Literature DB >> 17442320

Feasibility of noninvasive evaluation of biophysical properties of tissue-engineered cartilage by using quantitative MRI.

Shogo Miyata1, Tomokazu Numano, Kazuhiro Homma, Tetsuya Tateishi, Takashi Ushida.   

Abstract

The application of tissue-engineered cartilage in a clinical setting requires a noninvasive method to assess the biophysical and biochemical properties of the engineered cartilage. Since articular cartilage is composed of 70-80% water and has dense extracellular matrixes (ECM), it is considered that the condition of the water molecules in the tissue is correlated with its biomechanical property. Therefore, magnetic resonance imaging (MRI) represents a potential approach to assess the biophysical property of the engineered cartilage. In this study, we test the hypothesis that quantitative MRI can be used as a noninvasive assessment method to assess the biophysical property of the engineered cartilage. To reconstruct a model of cartilaginous tissue, chondrocytes harvested from the humeral head of calves were embedded in an agarose gel and cultured in vitro up to 4 weeks. Equilibrium Young's moduli were determined from the stress relaxation tests. After mechanical testing, MRI-derived parameters (longitudinal relaxation time T1, transverse relaxation time T2, and water self-diffusion coefficient D) were measured. The equilibrium Young's modulus of the engineered cartilage showed a tendency to increase with an increase in the culture time, whereas T1 and D decreased. Based on a regression analysis, T1 and D showed a strong correlation with the equilibrium Young's modulus. The results showed that T1 and D values derived from the MRI measurements could be used to noninvasively monitor the biophysical properties of the engineered cartilage.

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Year:  2007        PMID: 17442320     DOI: 10.1016/j.jbiomech.2007.02.002

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  13 in total

1.  Characterization of engineered cartilage constructs using multiexponential T₂ relaxation analysis and support vector regression.

Authors:  Onyi N Irrechukwu; David A Reiter; Ping-Chang Lin; Remigio A Roque; Kenneth W Fishbein; Richard G Spencer
Journal:  Tissue Eng Part C Methods       Date:  2012-02-21       Impact factor: 3.056

2.  The maturity of tissue-engineered cartilage in vitro affects the repairability for osteochondral defect.

Authors:  Cheng Zhe Jin; Jae-Ho Cho; Byung Hyune Choi; Li Ming Wang; Moon Suk Kim; So Ra Park; Jeong Ho Yoon; Jung Ho Yun; Hyun Ju Oh; Byoung-Hyun Min
Journal:  Tissue Eng Part A       Date:  2011-10-17       Impact factor: 3.845

3.  Magnetization transfer imaging provides a quantitative measure of chondrogenic differentiation and tissue development.

Authors:  Weiguo Li; Liu Hong; Liping Hu; Richard L Magin
Journal:  Tissue Eng Part C Methods       Date:  2010-05-10       Impact factor: 3.056

4.  Application of sodium triple-quantum coherence NMR spectroscopy for the study of growth dynamics in cartilage tissue engineering.

Authors:  Mrignayani Kotecha; Sriram Ravindran; Thomas M Schmid; Aishwarya Vaidyanathan; Anne George; Richard L Magin
Journal:  NMR Biomed       Date:  2013-02-03       Impact factor: 4.044

5.  Noninvasive assessment of glycosaminoglycan production in injectable tissue-engineered cartilage constructs using magnetic resonance imaging.

Authors:  Sharan Ramaswamy; Mehmet C Uluer; Stephanie Leen; Preeti Bajaj; Kenneth W Fishbein; Richard G Spencer
Journal:  Tissue Eng Part C Methods       Date:  2008-09       Impact factor: 3.056

6.  Characterization of engineered tissue construct mechanical function by magnetic resonance imaging.

Authors:  C P Neu; H F Arastu; S Curtiss; A H Reddi
Journal:  J Tissue Eng Regen Med       Date:  2009-08       Impact factor: 3.963

7.  Protein polymer MRI contrast agents: Longitudinal analysis of biomaterials in vivo.

Authors:  Lindsay S Karfeld-Sulzer; Emily A Waters; Ellen K Kohlmeir; Hermann Kissler; Xiaomin Zhang; Dixon B Kaufman; Annelise E Barron; Thomas J Meade
Journal:  Magn Reson Med       Date:  2011-01       Impact factor: 4.668

8.  Prediction of cartilage compressive modulus using multiexponential analysis of T(2) relaxation data and support vector regression.

Authors:  Onyi N Irrechukwu; Sarah Von Thaer; Eliot H Frank; Ping-Chang Lin; David A Reiter; Alan J Grodzinsky; Richard G Spencer
Journal:  NMR Biomed       Date:  2014-02-12       Impact factor: 4.044

Review 9.  Monitoring cartilage tissue engineering using magnetic resonance spectroscopy, imaging, and elastography.

Authors:  Mrignayani Kotecha; Dieter Klatt; Richard L Magin
Journal:  Tissue Eng Part B Rev       Date:  2013-06-04       Impact factor: 6.389

10.  Temporal development of near-native functional properties and correlations with qMRI in self-assembling fibrocartilage treated with exogenous lysyl oxidase homolog 2.

Authors:  Pasha Hadidi; Derek D Cissell; Jerry C Hu; Kyriacos A Athanasiou
Journal:  Acta Biomater       Date:  2017-09-28       Impact factor: 8.947

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