Automated perfusion-weighted MRI using localized arterial input functions.

Purpose: To investigate the utility of an automated perfusion-weighted MRI (PWI) method for estimating cerebral blood flow (CBF) based on localized arterial input functions (AIFs) as compared to the standard method of manual global AIF selection, which is prone to deconvolution errors due to the effects of delay and dispersion of the contrast bolus.

Materials And Methods: Analysis was performed on spin- and gradient-echo EPI images from 36 stroke patients. A local AIF algorithm created an AIF for every voxel in the brain by searching out voxels with the lowest delay and dispersion, and then interpolating and spatially smoothing them for continuity.

Effect of using local arterial input functions on cerebral blood flow estimation.

Purpose: To investigate a previously developed method for perfusion-weighted MRI (PWI) cerebral blood flow (CBF) estimation that uses local arterial input functions (AIFs) in stroke patients, and determine its ability to correct delay and/or dispersion (D/D) errors.

Materials And Methods: Analysis was performed on dynamic susceptibility contrast data from 36 stroke patients, and CBF maps were calculated with global- and local-AIF techniques using standard SVP based methods. The ratios of these maps were calculated and the mean ratios were calculated for voxels with both normal and abnormal time to peak or width.