3D Printing Microfluidics for Modeling Cerebral Small Vessel Pathology

Abstract

Cerebral small vessel disease (CSVD) is a leading cause of stroke and dementia, making the study of small vessel hemodynamics vital for advancing diagnostic and therapeutic strategies. This research focuses on fabricating microfluidic devices that replicate the lateral lenticulostriate arteries (LSA) to validate computational flow models of small cerebral vessels. A key challenge in studying CSVD is the lack of experimental validation for computational fluid dynamics (CFD) models, which are widely used to simulate hemodynamics. To address this, additive masked Stereolithography (mSLA) was employed to fabricate a microfluidic model of the LSAs. The study explored the impact of orientation, exposure time, and layer height on the roundness and error of the intended area of printed micro-pores, to optimize the manufacturing of a microfluidic device. The smallest printed pore measured 270 μm in diameter. Pores printed at a larger angle as assessed from the build plate were more likely to remain open, but exhibited a larger decrease in area compared to smaller angles. A lower exposure time exhibited a larger pore area, whereas a larger layer height showed a decrease in area from intended. The layer height and angle did not influence the roundness, whereas an increase in exposure time decreased the roundness of the pores. Additionally, flow experiments were conducted using a 3D printed microfluidic device to compare empirical data with CFD and analytical simulations. The encountered resistance was larger for the experimental results (3.19 ⋅10^11 Pa⋅s/m^3) compared to the analytical result (1.96 ⋅10^11 Pa⋅s/m^3) and the computational result (1.90 ⋅10^11 Pa⋅s/m^3), likely due to deviation from the intended size. Finally, arterial microfluidic devices were printed and flow was induced to showcase their functionality. Achieving precise channel dimensions remains the primary challenge in mSLA printing due to cumulative dosage effects.
This research bridges the gap between computational modeling and experimental validation, providing a platform for studying cerebral microcirculation. The findings demonstrate the feasibility of using commercially available 3D-printed microfluidic devices to replicate small cerebral vessels. The outcomes of this study contribute to the advancement of vascular biomodeling, with implications for future clinical applications in stroke and neurovascular research.