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bioRxiv · 10.1101/2021.12.13.472113

Tissue Optimisation Strategies for High Quality Ex Vivo Diffusion Imaging

Barrett, R. L. C.·Cash, D.·Simmons, C.·Kim, E.·Wood, T. C.·Stones, R.·Vernon, A. C.·Catani, M.·Dell'Acqua, F.
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Abstract

Ex vivo diffusion imaging can be used to study healthy and pathological tissue microstructure in the rodent brain with microscopic resolution, providing a link between in vivo MRI and ex vivo microscopy techniques. A major challenge for the successful acquisition of ex vivo diffusion imaging data however are changes in the relaxivity and diffusivity of brain tissue following perfusion fixation. In this study we address this question by examining the combined effects of tissue preparation factors that influence image quality, including tissue rehydration time, fixative concentration and contrast agent concentration. We present an optimisation strategy combining these factors to manipulate the T1 and T2 of fixed tissue and maximise signal-to-noise ratio (SNR) efficiency. Applying this strategy in the rat brain resulted in a doubling of SNR and an increase in SNR per unit time by 135% in grey matter and 88% in white matter. This enabled the acquisition of excellent quality high-resolution (78 {micro}m isotropic voxel size) diffusion data in less than 4 days, with a b-value of 4000 s/mm2, 30 diffusion directions and a field of view of 40 x 13 x 18 mm, using a 9.4 Tesla scanner with a standard 39 mm volume coil and a 660 mT/m 114 mm gradient insert. It was also possible to achieve comparable data quality for a standard resolution (150 {micro}m) diffusion dataset in 21/4 hours. In conclusion, the optimisation strategy presented here may be used to improve signal quality, increase spatial resolution and/or allow faster acquisitions in preclinical ex vivo diffusion MRI experiments.

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Barrett, R. L. C., Cash, D., Simmons, C., Kim, E., Wood, T. C., Stones, R., Vernon, A. C., Catani, M., Dell'Acqua, F.. 2021-12-14. Tissue Optimisation Strategies for High Quality Ex Vivo Diffusion Imaging. https://doi.org/10.1101/2021.12.13.472113

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