Reconstruction of major fibers using 7T multi-shell Hybrid Diffusion Imaging in mice

Madelaine Daianu; Russell E. Jacobs; Berislav V. Zlokovic; Axel Montagne; Paul M. Thompson

doi:10.1117/12.2207946

22 December 2015 Reconstruction of major fibers using 7T multi-shell Hybrid Diffusion Imaging in mice

Madelaine Daianu, Russell E. Jacobs, Berislav V. Zlokovic, Axel Montagne, Paul M. Thompson

Proceedings Volume 9681, 11th International Symposium on Medical Information Processing and Analysis; 968109 (2015) https://doi.org/10.1117/12.2207946
Event: 11th International Symposium on Medical Information Processing and Analysis (SIPAIM 2015), 2015, Cuenca, Ecuador

Abstract

Diffusion weighted imaging (DWI) can reveal the orientation of the underlying fiber populations in the brain. High angular resolution diffusion imaging (HARDI) is increasingly used to better resolve the orientation and mixing of fibers. Here, we assessed the added value of multi-shell q-space sampling on the reconstruction of major fibers using mathematical frameworks from q-ball imaging (QBI) and generalized q-sampling imaging (GQI), as compared to diffusion tensor imaging (DTI). We scanned a healthy mouse brain using 7-Tesla 5-shell HARDI (b=1000, 3000, 4000, 8000, 12000 s/mm²), also known as hybrid diffusion imaging (HYDI). We found that QBI may provide greater reconstruction accuracy for major fibers, which improves with the addition of higher b-value shells, unlike GQI or DTI (as expected). Although QBI is a special case of GQI, the major fiber orientation in QBI was more closely related to the orientation in DTI, rather than GQI. HYDI can aid the clinical outcomes of research and especially – more advanced human and animal connectomics projects to map the brain’s neural pathways and networks.

Citation Download Citation

Madelaine Daianu, Russell E. Jacobs, Berislav V. Zlokovic, Axel Montagne, and Paul M. Thompson "Reconstruction of major fibers using 7T multi-shell Hybrid Diffusion Imaging in mice", Proc. SPIE 9681, 11th International Symposium on Medical Information Processing and Analysis, 968109 (22 December 2015); https://doi.org/10.1117/12.2207946

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