Ofer Pasternak

Diffusion Tensor Imaging (DTI)-based White Matter Mapping in Brain Research: A Review

Diffusion tensor imaging (DTI) has become one of the most popular MRI techniques in brain research, as well as in clinical practice. The number of brain studies with DTI is growing steadily and, over the last decade, has produced more than 700 publications. Diffusion tensor imaging enables visualization and characterization of white matter fascicli in two and three dimensions. Since the introduction of this methodology in 1994, it has been used to study the white matter architecture and integrity of the normal and diseased brains (multiple sclerosis, stroke, aging, dementia, schizophrenia, etc.). Although it provided image contrast that was not available with routine MR techniques, unique information on white matter and 3D visualization of neuronal pathways, many questions were raised regarding the origin of the DTI signal. Diffusion tensor imaging is constantly validated, challenged, and developed in terms of acquisition scheme, image processing, analysis, and interpretation. While DTI offers a powerful tool to study and visualize white matter, it suffers from inherent artifacts and limitations. The partial volume effect and the inability of the model to cope with non-Gaussian diffusion are its two main drawbacks. Nevertheless, when combined with functional brain mapping, DTI provides an efficient tool for comprehensive, noninvasive, functional anatomy mapping of the human brain. This review summarizes the development of DTI in the last decade with respect to the specificity and utility of the technique in radiology and anatomy studies.

Free water elimination and mapping from diffusion MRI

Relating brain tissue properties to diffusion tensor imaging (DTI) is limited when an image voxel contains partial volume of brain tissue with free water, such as cerebrospinal fluid or edema, rendering the DTI indices no longer useful for describing the underlying tissue properties. We propose here a method for separating diffusion properties of brain tissue from surrounding free water while mapping the free water volume. This is achieved by fitting a bi‐tensor model for which a mathematical framework is introduced to stabilize the fitting. Applying the method on datasets from a healthy subject and a patient with edema yielded corrected DTI indices and a more complete tract reconstruction that passed next to the ventricles and through the edema. We were able to segment the edema into areas according to the condition of the underlying tissue. In addition, the volume of free water is suggested as a new quantitative contrast of diffusion MRI. The findings suggest that free water is not limited to the borders of the brain parenchyma; it therefore contributes to the architecture surrounding neuronal bundles and may indicate specific anatomical processes. The analysis requires a conventional DTI acquisition and can be easily merged with existing DTI pipelines. Magn Reson Med, 2009.

Characterization of displaced white matter by brain tumors using combined DTI and fMRI.

In vivo white matter tractography by diffusion tensor imaging (DTI) has become a popular tool for investigation of white matter architecture in the normal brain. Despite some unresolved issues regarding the accuracy of DTI, recent studies applied DTI for delineating white matter organization in the vicinity of brain lesions and especially brain tumors. Apart from the intrinsic limitations of DTI, the tracking of fibers in the vicinity or within lesions is further complicated due to changes in diseased tissue such as elevated water content (edema), tissue compression and degeneration. These changes deform the architecture of the white matter and in some cases prevent definite selection of the seed region of interest (ROI) from which fiber tracking begins. We show here that for displaced fiber systems, the use of anatomical approach for seed ROI selection yields insufficient results. Alternatively, we propose to select the seed points based on functional MRI activations which constrain the subjective seed ROI selection. The results are demonstrated on two major fiber systems: the pyramidal tract and the superior longitudinal fasciculus that connect critical motor and language areas, respectively. The fMRI based seed ROI selection approach enabled a more comprehensive mapping of these fiber systems. Furthermore, this procedure enabled the characterization of displaced white matter using the eigenvalue decomposition of DTI. We show that along the compressed fiber system, the diffusivity parallel to the fiber increases, while that perpendicular to the fibers decreases, leading to an overall increase in the fractional anisotropy index reflecting the compression of the fiber bundle. We conclude that definition of the functional network of a subject with deformed white matter should be done carefully. With fMRI, one can more accurately define the seed ROI for DTI based tractography and to provide a more comprehensive, functionally related, white matter mapping, a very important tool used in pre-surgical mapping.

