Model-free arterial spin labeling quantification approach for perfusion MRI.

Area of Science:

• Neuroimaging
• Medical Physics
• Radiology

Background:

• Cerebral blood flow (CBF) and arterial blood volume (aBV) are critical metrics in neuroimaging.
• Accurate quantification of these parameters is essential for diagnosing and monitoring various neurological conditions.
• Existing methods, such as dynamic susceptibility contrast (DSC) MRI, have limitations.

Purpose of the Study:

• To develop and validate a model-free arterial spin labeling (ASL) quantification approach.
• To measure cerebral blood flow (CBF) and arterial blood volume (aBV) simultaneously.
• To compare the proposed method with conventional kinetic modeling.

Main Methods:

• Acquisition of a train of multiple ASL images.
• Perfusion quantification using deconvolution, similar to DSC MRI.
• Estimation of local arterial input functions (AIFs) by subtracting specific image pairs.
• Voxel-by-voxel estimation of aBV based on tagged arterial blood bolus duration.
• Calculation of CBF using the residue function maximum, scaled by local aBV.

Main Results:

• The model-free ASL method provides averaged gray matter (GM) perfusion values of 38 +/- 2 ml/min/100 g and aBV of 0.93% +/- 0.06%.
• The average CBF value obtained was 10% lower than that from the standard general kinetic model (42 +/- 2 ml/min/100 g).
• Monte Carlo simulations demonstrated the performance of the new methodology compared to parametric fitting.

Conclusions:

• The proposed model-free ASL approach enables accurate quantification of CBF and aBV.
• This method offers a viable alternative to conventional kinetic modeling for perfusion imaging.
• Further validation and application in clinical settings are warranted.