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Keenlyside, A.

Publications and source records attributed to Keenlyside, A..

2 recordsLinked to original sources

The Extremely Brilliant Brain: An Isotropic Microscale Human Brain Dataset

We present an isotropic 7.72 {micro}m/voxel post-mortem human brain dataset acquired using Hierarchical Phase-Contrast Tomography (HiP-CT) at the ESRF Extremely Brilliant Source, beamline BM18. This fills a critical gap between whole-brain MRI at 100 {micro}m resolution and serial-section histological reconstructions at 20 {micro}m or finer. HiP-CT contrast, derived from X-ray phase shifts, enables rich 3D visualisation of complex neuroanatomy including white-matter bundles, microvasculature, and sub-nuclei. We provide open-source workflows for online data exploration, subvolume download, segmentation, and reintegration of analyses into the full dataset. We demonstrate the potential of this resource by tracing vasculature over long distances, segmenting nuclei, and extracting whitematter orientations with 3D structure-tensor analysis. High-resolution human brain datasets are transformative for quantitative neuroanatomy, circuit mapping, and validation of clinical imaging; this openly available resource is a critical step for global access to next-generation multiscale brain imaging.

neuroscience↗

Resolving near-micron scale features within a whole sheep head using Hierarchical Phase-Contrast Tomography

BackgroundHierarchical Phase-Contrast Tomography (HiP-CT) was developed to image ex vivo intact human soft-tissue organs with local near-micron scale resolution. PurposeWe demonstrate the application of HiP-CT in combination with the recently developed Eikonal Phase Retrieval (EPR) for resolving anatomical features in large hard and soft tissue structures on a sheep head, and show the applicability for zooming to resolve anatomical features with near-micron scale resolution. Materials and MethodsWe imaged an entire skinned sheep head prepared in 70 % ethanol with HiP-CT at an isotropic voxel size of 16.5 {micro}m using the recently developed Eikonal Phase Retrieval (EPR) to reduce artefacts from bones. Local tomography zooms were taken in regions of interest: the eye (4.23 {micro}m voxels) and the coronal suture (2.20 {micro}m voxels). To compare to clinical imaging, we acquired T2-weighted MRI and CT of the sheep head and evaluated the contrast-to-noise ratio for differentiation of white and grey matter in the brain for all modalities. Further evaluations on HiP-CT images include structure tensor analysis for structural orientation in the brain as well as fibre tracking in the coronal suture. ResultsHiP-CT combined with EPR achieved high contrast for both hard and soft tissue. Comparison to MRI showed similar soft-tissue contrast, but much higher spatial resolution. Structure tensor analysis in the brain revealed the orientation of the major white matter bundles. In the eye, near-micron scale features such as retinal layers and the bundles in the optic nerve were visualized. Fiber tracking allowed analysis of the orientation of collagen fiber bundles in the coronal suture. ConclusionThis work highlights the potential of HiP-CT to image a complete sheep head, ex vivo, and hierarchically zoom without sectioning to resolve few-microns features locally, enabling comprehensive three-dimensional visualization of intricate cranial structures and their spatial interrelations. Summary statementTechnical developments in HiP-CT enable ex vivo X-ray imaging of an intact sheep head with local resolution to near-micron scale, demonstrating future viability on a human head. Key resultsO_LIA whole sheep head was imaged with synchrotron-based hierarchical phase-contrast tomography coupled with Eikonal Phase-retrieval with 16.5 {micro}m isotropic voxels. C_LIO_LIThe high contrast for both hard and soft tissue enabled differentiation of brain white and grey matter, the optic nerve and bone features within the skull. C_LIO_LILocal tomography zoom scans in an eye (4.23 {micro}m voxels) and coronal suture (2.20 {micro}m voxels) allowed visualization and analysis of near-micron sized features. C_LI

bioengineering↗