Medical Devices and Human Tissue interaction 

motivation

How can someone predict the performance of new medical devices, their interaction with tissue (e.g., blood vessel walls) on the short- and long-term, to minimize unwanted complications? Rather recently, a medical device was recalled by the FDA as it resulted in patient deaths and serious injuries such as vessel damage, hemorrhage, and cerebral infarction (JET 7 Xtra Flex catheter). In addition, the device not only resulted in patient trauma, but also device failures occurred during medical procedures. The device ruptured or completely separated, leaving the internal support metallic coils exposed near the distal tip region.

 

Minimally invasive vascular therapy devices, such as catheters and stents, interact with the blood vessels of the patient. This interaction triggers short- and long-term mechanisms within the tissue which may be unwanted (e.g., damage to the vessel wall or re-occlusion of the blood vessel). The short-term device-tissue interaction effects are mainly introduced during the medical procedure and result from mechanical and hemodynamics effects:

 

In addition to changes in the mechanical state of the tissue, the new device will trigger an initial immune response. The combination of mechanical changes and inflammation can trigger long-term interaction effects such as growth (proliferation and matrix deposition –i.e. fibrosis-), remodeling (e.g., calcification and altered mechanical properties/tissue microstructure), and chronic inflammation. These interaction mechanisms are complex and patient-specific and need to be understood to estimate the risk of occurrence and to, ultimately, mitigate them.

Problem definition

Can you create interacting digital twins of a medical device and a patient vascular tissue (arteries) which can describe the relevant mechanisms that occur on short and long term, and ultimately, support the surgeon to predict which device is best to use for that particular patient? 

Working UNIT