Cerebral aneurysms pose a significant risk to patients, with the potential for growth and rupture leading to severe health outcomes. The current challenge lies in accurately predicting aneurysm behavior and assessing the effectiveness of various treatment devices, such as embolization coils and flow diverters.
Traditional in vitro models often lack the key functional and morphological features necessary for reliable evaluation, such as realistic mechanical properties and a dynamic cellular environment. Additionally, these models struggle to replicate the complex hemodynamic conditions found in vivo, limiting their utility in both clinical and research settings.
There is a critical need for advanced models that can better mimic the human vascular system to predict aneurysm growth, assess the efficacy of medical devices, and train healthcare professionals in device deployment.
To address these challenges, our multidisciplinary team, in collaboration with Lawrence Livermore National Laboratory, has developed a cutting-edge approach combining bioprinted vascular models with digital twin technology.
We have created three-dimensionally (3D) printed vascularized tissue structures using a gelatin-fibrin hydrogel matrix, with the inner walls seeded with human cerebral microvascular endothelial cells (hCMECs). These models faithfully replicate the cellular environment of cerebral vasculature, including aneurysms, allowing for accurate simulation of blood flow and mechanical stresses.
By integrating these physical models with digital twins, we model patient-specific hemodynamic flow to assess rupture risk or enable treatment planning. The digital twin aspect allows for high- resolution, personalized simulation and analysis, offering a non-invasive method to study the effects of different treatment strategies and device designs.
We have used this framework to assess characteristics of growing cerebral aneurysms1,2, deployment of devices like balloon-mounted stents3, and deployment of embolization coils4. Our combined approach offers a comprehensive solution to the current limitations in cerebral aneurysm modeling, providing a robust and adaptable platform for both clinical and research applications.