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
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 threedimensional
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.
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 threedimensional
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.