Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space
Department of Biomedical Engineering, McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada. Journal of Computer Assisted Tomography
(Impact Factor: 1.41).
03/1994; 18(2):192-205. DOI: 10.1097/00004728-199403000-00005
In both diagnostic and research applications, the interpretation of MR images of the human brain is facilitated when different data sets can be compared by visual inspection of equivalent anatomical planes. Quantitative analysis with predefined atlas templates often requires the initial alignment of atlas and image planes. Unfortunately, the axial planes acquired during separate scanning sessions are often different in their relative position and orientation, and these slices are not coplanar with those in the atlas. We have developed a completely automatic method to register a given volumetric data set with Talairach stereotaxic coordinate system.
The registration method is based on multi-scale, three-dimensional (3D) cross-correlation with an average (n > 300) MR brain image volume aligned with the Talariach stereotaxic space. Once the data set is re-sampled by the transformation recovered by the algorithm, atlas slices can be directly superimposed on the corresponding slices of the re-sampled volume. the use of such a standardized space also allows the direct comparison, voxel to voxel, of two or more data sets brought into stereotaxic space.
With use of a two-tailed Student t test for paired samples, there was no significant difference in the transformation parameters recovered by the automatic algorithm when compared with two manual landmark-based methods (p > 0.1 for all parameters except y-scale, where p > 0.05). Using root-mean-square difference between normalized voxel intensities as an unbiased measure of registration, we show that when estimated and averaged over 60 volumetric MR images in standard space, this measure was 30% lower for the automatic technique than the manual method, indicating better registrations. Likewise, the automatic method showed a 57% reduction in standard deviation, implying a more stable technique. The algorithm is able to recover the transformation even when data are missing from the top or bottom of the volume.
We present a fully automatic registration method to map volumetric data into stereotaxic space that yields results comparable with those of manually based techniques. The method requires no manual identification of points or contours and therefore does not suffer the drawbacks involved in user intervention such as reproducibility and interobserver variability.
Available from: Xue Hua
- "We employed TBM to analyze all available ADNI-2 scans at screening and 3, 6, 12, and 24 months. The basic steps of TBM involved linear registration, skull stripping, and nonlinear inverse consistent elastic intensity-based registration (Ashburner and Friston, 2003; Chung et al., 2001; Collins et al., 1994; Freeborough and Fox, 1998; Hua et al., 2013; Iglesias et al., 2011; Leow et al., 2005; Marsden and Hughes, 1994; Mazziotta et al., 2001; Riddle et al., 2004; Thompson et al., 2000; Toga, 1999; Yushkevich et al., 2010; for details, see Supplementary Material). We spatially normalized these longitudinal maps of tissue change across subjects by nonlinearly aligning all individual Jacobian maps to a minimal deformation target (MDT) made for the ADNI-1 study (Hua et al., 2013). "
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ABSTRACT: The goal of this work was to assess statistical power to detect treatment effects in Alzheimer's disease (AD) clinical trials using magnetic resonance imaging (MRI)-derived brain biomarkers. We used unbiased tensor-based morphometry (TBM) to analyze n = 5,738 scans, from Alzheimer's Disease Neuroimaging Initiative 2 participants scanned with both accelerated and nonaccelerated T1-weighted MRI at 3T. The study cohort included 198 healthy controls, 111 participants with significant memory complaint, 182 with early mild cognitive impairment (EMCI) and 177 late mild cognitive impairment (LMCI), and 155 AD patients, scanned at screening and 3, 6, 12, and 24 months. The statistical power to track brain change in TBM-based imaging biomarkers depends on the interscan interval, disease stage, and methods used to extract numerical summaries. To achieve reasonable sample size estimates for potential clinical trials, the minimal scan interval was 6 months for LMCI and AD and 12 months for EMCI. TBM-based imaging biomarkers were not sensitive to MRI scan acceleration, which gave results comparable with nonaccelerated sequences. ApoE status and baseline amyloid-beta positron emission tomography data improved statistical power. Among healthy, EMCI, and LMCI participants, sample size requirements were significantly lower in the amyloid+/ApoE4+ group than for the amyloid-/ApoE4- group. ApoE4 strongly predicted atrophy rates across brain regions most affected by AD, but the remaining 9 of the top 10 AD risk genes offered no added predictive value in this cohort.
