Development of Smart Patient-Specific 3D Printed Vascular Phantoms for Assessment of Flow Dynamics and Treatment Simulations Using Embedded Sensors

Cardiovascular Diseases (CVD) being the leading cause of death, investigating various methods for understanding the effects of these diseases is of utmost importance. Hemodynamic parameters such as blood pressure and flow rate are the first once affected by CVD. There have been various methods developed to study the flow dynamics using Computational Fluid Dynamics (CFD) which are computationally intensive and also uses unrealistic boundary conditions such as rigid vessel wall. This thesis focus on the developing methods combining 3D printing of patient-specific phantoms and sensors for measuring the mechanical parameters of flow in real-time and overcoming the pitfalls of CFD. The method of Lumped Parameter Model was used to verify the behavior of 3D printed idealized single vessel phantom as an RC circuit. In order to measure the flow parameters, pressure and flow sensors were used in conjunction with LabVIEW. An oscillatory flow (sine) with a flow rate of 350mL/min was used and LabVIEW recorded the recorded pressure and flow for different frequencies of flow wave in real-time using NI ELVIS II+ as a data acquisition system. Later the pressure and flow data were processed and the phase difference between pressure and flow, resistance and reactance were estimated. It was observed phase difference and reactance decreased with frequency, which showed that a compliant vessel behaves as a parallel RC circuit. We developed Smart Patient-Specific vascular models to provide a 3D display of pressure gradients on patient-specific coronary vascular geometries by combining 3D printed phantoms with pressure sensors. The coronary models printed include the three main coronary arteries and the aortic root. The pressure sensors were connected to these four locations and the data was acquired using NI ELVIS II+. A LabVIEW code was developed to measure the pressures at each vessel, calculate the Fractional Flow Reserve (FFR) for selected coronary vessel and display a 3D of a color-coded map of pressure for better visualization.

Grantor dc:publisher

State University of New York at Buffalo

Year dc:date.issued

2018

Author dc:creator

• Karkhanis, Nitant Vivek

Contributors dc:contributor

• Ionita, Ciprian
• Biomedical Engineering

• biomedical engineering
• electrical engineering

Statement dc:rights

• Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.
• Copyright retained by author.

Language dc:language

eng

Handle dc:identifier

http://hdl.handle.net/10477/78046

OAI record oai:identifier

https://ubir.buffalo.edu/oai/request?verb=GetRecord&metadataPrefix=qdc&identifier=oai%3Aubir.buffalo.edu%3A10477%2F78046