Introduction Endovascular devices are becoming more widely accepted ischemic stroke treatment options in patient healthcare. Current device testing methods must be developed to quantify downstream particulate migration. In vivo models are limited by local vessel structures and may lack neurovascular feeder vessels. Limited feedback devalues assessment of particulation and downstream migration of devices/materials. NAU’s Bioengineering Devices Lab has developed an in vitro blood flow and stroke model, which replicates the conditions of the neurovascular system. In prior workings, the in vitro model has quantified material particulation via filtration to capture particles and microscopy to analyze captured particles. Now, the process is a non-invasive method that has been developed in this study to allow researchers to quantify and characterize particles in real-time.

Materials and Methods These improvements are made possible through the utilization of digital imaging processing and total internal reflection fluorescence microscopy (TIRFM). A CMOS camera captures fluorescent particles in movement through the in vitro system through an in-line cuvette. A developed algorithm is advancing to process images and characterize particles (figure 1). During the procedure, PPODA-QT is injected into the in-vitro model’s aneurysm bubble and particulate downstream migration data is collected in real-time. The system integrates LabView (National Instruments, TX) to view and collect images. The pump delivers pulsatile flow with pressure profile that can be tuned to physiological conditions. The study then concentrates on the particulate downstream migration through the modified in-line cuvette section.

Results Long and short term testing is performed on the material to determine the potential material efficiency within the vascular system. Analysis of real-time data will quantify particle size and count. Results are then compared to (<USP 788> - table 1) regulations.

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Abstract E-099 Figure 1 An image of non-fluorescing particles. The images are captured and then processed to accumulate particle characteristics numerically and visually through color-coding

Conclusion The study results will help predict device performance within the neurovascular system to affirm the safety of the polymer biomaterial, PPODA-QT, in practical usage. Utilizing state of the art equipment and procedures, new innovative research can be conducted.

Disclosures I. Smith: None.