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J Tissue Eng Regen Med ; 3(6): 477-85, 2009 Aug.
Article in English | MEDLINE | ID: mdl-19530259

ABSTRACT

Non-invasive magnetic resonance imaging (MRI) is a technology that enables the characterization of multiple physical phenomena in living and engineered tissues. The mechanical function of engineered tissues is a primary endpoint for the successful regeneration of many biological tissues, such as articular cartilage, spine and heart. Here we demonstrate the application of MRI to characterize the mechanical function of engineered tissue. Phase contrast-based methods were demonstrated to characterize detailed deformation fields throughout the interior of native and engineered tissue, using an articular cartilage defect model as a study system. MRI techniques revealed that strain fields varied non-uniformly, depending on spatial position. Strains were highest in the tissue constructs compared to surrounding native cartilage. Tissue surface geometry corresponded to strain fields observed within the tissue interior near the surface. Strain fields were further evaluated with respect to the spatial variation in the concentration of glycosaminoglycans ([GAG]), critical proteoglycans in the extracellular matrix of cartilage, as determined by gadolinium-enhanced imaging. [GAG] also varied non-uniformly, depending on spatial position and was lowest in the tissue constructs compared to the surrounding cartilage. The use of multiple MRI techniques to assess tissue mechanical function provides complementary data and suggests that deformation is related to tissue geometry, underlying extracellular matrix constituents and the lack of tissue integration in the model system studied. Specialized and advanced MRI phase contrast-based methods are valuable for the detailed characterization and evaluation of mechanical function of tissue-engineered constructs.


Subject(s)
Magnetic Resonance Imaging , Materials Testing/methods , Tissue Engineering , Animals , Biomechanical Phenomena , Cartilage/cytology , Cattle , Glycosaminoglycans/metabolism , Models, Biological
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