Neurobiology of aging 11/2015; DOI:10.1016/j.neurobiolaging.2015.09.018 · 5.01 Impact Factor
- "All MRI volumes were rigidly rotated and translated (3 rotations and 3 translations) to match an initial atlas. All possible pair-wise 12-parameter transformations (3 rotations, translations, scales and shears) (Collins et al., 1994) were estimated and an average linear transformation was calculated for each image, thus effectively scaling each brain to the average size of the population. After applying the average transformation, MRI volumes were averaged in order to create a first population-based model. "
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Chronic high-frequency electrical deep brain stimulation (DBS) of the subcallosal cingulate region is currently being investigated clinically as a therapy for treatment of refractory depression. Experimental DBS of the homologous region, the ventromedial prefrontal cortex (VMPFC), in rodent models has previously demonstrated anti-depressant-like effects. Our goal was to determine if structural remodeling accompanies the alterations of brain function previously observed as a result of chronic DBS.
Here we applied 6h of high-frequency bilateral VMPFC DBS daily to 8 9-week old C57Bl/6 mice for 5days. We investigated the "micro-lesion" effect by using a sham stimulation group (8 mice) and a control group (8 mice with a hole drilled into the skull only). Whole brain anatomy was investigated post-mortem using high-resolution magnetic resonance imaging and areas demonstrating volumetric expansion were further investigated using histology and immunohistochemistry.
The DBS group demonstrated bilateral increases in whole hippocampus and the left thalamus volume compared to both sham and control groups. Local hippocampal and thalamic volume increases were also observed at the voxel-level; however these increases were observed in both DBS and sham groups. Follow-up immunohistochemistry in the hippocampus revealed DBS increased blood vessel size and synaptic density relative to the control group whereas the sham group demonstrated increased astrocyte size.
Our work demonstrates that DBS not only works by altering function with neural circuits, but also by structurally altering circuits at the cellular level. Neuroplastic alterations may play a role in mediating the clinical efficacy of DBS therapy.
NeuroImage 11/2015; 125:422-427. DOI:10.1016/j.neuroimage.2015.10.049 · 6.36 Impact Factor
Available from: PubMed Central
- "The first widely-adopted template was based on the brain of a single subject (Talairach and Tournoux, 1988). However, shortly thereafter a group of researchers from Canada, The United States, and Germany formed the International Consortium for Brain Mapping (ICBM), which set out to create standardized human brain atlases that were based on high-resolution anatomical MRI data from large populations of healthy control subjects (Evans et al., 1992, 1993; Collins et al., 1994; Mazziotta et al., 1995). These templates have since been adopted by neuroimaging researchers around the world for normalizing individual data for group analyses, and to this day are distributed with many popular image processing and fMRI analysis software packages (c.f., Brett et al., 2002; Lancaster et al., 2007). "
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ABSTRACT: Diffusion tensor imaging (DTI) is a powerful MRI technique that can be used to estimate both the microstructural integrity and the trajectories of white matter pathways throughout the central nervous system. This fiber tracking (aka, “tractography”) approach is often carried out using anatomically-defined seed points to identify white matter tracts that pass through one or more structures, but can also be performed using functionally-defined regions of interest (ROIs) that have been determined using functional MRI (fMRI) or other methods. In this study, we performed fMRI-guided DTI tractography between all of the previously defined nodes within each of six common resting-state brain networks, including the: dorsal Default Mode Network (dDMN), ventral Default Mode Network (vDMN), left Executive Control Network (lECN), right Executive Control Network (rECN), anterior Salience Network (aSN), and posterior Salience Network (pSN). By normalizing the data from 32 healthy control subjects to a standard template—using high-dimensional, non-linear warping methods—we were able to create probabilistic white matter atlases for each tract in stereotaxic coordinates. By investigating all 198 ROI-to-ROI combinations within the aforementioned resting-state networks (for a total of 6336 independent DTI tractography analyses), the resulting probabilistic atlases represent a comprehensive cohort of functionally-defined white matter regions that can be used in future brain imaging studies to: (1) ascribe DTI or other white matter changes to particular functional brain networks, and (2) compliment resting state fMRI or other functional connectivity analyses.
Frontiers in Human Neuroscience 11/2015; 9(585):1-20. DOI:10.3389/fnhum.2015.00585 · 3.63 Impact Factor
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