Abstract
Aim: Chiari malformation and syringomyelia are disorders of cerebrospinal fluid (CSF) dynamics, yet translation of mechanistic insights into patient care is limited by the low prevalence and heterogeneity of human disease, and by methodological constraints of in-vivo CSF measurements. In Cavalier King Charles Spaniels (CKCS), these conditions are highly prevalent and represent a clinically relevant companion animal model. However, existing canine CSF flow studies rely largely on phase-contrast magnetic resonance imaging (MRI) metrics that incompletely characterize three-dimensional flow. This study aimed to develop a computational fluid dynamics (CFD) framework to characterise CSF flow dynamics in CKCS, providing a translational approach for investigating CSF dynamics in both veterinary and human cases.
Methods: Retrospective MRI data from nine clinically normal CKCS were used to construct subject-specific craniospinal CSF geometries. CFD simulations yielded cardiac-driven oscillatory CSF motion under physiologically plausible boundary conditions, incorporating spinal compliance and zero net flow per cardiac cycle to characterize velocities and pressures.
Results: Simulations revealed pulsatile, laminar CSF flow with pronounced regional heterogeneity, dominant subarachnoid space (SAS) transport, complex flow patterns within the cerebral aqueduct, and a cycle-dependent pressure difference between the central canal and SAS with marked sensitivity to anatomical location and downstream spinal geometry.
Conclusion: These findings demonstrate that local anatomy strongly influences measured CSF velocities, limiting the translational reliability of isolated in vivo measurements while supporting CFD as a more robust framework for clinically meaningful interpretation. Establishing these baseline craniospinal flow characteristics provides a necessary reference for interpreting clinical CSF measurements and for extending computational analyses to dogs with Chiari-like malformation and syringomyelia.