Research

New Tractography Modalities

(a) Conventional tractography map existence of all fiber pathways, whereas (b) differential tractography uses longitudinal scans to map pathways with neuronal change for disease diagnosis or monitoring.http://dsi-studio.labsolver.org/Manual/differential-tractographyReference:

Differential tractography

Tractography analysis often separates tractography mapping step from its analysis, but higher sensitivity and specificity could be achieved by integrating them together as novel tractography modalities. To this end, we introduce "differential tractography," a new tractography modality that adopts a “tracking-the-differences” paradigm to track pathways with neuronal change in a patient.

Tool and documentation:

http://dsi-studio.labsolver.org/Manual/differential-tractography

Reference:

  • Yeh FC, Badre D, Verstynen T. Connectometry: a statistical approach harnessing the analytical potential of the local connectome. NeuroImage. 2016 Jan 15;125:162-71.2019 Nov 15;202:116131.

Correlational tractography

For group studies, we further adopting a “tracking-the-correlation” paradigm and introduce "correlational tractography" to map fiber pathways correlated with a study variable. The correlation analysis used, which we called connectometry, can leverage multiple regression, partial correlation, or non-parametric correlation to derive correlational tractography and study the circuit mechanism.

Tool and documentation:

http://dsi-studio.labsolver.org/Manual/diffusion-mri-connectometry

Reference:

  • Yeh FC, Badre D, Verstynen T. Connectometry: a statistical approach harnessing the analytical potential of the local connectome. NeuroImage. 2016 Jan 15;125:162-71.
  • Hula WD, Panesar S, Gravier ML, Yeh FC, Dresang HC, Dickey MW, Fernandez-Miranda JC. Structural white matter connectometry of word production in aphasia: an observational study. Brain. 2020 Aug 1;143(8):2532-44.
Correlational tractography showing pathways positively (red) and negatively (light yellow) correlated with semantic processing in patients with aphasic stroke. (Hula et al. Brain 143.8 (2020): 2532-2544.)

Construction of Tractography Atlases

Population averaged tractography atlas created using Human Connectome Project Data

Human Tractography Atlas

We introduced an expert-vetted, population-based atlas of the structural connectome derived from diffusion MRI data. This was achieved by creating a high-resolution template of diffusion patterns averaged across individual subjects and using tractography to generate trajectories of representative white matter fascicles. The trajectories were clustered and labeled by a team of experienced neuroanatomists.

This atlas of the structural connectome represents normative neuroanatomical organization of human brain white matter, complimentary to traditional histologically-derived and voxel-based white matter atlases, allowing for better modeling and simulation of brain connectivity for future connectomic studies as well as clinical and educational applications.

Download:

http://brain.labsolver.org

Reference:

  • Yeh FC, Panesar S, Fernandes D, Meola A, Yoshino M, Fernandez-Miranda JC, Vettel JM, Verstynen T. Population-averaged atlas of the macroscale human structural connectome and its network topology. NeuroImage. 2018 Sep 1;178:57-68.

Decode Structure-Function Relation using Diffusion MRI Connectomics

Local Connectome Fingerprints

Local connectome fingerprints (LCF) provide a subject-specific quantification of brain connections in a standard space at the voxel level. LCF does not map the entire connectome. It is derived from diffusion MRI to sense microscopic water movement restricted by axons and to capture piece-wise information of the human connectome at the voxel level. LCF allows us to study their connectivity from a bottom-up perspective.


LCF provides a highly specific measurement for characterizing brain connections and can achieve a uniqueness at 10-6. In comparison, the uniqueness achieved by other fingerprinting approaches such as fMRI or dMRI connectome is only around 1%~10% (error rate, lower the better). Their low specificity is due to the fact that fMRI is highly sensitive to the functional status of the brain and can be affected by subject's current brain activities, whereas dMRI connectomics uses fiber tracking methods or axonal tracing techniques, which is known to be sensitive to parameters and tends to give a substantial amount of false connections. LCF is based on diffusion MRI and does not rely on fiber tracking to quantify connectivity.


Data and Challenges:

http://dsi-studio.labsolver.org/download-images/local-connectome-fingerprints-of-hcp-1062-subjects-for-neofac-prediction


Reference:

Yeh FC, Vettel JM, Singh A, Poczos B, Grafton ST, Erickson KI, Tseng WY, Verstynen TD. Quantifying differences and similarities in whole-brain white matter architecture using local connectome fingerprints. PLoS computational biology. 2016 Nov 15;12(11):e1005203.

DSI Studio—An Integrative Platform for Neurosurgery Planning

DSI Studio

  • Brain tumor pre-surgical planning

  • sEEG electrodes and tractography visualization

Mapping the trajectories of human connectome and explore its properties is one of the largest endeavors in neuroscience. DSI Studio is an open source diffusion MRI analysis tool that maps brain connections, characterizes their biophysical metrics, and correlates the metrics with neuropsychological variables. It is a collective implementation of diffusion MRI methods and has established its unique scientific impact.

Website:http://dsi-studio.labsolver.org

http://dsi-studio.labsolver.org/download-images/local-connectome-fingerprints-of-hcp-1062-subjects-for-neofac-prediction


Reference: