Evidence map›Paper›PMID 42761721›Full record

ReviewImaging neuroscience (Cambridge, Mass.)2026

40 Years of diffusion MRI in the brain: From history to emerging frontiers.

Denis Le Bihan

Abstract readReviewHistorical Article
In one paragraph

Review in Imaging neuroscience (Cambridge, Mass.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Denis Le BihanNeuroSpin, CEA, CEA-Saclay Center, Paris-Saclay University, Gif-sur-Yvette, France.ORCID https://orcid.org/0000-0002-4454-729X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diffusion MRI transformed brain imaging by making MRI sensitive not only to anatomy and spin-relaxation contrast, but also to micrometer-scale water displacements over diffusion times of a few tens of milliseconds. The resulting signal is exquisitely sensitive to tissue organization, because cell membranes, myelin, axonal packing, orientation dispersion, exchange, as well as perfusion-related incoherent fluid motion all modulate the displacement distribution sampled by diffusing water molecules. In the brain, this sensitivity proved historically decisive in three domains. First, diffusion-weighted MRI enabled the early detection of acute ischemia by revealing tissue injury before it became apparent on conventional structural imaging, thereby supporting timely treatment and improving outcomes for millions of patients worldwide. Second, the strong orientational order of white matter produces diffusion anisotropy, which can be explored through a diffusion tensor imaging (DTI) framework, ultimately leading to the reconstruction of large-scale structural pathways and connectomes in vivo, relevant to psychiatric disorders. Third, advances in gradient hardware, multi-shell acquisition, and biophysical modeling extended the field beyond the original apparent diffusion coefficient (ADC) concept, revealing tissue microstructure through time-dependent and multi-compartment diffusion behavior, with applications to brain development and myelination disorders, neurodegeneration, and neurosurgery. This article reviews the brain-centered evolution of diffusion MRI from its physical foundations to its forward-looking frontiers. Throughout, the central argument is that diffusion MRI derives its power from sensitivity to microstructure, whereas its interpretation depends critically on model assumptions and acquisition design.

Indexed as

BrainDiffusion Magnetic Resonance ImagingAnimalsHistory, 20th CenturyHistory, 21st CenturyHumansacute strokebrain biomechanicsbrain microstructureconnectomeDfMRIdiffusion MRIDTIIVIMMREtractography

Identifiers

PMID42761721
PMCPMC13588315

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.