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. A generalized linear model (GLM) for predicting tissue outcome, and MTT lesion volumes were used to quantify the performance of the localized AIF method in comparison with global methods using ipsilateral and contralateral AIFs. RESULTS: The algorithm found local AIFs in each case without error and generated a higher area under the receiver operating characteristic (ROC) curve compared to both global-AIF methods. Similarly, the local MTT lesion volumes had the least mean squared error (MSE). CONCLUSION: Automated CBF calculation using local AIFs is feasible and appears to produce more useful CBF maps.

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. The locations of the voxels with high locally-defined to globally-defined CBF ratios were also mapped and the average underlying concentration-time curves for these voxels were calculated. RESULTS: The ratio of CBF estimates based on local AIFs to global AIFs was on average increased for D/D voxels. The voxels in which this ratio was high were commonly concentrated in the ipsilateral hemisphere, and these voxels also displayed underlying concentration-time curves that showed delay or dispersion. Conversely, there were no such findings based on high globally-defined to locally-defined CBF ratios. CONCLUSION: The local-AIF technique results in an increase in the calculated CBF values for tissues with D/D, consistent with a reduction in the errors associated with D/D.