Abstract
BACKGROUND: The spinal subarachnoid space (SSS) has a complex 3D fluid-filled geometry with multiple levels of anatomic complexity, the most salient features being the spinal cord and dorsal and ventral nerve rootlets. An accurate anthropomorphic representation of these features is needed for development of in vitro and numerical models of cerebrospinal fluid (CSF) dynamics that can be used to inform and optimize CSF-based therapeutics. METHODS: A subject-specific 3D model of the SSS was constructed based on high-resolution anatomic MRI. An expert operator completed manual segmentation of the CSF space with detailed consideration of the anatomy. 31 pairs of semi-idealized dorsal and ventral nerve rootlets (NR) were added to the model based on anatomic reference to the magnetic resonance (MR) imaging and cadaveric measurements in the literature. Key design criteria for each NR pair included the radicular line, descending angle, number of NR, attachment location along the spinal cord and exit through the dura mater. Model simplification and smoothing was performed to produce a final model with minimum vertices while maintaining minimum error between the original segmentation and final design. Final model geometry and hydrodynamics were characterized in terms of axial distribution of Reynolds number, Womersley number, hydraulic diameter, cross-sectional area and perimeter. RESULTS: The final model had a total of 139,901 vertices with a total CSF volume within the SSS of 97.3 cm(3). Volume of the dura mater, spinal cord and NR was 123.1, 19.9 and 5.8 cm(3). Surface area of these features was 318.52, 112.2 and 232.1 cm(2) respectively. Maximum Reynolds number was 174.9 and average Womersley number was 9.6, likely indicating presence of a laminar inertia-dominated oscillatory CSF flow field. CONCLUSIONS: This study details an anatomically realistic anthropomorphic 3D model of the SSS based on high-resolution MR imaging of a healthy human adult female. The model is provided for re-use under the Creative Commons Attribution-ShareAlike 4.0 International license (CC BY-SA 4.0) and can be used as a tool for development of in vitro and numerical models of CSF dynamics for design and optimization of intrathecal therapeutics.