Denis Le Bihan
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.