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: 3.59). 08/2007; 28(7):1313-9. DOI: 10.3174/ajnr.A0555
Source: PubMed


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, Oct 08, 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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    ABSTRACT: Diffusion tensor imaging (DTI) histogram metrics are correlated with clinical parameters in cerebral small vessel diseases (cSVD). Whether ADC histogram parameters derived from simple diffusion weighted imaging (DWI) can provide relevant markers for long term studies of cSVD remains unknown. CADASIL patients were evaluated by DWI and DTI in a large cohort study overa6-year period. ADC histogram parameters were compared to those derived from mean diffusivity (MD) histograms in 280 patients using intra-class correlation and Bland-Altman plots. Impact of image corrections applied to ADC maps was assessed and a mixed effect model was used for analyzing the effects of scanner upgrades. The results showed that ADC histogram parameters are strongly correlated to MD histogram parameters and that image corrections have only limited influence on these results. Unexpectedly, scanner upgrades were found to have major effects on diffusion measures with DWI or DTI that can be even larger than those related to patients' characteristics. These data support that ADC histograms from daily used DWI can provide relevant parameters for assessing cSVD, but the variability related to scanner upgrades as regularly performed in clinical centers should be determined precisely for longitudinal and multicentric studies using diffusion MRI in cSVD.
    PLoS ONE 05/2014; 9(5):e97173. DOI:10.1371/journal.pone.0097173 · 3.23 Impact Factor
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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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    ABSTRACT: Diffusion tensor imaging (DTI) provides functionally relevant information about white matter structure. Local anatomical connectivity information combined with fractional anisotropy (FA) and mean diffusivity (MD) may predict functional outcomes in stroke survivors. Imaging methods for predicting functional outcomes in stroke survivors are not well established. This work uses DTI to objectively assess the effects of a stroke lesion on white matter structure and sensorimotor function. A voxel-based approach is introduced to assess a stroke lesion's global impact on motor function. Anatomical T1-weighted and diffusion tensor images of the brain were acquired for nineteen subjects (10 post-stroke and 9 age-matched controls). A manually selected volume of interest was used to alleviate the effects of stroke lesions on image registration. Images from all subjects were registered to the images of the control subject that was anatomically closest to Talairach space. Each subject's transformed image was uniformly seeded for DTI tractography. Each seed was inversely transformed into the individual subject space, where DTI tractography was conducted and then the results were transformed back to the reference space. A voxel-wise connectivity matrix was constructed from the fibers, which was then used to calculate the number of directly and indirectly connected neighbors of each voxel. A novel voxel-wise indirect structural connectivity (VISC) index was computed as the average number of direct connections to a voxel's indirect neighbors. Voxel-based analyses (VBA) were performed to compare VISC, FA, and MD for the detection of lesion-induced changes in sensorimotor function. For each voxel, a t-value was computed from the differences between each stroke brain and the 9 controls. A series of linear regressions was performed between Fugl-Meyer (FM) assessment scores of sensorimotor impairment and each DTI metric's log number of voxels that differed from the control group. Correlation between the logarithm of the number of significant voxels in the ipsilesional hemisphere and total Fugl-Meyer score was moderate for MD (R2 = 0.512), and greater for VISC (R2 = 0.796) and FA (R2 = 0.674). The slopes of FA (p = 0.0036), VISC (p = 0.0005), and MD (p = 0.0199) versus the total FM score were significant. However, these correlations were driven by the upper extremity motor component of the FM score (VISC: R2 = 0.879) with little influence of the lower extremity motor component (FA: R2 = 0.177). The results suggest that a voxel-wise metric based on DTI tractography can predict upper extremity sensorimotor function of stroke survivors, and that supraspinal intraconnectivity may have a less dominant role in lower extremity function.
    Clinical neuroimaging 05/2013; 2(1):767-81. DOI:10.1016/j.nicl.2013.05.009 · 2.53 Impact Factor
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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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    ABSTRACT: Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.
    Frontiers in Neuroscience 03/2013; 7:31. DOI:10.3389/fnins.2013.00031 · 3.66 Impact Factor
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