LOcal Void Analysis of MAP scaffolds (LOVAMAP)

Our lab designs hydrogel microparticles (HMPs) that are interlinked to form microporous annealed particle (MAP) scaffolds for wound healing applications. The therapeutic effects of MAP are attributed, in part, to the void space between particles that creates inherent micro-porosity through which cells can infiltrate and migrate unhindered. Cell behavior is influenced by local geometry, and our goal is to design scaffolds that influence cells toward pro-healing behaviors. To accomplish this, we need a methodology for quantitatively characterizing the void space of MAP scaffolds in order to study the relationships between internal microarchitecture and therapeutic outcomes. The work presented here is a visually-rich dissertation that covers our approach for analyzing the void space of packed particles. We use techniques from computational geometry and graph theory to develop a robust methodology for segmenting the void space into natural pockets of open space and outputting a set of descriptors that characterize the space. Our methods are developed using simulated MAP scaffolds covering a range of particle compositions, including mixed particle sizes, stiffnesses, and shapes. Our software, called LOcal Void Analysis of MAP scaffolds (LOVAMAP), has allowed us to study many aspects of void space, including global descriptors like void volume fraction, local ‘pore’ measurements of size and shape, and additional features like ligand availability, paths, isotropy/anisotropy, and available regions for unhindered migration based on size. LOVAMAP is an enabling technology that can be used for analyzing real scaffolds or studying simulated scaffolds to inform material design. It serves as a platform for void space analysis that can easily be built upon to encompass ever-growing innovations in scaffold characterization.