Extracerebral hemodynamics can significantly influence DCS estimation of cerebral perfusion. Advanced analytical models can be used to remove the contribution of extracerebral hemodynamics; however, these models are highly sensitive to measurement noise. There is a need for an empirical determination of the optimal source-detector separation(s) (SDS) that improves the accuracy and reduces sensitivity to noise in the estimation of cerebral blood flow with these models. We performed a series in silicon simulations to quantify the influence of SDS on uniqueness, accuracy, and sensitivity to inaccuracies in model parameters using the three-layer inverse model. More details are here.
You are here: / / New paper out about the influence of source-detector separation on diffuse correlation spectroscopy measurements of cerebral blood flow with a multilayered analytical model