Mapping human neurocircuitry across scales with diffusion MRI and optical imaging

NIH RePORTER · NIH · R01 · $632,897 · view on reporter.nih.gov ↗

Abstract

Project summary: The overarching goals of this project are to image human white-matter circuitry ex vivo with cutting-edge technologies, including ultra-high gradient-strength diffusion MRI (dMRI) and direct measurements of axonal orientations with polarization-sensitive optical coherence tomography (PS-OCT); and use the microscopic-scale PS-OCT data to inform the development of more accurate algorithms for reconstructing brain circuitry from mesoscopic-scale dMRI. In the previous funding cycle, we constructed a unique, 48-channel receive array coil for imaging whole human brains on the 3T Connectome MRI scanner with high sensitivity at sub-mm resolution; we blocked human brains and imaged small samples with even higher-resolution dMRI in a pre-clinical scanner; and we compared the mesoscopic diffusion orientation estimates obtained from different q-space sampling schemes and reconstruction methods to microscopic measurements of in-plane axonal orientations from PS-OCT. This work provided us with several insights on the fiber configurations that are most challenging to dMRI techniques, as well as the relative contribution of acquisition parameters such as spatial and angular resolution to the accuracy of dMRI. In the next funding cycle, we propose to extend this work in ways that will allow us to use the optical microscopy data not only to assess the accuracy of existing dMRI analysis methods, but also to engineer the next generation of methods. First, we will use a modified PS-OCT setup that will allow us to measure not only in-plane but 3D orientations. Second, we will extend our ex vivo dMRI data acquisition to allow microstructural modeling, and we will use the ground-truth axonal orientations from PS-OCT to investigate whether MR-based microstructural indices are continuous along axon bundles and different between bundles, i.e., to test the basic premise of microstructure- guided tractography. Third, we will use the dMRI and PS-OCT data to train models for classifying different fiber configurations (crossing, branching, turning, etc) directly from dMRI. The ultimate goal of the proposed data acquisition and algorithmic development is to explore alternative (model-based or model-free) approaches to tackling the ambiguities that lead to errors in conventional dMRI tractography methods. This project will take advantage of the cutting-edge imaging technologies available at the MGH Martinos Center, and an investigative team with complementary expertise in tractography, microstructural analysis, and optics. The PI has a track record of developing open-source software tools and, during the previous cycle, spearheaded the IronTract Challenge, with the participation of tractography developers from 20 institutions worldwide. We will continue these practices of sharing software and data, as well as engaging the research community, during the next cycle. The proposed work will produce (i) a unique set of post mortem MRI and optical imaging data that can...

Key facts

NIH application ID
10889741
Project number
9R01NS127353-05A1
Recipient
MASSACHUSETTS GENERAL HOSPITAL
Principal Investigator
Anastasia Yendiki
Activity code
R01
Funding institute
NIH
Fiscal year
2024
Award amount
$632,897
Award type
9
Project period
2024-04-15 → 2029-02-28