This project will collect a unique, multi-modal, multi-contrast dataset with tracer injections and diffusion MRI in the same macaque brains. We will use this dataset to develop novel algorithms for inferring local fiber architectures from diffusion MRI. The goal is to overcome the limitations of current methods for diffusion orientation reconstruction, which are designed to resolve fiber crossings but not to distinguish between crossings and other configurations, such as branching, turning, fanning, etc. More broadly, the proposed dataset will allow us to investigate organizational principles of brain pathways and to provide a testbed for the neuroimaging community to evaluate the accuracy of diffusion tractography and microstructural modeling techniques. The project is a collaboration between groups with extensive expertise in diffusion MRI methodological development (MGH Martinos Center) and anatomical tracer studies (University of Rochester). We have previously collected high-resolution ex vivo diffusion MRI data on a set of macaque brains that had also received tracer injections. We have recently used these data in an open tractography challenge, with the participation of research teams from around the world. This was the first challenge of its kind to provide diffusion MRI data suitable for all state-of-the-art diffusion reconstruction methods (e.g., multi-shell or Cartesian grid sampling), in addition to providing the tracer injections in the same brains as the MRI scans. Our own preliminary studies and the challenge itself offer several insights into the performance of state-of-the-art tractography methods. For example, our results indicate that, while most tractography methods would require their parameters to be tuned differently to achieve optimal accuracy for different cortical seed regions, there are approaches that are robust across cortical areas. Furthermore, our results suggest that errors occur frequently in areas where the fiber architecture is not well modeled by a crossing. Thus there is a need for novel tractography approaches that go beyond the crossing-fiber paradigm. Here we propose to develop such an approach. Our prior work included injection sites in the frontal, prefrontal, and cingulate cortices only. Here we propose to investigate the extent to which our prior findings generalize across the brain, by performing tracer injections that sample a wider range of cortical areas. Furthermore, we will extend our acquisition protocol to acquire data appropriate not only for tractography, but also for microstructural and myelin mapping. These data will allow us to answer a broader range of questions about tractography, microstructure, and their intersection. Beyond the methodological development proposed in this project, the data will also be an invaluable resource to the neuroimaging community, providing researchers with a framework for the objective assessment of current diffusion MRI analysis methods and identifying areas for improvement to guide the development of next-generation techniques.
This project will study organizational principles of brain pathways with a combination of chemical tracing and diffusion MRI. The ultimate goal is to assess and improve the accuracy of diffusion MRI, which is currently the only technique for imaging these pathways non-invasively and studying their role in the healthy and diseased brain in vivo. The unique dataset collected by this project will provide a testbed that can aid the neuroimaging research community in identifying shortcomings of current diffusion MRI analysis techniques and provide guidance towards seeking alternative approaches that overcome these shortcomings.
