A study of diffusion tensor imaging by tissue-specific, smoothing-compensated voxel-based analysis

Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, Madison, WI 53705, USA.
NeuroImage (Impact Factor: 6.36). 11/2008; 44(3):870-83. DOI: 10.1016/j.neuroimage.2008.09.041
Source: PubMed


Voxel-based analysis (VBA) is commonly used for statistical analysis of image data, including the detection of significant signal differences between groups. Typically, images are co-registered and then smoothed with an isotropic Gaussian kernel to compensate for image misregistration, to improve the signal-to-noise ratio (SNR), to reduce the number of multiple comparisons, and to apply random field theory. Problems with typical implementations of VBA include poor tissue specificity from image misregistration and smoothing. In this study, we developed a new tissue-specific, smoothing-compensated (T-SPOON) method for the VBA of diffusion tensor imaging (DTI) data with improved tissue specificity and compensation for image misregistration and smoothing. When compared with conventional VBA methods, the T-SPOON method introduced substantially less errors in the normalized and smoothed DTI maps. Another confound of the conventional DTI-VBA is that it is difficult to differentiate between differences in morphometry and DTI measures that describe tissue microstructure. T-SPOON VBA decreased the effects of differential morphometry in the DTI VBA studies. T-SPOON and conventional VBA were applied to a DTI study of white matter in autism. T-SPOON VBA results were found to be more consistent with region of interest (ROI) measurements in the corpus callosum and temporal lobe regions. The T-SPOON method may be also applicable to other quantitative imaging maps such as T1 or T2 relaxometry, magnetization transfer, or PET tracer maps.

