bioRxivBioengineeringPreprint
Imaging the structural connectome with hybrid diffusion MRI-microscopy tractography
S. Zhu, I. N. Huszar, M. Cottaar, G. Daubney, N. Eichert, T. Hanayik, A. A. Khrapitchev, R. B. Mars, J. Mollink, J. Sallet, C. Scott, A. Smart, S. Jbabdi, K. L. Miller, A. F. Howard
Abstract
Neuroanatomical tract tracing methods are fundamental in providing "gold standard" estimates of brain connectivity. However, tracer methods cannot be performed in humans and even in animals, we can only study projections from typically one or two injection sites per animal sacrificed. Orientation-sensitive microscopy techniques such as PLI provide an alternative where they can visualise detailed fibre orientations at the micron-scale across the whole brain. However, these methods are often most informative on orientations within the 2D imaging plane, with less reliable or missing through-plane information, restricting 3D tract reconstruction. Conversely, dMRI can estimate fibre orientations in 3D but at low resolution, which leads to many false positive and negative estimates of fibre trajectories. To facilitate reconstruction of the microscopy-informed connectome, we develop a data-fusion method that complements 2D microscopy with through-plane information from diffusion MRI to construct 3D hybrid orientations that are both maximally informed by the high-resolution microscopy, have whole-brain coverage and can be input into existing tractography pipelines. Diffusion MRI can be readily acquired prior to microscopy meaning the same method is translatable across species, including in humans. Here we apply our method to an existing open-access macaque dataset and demonstrate (1) whole-brain microscopy-informed tractography (2) the advantages of hybrid tractography in two known tractography challenges, the gyral bias and bottleneck problem (3) how hybrid tractography appears to outperform diffusion-only tractography when compared to tracer data and (4) the generalisability of our hybrid method to different microscopy contrasts, facilitating wider translation.
- organism: non-human primate
- assay: imaging
- assay: structural biology
- research focus: synaptic & neural circuits
- approach: deep learning
- approach: statistical model
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