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Cited by 489

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Diffusion MR imaging: clinical applications.

Le Bihan, D, Turner, R, Douek, P, Patronas, N·1992·American Journal of Roentgenology

Abstract

Water self-diffusion, a recently discovered source of contrast on MR images, has already shown promise for some clinical applications. Most studies have been of the brain, essentially for technical reasons. Diffusion is useful in distinguishing the different components of brain tumors (cystic regions, edema, necrosis) from the tumor core itself. Recent studies have shown that diffusion is anisotropic in brain white matter (i.e., dependent on the fiber tract's orientation in space), offering new insights into myelin disorders. Diffusion is also dramatically altered in the minutes following ischemic injury in the cat brain, which may have tremendous impact for the diagnosis and management of hyperacute stroke. With ultrafast acquisition schemes, diffusion imaging has also been used outside the CNS, for instance, in the eye and kidney. Future applications include diffusion-localized spectroscopy and temperature imaging. This article reviews recent progress in this field and suggests potential applications.

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Metadata

Authors
Le Bihan, D., Turner, R., Douek, P., & Patronas, N.
Venue
American Journal of Roentgenology
Published
1992-09
Volume
159
Issue
3
Pages
591-599
ISSN
  • 0002-9580 (ISSN-L)
  • 0361-803X
  • 1546-3141
OpenAlex
W1999348312
Cited by
489
References
0
FWCI
7.77
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Diffusion MR imaging: clinical applications. https://app.cochat.ai/papers/10.2214/ajr.159.3.1503032
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Le Bihan, D., Turner, R., Douek, P., & Patronas, N. (1992). Diffusion MR imaging: clinical applications. American Journal of Roentgenology. https://doi.org/10.2214/ajr.159.3.1503032

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.