Fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) are commonly used as MRI biomarkers of white matter microstructure in diffusion MRI studies of neurodevelopment, brain aging, and neurologic injury/disease. Some of the more frequent practices include performing voxel-wise or region-based analyses of these measures to cross-sectionally compare individuals or groups, longitudinally assess individuals or groups, and/or correlate with demographic, behavioral or clinical variables. However, it is now widely recognized that the majority of cerebral white matter voxels contain multiple fiber populations with different trajectories, which renders these metrics highly sensitive to the relative volume fractions of the various fiber populations, the microstructural integrity of each constituent fiber population, and the interaction between these factors. Many diffusion imaging experts are aware of these limitations and now generally avoid using FA, AD or RD (at least in isolation) to draw strong reverse inferences about white matter microstructure, but based on the continued application and interpretation of these metrics in the broader biomedical/neuroscience literature, it appears that this has perhaps not yet become common knowledge among diffusion imaging end-users. Therefore, this paper will briefly discuss the complex biophysical underpinnings of these measures in the context of crossing fibers, provide some intuitive “thought experiments” to highlight how conventional interpretations can lead to incorrect conclusions, and suggest that future studies refrain from using (over-interpreting) FA, AD, and RD values as standalone biomarkers of cerebral white matter microstructure.

Purpose: Postmortem MRI can be used to reveal important pathologies and establish radiology–pathology correlations. However, quantitative MRI values are altered by tissue fixation. Therefore, the purpose of this study was to investigate time-dependent effects of formalin fixation on MRI relaxometry (T₁ and T₂), diffusion tensor imaging (fractional anisotropy, FA; and mean diffusivity, MD), and myelin water fraction (MWF) measurements throughout intact human brain specimens. Methods: Two whole, neurologically-healthy human brains were immersed in 10% formalin solution and scanned at 13 time points between 0 and 1,032 h. Whole-brain maps of longitudinal (T₁) and transverse (T₂) relaxation times, FA, MD, and MWF were generated at each time point to illustrate spatiotemporal changes, and region-of-interest analyses were then performed in eight brain structures to quantify temporal changes with progressive fixation. Results: Although neither of the diffusion measures (FA nor MD) showed significant changes as a function of formalin fixation time, both T₁ and T₂-relaxation times significantly decreased, and MWF estimates significantly increased with progressive fixation until (and likely beyond) our final measurements were taken at 1,032 h. Conclusion: These results suggest that T₁-relaxation, T₂-relaxation and MWF estimates must be performed quite early in the fixation process to avoid formalin-induced changes compared to in vivo values; and furthermore, that different ex vivo scans within an experiment must be acquired at consistent (albeit still early) fixation intervals to avoid fixative-related differences between samples. Conversely, ex vivo diffusion measures (FA and MD) appear to depend more on other factors (e.g., pulse sequence optimization, sample temperature, etc.).

Functional magnetic resonance imaging (fMRI) of the cortex is a powerful tool for neuroscience research, and its use has been extended into the brainstem and spinal cord as well. However, there are significant technical challenges with extrapolating the developments that have been achieved in the cortex to their use in the brainstem and spinal cord. Here, we develop a normalized coordinate system for the cervical spinal cord and brainstem, demonstrating a semiautomated method for spatially normalizing and coregistering fMRI data from these regions. fMRI data from 24 experiments in eight volunteers are normalized and combined to create the first anatomical reference volume, and based on this volume, we define a standardized region-of-interest (ROI) mask, as well as a map of 52 anatomical regions, which can be applied automatically to fMRI results. The normalization is demonstrated to have an accuracy of less than 2 mm in 93% of anatomical test points. The reverse of the normalization procedure is also demonstrated for automatic alignment of the standardized ROI mask and region-label map with fMRI data in its original (unnormalized) format. A reliable method for spatially normalizing fMRI data is essential for analyses of group data and for assessing the effects of spinal cord injury or disease on an individual basis by comparing with results from healthy subjects.