Dr. Chung-Hao Lee is an associate professor of Bioengineering at the University of California, Riverside (UCR). His research program focuses on computational/experimental biomechanics and precision medicine to address several cardiovascular and cerebrovascular diseases, including tricuspid valve regurgitation in congenital heart defects and brain aneurysms. Dr. Lee received a PhD in Civil Engineering (with his doctoral research on multiscale computational biomolecular mechanics) from UCLA in 2011, followed by a postdoctoral training at the University of Texas at Austin, working on cardiovascular heart valve biomechanics. Before he joined UCR, Dr. Lee was an Assistant/Associate Professor of Mechanical Engineering at the University of Oklahoma (2016-2023). Since his faculty career, Dr. Lee has published 65 journal papers and 3 book chapters, with his research supported by the American Heart Association Scientist Development Grant, National Institutes of Health R01 Grants, among others. He is the recipient of OU’s University Distinguished Teaching Award and he became a fellow of the American Heart Association in 2023.
Intracranial aneurysms (or brain aneurysms) are a focal dilation of brain artery vessels that affect about 1.3 million Americans. The aneurysms, left untreated, can progressively grow, weaken the vessel wall, and eventually rupture, causing devastating hemorrhagic strokes. Despite recent advancements in minimally invasive endovascular procedures, such as coiling and flow diversion, the long-term outcomes still remain suboptimal. To address the aneurysm recurrence issue that current therapeutics are facing, we propose a novel aneurysm filling method, which combines shape memory polymers, additive manufacturing, and computational modeling-guided iterative design, for patient-specific treatment of unruptured intracranial aneurysms. In this presentation, I will first introduce the characterizations of the fundamental properties of the chosen shape memory polymers (SMPs). Then, I will present our innovative developments of a template-leaching indirect 3D printing technique for fabricating patient-specific SMP devices, together with an integrated component for device delivery and detachment. Finally, I will discuss how we introduce computational modeling to guide the design of our SMP-based embolic devices. Tailoring our aneurysm treatment devices to each patient’s vascular geometry and circulation has great clinical potential to maximizing aneurysm filling, improving immediate aneurysm occlusion rates, and avoiding aneurysm recurrence that causes surgical reoperations and additional healthcare burden.