NeuroImage
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Randomized Controlled Trial
Determining the optimal level of smoothing in cortical thickness analysis: a hierarchical approach based on sequential statistical thresholding.
The extent of smoothing applied to cortical thickness maps critically influences sensitivity, anatomical precision and resolution of statistical change detection. Theoretically, it could be optimized by increasing the trade-off between vertex-wise sensitivity and specificity across several levels of smoothing. But to date neither parametric nor nonparametric methods are able to control the error at the vertex level if the null hypothesis is rejected after smoothing of cortical thickness maps. ⋯ The hierarchical method was further validated in a cross-sectional study comparing moderate Alzheimer's disease (AD) patients with healthy elderly subjects. Results suggest that the extent of cortical thinning reported in previous AD studies might be artificially inflated by the choice of inadequate smoothing. In these cases, interpretation should be based on the location of local maxima of suprathreshold regions rather than on the spatial extent of the detected signal in the statistical parametric map.
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Quantitative assessment of the myelin water content in the brain can substantially improve our understanding of white matter diseases such as multiple sclerosis. In this study, in vivo myelin water content was estimated using T(2)* relaxation with multi-slice acquisitions in magnetic resonance imaging (MRI). The main advantages of using T(2)* relaxation are (1) a low specific absorption rate (SAR), which is especially beneficial for imaging at high field strengths, (2) a short first-echo time (approximately 2 ms) and short echo spacing (approximately 1 ms), which allows for the acquisition of multiple sampling points during the fast decay of the myelin water signal, and (3) fast multi-slice acquisitions. ⋯ Local field gradients (LFG) were estimated from the acquired multi-slice data, and the LFG-induced signal decays were corrected with a first-order approximation of LFG using the sinc function. The corrected T(2)* signal decays were analyzed with a three-pool model to quantify MWF. Our results demonstrate the feasibility of in vivo multi-slice mapping of MWF using multi-compartmental analysis of the T(2)* signal decay.
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Structural magnetic resonance imaging (MRI) of brain tissue loss and physiological imaging of regional cerebral blood flow (rCBF) can provide complimentary information for the characterization of brain disorders, such as Alzheimer's disease (AD) but studies into gains in classification power for AD using these image modalities jointly have been limited. Our aim in this study was to determine the joint contribution of structural and perfusion-weighted imaging for the classification of AD in a cross-sectional study using an integrated multimodality MRI processing framework and a cortical surface-based analysis approach. We used logistic regression analysis to determine sequentially the value of cortical thickness, rCBF, and cortical thickness and rCBF jointly for classification for diagnosis of AD compared to controls. ⋯ However there was also a positive interaction between reduced rCBF and cortical thinning in the right superior temporal sulcus, implying that structural and physiological brain alterations in AD can be complementary. Compared to reduced rCBF, regional cortical thinning better explained the variability in dementia severity. In conclusion, structural brain alterations compared to physiological variations are the dominant features of MRI in AD.
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Comparative Study
Quantitative evaluation of LDDMM, FreeSurfer, and CARET for cortical surface mapping.
Cortical surface mapping has been widely used to compensate for individual variability of cortical shape and topology in anatomical and functional studies. While many surface mapping methods were proposed based on landmarks, curves, spherical or native cortical coordinates, few studies have extensively and quantitatively evaluated surface mapping methods across different methodologies. In this study we compared five cortical surface mapping algorithms, including large deformation diffeomorphic metric mapping (LDDMM) for curves (LDDMM-curve), for surfaces (LDDMM-surface), multi-manifold LDDMM (MM-LDDMM), FreeSurfer, and CARET, using 40 MRI scans and 10 simulated datasets. ⋯ Our results revealed that the LDDMM-curve, MM-LDDMM, and CARET approaches best aligned the local curve features with their own curves. The MM-LDDMM approach was also found to be the best in aligning the local regions and cortical folding patterns (e.g., curvature) as compared to the other mapping approaches. The simulation experiment showed that the MM-LDDMM mapping yielded less local and global deformation errors than the CARET and FreeSurfer mappings.
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Case Reports
DTI fiber tracking to differentiate demyelinating diseases from diffuse brain stem glioma.
Intrinsic diffuse brainstem tumors and demyelinating diseases primarily affecting the brainstem can share common clinical and radiological features, sometimes making the diagnosis difficult especially at the time of first clinical presentation. To explore the potential usefulness of new MRI sequences in particular diffusion tensor imaging fiber tracking in differentiating these two pathological entities, we review a series of brainstem tumors and demyelinating diseases treated at our institution. ⋯ DTI fiber tracking of the pyramid tracts in patients with suspected intrinsic brainstem tumor or demyelinating disease presents two clearly different patterns that may help in differentiating between these two pathologies when conventional MRI and clinical data are inconclusive.