Advanced Methods to Study White Matter Microstructure

3.3.1

Introduction: Diffusion Imaging and Tissue Microstructure

Diffusion imaging and particularly diffusion tensor imaging (DTI) have become standard tools for assessment of white matter in the brain. Although somewhat more technically challenging to implement in the spinal cord, these methods are now also commonplace in studies of the spinal cord.

DTI provides two unique pieces of information over any preceding method. First, it provides an estimate of the dominant orientation of local fibers in each image voxel. That information is the foundation of tractography and structural connectivity mapping in the brain. In the spinal cord fiber orientation information is less useful, since the fiber structure is simpler and generally predicted quite easily, but disruptions to that structure may still be important in injury or disease.

The second key information from DTI is a set of orientationally invariant indices, e.g., fractional anisotropy (FA) and mean diffusivity (MD) that provide crude, but useful, markers of microstructural integrity. These quantitative parameters have been used widely in the brain, spinal cord, and peripheral nervous system, as well as a range of other organs and tissue types. For a full description of DTI theory and application to the spinal cord, see Chapter 3.1 .

In recent years, some drawbacks in both these unique aspects of DTI have become increasingly evident. The DT model provides only a single fiber orientation in each image voxel and fails in areas of heterogenous white matter such as fiber crossings. Crossing fibers are less widespread in the spinal cord, where the white matter is more regularly ordered, but crossings and other complex fiber configurations do occur. Moreover, the simple DTI microstructure indices lack specificity. White matter contains several cellular components (cells, axons, myelin), each with its own dimensions, density, and other properties that affect water mobility. Simple parameters such as the FA or MD provide only a very crude description of the complex environment that summarizes many different effects. The recent trend in diffusion imaging has been to develop more sophisticated models that enable estimation of these different components individually to provide more specific information on the geometry and physiology of white matter tissue. This chapter summarizes the state of the art for studying white matter through diffusion and speculates on their potential in the spinal cord.

3.3.2

Advanced Methods for Studying White Matter

As the b -value increases, the DT model rapidly becomes inadequate to explain diffusion measurements from white matter. Significant departures occur even at b = 1000 s/mm ² in vivo. These departures indicate a non-monoexponential decay of the signal arising from complex diffusion processes in multiple compartments. The existence of non-Gaussian diffusion in neuronal tissue has motivated over the last decade several innovations in data acquisition and analysis to capture and exploit the extra information in the signal to estimate more useful tissue features. These methods divide into two groups: (1) model based and (2) model free. While all approaches assume some kind of underlying signal model, the classification refers to the use (or not) of a biophysical model with parameters reflecting specific tissue properties. For a detailed treatment of the model-free methods, see Chapter 3.2 .