Microstructural changes in the brain after long-term post-concussion symptoms: A randomized trial.

A recent randomized controlled trial in young patients with long-term post-concussion symptoms showed that a novel behavioral intervention "Get going After concussIoN" is superior to enhanced usual care in terms of symptom reduction. It is unknown whether these interventional effects are associated with microstructural brain changes. The aim of this study was to examine whether diffusion-weighted MRI indices, which are sensitive to the interactions between cellular structures and water molecules' Brownian motion, respond differently to the interventions of the above-mentioned trial and whether such differences correlate with the improvement of post-concussion symptoms. Twenty-three patients from the intervention group (mean age 22.8, 18 females) and 19 patients from the control group (enhanced usual care) (mean age 23.9, 14 females) were enrolled. The primary outcome measure was the mean kurtosis tensor, which is sensitive to the microscopic complexity of brain tissue. The mean kurtosis tensor was significantly increased in the intervention group (p = 0.003) in the corpus callosum but not in the thalamus (p = 0.78) and the hippocampus (p = 0.34). An increase in mean kurtosis tensor in the corpus callosum tended to be associated with a reduction in symptoms, but this association did not reach significance (p = 0.059). Changes in diffusion tensor imaging metrics did not differ between intervention groups and were not associated with symptoms. The current study found different diffusion-weighted MRI responses from the microscopic cellular structures of the corpus callosum between patients receiving a novel behavioral intervention and patients receiving enhanced usual care. Correlations with improvement of post-concussion symptoms were not evident.

White matter biomarkers from diffusion MRI.

As part of an issue celebrating 2 decades of Joseph Ackerman editing the Journal of Magnetic Resonance, this paper reviews recent progress in one of the many areas in which Ackerman and his lab has made significant contributions: NMR measurement of diffusion in biological media, specifically in brain tissue. NMR diffusion signals display exquisite sensitivity to tissue microstructure, and have the potential to offer quantitative and specific information on the cellular scale orders of magnitude below nominal image resolution when combined with biophysical modeling. Here, I offer a personal perspective on some recent advances in diffusion imaging, from diffusion kurtosis imaging to microstructural modeling, and the connection between the two. A new result on the estimation accuracy of axial and radial kurtosis with axially symmetric DKI is presented. I moreover touch upon recently suggested generalized diffusion sequences, promising to offer independent microstructural information. We discuss the need and some methods for validation, and end with an outlook on some promising future directions.

The displacement correlation tensor: microstructure, ensemble anisotropy and curving fibers.

Experiments with multiple diffusion wave vectors are known to carry more information than what is available from standard diffusion experiments. Here we consider a special case of this class of pulse sequences, the double wave vector diffusion experiment, and use the cumulant expansion of the signal to introduce the displacement correlation tensor. We discuss its physical interpretation and properties, noting in particular that its short time behavior allows determination of the surface to volume ratio of the pore space. We present a general expression for the displacement correlation tensor, and provide explicit expressions for a few model geometries. We then show that the scatter matrix characterizing the orientation distribution of an ensemble of cylinders is simply related to the displacement correlation tensor. This result is generalized to ensembles of pores with arbitrary shapes allowing a precise formulation of the influence of microstructural and ensemble anisotropy on the double wave vector diffusion signal in the Gaussian phase approximation. Finally, as a new application of the double wave vector diffusion signal, we analyze its behavior in a curving fiber, and suggest that the displacement correlation tensor may be used to estimate sub-voxel fiber curvature and deflection angle. The theoretical results are corroborated by computer simulations.