Reproducibility of quantitative tractography methods applied to cerebral white matter

Abstract

Tractography based on diffusion tensor imaging (DTI) allows visualization of white matter tracts. In this study, protocols to reconstruct eleven major white matter tracts are described. The protocols were refined by several iterations of intra- and inter-rater measurements and identification of sources of variability. Reproducibility of the established protocols was then tested by raters who did not have previous experience in tractography. The protocols were applied to a DTI database of adult normal subjects to study size, fractional anisotropy (FA), and T₂ of individual white matter tracts. Distinctive features in FA and T₂ were found for the corticospinal tract and callosal fibers. Hemispheric asymmetry was observed for the size of white matter tracts projecting to the temporal lobe. This protocol provides guidelines for reproducible DTI-based tract-specific quantification.

Introduction

Three-dimensional tract reconstruction (tractography) based on diffusion tensor imaging (DTI) is becoming a widely-used tool to study human white matter anatomy (Basser et al., 2000, Conturo et al., 1999, Jones et al., 1999b, Lazar et al., 2003, Mori et al., 1999, Mori et al., 2005, Parker et al., 2002, Poupon et al., 2000). This technology allows us to visualize trajectories of specific white matter fiber bundles and has potential to perform quantitative evaluation of properties of individual tracts. This provides exciting opportunities to assess the impact of diseases on specific white matter tracts. Once the location of a tract is defined, its size can be measured. Further, by superimposing tract coordinates on various MR parameter maps such as T₁, T₂, magnetization transfer ratio (MTR), and diffusion anisotropy, the myelination and axonal status of individual tracts may be monitored (Glenn et al., 2003, Pagani et al., 2005, Partridge et al., 2004, Stieltjes et al., 2001, Virta et al., 1999, Wilson et al., 2003, Xue et al., 1999). However, questions remain whether the tractography results reflect true neuroanatomical details and are sufficiently reproducible to be used as a tool for quantitative analyses.

In terms of validity, there is mounting evidence that tracking results of many prominent white matter tracts agree very well with classical definitions based on postmortem studies (Basser et al., 2000, Catani et al., 2002, Conturo et al., 1999, Jellison et al., 2004, Mori et al., 1999, Mori et al., 2002, Poupon et al., 2000, Stieltjes et al., 2001, Wakana et al., 2004). On the other hand, it is well known that the technique can produce false positive and false negative results due to noise, partial volume effects, and complex fiber architectures within a pixel (Pierpaoli et al., 2001, Wiegell et al., 2000). One way to raise the confidence level of validity is to employ anatomical constraints by employing multiple regions of interest (ROIs) (Conturo et al., 1999, Huang et al., 2004). This technique requires a priori knowledge about the trajectory and can be used only for well-characterized white matter tracts. This approach should reduce the number of false positive, but is unlikely to be 100% accurate.

While it is difficult to completely characterize the validity of tractography, we can measure its reproducibility. If we can develop a scheme to reproducibly define coordinates of specific white matter tracts, this technique should be a valuable tool to test hypotheses as to whether any of these specific tracts are involved in the disease of interest. Within a given set of imaging parameters, we expect reconstruction reproducibility to vary among white matter tracts depending on their size and trajectory. Therefore, it is important to establish reproducible tracking protocols.

One of the major sources of variability, in addition to noise and partial volume effects, comes from placement of reference ROIs to identify specific white matter tracts. By devising clever ROI drawing schemes, which are based on anatomical features of individual tracts and using regions that are sufficiently large, it is possible to come up with a robust protocol that is rather insensitive to small variations in the ROI drawing (Huang et al., 2004). The protocol can be iteratively improved by measuring intra and inter-rater variability and by identifying and describing the source of variations. The purpose of this paper is to develop such robust protocols and identify white matter tracts that can be reconstructed reproducibly. The reproducibility was characterized by spatial matching among different trials by the same rater (intra-rater) and multiple raters (inter-rater) using the same subject (inter-measurement). In the second part of the study we applied the established protocols to measure size, fractional anisotropy, and T₂ of each tract using our normal DTI database. This study leads to multi-parametric mapping of the normal white matter and the range of normal variations in a tract-by-tract basis.