Principles and Limitations of Computational Algorithms in Clinical Diffusion Tensor MR Tractography

Abstract

SUMMARY:There have been numerous reports documenting the graphic reconstruction of 3D white matter architecture in the human brain by means of diffusion tensor MR tractography. Different from other reviews addressing the physics and clinical applications of DTI, this article reviews the computational principles of tractography algorithms appearing in the literature. The simplest voxel-based method and 2 widely used subvoxel approaches are illustrated first, together with brief notes on parameter selection and the restrictions arising from the distinct attributes of tract estimations. Subsequently, some advanced techniques attempting to offer improvement in various aspects are briefly introduced, including the increasingly popular research tracking tool using HARDI. The article explains the inherent technical limitations in most of the algorithms reported to date and concludes by providing a reference guideline for formulating routine applications of this important tool to clinical neuroradiology in an objective and reproducible manner.ABBREVIATIONS CC ϭ corpus callosum; DTI ϭ diffusion tensor imaging; FA ϭ fractional anisotropy; HARDI ϭ high angular resolution diffusion imaging A t the beginning of the 21st century, the radiologic community witnessed the tremendous technical progress toward noninvasive investigations of the white matter architecture in the central nervous system. Thanks to the advancement of DTI plus the ever-growing computer technology of the socalled tractography methods, a comprehensive visualization of the white matter fiber bundles and their relationships to tumors (Fig 1) can be readily displayed without the need for any surgery.1 Needless to say, the potential implications in presurgical planning are huge, particularly if the related technology can be executed objectively and automatically on a daily basis, with the reliability approaching a level that is highly acceptable in routine practice.This article attempts to provide a pedagogic overview of the aspects of diffusion MR tractography that clinical neuroradiologists may find helpful for routine use. Because an overview of data acquisition via DTI and potential clinical applications has been provided in several review articles, 1-3 only the computational means to perform the tractography will be introduced here. In addition, only selective methods will be mentioned, because detailed comprehensive explanations about the massive amount of newly proposed algorithms are neither necessary nor insightful. At the same time, the ultimate restrictions originating from the computation methods will be addressed. With the basic concepts understood, extensions to more sophisticated algorithms would ideally be easily comprehensible. Finally, we conclude with a suggestive guideline for optimal use of diffusion MR tractography in clinical neuroradiology, emphasizing particularly the preparatory work that ought to be done before routine application. The mathematics in this entire article, though inevitable, will be kept at a minimum to ensure readabili...

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