Whole-Brain Histogram and Voxel-Based Analyses of Diffusion Tensor Imaging in Patients with Leukoaraiosis: Correlation with Motor and Cognitive Impairment

Radiodiagnostic Section, Department of Clinical Physiopathology, University of Florence, Florence, and Medical Physics, Azienda Ospedaliera Universitaria Pisana, Pisa, Italy.
American Journal of Neuroradiology (Impact Factor: 3.68). 08/2007; 28(7):1313-9. DOI: 10.3174/ajnr.A0555
Source: PubMed

ABSTRACT Cerebral white matter changes, termed leukoaraiosis (LA), appearing as areas of increased signal intensity in T2-weighted MR images, are common in elderly subjects, but the possible correlation of LA with cognitive or motor deficit has not been established. We hypothesized that histogram and voxel-based analyses of whole-brain mean diffusivity (MD) and fractional anisotropy (FA) maps calculated from diffusion tensor imaging (DTI) could be more sensitive tools than visual scales to investigate the clinical correlates of LA.
Thirty-six patients of the Leukoaraiosis and Disability Study were evaluated with fluid-attenuated inversion recovery for LA extension, T1-weighted images for volume, and DTI for MD and FA. The extent of LA was rated visually. The normalized total, gray, and white matter brain volumes were computed, as well as the 25th percentile, 50th percentile, kurtosis, and skewness of the MD and FA maps of the whole brain. Finally, voxel-based analysis on the maps of gray and white matter volume, MD, and FA was performed with SPM2 software. Correlation analyses between visual or computerized data and motor or neuropsychologic scale scores were performed using the Spearman rank test and the SPM2 software.
The visual score correlated with some MD and FA histogram metrics (P<.01). However, only the 25th and 50th percentiles, kurtosis, and skewness of the MD and FA histograms correlated with motor or neuropsychologic deficits. Voxel-based analysis revealed a correlation (P<.05 corrected for multiple comparisons) between a large cluster of increased MD in the corpus callosum and pericallosal white matter and motor deficit.
These results are consistent with the hypothesis that histogram and voxel-based analyses of the whole-brain MD and FA maps are more sensitive tools than the visual evaluation for clinical correlation in patients with LA.

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Available from: Emilia Salvadori, Sep 02, 2015
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    • "Metrics derived from whole brain MD histograms using DTI previously emerged as reliable and precise markers of disease severity and appeared particularly promising for monitoring disease progression in cSVD[10], [11], [13], [15], [21], [22].Although some studies based on routine DWI-derived ADC histograms already provided significant results[24], different diffusion MR techniques for assessing microstructural changes in cSVD have not been directly compared so far. In the present study, ADC histogram parameters obtained with DWI were found strongly correlated to parameters derived from MD histograms after CSF removal obtained with DTI and considered as the “gold standard” measure of diffusion in cSVD. "
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    • "A voxel-based analysis involves the normalization of images (through registration and spatial filtering) followed by statistical comparisons of DTI parameters of the resulting maps (Ashburner and Friston, 2000; Wright et al., 1995). These analyses have been applied to DTI parameters of the brain in normal development and aging (Della Nave et al., 2007; Snook et al., 2007), following traumatic injury (Bendlin et al., 2008; Chu et al., 2010) and during progressive disease (Agosta et al., 2007; Sage et al., 2009; Thivard et al., 2007). Conversely, there are limitations to voxel-based analyses including dependence on the quality of image registration across subjects and effects of smoothing applied to the images (Abe et al., 2010; Ashburner and Friston, 2001; Bookstein, 2001; Van Hecke et al., 2011). "
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    • "The histogram of each diffusion parameter presents the mean, the peak height and location, values that can be used to compare groups through statistical tests (Figure 1M). Histograms allow analysis of whole brain in an automated way, without any a priori specified ROI; however, such an approach requires the removal of the tissue of no interest (typically CSF), does not retain any information about the location of abnormalities and is sensitive to partial volume effect from atrophy (Della Nave et al., 2007; Jones and Cercignani, 2010; Zhou et al., 2011a). For such approach, tools such as TrackVis or MedINRIA can be used. "
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