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Casula V, Kajabi AW. Quantitative MRI methods for the assessment of structure, composition, and function of musculoskeletal tissues in basic research and preclinical applications. MAGMA (NEW YORK, N.Y.) 2024:10.1007/s10334-024-01174-7. [PMID: 38904746 DOI: 10.1007/s10334-024-01174-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 05/04/2024] [Accepted: 05/30/2024] [Indexed: 06/22/2024]
Abstract
Osteoarthritis (OA) is a disabling chronic disease involving the gradual degradation of joint structures causing pain and dysfunction. Magnetic resonance imaging (MRI) has been widely used as a non-invasive tool for assessing OA-related changes. While anatomical MRI is limited to the morphological assessment of the joint structures, quantitative MRI (qMRI) allows for the measurement of biophysical properties of the tissues at the molecular level. Quantitative MRI techniques have been employed to characterize tissues' structural integrity, biochemical content, and mechanical properties. Their applications extend to studying degenerative alterations, early OA detection, and evaluating therapeutic intervention. This article is a review of qMRI techniques for musculoskeletal tissue evaluation, with a particular emphasis on articular cartilage. The goal is to describe the underlying mechanism and primary limitations of the qMRI parameters, their association with the tissue physiological properties and their potential in detecting tissue degeneration leading to the development of OA with a primary focus on basic and preclinical research studies. Additionally, the review highlights some clinical applications of qMRI, discussing the role of texture-based radiomics and machine learning in advancing OA research.
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Affiliation(s)
- Victor Casula
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland.
| | - Abdul Wahed Kajabi
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
- Department of Radiology, University of Minnesota, Minneapolis, MN, USA
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Cobianchi Bellisari F, De Marino L, Arrigoni F, Mariani S, Bruno F, Palumbo P, De Cataldo C, Sgalambro F, Catallo N, Zugaro L, Di Cesare E, Splendiani A, Masciocchi C, Giovagnoni A, Barile A. T2-mapping MRI evaluation of patellofemoral cartilage in patients submitted to intra-articular platelet-rich plasma (PRP) injections. LA RADIOLOGIA MEDICA 2021; 126:1085-1094. [PMID: 34008045 PMCID: PMC8292236 DOI: 10.1007/s11547-021-01372-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 05/05/2021] [Indexed: 12/20/2022]
Abstract
This study evaluated the ability of T2 mapping magnetic resonance imaging at 3 T, in addition to morphological sequences, to assess efficacy of platelet-rich plasma (PRP) injections, characterizing qualitatively and quantitatively the grade of knee cartilage repair in patients with patellofemoral chondropathy. We retrospectively studied 34 patients (22 men, 12 women, mean age 41.8 years, including 22 men) with patellofemoral knee chondropathy, who underwent intra-articular PRP injections and completed a clinical and instrumental follow-up. As control group, we evaluated 34 patients who underwent non-operative therapy. All patients were submitted to clinical (using VAS and WOMAC index) and imaging studies with 3 T magnetic resonance with cartilage analysis with T2 mapping sequences for cartilage analysis before and after treatment. In the study group, mean pre-treatment T2 relaxation time values were 44.2 ± 2.5 ms, considering all articular cartilage compartments, with significant reduction at the follow-up (p < 0.001). At the index compartment, mean pre-treatment T2 relaxation times values were 47.8 ± 3.6 ms, with statistically significant reduction at the follow-up (p < 0.001). Evaluation of focal cartilage lesions reported pre-treatment mean T2 value of 70.1 ± 13.0 ms and post-treatment mean value of 59.9 ± 4.6 ms (p < 0.001). From a clinical point of view, the pre-treatment WOMAC and VAS scores were 18.3 ± 4.5 and 7 (IQR:6-7.2), respectively; the post-treatment values were 7.3 ± 3.2 and 2 (IQR: 1.7-3.0), respectively (p < 0.001). In the control group, despite clinical improvement, we didn't find significant T2 values change during the follow-up period. In conclusion, T2 mapping is a valuable indicator for chondropathy and treatment-related changes over time.
