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Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging.

Axer M, Strohmer S, Gräßel D, Bücker O, Dohmen M, Reckfort J, Zilles K, Amunts K - Front Neuroanat (2016)

Bottom Line: We have successfully established a concept to bridge the spatial scales from microscopic fiber orientation measurements based on 3D-Polarized Light Imaging (3D-PLI) to meso- or macroscopic dimensions.By creating orientation distribution functions (pliODFs) from high-resolution vector data via series expansion with spherical harmonics utilizing high performance computing and supercomputing technologies, data fusion with Diffusion Magnetic Resonance Imaging has become feasible, even for a large-scale dataset such as the human brain.Validation of our approach was done effectively by means of two types of datasets that were transferred from fiber orientation maps into pliODFs: simulated 3D-PLI data showing artificial, but clearly defined fiber patterns and real 3D-PLI data derived from sections through the human brain and the brain of a hooded seal.

View Article: PubMed Central - PubMed

Affiliation: Research Centre Jülich, Institute of Neuroscience and Medicine Jülich, Germany.

ABSTRACT
Research of the human brain connectome requires multiscale approaches derived from independent imaging methods ideally applied to the same object. Hence, comprehensible strategies for data integration across modalities and across scales are essential. We have successfully established a concept to bridge the spatial scales from microscopic fiber orientation measurements based on 3D-Polarized Light Imaging (3D-PLI) to meso- or macroscopic dimensions. By creating orientation distribution functions (pliODFs) from high-resolution vector data via series expansion with spherical harmonics utilizing high performance computing and supercomputing technologies, data fusion with Diffusion Magnetic Resonance Imaging has become feasible, even for a large-scale dataset such as the human brain. Validation of our approach was done effectively by means of two types of datasets that were transferred from fiber orientation maps into pliODFs: simulated 3D-PLI data showing artificial, but clearly defined fiber patterns and real 3D-PLI data derived from sections through the human brain and the brain of a hooded seal.

No MeSH data available.


Related in: MedlinePlus

Real and simulated brain section from the hooded seal. (A) Blockface image of the optic chiasm of the hooded seal before sectioning. (B) Fiber orientation map of a medial section through the optic chiasm. Optic nerves and optic tracts appear as massive and rather homogeneous fiber bundles. Most fiber tracts from the optic nerves decussate to the contralateral optic tract. (C) The decussation zone in the center (i.e., the chiasm) is characterized by a patch pattern produced by small fiber tracts (red and green color; exemplary orientations are indicated by black lines) and fiber crossings characterized by signal attenuation (blue color; exemplary highlighted by white arrow). Based on this FOM, pliODFs were created for super-voxel dimensions of 40 × 40 × 1 native voxels. (D,E) demonstrate different enlargements of the field of pliODFs overlaid with the input FOM. (F) FOM of a simulated section through the optic chiasm and (G) corresponding pliODFs for super-voxel dimensions of 40 × 40 × 1 native voxels. (H) Zoom into the FOM of the fiber decussation zone and (I) corresponding pliODFs. The effects of crossing and bending fibers on the ODF shapes are obvious.
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Figure 5: Real and simulated brain section from the hooded seal. (A) Blockface image of the optic chiasm of the hooded seal before sectioning. (B) Fiber orientation map of a medial section through the optic chiasm. Optic nerves and optic tracts appear as massive and rather homogeneous fiber bundles. Most fiber tracts from the optic nerves decussate to the contralateral optic tract. (C) The decussation zone in the center (i.e., the chiasm) is characterized by a patch pattern produced by small fiber tracts (red and green color; exemplary orientations are indicated by black lines) and fiber crossings characterized by signal attenuation (blue color; exemplary highlighted by white arrow). Based on this FOM, pliODFs were created for super-voxel dimensions of 40 × 40 × 1 native voxels. (D,E) demonstrate different enlargements of the field of pliODFs overlaid with the input FOM. (F) FOM of a simulated section through the optic chiasm and (G) corresponding pliODFs for super-voxel dimensions of 40 × 40 × 1 native voxels. (H) Zoom into the FOM of the fiber decussation zone and (I) corresponding pliODFs. The effects of crossing and bending fibers on the ODF shapes are obvious.

Mentions: FOMs taken from hooded seal brain tissue show the optic nerve traversing through the optic chiasm into the optic tract (Figures 5A,B). The center of the optic chiasm reveals decussate fiber populations alternating with blue dots caused by signal attenuation (white arrow, Figure 5C). A pattern of crossing fiber tracts was used to prove the functionality of our implementation in a realistic setting. The FOMs were sampled using a histogram binning of (50 latitudes × 100 longitudes + 2 polar caps) = 5002 bins with a super-voxel size of 52 × 52 × 70 μm3, which is equivalent to 40 × 40 × 1 native voxels. The series expansion of the pliODFs was confined to the 6th band. The fused images of the high-resolution FOMs with the corresponding pliODFs demonstrated a sound resampling (Figures 5D,E). The simulated chiasm of the hooded seal was analyzed accordingly and showed concordant results (Figures 5H,I).


Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging.

Axer M, Strohmer S, Gräßel D, Bücker O, Dohmen M, Reckfort J, Zilles K, Amunts K - Front Neuroanat (2016)

Real and simulated brain section from the hooded seal. (A) Blockface image of the optic chiasm of the hooded seal before sectioning. (B) Fiber orientation map of a medial section through the optic chiasm. Optic nerves and optic tracts appear as massive and rather homogeneous fiber bundles. Most fiber tracts from the optic nerves decussate to the contralateral optic tract. (C) The decussation zone in the center (i.e., the chiasm) is characterized by a patch pattern produced by small fiber tracts (red and green color; exemplary orientations are indicated by black lines) and fiber crossings characterized by signal attenuation (blue color; exemplary highlighted by white arrow). Based on this FOM, pliODFs were created for super-voxel dimensions of 40 × 40 × 1 native voxels. (D,E) demonstrate different enlargements of the field of pliODFs overlaid with the input FOM. (F) FOM of a simulated section through the optic chiasm and (G) corresponding pliODFs for super-voxel dimensions of 40 × 40 × 1 native voxels. (H) Zoom into the FOM of the fiber decussation zone and (I) corresponding pliODFs. The effects of crossing and bending fibers on the ODF shapes are obvious.
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Figure 5: Real and simulated brain section from the hooded seal. (A) Blockface image of the optic chiasm of the hooded seal before sectioning. (B) Fiber orientation map of a medial section through the optic chiasm. Optic nerves and optic tracts appear as massive and rather homogeneous fiber bundles. Most fiber tracts from the optic nerves decussate to the contralateral optic tract. (C) The decussation zone in the center (i.e., the chiasm) is characterized by a patch pattern produced by small fiber tracts (red and green color; exemplary orientations are indicated by black lines) and fiber crossings characterized by signal attenuation (blue color; exemplary highlighted by white arrow). Based on this FOM, pliODFs were created for super-voxel dimensions of 40 × 40 × 1 native voxels. (D,E) demonstrate different enlargements of the field of pliODFs overlaid with the input FOM. (F) FOM of a simulated section through the optic chiasm and (G) corresponding pliODFs for super-voxel dimensions of 40 × 40 × 1 native voxels. (H) Zoom into the FOM of the fiber decussation zone and (I) corresponding pliODFs. The effects of crossing and bending fibers on the ODF shapes are obvious.
Mentions: FOMs taken from hooded seal brain tissue show the optic nerve traversing through the optic chiasm into the optic tract (Figures 5A,B). The center of the optic chiasm reveals decussate fiber populations alternating with blue dots caused by signal attenuation (white arrow, Figure 5C). A pattern of crossing fiber tracts was used to prove the functionality of our implementation in a realistic setting. The FOMs were sampled using a histogram binning of (50 latitudes × 100 longitudes + 2 polar caps) = 5002 bins with a super-voxel size of 52 × 52 × 70 μm3, which is equivalent to 40 × 40 × 1 native voxels. The series expansion of the pliODFs was confined to the 6th band. The fused images of the high-resolution FOMs with the corresponding pliODFs demonstrated a sound resampling (Figures 5D,E). The simulated chiasm of the hooded seal was analyzed accordingly and showed concordant results (Figures 5H,I).

Bottom Line: We have successfully established a concept to bridge the spatial scales from microscopic fiber orientation measurements based on 3D-Polarized Light Imaging (3D-PLI) to meso- or macroscopic dimensions.By creating orientation distribution functions (pliODFs) from high-resolution vector data via series expansion with spherical harmonics utilizing high performance computing and supercomputing technologies, data fusion with Diffusion Magnetic Resonance Imaging has become feasible, even for a large-scale dataset such as the human brain.Validation of our approach was done effectively by means of two types of datasets that were transferred from fiber orientation maps into pliODFs: simulated 3D-PLI data showing artificial, but clearly defined fiber patterns and real 3D-PLI data derived from sections through the human brain and the brain of a hooded seal.

View Article: PubMed Central - PubMed

Affiliation: Research Centre Jülich, Institute of Neuroscience and Medicine Jülich, Germany.

ABSTRACT
Research of the human brain connectome requires multiscale approaches derived from independent imaging methods ideally applied to the same object. Hence, comprehensible strategies for data integration across modalities and across scales are essential. We have successfully established a concept to bridge the spatial scales from microscopic fiber orientation measurements based on 3D-Polarized Light Imaging (3D-PLI) to meso- or macroscopic dimensions. By creating orientation distribution functions (pliODFs) from high-resolution vector data via series expansion with spherical harmonics utilizing high performance computing and supercomputing technologies, data fusion with Diffusion Magnetic Resonance Imaging has become feasible, even for a large-scale dataset such as the human brain. Validation of our approach was done effectively by means of two types of datasets that were transferred from fiber orientation maps into pliODFs: simulated 3D-PLI data showing artificial, but clearly defined fiber patterns and real 3D-PLI data derived from sections through the human brain and the brain of a hooded seal.

No MeSH data available.


Related in: MedlinePlus