Abstract
To foster the efficient development of 3D cell culture models, we developed a strategy to assess the liquid flow perfusion through biocompatible scaffolds. Biocompatible scaffolds play a crucial role in creating 3D in vitro models for precision medicine. Therefore, it is imperative to thoroughly characterise the physical properties of these scaffolds. In this study, we leverage nuclear magnetic resonance imaging (MRI) to examine the diffusivity and perfusion properties of commonly used cryogels and hydrogels. We used deuterium oxide (i.e. heavy water) as a contrast agent to monitor the reduction in proton concentration from water within the scaffolds due to molecular motion. By analysing pixel intensity in MRI images, we extract information on the diffusion speed and perfusion efficacy of these materials. This approach allowed us to investigate passive water diffusion in a carboxymethyl cellulose cryogel and polyethylene glycol diacrylate hydrogel. The diffusion rates differed by 50% between the two scaffolds. Furthermore, we measured their perfusion properties in a PDMS microfluidic chip.
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Data Processing Scripts
Description
This repository contains all the Python scripts developed to process the MRI data from the paper "Leveraging Magnetic Resonance Imaging to Study Biocompatible Scaffolds Perfusion for Lab-on-a-Chip Systems".
The MRI data generated and processed for this study can be found at https://doi.org/10.34810/data1028.
For any doubts, please contact David Gomez-Cabeza ([email protected]).
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