HiP-CT: A Multiscale X-ray Imaging Framework for Linking Diffusion MRI to Human Brain Microstructure

Brain microstructure—including axonal organization, cellular architecture, and vascular networks—is a key determinant of brain function and a sensitive marker of disease, yet remains challenging to capture across spatial scales in intact human tissue. Hierarchical Phase-Contrast Tomography (HiP-CT), a synchrotron X-ray phase-contrast imaging technique, enables non-destructive, isotropic three-dimensional imaging of whole human brains with hierarchical zooming from millimetre-scale overviews to cellular resolution within the same specimen (Walsh et al., 2021). This density-based contrast provides direct visualization of white-matter fiber organization, microvasculature, and subcortical structures within a unified anatomical framework.

In this talk, I will present a multiscale imaging pipeline centered on HiP-CT, integrating whole-brain imaging with targeted high-resolution X-ray imaging down to individual myelinated axons. Using post mortem human brains with short post-mortem intervals (PMI), we extend this framework to nanoscale X-ray tomography, enabling visualization of cellular and sub-cellular features within well-preserved tissue. We show that HiP-CT can be used to extract fiber orientation distributions and perform tractography analogous to diffusion MRI, while revealing substantially greater microstructural detail. By registering HiP-CT whole-brain overviews to ultra-high-resolution post mortem structural and diffusion MRI, we place these data within a neuroimaging framework familiar to the MRI community, enabling direct comparison with diffusion-derived measures. This is particularly powerful in regions where MRI is most challenged, such as subcortical nuclei, inter-nuclear regions, and transition zones with low anisotropy. Finally, I will discuss the opportunities and challenges of using HiP-CT as a microstructural reference modality for validating and refining diffusion MRI models, and for linking whole-brain neuroimaging to underlying human brain microstructure across scales.