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

作者：Leferink Anne M; Fratila Raluca M; Koenrades Maaike A; van Blitterswijk Clemens A; Velders Aldrik; Moroni Lorenzo^*

来源：PLos One, 2014, 9(12): e115000.

DOI：10.1371/journal.pone.0115000

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.

• 出版日期2014-12-12