A method to remove the influence of fixative concentration on post-mortem T₂maps using a Kinetic Tensor model

Abstract

Formalin fixation has been shown to substantially reduce T2 estimates when performing post-mortem imaging, primarily driven by the presence of bulk fixative in tissue. Prior to scanning, post-mortem tissue samples are often placed into a fluid that has more favourable imaging properties, such as matched magnetic susceptibility. This study investigates whether there is any evidence for a change in T2 in regions close to the tissue surface in post-mortem T2 maps due to fixative outflux into this surrounding fluid. Furthermore, we investigate whether a simulated spatial map of fixative concentration can be used as a confound regressor to reduce T2 inhomogeneity. To achieve this, T2 maps and diffusion tensor estimates were obtained in 14 whole, formalin fixed post-mortem brains placed in fluorinert approximately 48 hours prior to scanning. This consisted of 7 brains fixed with 10% formalin and 7 brains fixed with 10% neutral buffered formalin (NBF). Fixative outflux was modelled using a Kinetic Tensor (KT) model, which incorporates voxelwise diffusion tensor estimates to account for diffusion anisotropy and tissue-specific diffusion coefficients. Brains fixed with 10% NBF revealed a spatial T2 pattern consistent with the modelled fixative outflux. Confound regression of fixative concentration reduced T2 inhomogeneity across both white and grey matter, with the greatest reduction attributed to the KT model vs simpler models of fixative outflux. No such effect was observed in brains fixed with 10% formalin. Correlations with ferritin and myelin proteolipid protein (PLP) histology lead to an increased similarity for the relationship between T2 and PLP for the two fixative types after KT correction. Only small correlations were identified between T2 and ferritin before and after KT correction.

The Digital Brain Bank, an open access platform for post-mortem datasets

“…All fixed non-human brains and excised tissue blocks scanned at the University of Oxford were prepared by soaking the samples in phosphate buffered saline (PBS) prior to scanning, which increases image SNR by raising T2-values closer to those found in vivo (Shepherd et al, 2009). This was not performed in whole human brains, as brain size necessitates a soaking time of multiple weeks for the buffer fluid to penetrate throughout tissue (Dawe et al, 2009;Tendler, Qi, et al, 2020;Yong-Hing, Obenaus, Stryker, Tong, & Sarty, 2005) which was incompatible with our experimental design. We note that soaking tissue for an insufficient time can lead to artificial 'boundaries' in resulting images, where PBS has not penetrated into deep tissue (Miller et al, 2011).…”

“…T1 maps were fitted assuming mono-exponential signal recovery. T2 maps were processed using an extended phase graph (EPG) fitting scheme, which accounts for B1-inhomogeneity at 7T (details of acquisition and processing are described in (Tendler, Qi, et al, 2020)).…”

“…Polarised light imaging (4 μm in-plane) in the anterior commissure, corpus callosum, pons, thalamus and visual cortex (same brain) Dataset described in this publication (Methodology in Supporting Information), Diffusion MRI processing described in , T2 mapping described in (Tendler, Qi, et al, 2020)…”

“…Polarised light imaging (4 μm in-plane), bright field microscopy images of immunohistochemistry stains (0.25 μm in-plane) for PLP (myelin) and GFAP (astrocyte) in three excised human corpus callosum samples (same samples) (Mollink et al, 2017) (Roumazeilles et al, 2020), 3x Macaque monkey and 3x Ring-Tailed Lemur described in (Lange et al, 2020), all other datasets described on the Digital Brain Bank website. (Wang et al, 2020), Diffusion MRI processing described in , T2 mapping described in (Tendler, Qi, et al, 2020) Table 1: Description of all datasets provided in the first release to the Digital Brain Bank. MRI resolutions provided when consistent across all images in a single dataset (iso.…”

“…Dataset described in this publication (Methodology in Supporting Information), Diffusion MRI processing described in , T2 mapping described in (Tendler, Qi, et al, 2020)…”