
==== Front
bioRxiv
BIORXIV
bioRxiv
2692-8205
Cold Spring Harbor Laboratory

10.1101/2024.08.20.608859
preprint
1
Article
Revisiting equivalent optical properties for cerebrospinal fluid to improve diffusion-based modeling accuracy in the brain
Lewis Aiden Vincent http://orcid.org/0000-0001-6826-8925

Fang Qianqian http://orcid.org/0000-0003-0805-935X

21 8 2024
2024.08.20.608859https://creativecommons.org/licenses/by-nd/4.0/ This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.
http://biorxiv.org/lookup/doi/10.1101/2024.08.20.608859
nihpp-2024.08.20.608859.pdf
Abstract

Significance

The diffusion approximation (DA) is used in functional near-infrared spectroscopy (fNIRS) studies despite its known limitations due to the presence of cerebrospinal fluid (CSF). Nearly all of these studies rely on a set of empirical CSF optical properties, recommended by a previous simulation study, that were not selected for the purpose of minimizing DA modeling errors.

Aim

We aim to directly quantify the accuracy of DA solutions in brain models by comparing those with the goldstandard solutions produced by the mesh-based Monte Carlo (MMC), based on which we derive updated recommendations.

Approach

For both a 5-layer head and Colin27 atlas models, we obtain DA solutions by independently sweeping the CSF absorption ( μ a ) and reduced scattering coefficients. Using an MMC solution with literature CSF optical properties as reference, we compute the errors for surface fluence, total brain sensitivity and brain energy-deposition, and identify the optimized settings where the such error is minimized.

Results

Our results suggest that previously recommended CSF properties can cause significant errors (8.7% to 52%) in multiple tested metrics. By simultaneously sweeping μ a and , we can identify infinite numbers of solutions that can exactly match DA with MMC solutions for any single tested metric. Furthermore, it is also possible to simultaneously minimize multiple metrics at multiple source/detector separations, leading to our new recommendation of setting while maintaining physiological μ a for CSF in DA simulations.

Conclusion

Our new recommendation of CSF equivalent optical properties can greatly reduce the model mismatches between DA and MMC solutions at multiple metrics without sacrificing computational speed. We also show that it is possible to eliminate such a mismatch for a single or a pair of metrics of interest.
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pmc
