  Transcranial ultrasound simulations are increasingly used to predict in situ
exposure parameters for ultrasound therapies in the brain. However, there can
be considerable uncertainty in estimating the acoustic medium properties of the
skull and brain from computed tomography (CT) images. Here, we show how the
resulting uncertainty in the simulated acoustic field can be predicted in a
computationally efficient way using linear uncertainty propagation. Results for
a representative transcranial simulation using a focused bowl transducer at 500
kHz show good agreement with unbiased uncertainty estimates obtained using
Monte Carlo.