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    • "Both approaches are mainly hypothesis driven and have therefore usually been limited to single regions or specific tracts (Aoki et al., 2013), such as the midsagittal portion of the corpus callosum (Frazier and Hardan, 2009), or the core of the arcuate and uncinate fasciculus (Hardan et al., 2000;Fletcher et al., 2010), but sample sizes have tended to be small (Billeci et al., 2012;Travers et al., 2012;Mueller et al., 2013). Other studies based on meta-analytical approaches (Radua et al., 2011;Aoki et al., 2013;Cauda et al., 2014), voxel-based morphometry (Barnea-Goraly et al., 2004;Keller et al., 2007;Cheung et al., 2009;Ke et al., 2009;Lee et al., 2009;Bloemen et al., 2010;Noriuchi et al., 2010;Groen et al., 2011;Jou et al., 2011), and tract-based spatial statistics (TBSS) (Barnea-Goraly et al., 2010;Cheng et al., 2010;Sahyoun et al., 2010;Jou et al., 2011;Shukla et al., 2010;Walker et al., 2012) have attempted to overcome some of the limitations attributable to small sample size and/or operator-dependent biases. However, it remains unclear whether the findings, if replicated in larger studies, are indicative of tract-specific anomalies in ASD or part of a more generalized brain abnormality (Wolff et al., 2012). "
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    ABSTRACT: It has been postulated that autism spectrum disorder is underpinned by an ‘atypical connectivity’ involving higher-order association brain regions. To test this hypothesis in a large cohort of adults with autism spectrum disorder we compared the white matter networks of 61 adult males with autism spectrum disorder and 61 neurotypical controls, using two complementary approaches to diffusion tensor magnetic resonance imaging. First, we applied tract-based spatial statistics, a ‘whole brain’ non-hypothesis driven method, to identify differences in white matter networks in adults with autism spectrum disorder. Following this we used a tract-specific analysis, based on tractography, to carry out a more detailed analysis of individual tracts identified by tract-based spatial statistics. Finally, within the autism spectrum disorder group, we studied the relationship between diffusion measures and autistic symptom severity. Tract-based spatial statistics revealed that autism spectrum disorder was associated with significantly reduced fractional anisotropy in regions that included frontal lobe pathways. Tractography analysis of these specific pathways showed increased mean and perpendicular diffusivity, and reduced number of streamlines in the anterior and long segments of the arcuate fasciculus, cingulum and uncinate—predominantly in the left hemisphere. Abnormalities were also evident in the anterior portions of the corpus callosum connecting left and right frontal lobes. The degree of microstructural alteration of the arcuate and uncinate fasciculi was associated with severity of symptoms in language and social reciprocity in childhood. Our results indicated that autism spectrum disorder is a developmental condition associated with abnormal connectivity of the frontal lobes. Furthermore our findings showed that male adults with autism spectrum disorder have regional differences in brain anatomy, which correlate with specific aspects of autistic symptoms. Overall these results suggest that autism spectrum disorder is a condition linked to aberrant developmental trajectories of the frontal networks that persist in adult life.
    Full-text · Article · Jan 2016 · Brain
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    • "As a result, neuroimaging studies are increasingly focusing on distributed brain networks in ASD (Noonan et al. 2009; Just et al. 2012). Diffusion-weighted imaging studies have demonstrated local as well as global differences in white matter microstructure in individuals with ASD, who are often reported to have decreased fractional anisotropy (Barnea-Goraly et al. 2004; Alexander et al. 2007; Keller et al. 2007; Sundaram et al. 2008; Thakkar et al. 2008; Lee et al. 2009) and increased mean diffusivity (Alexander et al. 2007; Barnea-Goraly et al. 2010; Fletcher et al. 2010; Sivaswamy et al. 2010), indicating aberrant organization and reduced coherence within white matter tracts. Although specific findings are variable in the literature (Mak-Fan et al. 2012; Travers et al. 2012), the abnormalities are typically widespread and encompass various fiber tracts, including corpus callosum, internal capsule, arcuate fasciculus, uncinate fasciculus, as well as projections to numerous locations in orbitofrontal and medial prefrontal cortex, cingulate cortex, and temporal lobes. "
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    ABSTRACT: Autism spectrum disorder (ASD) includes deficits in social cognition, communication, and executive function. Recent neuroimaging studies suggest that ASD disrupts the structural and functional organization of brain networks and, presumably, how they generate information. Here, we relate deficits in an aspect of cognitive control to network-level disturbances in information processing. We recorded magnetoencephalography while children with ASD and typically developing controls performed a set-shifting task designed to test mental flexibility. We used multiscale entropy (MSE) to estimate the rate at which information was generated in a set of sources distributed across the brain. Multivariate partial least-squares analysis revealed 2 distributed networks, operating at fast and slow time scales, that respond completely differently to set shifting in ASD compared with control children, indicating disrupted temporal organization within these networks. Moreover, when typically developing children engaged these networks, they achieved faster reaction times. When children with ASD engaged these networks, there was no improvement in performance, suggesting that the networks were ineffective in children with ASD. Our data demonstrate that the coordination and temporal organization of large-scale neural assemblies during the performance of cognitive control tasks is disrupted in children with ASD, contributing to executive function deficits in this group.
    Full-text · Article · Apr 2014 · Cerebral Cortex
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    • "Correlation analyses between WM tissue properties and cognitive alterations were performed on a voxel-by-voxel basis. Diffusion-derived maps used for regression analyses were created using a novel data processing technique that increases tissue specificity and compensates for the effect of the spatial smoothing (Lee et al., 2009). "
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    ABSTRACT: Fragile X-associated tremor/ataxia syndrome (FXTAS) is a late-onset movement disorder associated with FMR1 premutation alleles. Asymptomatic premutation (aPM) carriers have preserved cognitive functions, but they present subtle executive deficits. Current efforts are focusing on the identification of specific cognitive markers that can detect aPM carriers at higher risk of developing FXTAS. This study aims at evaluating verbal memory and executive functions as early markers of disease progression while exploring associated brain structure changes using diffusion tensor imaging. We assessed 30 aPM men and 38 intrafamilial controls. The groups perform similarly in the executive domain except for decreased performance in motor planning in aPM carriers. In the memory domain, aPM carriers present a significant decrease in verbal encoding and retrieval. Retrieval is associated with microstructural changes of the white matter (WM) of the left hippocampal fimbria. Encoding is associated with changes in the WM under the right dorsolateral prefrontal cortex, a region implicated in relational memory encoding. These associations were found in the aPM group only and did not show age-related decline. This may be interpreted as a neurodevelopmental effect of the premutation, and longitudinal studies are required to better understand these mechanisms.
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