Construction of brain structural connectivity network using a novel integrated algorithm based on ensemble average propagator.
Comput Biol Med
; 112: 103384, 2019 09.
Article
em En
| MEDLINE
| ID: mdl-31404719
ABSTRACT
An important task for neuroscience is to accurately construct structural connectivity network of human brain. Tractography constructed based on high angular resolution diffusion imaging (HARDI) provides valuable information of human brain structural connections. Existing algorithms, mainly categorized as deterministic or probabilistic, come with inherent limitations (e.g., fiber direction uncertainty induced by noise, or anatomically unreasonable connections and heavy computational cost). In this study, a novel integrated algorithm was proposed to construct brain structural connectivity network by incorporating the deterministic path planning and probabilistic connection strength estimation, based on ensemble average propagator (EAP). We first estimated EAPs from multi-shell samples using the spherical polar Fourier imaging (SPFI), and then extracted diffusion orientations coinciding with neural fiber tracts. Only under angular constraints, the deterministic path planning algorithm was subsequently used to find all reasonable pathways between pairwise white matter (WM) voxels in different regions of interest (ROIs). Consequently, a train of consecutive WM voxels along each of the identified pathways was determined, and the connection strength of these pathways was computed by integrating their EAP alignment over a solid angle. The connection strength of a pair of WM voxels was assigned as the connection strength with the largest connection possibility. Finally, the connection strength between two ROIs was calculated as the sum of all the connection probabilities of each pair of WM voxels in the ROIs. A comparison against voxel-graph based probabilistic tractography method was performed on Fibercup phantom dataset, and the results demonstrated that the proposed method can produce better structural connection and is more computationally economical. Lastly, three datasets from Human Connectome Project (HCP) S1200 group were tested and their structural connectivity networks were constructed for topological analysis. The results showed great consistency in network metrics with previous WM network studies in healthy adults.
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Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Algoritmos
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Processamento de Imagem Assistida por Computador
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Encéfalo
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Imagem de Tensor de Difusão
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Substância Branca
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Modelos Neurológicos
Tipo de estudo:
Prognostic_studies
Limite:
Adult
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Female
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Humans
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Male
Idioma:
En
Revista:
Comput Biol Med
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
China