Parylene MEMS patency sensor for assessment of hydrocephalus shunt obstruction
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Neurosurgical ventricular shunts inserted to treat hydrocephalus experience a cumulative failure rate of 80 % over 12 years; obstruction is responsible for most failures with a majority occurring at the proximal catheter. Current diagnosis of shunt malfunction is imprecise and involves neuroimaging studies and shunt tapping, an invasive measurement of intracranial pressure and shunt patency. These patients often present emergently and a delay in care has dire consequences. A microelectromechanical systems (MEMS) patency sensor was developed to enable direct and quantitative tracking of shunt patency in order to detect proximal shunt occlusion prior to the development of clinical symptoms thereby avoiding delays in treatment. The sensor was fabricated on a flexible polymer substrate to eventually allow integration into a shunt. In this study, the sensor was packaged for use with external ventricular drainage systems for clinical validation. Insights into the transduction mechanism of the sensor were obtained. The impact of electrode size, clinically relevant temperatures and flows, and hydrogen peroxide (H2O2) plasma sterilization on sensor function were evaluated. Sensor performance in the presence of static and dynamic obstruction was demonstrated using 3 different models of obstruction. Electrode size was found to have a minimal effect on sensor performance and increased temperature and flow resulted in a slight decrease in the baseline impedance due to an increase in ionic mobility. However, sensor response did not vary within clinically relevant temperature and flow ranges. H2O2 plasma sterilization also had no effect on sensor performance. This low power and simple format sensor was developed with the intention of future integration into shunts for wireless monitoring of shunt state and more importantly, a more accurate and timely diagnosis of shunt failure.
KeywordsPatency Sensor Parylene C Hydrocephalus Obstruction
This work was funded in part by the NSF under award number EFRI-1332394, the University of Southern California Coulter Translation award, and the University of Southern California Provost Ph.D. Fellowship (BK). The authors thank Dr. Donghai Zhu of the Keck Photonics Laboratory for help with fabrication, and members of the Biomedical Microsystems Laboratory of USC for their assistance.
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