The purpose of this study was to determine if the noninvasive and nondestructive technique of magnetic resonance imaging could be used to quantify the amount of repair tissue that fills surgically-induced chondral defects in the rabbit. Sixteen 4-mm diameter full-thickness chondral defects were created. A photopolymerizable hydrogel was used to seal the defects as a treatment modality. At 5 weeks, the animals were sacrificed and the distal femur was subjected to MRI analyses at high field (9.4 T). The transverse relaxation time (T(2)) in each defect was measured. Histology and histomorphometric analysis were used to quantify the amount of repair tissue that filled each defect. The relationship between T(2) and percent tissue fill was found to fit well to a negatively sloped, linear model. The linear (Pearson's product-moment) correlation coefficient was found to be r = -0.82 and the associated coefficient of determination was r(2) = 0.67. This correlation suggests that the MRI parameter T(2) can be used to track changes in the amount of repair tissue that fills cartilage defects. This would be especially useful in in vivo cartilage tissue engineering studies that attempt to determine optimal biomaterials for scaffold design.
[Show abstract][Hide abstract] ABSTRACT: The glycosaminoglycan (GAG) content of engineered cartilage is a determinant of biochemical and mechanical quality. The ability to measure the degree to which GAG content is maintained or increases in an implant is therefore of importance in cartilage repair procedures. The gadolinium exclusion magnetic resonance imaging (MRI) method for estimating matrix fixed charge density (FCD) is ideally suited to this. One promising approach to cartilage repair is use of seeded injectable hydrogels. Accordingly, we assess the reliability of measuring GAG content in such a system ex vivo using MRI. Samples of the photopolymerizable hydrogel, poly(ethylene oxide) diacrylate, were seeded with bovine chondrocytes (approximately 2.4 million cells/sample). The FCD of the constructs was determined using MRI after 9, 16, 29, 36, 43, and 50 days of incubation. Values were correlated with the results of biochemical determination of GAG from the same samples. FCD and GAG were found to be statistically significantly correlated (R2 = 0.91, p < 0.01). We conclude that MRI-derived FCD measurements of FCD in injectable hydrogels reflect tissue GAG content and that this methodology therefore has potential for in vivo monitoring of such constructs.
Tissue Engineering Part C Methods 07/2008; 14(3):243-9. DOI:10.1089/ten.tec.2007.0423 · 4.64 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Assessment of tissue regeneration is essential to optimize the stages of tissue engineering (cell proliferation, tissue development and implantation). Optical and X-ray imaging have been used in tissue engineering to provide useful information, but each has limitations: for example, poor depth penetration and radiation damage. Magnetic resonance imaging (MRI) largely overcomes these restrictions, exhibits high resolution (approximately 100 microm) and can be applied both in vitro and in vivo. Recently, MRI has been used in tissue engineering to generate spatial maps of tissue relaxation times (T(1), T(2)), water diffusion coefficients, and the stiffness (shear moduli) of developing engineered tissues. In addition, through the use of paramagnetic and superparamagnetic contrast agents, MRI can quantify cell death, assess inflammation, and visualize cell trafficking and gene expression. After tissue implantation MRI can be used to observe the integration of a tissue implant with the surrounding tissues, and to check for early signs of immune rejection. In this review, we describe and evaluate the growing role of MRI in the assessment of tissue engineered constructs. First, we briefly describe the underlying principles of MRI and the expected changes in relaxation times (T(1), T(2)) and the water diffusion coefficient that are the basis for MR contrast in developing tissues. Next, we describe how MRI can be applied to evaluate the tissue engineering of mesenchymal tissues (bone, cartilage, and fat). Finally, we outline how MRI can be used to monitor tissue structure, composition, and function to improve the entire tissue engineering process.
Journal of Bioscience and Bioengineering 01/2009; 106(6):515-27. DOI:10.1263/jbb.106.515 · 1.88 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Engineering of adipose tissue by implantation of preadipocytes within biodegradable materials has already been extensively reported. However, a method that allows to accurately determine the resorption rate of adipose tissue constructs has not been described to date. The purpose of this study was to determine whether the non-invasive and non-destructive technique of magnetic resonance imaging (MRI) could be used to assess the resorption rate of adipose tissue substitutes after injection of human preadipocytes within fibrin into athymic nude mice. Different concentrations of undifferentiated preadipocytes were injected within fibrin into athymic nude mice. Two days, 3 months and 6 months post-implantation, the mice were anaesthetised and an MRI was performed using a 9.4 Tesla device in order to determine both volume and resorption rate of the implants. Subsequently, the specimens were explanted and qualitative analysis of adipose tissue formation was performed by histological examination. After implantation, a progressive resorption of all constructs was macroscopically observed. Implants could be easily visualised and delimited from the surrounding tissues by MRI. Magnetic resonance analysis demonstrated a resorption rate of the implants of 99-100% at 6 months, which was also confirmed by histological analysis. In the remaining implants, formation of human adipose tissue could be immunohistologically confirmed. Here, we show that MRI provides an efficient and non-invasive method for the assessment of implant resorption in adipose tissue engineering.
Journal of Plastic Reconstructive & Aesthetic Surgery 01/2011; 64(1):117-22. DOI:10.1016/j.bjps.2010.03.042 · 1.42 Impact Factor
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