Modeling inflow effects in fast fMRI to quantify fluid flow

Fast fMRI has recently been shown to be an effective method for detecting dynamic changes in cerebrospinal fluid flow, enabling measurement of a critical process for maintenance of brain health. However, while the inflow signal measured using fast fMRI is a surrogate for the underlying flow dynamics, it does not directly reflect the velocity and dynamics of flow. To understand the mapping between flow and the flow-enhanced MR signals they generate, we developed and validated a mathematical forward model that uses velocity as input and simulates dynamic fMRI inflow signal intensities for each slice of the imaging volume.