Neurite Exchange Imaging (NEXI): a minimal model of diffusion in gray matter with inter‐compartment water exchange
Open accessAbstract
Biophysical models of diffusion in white matter have been center-stage over the past two decades and are essentially based on what is now commonly referred to as the "Standard Model" (SM) of non-exchanging anisotropic compartments with Gaussian diffusion. In this work, we focus on diffusion MRI in gray matter, which requires rethinking basic microstructure modeling blocks. In particular, at least three contributions beyond the SM need to be considered for gray matter: water exchange across the cell membrane - between neurites and the extracellular space; non-Gaussian diffusion along neuronal and glial processes - resulting from structural disorder; and signal contribution from soma. For the first contribution, we propose Neurite Exchange Imaging (NEXI) as an extension of the SM of diffusion, which builds on the anisotropic Kärger model of two exchanging compartments. Using datasets acquired at multiple diffusion weightings (b) and diffusion times (t) in the rat brain in vivo, we investigate the suitability of NEXI to describe the diffusion signal in the gray matter, compared to the other two possible contributions. Our results for the diffusion time window 20-45 ms show minimal diffusivity time-dependence and more pronounced kurtosis decay with time, which is well fit by the exchange model. Moreover, we observe lower signal for longer diffusion times at high b. In light of these observations, we identify exchange as the mechanism that best explains these signal signatures in both low-b and high-b regime, and thereby propose NEXI as the minimal model for gray matter microstructure mapping. We finally highlight multi-b multi-t acquisition protocols as being best suited to estimate NEXI model parameters reliably. Using this approach, we estimate the inter-compartment water exchange time to be 15 - 60 ms in the rat cortex and hippocampus in vivo, which is of the same order or shorter than the diffusion time in typical diffusion MRI acquisitions. This suggests water exchange as an essential component for interpreting diffusion MRI measurements in gray matter.
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Exchange-sensitive NEXI and SMEX/SANDIX models suggest that inter-compartment water exchange and diffusion-time dependence substantially affect gray-matter diffusion signals but are not explicitly modeled by conventional SANDI.
“Although they correlate with the Allen Brain Atlas, 93 exchange‐sensitive NEXI 55 and SMEX/SANDIX 54 models suggest that inter‐compartment water exchange and diffusion‐time dependence substantially affect gray‐matter diffusion signals but are not explicitly modeled by conventional SANDI.”
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Flagged first, then by citations
Research works printed but not linked: 7
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Cited by
Sorted by citations
Diffusion time dependence, power‐law scaling, and exchange in gray matter
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“NEXI/SMEX address gray matter more directly by including inter-compartment exchange in a minimal model tailored to such tissue ( Jelescu et al., 2022; Olesen et al., 2022).”
- Authors
- Jelescu, I. O., de Skowronski, A., Geffroy, F., Palombo, M., & Novikov, D. S.
- Affiliations
- Centre Hospitalier Universitaire Vaudois (CH)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- University College London (GB)
- New York University (US)
- Corresponding author
- Jelescu, Ileana O.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2022-08
- Volume
- 256
- Pages
- 119277
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC10363376
- OpenAlex
- W3193827989
- Cited by
- 177
- References
- 103
- Citations by year
- 2026: 34 · 2025: 53 · 2024: 49 · 2023: 26 · 2022: 15
- FWCI
- 20.33
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- SERVAL (Université de Lausanne) (publishedVersion, cc-by-nc-nd)
- ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
- PubMed Central (acceptedVersion, cc-by-nc-nd)
- arXiv (Cornell University) (submittedVersion)
- IRIS (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- arXiv (Cornell University)
- Funders
- Université de Lausanne
- Center for Advanced Imaging Innovation and Research (CAI 2 R)
- Centre d'Imagerie BioMédicale
- École Polytechnique Fédérale de Lausanne
- National Institutes of Health
- Centre Hospitalier Universitaire Vaudois
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (PCEFP2_194260)
- National Institute of Neurological Disorders and Stroke (R01 NS088040)
- Hôpitaux Universitaires de Genève
- Université de Genève
- UK Research and Innovation (MR/T020296/2)
- National Institute of Biomedical Imaging and Bioengineering (P41 EB017183)
- 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
- non-Gaussian diffusion, gray matter microstructure, rat cortex, rat hippocampus
- MeSH terms
- Animals, Brain, Humans, Water, Neurites, Diffusion Magnetic Resonance Imaging, Rats, White Matter, Gray Matter
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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