Measure pores in 3D for better wound healing

Biomedical engineers at Duke University have developed a method to identify and characterize empty spaces between particles in any packaged structure. By mapping these empty spaces, researchers can better understand how cells and other phenomena respond to their environment.

The research was published November 21 in the journal Nature Computational Science.

It’s a common board game: candy, candy corn, gumdrops, or other small objects are packed into a container, people guess how many objects are in the jar, and which one The best guess will win a prize. While there are many methods for counting objects to get the most accurate estimate, Tatiana Segura, professor of biomedical engineering at Duke University, Lindsay Riley, postdoctoral researcher in the Segura lab, and Peter Cheng, founder from Ninjabyte Computing, have designed a new method. approach that turned the game around.

“We didn’t want to count objects. Instead, we were interested in the number of open pockets of empty space between objects,” Riley explained. “For many systems, understanding that empty space, or what we call empty space, is actually more important than the objects themselves.”

The Segura lab is developing hydrogels, called microparticle annealed particle (MAP) gels, composed of microparticles that can be injected into wounds to create a scaffold that promotes wound healing. Once these particles are packed into the wound or a culture dish, they leave open spaces between the particles in which cells can grow. Because cells respond to the microarchitecture of their environment, the team wanted a tool that would allow them to better understand the geometry of the empty spaces where these cells were growing, whether in a healing wound or in a box of Petri.

“To better understand what drives cellular behavior in MAP gels, we needed to find a way to precisely separate the interconnected empty space of our scaffolds into pockets that we could study individually,” Segura said.

Using techniques from mathematical fields such as graph theory and computational geometry, the team developed LOVAMAP, short for local void analysis using the per-particle medial axis configuration. LOVAMAP identifies each distinct open pocket (or 3D pore) between particles, and their approach focuses on precision using information embedded in the particle configuration itself. These pores include any continuous space in which an object can move, both inside and outside the scaffold.

“Now that we can accurately identify 3D pores in packed particles, we can begin to understand what determines their shape and connectivity and which 3D pore shapes are responsible for different cellular behaviors,” Segura said.

“We can do this for any type of packed particles, allowing us to study how different particle shapes lead to different 3D pore structures. For example, we can see that packed rods lead to 3D pores The more elongated, the packed spheres create the more open ones.” “

Beyond extending the software to better understand patterns between particle types and empty space, such as connectivity between 3D pores, Segura and his lab will use LOVAMAP to advance their wound healing research in comparing how cellular behavior is influenced by different 3D pores. mapped by their software. According to Segura, this knowledge will help them optimize their equipment to promote better healing of skin and brain wounds.

Although Segura and Riley have no plans to use LOVAMAP to win board games, they would still be happy to use the software to study the system.

“If you can tell me the average diameter of the gumballs and how tightly packed the gumballs are, I can tell you – with reasonable confidence – how many 3D pores there are in the jar,” Riley said. “And I can also give you the average pore size.”