Imaging cellular and subcellular structure of human brain tissue using micro computed tomography

Abstract

Brain tissues have been an attractive subject for investigations in neuropathology, neuroscience, and neurobiol- ogy. Nevertheless, existing imaging methodologies have intrinsic limitations in three-dimensional (3D) label-free visualisation of extended tissue samples down to (sub)cellular level. For a long time, these morphological features were visualised by electron or light microscopies. In addition to being time-consuming, microscopic investigation includes specimen fixation, embedding, sectioning, staining, and imaging with the associated artefacts. More- over, optical microscopy remains hampered by a fundamental limit in the spatial resolution that is imposed by the diffraction of visible light wavefront. In contrast, various tomography approaches do not require a complex specimen preparation and can now reach a true (sub)cellular resolution. Even laboratory-based micro computed tomography in the absorption-contrast mode of formalin-fixed paraffin-embedded (FFPE) human cerebellum yields an image contrast comparable to conventional histological sections. Data of a superior image quality was obtained by means of synchrotron radiation-based single-distance X-ray phase-contrast tomography enabling the visualisation of non-stained Purkinje cells down to the subcellular level and automated cell counting. The question arises, whether the data quality of the hard X-ray tomography can be superior to optical microscopy. Herein, we discuss the label-free investigation of the human brain ultramorphology be means of synchrotron radiation-based hard X-ray magnified phase-contrast in-line tomography at the nano-imaging beamline ID16A (ESRF, Grenoble, France). As an example, we present images of FFPE human cerebellum block. Hard X-ray tomography can provide detailed information on human tissues in health and disease with a spatial resolution below the optical limit, improving understanding of the neuro-degenerative diseases.