Improving Spatial Normalization of Brain Diffusion MRI to Measure Longitudinal Changes of Tissue Microstructure in the Cortex and White Matter

Background: Fractional anisotropy (FA) and mean diffusivity (MD) are frequently used to evaluate longitudinal changes in white matter (WM) microstructure. Recently, there has been a growing interest in identifying experience-dependent plasticity in gray matter using MD. Improving registration has thus become a major goal to enhance the detection of subtle longitudinal changes in cortical microstructure.

Purpose: To optimize normalization of diffusion tensor images (DTI) to improve registration in gray matter and reduce variability associated with multisession registrations.

Study type: Prospective longitudinal study.

Subjects: Twenty-one healthy subjects (18-31 years old) underwent nine MRI scanning sessions each.

Field strength/sequence: 3.0T, diffusion-weighted multiband-accelerated sequence, MP2RAGE sequence.

Assessment: Diffusion-weighted images were registered to standard space using different pipelines that varied in the features used for normalization, namely, the nonlinear registration algorithm (FSL vs. ANTs), the registration target (FA-based vs. T₁ -based templates), and the use of intermediate individual (FA-based or T₁ -based) targets. We compared the across-session test-retest reproducibility error of these normalization approaches for FA and MD in white and gray matter.

Statistical tests: Reproducibility errors were compared using a repeated-measures analysis of variance with pipeline as the within-subject factor.

Results: The registration of FA data to the FMRIB58 FA atlas using ANTs yielded lower reproducibility errors in white matter (P < 0.0001) with respect to FSL. Moreover, using the MNI152 T₁ template as the target of registration resulted in lower reproducibility errors for MD (P < 0.0001), whereas the FMRIB58 FA template performed better for FA (P < 0.0001). Finally, the use of an intermediate individual template improved reproducibility when registration of the FA images to the MNI152 T₁ was carried out within modality (FA-FA) (P < 0.05), but not via a T₁ -based individual template.

Data conclusion: A normalization approach using ANTs to register FA images to the MNI152 T₁ template via an individual FA template minimized test-retest reproducibility errors both for gray and white matter.

Level of evidence: 1 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;52:766-775.