Human cerebellar microstructure with 7T MRI: spherical b-tensor encoding and super resolution reconstruction

Abstract

Cerebellar function and structure remain less studied compared to the cerebrum, and while high-resolution 7T gives superior anatomical information, methods to visualise its microstructure in vivo are not widely available. However, improved understanding of cerebellar microstructure is highly clinically relevant: the granular layer of the cerebellum, located in the grey matter, contains the majority of the brain’s neurons and has been shown in post mortem studies to be affected by various diseases. The limited spatial resolution of MR does not resolve individual cell layers, but advanced diffusion techniques can infer properties of the microstructure. The aim of this work was to implement a combination of spherical b-tensor encoding using free waveforms, B1+ field shimming and super-resolution reconstruction (SRR) at 7T and evaluate the method in healthy volunteers. Diffusion-weighted signals and normalised diffusion signals were compared between the grey and white matter of the cerebellum and the occipital lobe as well as across 30 smaller ROIs in the cerebellum. The normalised diffusion signal obtained with spherical tensor encoding relates to cell density, and was found to be increased in the cerebellar cortex relative to the occipital cortex, consistent with previous findings. In the cerebellar cortex, the normalised diffusion signal followed a pattern similar to the thickness of the granular layer reported post mortem. Specifically, increased normalised diffusion signal values were found in lobules VII-VIII and Crus I/II, while lower values were found in lobules I-V. We successfully implemented spherical tensor encoding and SRR at 7T to image the human cerebellum, showing consistent results with those obtained at 3T, with an increased normalised diffusion signal in the cerebellum relative to that found in the cerebral cortex.