How and how not to correct for CSF-contamination in diffusion MRI

Diffusion MRI is used extensively to investigate changes in white matter microstructure related to brain development and pathology. Ageing, however, is also associated with significant white and grey matter loss which in turn can lead to cerebrospinal fluid (CSF) based partial volume artefacts in diffusion MRI metrics. This is especially problematic in regions prone to CSF contamination, such as the fornix and the genu of corpus callosum, structures that pass through or close to the ventricles respectively. The aim of this study was to model the effects of CSF contamination on diffusion MRI metrics, and to evaluate different post-acquisition strategies to correct for CSF-contamination: Controlling for whole brain volume and correcting on a voxel-wise basis using the Free Water Elimination (FWE) approach. Using the fornix as an exemplar of a structure prone to CSF-contamination, corrections were applied to tract-specific and voxel-based [tract based spatial statistics (TBSS)] analyses of empirical DT-MRI data from 39 older adults (53-93 years of age). In addition to significant age-related decreases in whole brain volume and fornix tissue volume fraction, age was also associated with a reduction in mean fractional anisotropy and increase in diffusivity metrics in the fornix. The experimental data agreed with the simulations in that diffusivity metrics (mean diffusivity, axial and radial diffusivity) were more prone to partial volume CSF-contamination errors than fractional anisotropy. After FWE-based voxel-by-voxel partial volume corrections, the significant positive correlations between age and diffusivity metrics, in particular with axial diffusivity, disappeared whereas the correlation with anisotropy remained. In contrast, correcting for whole brain volume had little effect in removing these spurious correlations. Our study highlights the importance of correcting for CSF-contamination partial volume effects in the structures of interest on a voxel-by-voxel basis prior to drawing inferences about underlying changes in white matter structures and have implications for the interpretation of many recent diffusion MRI results in ageing and disease.

Diffusion MRI of Structural Brain Plasticity Induced by a Learning and Memory Task

Background Activity-induced structural remodeling of dendritic spines and glial cells was recently proposed as an important factor in neuroplasticity and suggested to accompany the induction of long-term potentiation (LTP). Although T1 and diffusion MRI have been used to study structural changes resulting from long-term training, the cellular basis of the findings obtained and their relationship to neuroplasticity are poorly understood. Methodology/Principal Finding Here we used diffusion tensor imaging (DTI) to examine the microstructural manifestations of neuroplasticity in rats that performed a spatial navigation task. We found that DTI can be used to define the selective localization of neuroplasticity induced by different tasks and that this process is age-dependent in cingulate cortex and corpus callosum and age-independent in the dentate gyrus. Conclusion/Significance We relate the observed DTI changes to the structural plasticity that occurs in astrocytes and discuss the potential of MRI for probing structural neuroplasticity and hence indirectly localizing LTP.

Excessive Extracellular Volume Reveals a Neurodegenerative Pattern in Schizophrenia Onset

Diffusion MRI has been successful in identifying the existence of white matter abnormalities in schizophrenia in vivo. However, the role of these abnormalities in the etiology of schizophrenia is not well understood. Accumulating evidence from imaging, histological, genetic, and immunochemical studies support the involvement of axonal degeneration and neuroinflammation—ubiquitous components of neurodegenerative disorders—as the underlying pathologies of these abnormalities. Nevertheless, the current imaging modalities cannot distinguish neuroinflammation from axonal degeneration, and therefore provide little specificity with respect to the pathophysiology progression and whether it is related to a neurodegenerative process. Free-water imaging is a new methodology that is sensitive to water molecules diffusing in the extracellular space. Excessive extracellular volume is a surrogate biomarker for neuroinflammation and can be separated out to reveal abnormalities such as axonal degeneration that affect diffusion characteristics in the tissue. We applied free-water imaging on diffusion MRI data acquired from schizophrenia-diagnosed human subjects with a first psychotic episode. We found a significant increase in the extracellular volume in both white and gray matter. In contrast, significant signs of axonal degeneration were limited to focal areas in the frontal lobe white matter. Our findings demonstrate that neuroinflammation is more prominent than axonal degeneration in the early stage of schizophrenia, revealing a pattern shared by many neurodegenerative disorders, in which prolonged inflammation leads to axonal degeneration. These findings promote anti-inflammatory treatment for early diagnosed schizophrenia patients.

Diffusion tensor imaging of the median nerve in healthy and carpal tunnel syndrome subjects

To determine if diffusion tensor imaging (DTI) of the median nerve could allow identification of patients with carpal tunnel syndrome (CTS).

