An open source image processing method to quantitatively assess tissue growth after non-invasive magnetic resonance imaging in human bone marrow stromal cell seeded 3D polymeric scaffolds.

• Main Authors: Anne M Leferink, Raluca M Fratila, Maaike A Koenrades, Clemens A van Blitterswijk, Aldrik Velders, Lorenzo Moroni
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2014-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC4264848?pdf=render
• ISSN: 1932-6203

Monitoring extracellular matrix (ECM) components is one of the key methods used to determine tissue quality in three-dimensional (3D) scaffolds for regenerative medicine and clinical purposes. This is even more important when multipotent human bone marrow stromal cells (hMSCs) are used, as it could offer a method to understand in real time the dynamics of stromal cell differentiation and eventually steer it into the desired lineage. Magnetic Resonance Imaging (MRI) is a promising tool to overcome the challenge of a limited transparency in opaque 3D scaffolds. Technical limitations of MRI involve non-uniform background intensity leading to fluctuating background signals and therewith complicating quantifications on the retrieved images. We present a post-imaging processing sequence that is able to correct for this non-uniform background intensity. To test the processing sequence we investigated the use of MRI for in vitro monitoring of tissue growth in three-dimensional poly(ethylene oxide terephthalate)-poly(butylene terephthalate) (PEOT/PBT) scaffolds. Results showed that MRI, without the need to use contrast agents, is a promising non-invasive tool to quantitatively monitor ECM production and cell distribution during in vitro culture in 3D porous tissue engineered constructs.