Probing Tissue Microarchitecture of the Baby Brain via Spherical Mean Spectrum Imaging
| Autor: | Kim-Han Thung, Geng Chen, Weili Lin, Tiantian Xu, Pew Thian Yap, Haiyong Wu, Xifeng Wang, Ye Wu, Dinggang Shen, Khoi Minh Huynh |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
FOS: Physical sciences
computer.software_genre Thermal diffusivity Article 030218 nuclear medicine & medical imaging Spherical mean 03 medical and health sciences 0302 clinical medicine Nuclear magnetic resonance Voxel Fractional anisotropy Neurites FOS: Electrical engineering electronic engineering information engineering Humans Electrical and Electronic Engineering Diffusion (business) Physics Radiological and Ultrasound Technology Orientation (computer vision) Isotropy Image and Video Processing (eess.IV) Brain Electrical Engineering and Systems Science - Image and Video Processing Physics - Medical Physics Computer Science Applications Diffusion Magnetic Resonance Imaging Diffusion Tensor Imaging Anisotropy Medical Physics (physics.med-ph) computer Software Diffusion MRI |
| Zdroj: | IEEE Trans Med Imaging |
| Popis: | During the first years of life, the human brain undergoes dynamic spatially-heterogeneous changes, involving differentiation of neuronal types, dendritic arborization, axonal ingrowth, outgrowth and retraction, synaptogenesis, and myelination. To better quantify these changes, this article presents a method for probing tissue microarchitecture by characterizing water diffusion in a spectrum of length scales, factoring out the effects of intra-voxel orientation heterogeneity. Our method is based on the spherical means of the diffusion signal, computed over gradient directions for a fixed set of diffusion weightings (i.e., b-values). We decompose the spherical mean series at each voxel into a spherical mean spectrum (SMS), which essentially encodes the fractions of spin packets undergoing fine- to coarse-scale diffusion processes, characterizing hindered and restricted diffusion stemming respectively from extra- and intra-neurite water compartments. From the SMS, multiple orientation distribution invariant indices can be computed, allowing for example the quantification of neurite density, microscopic fractional anisotropy ($\mu$FA), per-axon axial/radial diffusivity, and free/restricted isotropic diffusivity. We show maps of these indices for baby brains, demonstrating that microscopic tissue features can be extracted from the developing brain for greater sensitivity and specificity to development related changes. Also, we demonstrate that our method, called spherical mean spectrum imaging (SMSI), is fast, accurate, and can overcome the biases associated with other state-of-the-art microstructure models. |
| Databáze: | OpenAIRE |
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