Use of computational fluid dynamics for 3D fiber tract visualization on human high-thickness histological slices: histological mesh tractography.
Brain Struct Funct
; 226(2): 323-333, 2021 Mar.
Article
em En
| MEDLINE
| ID: mdl-33389040
Understanding the intricate three-dimensional relationship between fiber bundles and subcortical nuclei is not a simple task. It is of paramount importance in neurosciences, especially in the field of functional neurosurgery. The current methods for in vivo and post mortem fiber tract visualization have shortcomings and contributions to the field are welcome. Several tracts were chosen to implement a new technique to help visualization of white matter tracts, using high-thickness histology and dark field images. Our study describes the use of computational fluid dynamic simulations for visualization of 3D fiber tracts segmented from dark field microscopy in high-thickness histological slices (histological mesh tractography). A post mortem human brain was MRI scanned prior to skull extraction, histologically processed and serially cut at 430 µm thickness as previously described by our group. High-resolution dark field images were used to segment the outlines of the structures. These outlines served as basis for the construction of a 3D structured mesh, were a Finite Volume Method (FVM) simulation of water flow was performed to generate streamlines representing the geometry. The simulations were accomplished by an open source computer fluid dynamics software. The resulting simulation rendered a realistic 3D impression of the segmented anterior commissure, the left anterior limb of the internal capsule, the left uncinate fascicle, and the dentato-rubral tracts. The results are in line with clinical findings, diffusion MR imaging and anatomical dissection methods.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Encéfalo
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Imagem de Tensor de Difusão
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Substância Branca
Limite:
Humans
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Male
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Middle aged
Idioma:
En
Revista:
Brain Struct Funct
Ano de publicação:
2021
Tipo de documento:
Article