The Comprehensive Subcortical and Cerebellar Atlas of the Human Brain using multimodal MRI at 7T.
Poster No:
1746
Submission Type:
Abstract Submission
Authors:
Kadharbatcha Saleem1, Alexandru Avram1, Daniel Glen2, Cecil Yen2, Peter Basser1
Institutions:
1Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH, Bethesda, MD, 2National Institute of Mental Health (NIMH), NIH, Bethesda, MD
First Author:
Kadharbatcha Saleem
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH
Bethesda, MD
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH
Bethesda, MD
Co-Author(s):
Alexandru Avram
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH
Bethesda, MD
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH
Bethesda, MD
Peter Basser
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH
Bethesda, MD
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH
Bethesda, MD
Introduction:
The subcortical areas are important targets for neuromodulation devices in the development of new treatments for motor and cognitive-related symptoms [1]. However, detailed parcellation of the subcortical regions using multimodal MRI is limited. Here, we generated a comprehensive Subcortical Atlas of the Human Brain in MNI coordinates using nine microstructural parameters derived from ex vivo ultrahigh-resolution mean apparent propagator (MAP) MRI [2-5], a powerful diffusion MRI framework. We also generated a gray and white matter atlas of the cerebellum derived from the in vivo MNI template and a whole brain connectome dMRI dataset. Tracing and validating these atlas-based deep brain regions is imperative for neurosurgical planning, navigation of deep brain stimulation probes, localization of functional activation regions in fMRI, cross-species comparison, and establishing brain structure-function relationships.
Methods:
We dissected the entire human brainstem, including the thalamus and the basal ganglia, but not the cerebellum, from a postmortem formalin-fixed adult female brain (age: 24 years old; PMI: 34 hr; fixation time: ~6 months). We placed the specimen inside the custom-made mold and container assembly (Fig. 1A-B) and scanned it on a 7T MRI scanner and a MAP-MRI acquisition with 250 μm resolution. We acquired 104 DWIs with multiple b-values (bmax=10000 s/mm2), and pulse duration, and separation of δ=8 ms and Δ=28 ms, respectively. In each voxel, we estimated the MAP and computed microstructural DTI/MAP parameters: fractional anisotropy (FA); mean, axial, and radial diffusivities (MD, AD, and RD, respectively); propagator anisotropy (PA), non-gaussianity (NG), return-to-origin probability (RTOP), return-to-axis probability (RTAP), and return-to-plane probability (RTPP), along with the fiber orientation distribution (FOD) [6] functions. We computed the MT ratio (MTR) from 3D gradient echo images acquired with and without MT preparation. The total duration of the MAP-MRI scan was 62 h and 25 min, and the MT scan was 13 h and 7 min.
We registered the microstructural parameters derived from the ex vivo MAP-MRI dataset to the in vivo MNI_icbm152 template [7]. We also registered the direction-encoded color (DEC) volume derived from the in vivo human whole-brain connectome diffusion MRI and the BigBrain dataset to the same MNI volume [8,9]. All these volumes registered well to the standard MNI space (Fig. 1C), helping us delineate different subcortical nuclei and white matter fiber tracts directly in the MNI template space.
We registered the microstructural parameters derived from the ex vivo MAP-MRI dataset to the in vivo MNI_icbm152 template [7]. We also registered the direction-encoded color (DEC) volume derived from the in vivo human whole-brain connectome diffusion MRI and the BigBrain dataset to the same MNI volume [8,9]. All these volumes registered well to the standard MNI space (Fig. 1C), helping us delineate different subcortical nuclei and white matter fiber tracts directly in the MNI template space.
Results:
We identified and segmented the subregions of the basal ganglia, thalamus, brainstem, amygdala, cerebellum, etc., directly in the coordinates of the in vivo MNI template using the warped ex vivo MAP-MRI, T2W, and MTR images (Fig. 1D; e.g., thalamus). In addition, we also segmented the cerebellar lobules and fiber bundles using the MAP-MRI and FOD-derived DEC map [8,10] (Fig. 1E). These novel brain segmentation are called the Subcortical Atlas of the Human Brain (SAHB) and the Human Cerebellar Atlas (HCA). Figure 2A-B shows two atlases in 2D axial, sagittal, or coronal MRI and 3D.
We also validated the atlas-based areal boundaries of segmented subcortical and cerebellar areas by registering these in vivo SAHB and HCA templates to individual in vivo T1W MRI volumes of control human subjects of different age groups and genders, using a sequence of affine and nonlinear registration steps. This procedure resulted in both SAHB and HCA atlases registered to the individual subject space (Fig. 2C; specific to cerebellar or HCA atlas). These results demonstrate that affine and nonlinear warpings are sufficient to distinguish and provide atlas-based estimates of areal boundaries in control subjects in vivo.
We also validated the atlas-based areal boundaries of segmented subcortical and cerebellar areas by registering these in vivo SAHB and HCA templates to individual in vivo T1W MRI volumes of control human subjects of different age groups and genders, using a sequence of affine and nonlinear registration steps. This procedure resulted in both SAHB and HCA atlases registered to the individual subject space (Fig. 2C; specific to cerebellar or HCA atlas). These results demonstrate that affine and nonlinear warpings are sufficient to distinguish and provide atlas-based estimates of areal boundaries in control subjects in vivo.
Conclusions:
The MAP-MRI enabled noninvasive segmentation of subcortical regions in the human brain. The 3D atlas provides a readily usable standard for region definition, while the template provides a standard reference and space.
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Subcortical Structures 1
White Matter Anatomy, Fiber Pathways and Connectivity
Neuroinformatics and Data Sharing:
Brain Atlases 2
Novel Imaging Acquisition Methods:
Diffusion MRI
Multi-Modal Imaging
Keywords:
Brainstem
Cerebellum
CHEMOARCHITECTURE
Data Registration
HIGH FIELD MR
MRI
Open-Source Software
Sub-Cortical
Thalamus
White Matter
1|2Indicates the priority used for review
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Provide references using APA citation style.
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3. Avram A, Sarlls JE, Barnett AS, Özarslan E, Thomas C, Irfanoglu MO, Hutchinson E, Pierpaoli C, Basser PJ (2016). Clinical feasibility of using mean apparent propagator (MAP) MRI to characterize brain tissue microstructure. Neuroimage 127:422-434.
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