Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 3 de 3
Filtrar
Mais filtros

Bases de dados
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
Neuroimage ; 236: 118080, 2021 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-33882348

RESUMO

The brainstem is one of the most densely packed areas of the central nervous system in terms of gray, but also white, matter structures and, therefore, is a highly functional hub. It has mainly been studied by the means of histological techniques, which requires several hundreds of slices with a loss of the 3D coherence of the whole specimen. Access to the inner structure of the brainstem is possible using Magnetic Resonance Imaging (MRI), but this method has a limited spatial resolution and contrast in vivo. Here, we scanned an ex vivo specimen using an ultra-high field (11.7T) preclinical MRI scanner providing data at a mesoscopic scale for anatomical T2-weighted (100 µm and 185 µm isotropic) and diffusion-weighted imaging (300 µm isotropic). We then proposed a hierarchical segmentation of the inner gray matter of the brainstem and defined a set of rules for each segmented anatomical class. These rules were gathered in a freely accessible web-based application, WIKIBrainStem (https://fibratlas.univ-tours.fr/brainstems/index.html), for 99 structures, from which 13 were subdivided into 29 substructures. This segmentation is, to date, the most detailed one developed from ex vivo MRI of the brainstem. This should be regarded as a tool that will be complemented by future results of alternative methods, such as Optical Coherence Tomography, Polarized Light Imaging or histology… This is a mandatory step prior to segmenting multiple specimens, which will be used to create a probabilistic automated segmentation method of ex vivo, but also in vivo, brainstem and may be used for targeting anatomical structures of interest in managing some degenerative or psychiatric disorders.


Assuntos
Atlas como Assunto , Tronco Encefálico/anatomia & histologia , Substância Cinzenta/anatomia & histologia , Imageamento por Ressonância Magnética/métodos , Neuroimagem/métodos , Tronco Encefálico/diagnóstico por imagem , Substância Cinzenta/diagnóstico por imagem , Humanos
2.
Neuroimage ; 103: 106-118, 2014 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-25234114

RESUMO

INTRODUCTION: Diffusion tractography relies on complex mathematical models that provide anatomical information indirectly, and it needs to be validated. In humans, up to now, tractography has mainly been validated by qualitative comparison with data obtained from dissection. No quantitative comparison was possible because Magnetic Resonance Imaging (MRI) and dissection data are obtained in different reference spaces, and because fiber tracts are progressively destroyed by dissection. Here, we propose a novel method and software (FIBRASCAN) that allow accurate reconstruction of fiber tracts from dissection in MRI reference space. METHOD: Five human hemispheres, obtained from four formalin-fixed brains were prepared for Klingler's dissection, placed on a holder with fiducial markers, MR scanned, and then dissected to expose the main association tracts. During dissection, we performed iterative acquisitions of the surface and texture of the specimens using a laser scanner and two digital cameras. Each texture was projected onto the corresponding surface and the resulting set of textured surfaces was coregistered thanks to the fiducial holders. The identified association tracts were then interactively segmented on each textured surface and reconstructed from the pile of surface segments. Finally, the reconstructed tracts were coregistered onto ex vivo MRI space thanks to the fiducials. Each critical step of the process was assessed to measure the precision of the method. RESULTS: We reconstructed six fiber tracts (long, anterior and posterior segments of the superior longitudinal fasciculus; Inferior fronto-occipital, Inferior longitudinal and uncinate fasciculi) from cadaveric dissection and ported them into ex vivo MRI reference space. The overall accuracy of the method was of the order of 1mm: surface-to-surface registration=0.138mm (standard deviation (SD)=0.058mm), deformation of the specimen during dissection=0.356mm (SD=0.231mm), and coregistration surface-MRI=0.6mm (SD=0.274mm). The spatial resolution of the method (distance between two consecutive surface acquisitions) was 0.345mm (SD=0.115mm). CONCLUSION: This paper presents the robustness of a novel method, FIBRASCAN, for accurate reconstruction of fiber tracts from dissection in the ex vivo MR reference space. This is a major step toward quantitative comparison of MR tractography with dissection results.


Assuntos
Córtex Cerebral/anatomia & histologia , Processamento de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Vias Neurais/anatomia & histologia , Substância Branca/anatomia & histologia , Cadáver , Imagem de Tensor de Difusão/métodos , Dissecação , Humanos , Software
3.
Stud Health Technol Inform ; 184: 392-6, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-23400190

RESUMO

This paper presents an immersive visualization tool that helps anatomists to establish a ground truth for brain white matter fiber bundles. Each step of a progressive anatomical dissection of human brain hemisphere is acquired using a high resolution 3D laser scanner and a photographic device. Each resulting surface is textured with a high resolution image and registered into a common 3D space using fiducial landmarks. Surfaces can be visualized using stereoscopic hardware and are interactively selectable. The tool allows the user to identify specific fiber bundle parts. Extracted fiber bundles are stacked together and rendered in stereoscopy with the corresponding MR volume. Surgeons have validated this tool for creating ground truth in medical imaging with the perspective of validating tractography algorithms.


Assuntos
Encéfalo/citologia , Imagem de Tensor de Difusão/métodos , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Modelos Neurológicos , Fibras Nervosas Mielinizadas/ultraestrutura , Interface Usuário-Computador , Gráficos por Computador , Simulação por Computador , Dissecação/métodos , Humanos
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA