Abstract
BackgroundThe current automatic techniques for measuring arterial input function (AIF) and venous output (VOF) on cerebral computed tomography perfusion images are prone to motion artifact and random noise, and their failure rates vary between 10% and 65%. We developed a new automatic technique to overcome these problems. MethodsA principle axis transformation was applied to perfusion images to correct for translational and rotational motion artifacts. Bone voxels and neighboring voxels were removed from the perfusion images. Only brain voxels were included in the AIF and VOF measurement procedures. The selection criteria, such as large area under the concentration–time curve, early arrival of contrast agents, and narrow effective width, were used to select appropriate arterial and venous voxels for the AIF and VOF measurements. The proposed automatic technique was tested in 20 patients with unilateral cerebral arterial stenosis. The results of the proposed technique were compared to the results obtained by manual measurements and commercially available automatic selection software. ResultsThe AIFs and VOFs were successfully measured using the proposed automatic technique in all 20 patients. The curve shapes, including the area under the concentration–time curve, peak concentration, time to peak, and effective width of the automatically measured AIFs or VOFs were comparable to that were measured manually. ConclusionThe proposed automatic measurement technique successfully overcomes the motion artifact and random noise problems encountered in measuring AIF and VOF. It can be easily integrated into software for the automatic calculation of cerebral blood volume and flow.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.