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Improving model-based functional near-infrared spectroscopy analysis using mesh-based anatomical and light-transport
Anh Phong Tran1, Shijie Yan2, Qianqian Fang3,2
1Northeastern University, Department of Chemical Engineering, Boston, Massachusetts, United States.
Neurophotonics
|March 3, 2020
Summary
Accurate anatomical models are crucial for functional near-infrared spectroscopy (fNIRS) brain imaging. This study introduces a new method for creating high-quality brain meshes, improving photon transport simulations and brain activity quantification in fNIRS research.
Area of Science:
- Neuroimaging
- Biomedical Engineering
- Computational Science
Background:
- Functional near-infrared spectroscopy (fNIRS) is a key tool for brain research.
- Accurate fNIRS analysis depends on precise computational models of photon transport through brain anatomy.
- Existing anatomical modeling methods may limit the accuracy of fNIRS quantification.
Purpose of the Study:
- To emphasize the critical role of accurate anatomical modeling in fNIRS studies.
- To present a robust method for generating high-quality tetrahedral mesh models of the brain and full head.
- To enhance neuroimaging analysis through improved anatomical representations.
Main Methods:
- Developed a novel surface-based pipeline for creating brain mesh models from segmented volumetric scans.
- Generated multilayered surfaces and tetrahedral mesh models with processing times of minutes.
- Utilized open-source toolboxes 'Brain2Mesh' and 'Iso2Mesh' for mesh generation.
Main Results:
- Successfully generated diverse, high-quality brain mesh models from public brain atlases.
- Compared voxel-based, tetrahedral mesh, and layered-slab brain models.
- Demonstrated significant discrepancies in brain partial pathlengths (up to 166%) with approximated anatomies.
Conclusions:
- High-quality brain mesh generation is essential for accurate quantification in fNIRS.
- The proposed method offers improved accuracy over conventional techniques.
- Open-source tools are available to facilitate advanced fNIRS neuroimaging analysis.
