Additive manufacturing of personalized scaffolds for vascular cell studies in large arteries: A case study on carotid arteries in sickle cell disease patients

Abstract

Patient-specific models have increasingly gained significance in medical and research domains. In the context of hemodynamic studies, computational fluid dynamics emerges as a highly innovative and promising approach. We propose to augment these computational studies with cell-based experiments in individualized artery geometries using personalized scaffolds and vascular cell experiments. Previous research has demonstrated that the development of Sickle Cell Disease (SCD)-Related Vasculopathy is dependent on personal geometries and flow characteristics of the carotid artery. This fact leaves conventional animal experiments unsuitable for gaining patient-specific insights into cellular signaling, as they cannot replicate the personalized geometry. These personalized dynamics of cellular signaling may further impact disease progression, yet remains unclear. This paper presents a six-step methodology for creating personalized large artery scaffolds, focusing on high-precision models that yield biologically interpretable patient-specific results. The methodology outlines the creation of personalized large artery models via Additive Manufacturing suitably for supporting cell culture and other cellular experiments. Additionally, it discusses how different Computer-Aided-Design (CAD) construction modes can be used to obtain high-precision personalized models, while simplifying model reconfigurations and facilitating adjustments to general designs such as system connections to bioreactors, fluidic systems and visualization tools. A proposal for quality control measures to ensure geometric congruence for biological relevance of the results is added. This innovative, interdisciplinary approach appears promising for gaining patient-specific insights into pathophysiology, highlighting the importance of personalized medicine for understanding complex diseases.