Automatic calculation of the arterial input function for cerebral perfusion imaging with MR imaging

Area of Science:

• Neuroimaging
• Medical Physics
• Radiology

Background:

• Dynamic susceptibility contrast (DSC) MRI is crucial for assessing cerebral perfusion.
• Accurate determination of the arterial input function (AIF) is essential for reliable DSC-MRI analysis.
• Manual AIF selection is time-consuming and operator-dependent.

Purpose of the Study:

• To develop and validate an automated method for arterial input function (AIF) determination.
• To enable rapid and reliable assessment of cerebral perfusion parameters using DSC-MRI.
• To reduce operator input and postprocessing time in DSC-MRI.

Main Methods:

• An automated method for AIF determination was developed.
• The automated method was applied to 100 patients undergoing DSC-MRI.
• Cerebral perfusion images (relative blood flow, relative cerebral blood volume, mean transit time) were generated.
• Validation was performed in 20 patients by comparing automated AIF with manual selection.

Main Results:

• The automated AIF method successfully generated images of relative blood flow, relative cerebral blood volume, and mean transit time in 100 patients.
• In 20 patients, the automated AIF voxel correlated with a large cerebral artery.
• The automated AIF exhibited reduced partial-volume averaging compared to manual AIF selection.
• The automated method demonstrated reliability in determining AIF for DSC-MRI.

Conclusions:

• An automated method for AIF determination in DSC-MRI is feasible and reliable.
• This automated approach significantly reduces operator input and postprocessing time.
• The method facilitates rapid and accurate assessment of cerebral perfusion.