- Issue
- Pt 2
- Pages
- 305-312
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- PMC
- PMC4039075
- OpenAlex
- W188359927
- Cited by
- 94
- References
- 3
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 9 · 2023: 8 · 2022: 8 · 2021: 14 · 2020: 4 · 2019: 7 · 2018: 8 · 2017: 9 · 2016: 3 · 2015: 5 · 2014: 2 · 2013: 3 · 2012: 1
- FWCI
- 10.35
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Lecture notes in computer science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- National Institute of Mental Health (R01MH092862, R01MH074794)
- National Institute of Biomedical Imaging and Bioengineering (P41EB015902)
- National Center for Research Resources (P41RR013218)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › NMR spectroscopy and applications
- Keywords
- multi-shell diffusion MRI, brain microstructure, extracellular water, diffusion tensor imaging, neuroinflammation, brain atrophy, cerebral edema
- MeSH terms
- Algorithms, Body Water, Brain, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Sensitivity and Specificity, Reproducibility of Results, Diffusion Magnetic Resonance Imaging, Extracellular Fluid
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