Accuracy of diffuse correlation spectroscopy measurements of cerebral blood flow when using a three-layer analytical model

Diffuse correlation spectroscopy (DCS) is a non-invasive optical technology for the assessment of an index of cerebral blood flow (CBFi). Analytical methods that model the head as a three-layered medium (i.e., scalp, skull, brain) are becoming more commonly used to minimize the contribution of extracerebral layers to the measured DCS signal in adult cerebral blood flow studies. However, these models rely on a priori knowledge of layer optical properties and thicknesses. Errors in these values can lead to errors in the estimation of CBFi, although the magnitude of this influence has not been rigorously characterized. Herein, we investigate the accuracy of measuring cerebral blood flow with a three-layer model when errors in layer optical properties or thicknesses are present. Through a series of in silico experiments, we demonstrate that CBFi is highly sensitive to errors in brain optical properties and skull and scalp thicknesses. Relative changes in CBFi are less sensitive to optical properties but are influenced by errors in layer thickness. Thus, when using the three-layer model, accurate estimation of scalp and skull thickness are required for reliable results. (c) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Automated summary

Research demonstrates that errors in brain optical properties and scalp and skull thicknesses can significantly impact the estimation of cerebral blood flow index when using a three-layer model. While changes in blood flow index are less sensitive to optical properties, they are influenced by errors in layer thickness. Accuracy in estimating scalp and skull thickness are crucial for reliable results when utilizing the three-layer model.