Key result
Automated voxel classification successfully facilitated the integration of atlas-guided diffuse optical tomography with graph theory analysis to quantify resting-state functional brain networks.
The automated voxel classification method enables the use of graph theory analysis with atlas-guided diffuse optical tomography for assessing functional brain networks.
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Supports noninvasive NIRS network assessment in research; leaves open clinical translation pending validation.
Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.
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Li et al. (2016) studied Healthy adults (resting-state functional connectivity) (n=15). Automated voxel classification (AVC) with atlas-guided diffuse optical tomography (atlas-DOT) vs. Older adults (for network metric comparison) was evaluated on Reproducibility of resting-state functional connectivity measurements and changes in brain network metrics. Automated voxel classification successfully facilitated the integration of atlas-guided diffuse optical tomography with graph theory analysis to quantify resting-state functional brain networks.
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