Improved accuracy of cerebral blood flow quantification in the presence of systemic physiology cross-talk using multi-layer Monte Carlo modeling

Improved accuracy of cerebral blood flow quantification in the presence of systemic physiology cross-talk using multi-layer Monte Carlo modeling

Significance: Contamination of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow (CBF) due to systemic physiology remains a significant challenge in the clinical translation of DCS for neuromonitoring. Tunable, multi-layer Monte Carlo-based (MC) light transport models have t...

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Bibliographic Details
Published in:Neurophotonics (Print) Vol. 8; no. 1; p. 015001
Main Authors: Wu, Melissa M, Chan, Suk-Tak, Mazumder, Dibbyan, Tamborini, Davide, Stephens, Kimberly A, Deng, Bin, Farzam, Parya, Chu, Joyce Yawei, Franceschini, Maria Angela, Qu, Jason Zhensheng, Carp, Stefan A
Format: Journal Article
Language:English
Published: United States Society of Photo-Optical Instrumentation Engineers 01-01-2021
S P I E - International Society for
Subjects:
Approximation
Blood flow
Blood pressure
Cerebral blood flow
Contamination
Gases
Hypercapnia
Light
Performance evaluation
Research Papers
Respiration
Scalp
Simulation
Spectroscopy
Spectrum analysis
United States > US
Colorado
cerebral blood flow
Monte Carlo
diffuse correlation spectroscopy
multi-layer
hypercapnia
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Summary:Significance: Contamination of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow (CBF) due to systemic physiology remains a significant challenge in the clinical translation of DCS for neuromonitoring. Tunable, multi-layer Monte Carlo-based (MC) light transport models have the potential to remove extracerebral flow cross-talk in cerebral blood flow index (CBFi) estimates. Aim: We explore the effectiveness of MC DCS models in recovering accurate CBFi changes in the presence of strong systemic physiology variations during a hypercapnia maneuver. Approach: Multi-layer slab and head-like realistic (curved) geometries were used to run MC simulations of photon propagation through the head. The simulation data were post-processed into models with variable extracerebral thicknesses and used to fit DCS multi-distance intensity autocorrelation measurements to estimate CBFi timecourses. The results of the MC CBFi values from a set of human subject hypercapnia sessions were compared with CBFi values estimated using a semi-infinite analytical model, as commonly used in the field. Results: Group averages indicate a gradual systemic increase in blood flow following a different temporal profile versus the expected rapid CBF response. Optimized MC models, guided by several intrinsic criteria and a pressure modulation maneuver, were able to more effectively separate CBFi changes from scalp blood flow influence than the analytical fitting, which assumed a homogeneous medium. Three-layer models performed better than two-layer ones; slab and curved models achieved largely similar results, though curved geometries were closer to physiological layer thicknesses. Conclusion: Three-layer, adjustable MC models can be useful in separating distinct changes in scalp and brain blood flow. Pressure modulation, along with reasonable estimates of physiological parameters, can help direct the choice of appropriate layer thicknesses in MC models.
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ISSN:2329-423X
2329-4248
DOI:10.1117/1.NPh.8.1.015001