While this fundamental objective is common throughout diffusion tractography, strategies for achieving it vary greatly from algorithm to algorithm. In attempting to reconstruct fiber bundles or draw inferences about axonal connectivity, tractography algorithms aim to find paths through the data field along which diffusion is least hindered. This assumption is explained and investigated in detail in other chapters in this book but, throughout the complexities in the remainder of this chapter, it is crucial to remember the fundamental measurement upon which all of our inference relies. Hence when we measure diffusion along many different orientations, we expect to see diffusion preferred in orientations that correspond to axonal fiber orientations. In this chapter, we will outline the principles behind diffusion tractography.Īll diffusion tractography techniques rely on one fundamental assumption: that when a number of axons align themselves along a common axis, the diffusion of water molecules will be hindered to a greater extent across this axis than along it. The following chapters will highlight many situations in which non-invasive measurements are essential in basic neuroscience and clinical research, and demonstrate their potential for surgery. However, their non-invasive nature and ease of measurement mean that tractography studies can address scientific and clinical questions that cannot be answered by any other means ( Passingham, 2013). By comparison with invasive techniques (see Chapter 17), tractography measurements are indirect, difficult to interpret quantitatively, and error-prone (see Chapter 20). Tractography is the only available tool for identifying and measuring these pathways non-invasively and in vivo. These pathways form the substrate for information transfer between remote brain regions and are therefore central to our understanding of function in both the normal and diseased brain. Magnetic resonance diffusion tractography is a method for identifying white matter pathways in the living human brain. Saad Jbabdi, in Diffusion MRI (Second Edition), 2014 19.1 Introduction 101 There is also evidence from an observation study suggesting better clinical outcomes, as measured by postoperative motor deterioration and 6-month Karnofsky performance scores, in patients in whom DTI tractography was part of preoperative planning. 103 Combining DTI and intraoperative subcortical stimulation can reduce surgery duration, patient fatigue, and the incidence of intraoperative seizures. 101,102 When DTI tractography data were mapped onto anatomic images in a neuronavigation system, the mean distance between intraoperative subcortical stimulation sites and DTI-determined corticospinal tract was 8.7 ± 3.1 mm. To date, several studies have suggested its high sensitivity in detecting corticospinal and language tracts comparing to intraoperative subcortical mapping. 121-24).Īs with fMRI, definitive benefit of DTI tractography for preoperative planning has not been confirmed by large randomized trials. This knowledge provides a basis for preoperative planning, in that it enables one to recognize potentially important tracts near the target lesions or along the path of the surgical approach (see Fig. When the measured directionalities of individual voxels are represented graphically, ideally overlaid with brain and target lesion(s), tractography allows visualization of how white matter tracts are anatomically related to lesion(s). 100 By assessing the directionality of water diffusivity in each small imaging voxel and then linking the measures of maximal diffusivity end to end, one can begin to discern the trajectories of white matter tracts. Tractography derived from DTI is based on the biophysical observation that water molecules within axons move in a relatively unconstrained manner longitudinally along the length of the axon. Richard Winn MD, in Youmans and Winn Neurological Surgery, 2017 Diffusion Tensor Imaging and Tractography
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