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.

Alzheimer’s disease (AD) is usually framed as a proteinopathy and network disorder, but this view may be incomplete. We propose a mechanobiological hypothesis in which synaptic micromechanics, regional brain softening, vascular pulsatility, and glymphatic transport are parts of a coupled fluid–solid system whose failure contributes to AD progression. In this framework, early synaptic and glial mechanical fragility reduces the capacity of vulnerable circuits to maintain stable structure, efficient signaling, and waste clearance, while age-related tissue softening and impaired perivascular transport amplify amyloid and tau accumulation, network dysfunction, and cognitive decline. This framework integrates converging evidence from dendritic spine to glymphatic system biology, concordant results obtained with diffusion MRI and magnetic resonance elastography, and treats altered tissue mechanics not merely as a correlate of degeneration but as a potentially active multicomponent of disease expression. It further predicts that biomechanical alterations should be detectable before gross atrophy, should covary with glymphatic impairment, and may help explain why molecular pathology and clinical symptoms are often only partly aligned. By positioning brain mechanics as an interface between protein aggregation, synaptic dysfunction, and impaired clearance, this framework identifies testable imaging biomarkers and suggests potential early-stage intervention strategies aimed at preserving tissue resilience as well as reducing pathological protein burden.

Music, though not biologically essential for survival, engages the brain as a whole-system phenomenon. Neuroimaging studies show that music perception and performance recruit distributed networks involving auditory, motor, emotional, memory, and reward circuits, partially distinct from language systems. Musical training induces measurable structural plasticity in gray and white matter, particularly when begun early in life, though excessive repetition may lead to maladaptive changes such as focal dystonia. Music performance relies on multimodal integration and predictive coding, with mental imagery activating neural patterns similar to actual playing. Live music further enhances emotional and social neural coupling. By engaging ancient reward pathways, music demonstrates how abstract sound structures can reshape brain anatomy, synchronize networks, and evoke powerful emotional experiences.

Intravoxel incoherent motion (IVIM) MRI allows for simultaneous assessment of tissue microcirculation (perfusion) and diffusion of water. In single‐center studies, IVIM has shown great potential for diagnosis, treatment outcome prediction, and treatment monitoring for many different diseases and organs. However, heterogeneity in data acquisition protocols, pre‐processing pipelines, and post‐processing routines yields differences in reported IVIM parameters, which has constrained large‐scale deployment of IVIM. Moreover, deploying IVIM protocols and analysis typically requires technical expertise, further challenging wider use, especially for clinicians. In this consensus paper, to accelerate the deployment of IVIM, we provide recommendations and harmonize protocols for brain, breast, kidney, liver, muscle, and pancreas IVIM studies. For this goal we organized multiple questionnaires and held a dedicated workshop. To ensure a level of standardized, reproducible results, without restricting innovation, we suggest a small subset of b ‐values to always be measured and analyzed separately, and to which more extensive b ‐value sampling can be added for advanced investigations. We further introduce detailed recommendations on acquisition protocols and analysis pipelines. To increase consistency, repeatability, and reproducibility, we highly recommend that these protocols and pipelines be deployed by scientists and clinicians for IVIM studies. For advanced users who desire different protocols or analysis approaches, we suggest adding results from our suggested protocols and analysis pipeline in the supplemental part of their paper to enable retrospective studies.

Ota T, et al. Korean J Radiol. 2026 ;27:e71. https://doi.org/10.3348/kjr.2026.0242

The understanding of the human brain is one of the main scientific challenges of the twenty-first century. In the early 2000s, the French Atomic Energy Commission launched a program to conceive and build a human magnetic resonance imaging scanner operating at 11.7 T. We have now acquired human brain images in vivo at such a magnetic field. We deployed parallel transmission tools to mitigate the radiofrequency field inhomogeneity problem and tame the specific absorption rate. The safety of human imaging at such high field strength was demonstrated using physiological, vestibular, behavioral and genotoxicity measurements on the imaged volunteers. Our technology yields T₂ and T₂^*-weighted images reaching mesoscale resolutions within short acquisition times and with a high signal and contrast-to-noise ratio.