White matter correlates of cognitive domains in normal aging with diffusion tensor imaging

The ability to perform complex as well as simple cognitive tasks engages a network of brain regions that is mediated by the white matter fiber bundles connecting them. Different cognitive tasks employ distinctive white matter fiber bundles. The temporal lobe and its projections subserve a variety of key functions known to deteriorate during aging. In a cohort of 52 healthy subjects (ages 25–82 years), we performed voxel-wise regression analysis correlating performance in higher-order cognitive domains (executive function, information processing speed, and memory) with white matter integrity, as measured by diffusion tensor imaging (DTI) fiber tracking in the temporal lobe projections [uncinate fasciculus (UF), fornix, cingulum, inferior longitudinal fasciculus (ILF), and superior longitudinal fasciculus (SLF)]. The fiber tracts were spatially registered and statistical parametric maps were produced to spatially localize the significant correlations. Results showed that performance in the executive function domain is correlated with DTI parameters in the left SLF and right UF; performance in the information processing speed domain is correlated with fractional anisotropy (FA) in the left cingulum, left fornix, right and left ILF and SLF; and the memory domain shows significant correlations with DTI parameters in the right fornix, right cingulum, left ILF, left SLF and right UF. These findings suggest that DTI tractography enables anatomical definition of region of interest (ROI) for correlation of behavioral parameters with diffusion indices, and functionality can be correlated with white matter integrity.

White Matter Microstructure in Individuals at Clinical High Risk of Psychosis: A Whole-Brain Diffusion Tensor Imaging Study

BACKGROUND The study of individuals at clinical high risk (CHR) for psychosis provides an important opportunity for unraveling pathological mechanisms underlying schizophrenia and related disorders. A small number of diffusion tensor magnetic resonance imaging (DTI) studies in CHR samples have yielded anatomically inconsistent results. The present study is the first to apply tract-based spatial statistics (TBSS) to perform a whole-brain DTI analysis in CHR subjects. METHODS A total of 28 individuals meeting CHR criteria and 34 healthy controls underwent DTI. TBSS was used for a group comparison of fractional anisotropy (FA), as well as axial, radial, and mean diffusivity (AD, RD, and MD). Conversion to psychosis was monitored during a mean follow-up period of 12.3 months. RESULTS The rate of conversion to psychosis was relatively low (4%). TBSS revealed increased MD in several clusters in the right hemisphere, most notably in the superior longitudinal fasciculus (SLF), posterior corona radiata, and corpus callosum (splenium and body). Increased RD was restricted to a smaller area in the posterior parietal lobe. CONCLUSION We present further evidence that white matter microstructure is abnormal in CHR individuals, even in a sample in which the vast majority do not transition to psychosis over the following year. In accord with previous studies on CHR individuals and patients with early-onset schizophrenia, our findings suggest an important pathological role for the parietal lobe and especially the SLF. The latter is known to undergo particularly dynamic microstructural changes during adolescence and early adulthood, a critical phase for the development of psychotic illness.

Longitudinal changes in free-water within the substantia nigra of Parkinson’s disease

There is a clear need to develop non-invasive markers of substantia nigra progression in Parkinsons disease. We previously found elevated free-water levels in the substantia nigra for patients with Parkinsons disease compared with controls in single-site and multi-site cohorts. Here, we test the hypotheses that free-water levels in the substantia nigra of Parkinsons disease increase following 1 year of progression, and that baseline free-water levels in the substantia nigra predict the change in bradykinesia following 1 year. We conducted a longitudinal study in controls (n = 19) and patients with Parkinsons disease (n = 25). Diffusion imaging and clinical data were collected at baseline and after 1 year. Free-water analyses were performed on diffusion imaging data using blinded, hand-drawn regions of interest in the posterior substantia nigra. A group effect indicated free-water values were increased in the posterior substantia nigra of patients with Parkinsons disease compared with controls (P = 0.003) and we observed a significant group × time interaction (P < 0.05). Free-water values increased for the Parkinsons disease group after 1 year (P = 0.006), whereas control free-water values did not change. Baseline free-water values predicted the 1 year change in bradykinesia scores (r = 0.74, P < 0.001) and 1 year change in Montreal Cognitive Assessment scores (r = -0.44, P = 0.03). Free-water in the posterior substantia nigra is elevated in Parkinsons disease, increases with progression of Parkinsons disease, and predicts subsequent changes in bradykinesia and cognitive status over 1 year. These findings demonstrate that free-water provides a potential non-invasive progression marker of the substantia nigra.