Analysis of partial volume effects in diffusion‐tensor MRI

Abstract

The diffusion tensor is currently the accepted model of diffusion in biological tissues. The measured diffusion behavior may be more complex when two or more distinct tissues with different diffusion tensors occupy the same voxel. In this study, a partial volume model of MRI signal behavior for two diffusion-tensor compartments is presented. Simulations using this model demonstrate that the conventional single diffusion tensor model could lead to highly variable and inaccurate measurements of diffusion behavior. The differences between the single and twotensor models depend on the orientations, fractions, and exchange between the two diffusion tensor compartments, as well as the diffusion-tensor encoding technique and diffusionweighting that is used in the measurements. The current single compartment model's inaccuracies could cause diffusionbased characterization of cerebral ischemia and white matter connectivity to be incorrect. A diffusion-tensor MRI imaging experiment on a normal human brain revealed significant partial volume effects between oblique white matter regions when using very large voxels and large diffusion-weighting (b ϳ 2.69 ؋ 10 3 sec/mm 2 ). However, the apparent partial volume effects in white matter decreased significantly when smaller voxel dimensions were used. The diffusion-tensor is a mathematically elegant description of diffusion as a function of direction. Basser and Pierpaoli (1) applied the tensor formalism to diffusion measurements of biological tissues obtained by MRI and NMR spectroscopy. One of the most important observations is that organized fibrous tissues, such as muscle and cerebral white matter, demonstrate anisotropic diffusion. The direction of greatest diffusivity corresponds to the fiber axis direction. The diffusion tensor describes the magnitude of the water diffusion, the degree of diffusion anisotropy, and the orientation of the anisotropy.Measurements of the diffusion tensor and its components (i.e., the trace) have been found to have several applications in the human brain (2,3). The trace of the diffusion tensor has been found to be valuable for detecting and evaluating brain ischemia and stroke (4,5). Measures of diffusion tensor anisotropy have been used to study white matter in terms of morphology (6), disease and trauma (8,9), brain development (10,11), and neurosurgical planning (12). Several investigators have recently proposed using the principal eigenvectors of the diffusion tensor to estimate white matter connectivity (13)(14)(15). Each of these applications will be influenced by the accuracy of the measurements of the diffusion tensor. Recent studies have investigated the effects of measurement noise (16,17) and the tensor encoding strategy (18) on the accuracy of the diffusion tensor and its derived parameters.Partial volume effects can also significantly influence the accuracy of diffusion tensor measurements. This is particularly true for most DT-MRI studies that use EPI techniques with relatively large voxels (ϳ1.5-5.0 mm on a side). Previous stud...

Hybrid diffusion imaging

“…Consequently, in regions with complex white matter organization, changes or differences in diffusion tensor measures may reflect either changes in either the tissue microstructure or the partial volume averaging components. As the diffusion weighting is increased the profiles of apparent diffusivity reveal non-Gaussian diffusion behavior in voxels with partial volume averaging (Niendorf et al, 1996;Mulkern et al, 1999;Assaf and Cohen, 1998a , 1998b , 1999b , 2000Clark and Le Bihan, 2000;Alexander et al, 2001;Alexander et al, 2002;Frank, 2002;). Despite these limitations, the applications of diffusion tensor imaging have been rapidly growing, mainly because of the relative simplicity and good acquisition efficiency (e.g., it can be acquired in clinically acceptable times).…”

Characteristics of the aberrant pyramidal tract in comparison with the pyramidal tract in the human brain

“…We believe that the methodology and results of this study would be helpful in research on the APT in the human brain. However, limitation of DTI should be considered [19-21]. Even though DTI is a powerful anatomic imaging tool that can demonstrate the gross fiber architecture, limitation of DTI such as partial-volume effects which are non-trivial problems in interpreting of diffusion-weighted signal could influence the tract including the DTI parameters such as FA and MD [19-21].…”

“…However, limitation of DTI should be considered [19-21]. Even though DTI is a powerful anatomic imaging tool that can demonstrate the gross fiber architecture, limitation of DTI such as partial-volume effects which are non-trivial problems in interpreting of diffusion-weighted signal could influence the tract including the DTI parameters such as FA and MD [19-21]. In detail, the fiber bundles which are passing through narrow area could lead to dispersed patterns of low confidence connections downstream of the bottleneck.…”

High‐resolution diffusion tensor imaging of the human pons with a reduced field‐of‐view, multishot, variable‐density, spiral acquisition at 3 T

“…As the spatial resolution increases, higher FA values are encountered in voxels containing primarily WM, and lower FA values are shown in areas of gray matter (GM) located next to WM tracts. At low in-plane resolution, significant partial volume effects occur in the interface of WM with CSF (i.e., middle cerebellar peduncle), the areas containing population of WM fibers with different orientations, and the boundaries between gray and WM (7). Specifically, the islands of the corticospinal tract fibers, which are dispersed among transverse pontine fibers and the pontine nuclei, can be resolved with much greater accuracy by using 0.8 ϫ 0.8 mm 2 voxels (Fig.…”

“…Both the accuracy of the derived anisotropy metrics (4) and the performance of DTI tractography (5,6) rely strongly on the spatial resolution of the DTI acquisition (7). Performing in vivo DTI of certain anatomic regions, such as the brainstem (8), the cervical spine (9), and the optical nerve (10), is extremely challenging for the following three main reasons.…”