Journal
FRONTIERS IN NEUROSCIENCE
Volume 10, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fnins.2016.00418
Keywords
HARDI; multi-shell; diffusion spectrum imaging; connectome; connectomics; graph theoretical analysis; network measures
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Funding
- Army Research Laboratory [W911NF-10-2-0022]
- NSF BIGDATA Grant [1247658]
- Human Connectome Project, WU-Minn Consortium [1U54MH091657 NIH]
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [1247658] Funding Source: National Science Foundation
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Multi shell and diffusion spectrum imaging (DSI) are becoming increasingly popular methods of acquiring diffusion MRI data in a research context. However, single-shell acquisitions, such as diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), still remain the most common acquisition schemes in practice. Here we tested whether multi-shell and DSI data have conversion flexibility to be interpolated into corresponding HARDI data. We acquired multi-shell and DSI data on both a phantom and in vivo human tissue and converted them to HARDI. The correlation and difference between their diffusion signals, anisotropy values, diffusivity measurements, fiber orientations, connectivity matrices, and network measures were examined. Our analysis result showed that the diffusion signals, anisotropy, diffusivity, and connectivity matrix of the HARDI converted from multi-shell and DSI were highly correlated with those of the HARDI acquired on the MR scanner, with correlation coefficients around 0.8 similar to 0.9. The average angular error between converted and original HARDI was 20.7 degrees at voxels with signal-to-noise ratios greater than 5. The network topology measures had less than 2% difference, whereas the average nodal measures had a percentage difference around 4 similar to 7%. In general, multi-shell and DSI acquisitions can be converted to their corresponding single-shell HARDI with high fidelity. This supports multi-shell and DSI acquisitions over HARDI acquisition as the scheme of choice for diffusion acquisitions.
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