A dynamically coupled kinetic model for Arterial Spin Labeling: Enhancing the reliability of ventricular cerebrospinal fluid renewal quantification in vivo

Arterial spin labeling (ASL) provides a valuable non-invasive tool for investigating cerebrospinal fluid (CSF) dynamics. While existing generalized kinetic models provide a useful analytical framework, incorporating explicit fluid mass-conservation constraints may improve the reliability of ventricular CSF quantification. We developed and validated a physics-constrained kinetic model that assumes a constant ventricular volume, under which the volumetric influx and efflux rates are balanced. Under this assumption, the localized CSF renewal rate (f) is modeled as a distinct washout process that acts jointly with intrinsic CSF T1 relaxation R1,CSF, yielding an effective decay rate Reff = R1,CSF + f, providing a more mechanistically interpretable description of the post-arrival signal decay. The model was further tailored to the global inversion physics of the FAIR (Flow-sensitive Alternating Inversion Recovery) sequence and incorporates an explicit zero-clamped pre-arrival boundary condition. When applied to an in vivo preclinical dataset, the proposed model, improved fitting stability and removed the finite-bolus truncation observed in the raw conventional model. Compared with the conventional model, the proposed model showed significantly improved goodness-of-fit (R2 = 0.95 {+/-} 0.05 vs. 0.82 {+/-} 0.06, p < 0.001) and a lower Akaike Information Criterion (AIC = 94.96 {+/-} 5.83 vs. 106.93 {+/-} 2.50, p < 0.001), suggesting it provides a more adequate and efficient representation of CSF dynamics. The proposed model yielded CSF dynamics estimates 14.70% higher than those obtained with the conventional model, with a mean ventricular CSF renewal time of 4.01 {+/-} 0.97 min and a renewal-equivalent volumetric flow rate of 0.97 {+/-} 0.41 {micro}L/min. The resulting estimates might be interpreted as localized, ASL-derived renewal metrics rather than direct measurements of net CSF production.