Diffusion MRI was introduced in 1985, showing how the diffusive motion of molecules, especially water, could be spatially encoded with MRI to produce images revealing the underlying structure of biologic tissues at a microscopic scale. Diffusion is one of several Intravoxel Incoherent Motions (IVIM) accessible to MRI together with blood microcirculation. Diffusion imaging first revolutionized the management of acute cerebral ischemia by allowing diagnosis at an acute stage when therapies can still work, saving the outcomes of many patients. Since then, the field of diffusion imaging has expanded to the whole body, with broad applications in both clinical and research settings, providing insights into tissue integrity, structural and functional abnormalities from the hindered diffusive movement of water molecules in tissues. Diffusion imaging is particularly used to manage many neurologic disorders and in oncology for detecting and classifying cancer lesions, as well as monitoring treatment response at an early stage. The second major impact of diffusion imaging concerns the wiring of the brain (Diffusion Tensor Imaging, DTI), allowing to obtain from the anisotropic movement of water molecules in the brain white-matter images in 3 dimensions of the brain connections making up the Connectome. DTI has opened up new avenues of clinical diagnosis and research to investigate brain diseases, neurogenesis and aging, with a rapidly extending field of application in psychiatry, revealing how mental illnesses could be seen as Connectome spacetime disorders. Adding that water diffusion is closely associated to neuronal activity, as shown from diffusion fMRI, one may consider that diffusion MRI is ideally suited to investigate both brain structure and function. This article retraces the early days and milestones of diffusion MRI which spawned over 40 years, showing how diffusion MRI emerged and expanded in the research and clinical fields, up to become a pillar of modern clinical imaging.

Objectives: Fat-signal suppression is essential for breast diffusion magnetic resonance imaging (or diffusion-weighted MRI, DWI) as the very low diffusion coefficient of fat tends to decrease absolute diffusion coefficient (ADC) values. Among several methods, the STIR (short-tau inversion recovery) method is a popular approach, but signal suppression/attenuation is not specific to fat contrary to other methods such as SPAIR (spectral adiabatic (or attenuated) inversion recovery). This article focuses on those two techniques to illustrate the importance of appropriate fat suppression in breast DWI, briefly presenting the pros and cons of both approaches. Methods and results: We show here through simulation and data acquired in a dedicated breast DWI phantom made of vials with water and various concentrations of polyvinylpyrrolidone (PVP) how ADC values obtained with STIR DWI may be biased toward tissue components with the longest T1 values: ADC values obtained with STIR fat suppression may be over/underestimated depending on the T1 and ADC profile within tissues. This bias is also illustrated in two clinical examples. Conclusion: Fat-specific methods should be preferred over STIR for fat-signal suppression in breast DWI, such as SPAIR which also provides a higher sensitivity than STIR for lesion detection. One should remain aware, however, that efficient fat-signal suppression with SPAIR requires good B0 shimming to avoid ADC underestimation from residual fat contamination. Clinical relevance statement: The spectral adiabatic (or attenuated) inversion recovery (SPAIR) method should be preferred over short-tau inversion recovery (STIR) for fat suppression in breast DWI. Key Points: Fat-signal suppression is essential for breast DWI; the SPAIR method is recommended. Short-tau inversion recovery (STIR) is not specific to fat; as a result, SNR is decreased and ADC values may be over- or underestimated. The STIR fat-suppression method must not be used after the injection of gadolinium-based contrast agents.

The understanding of the human brain is one of the main scientific challenges of the 21^st century. In this context, in the early 2000s the French Atomic Energy Commission (CEA) launched a program to conceive and build the first human MRI scanner operating at 11.7T. More than a decade of developments followed to deliver the magnet while six more years were necessary to complete the commissioning and finally obtain approval from the regulatory agencies to acquire the first ever human brain images in vivo at such magnetic field. We deployed parallel transmission tools to mitigate the radiofrequency field inhomogeneity problem and tame the specific absorption rate. To assure the safety of human imaging at such high field strength, we performed physiological, vestibular, behavioral and genotoxicity measurements on the volunteers. The data shows no evidence of adverse effects. The unprecedented field strength combined with the acquisition techniques deployed yield T₂ and T₂^*-weighted images reaching mesoscale resolutions within short acquisition times and with a high signal and contrast to noise ratio.