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Affiliation(s)
- Flavia Cobianchi Bellisari
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy.
| | - Luigi De Marino
- Department of Radiologic Sciences, Azienda Ospedaliero Universitaria Ospedali Riuniti, Università Politecnica Delle Marche, Ancona, Italy
| | - Francesco Arrigoni
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
| | - Silvia Mariani
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
| | - Federico Bruno
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
| | - Pierpaolo Palumbo
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
| | - Camilla De Cataldo
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
| | - Ferruccio Sgalambro
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
| | - Nadia Catallo
- Department of Health Sciences, University of L'Aquila, L'Aquila, Italy
| | - Luigi Zugaro
- Radiology Department, S. Salvatore Hospital, L'Aquila, Italy
| | - Ernesto Di Cesare
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
| | - Alessandra Splendiani
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
| | - Carlo Masciocchi
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
| | - Andrea Giovagnoni
- Department of Radiologic Sciences, Azienda Ospedaliero Universitaria Ospedali Riuniti, Università Politecnica Delle Marche, Ancona, Italy
| | - Antonio Barile
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Via Vetoio, 1, 67100, L'Aquila, Italy
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Soheilmoghaddam F, Rumble M, Cooper-White J. High-Throughput Routes to Biomaterials Discovery. Chem Rev 2021; 121:10792-10864. [PMID: 34213880 DOI: 10.1021/acs.chemrev.0c01026] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Many existing clinical treatments are limited in their ability to completely restore decreased or lost tissue and organ function, an unenviable situation only further exacerbated by a globally aging population. As a result, the demand for new medical interventions has increased substantially over the past 20 years, with the burgeoning fields of gene therapy, tissue engineering, and regenerative medicine showing promise to offer solutions for full repair or replacement of damaged or aging tissues. Success in these fields, however, inherently relies on biomaterials that are engendered with the ability to provide the necessary biological cues mimicking native extracellular matrixes that support cell fate. Accelerating the development of such "directive" biomaterials requires a shift in current design practices toward those that enable rapid synthesis and characterization of polymeric materials and the coupling of these processes with techniques that enable similarly rapid quantification and optimization of the interactions between these new material systems and target cells and tissues. This manuscript reviews recent advances in combinatorial and high-throughput (HT) technologies applied to polymeric biomaterial synthesis, fabrication, and chemical, physical, and biological screening with targeted end-point applications in the fields of gene therapy, tissue engineering, and regenerative medicine. Limitations of, and future opportunities for, the further application of these research tools and methodologies are also discussed.
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Affiliation(s)
- Farhad Soheilmoghaddam
- Tissue Engineering and Microfluidics Laboratory (TEaM), Australian Institute for Bioengineering and Nanotechnology (AIBN), University Of Queensland, St. Lucia, Queensland, Australia 4072.,School of Chemical Engineering, University Of Queensland, St. Lucia, Queensland, Australia 4072
| | - Madeleine Rumble
- Tissue Engineering and Microfluidics Laboratory (TEaM), Australian Institute for Bioengineering and Nanotechnology (AIBN), University Of Queensland, St. Lucia, Queensland, Australia 4072.,School of Chemical Engineering, University Of Queensland, St. Lucia, Queensland, Australia 4072
| | - Justin Cooper-White
- Tissue Engineering and Microfluidics Laboratory (TEaM), Australian Institute for Bioengineering and Nanotechnology (AIBN), University Of Queensland, St. Lucia, Queensland, Australia 4072.,School of Chemical Engineering, University Of Queensland, St. Lucia, Queensland, Australia 4072
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Vermeulen S, de Boer J. Screening as a strategy to drive regenerative medicine research. Methods 2020; 190:80-95. [PMID: 32278807 DOI: 10.1016/j.ymeth.2020.04.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 03/30/2020] [Accepted: 04/06/2020] [Indexed: 02/07/2023] Open
Abstract
In the field of regenerative medicine, optimization of the parameters leading to a desirable outcome remains a huge challenge. Examples include protocols for the guided differentiation of pluripotent cells towards specialized and functional cell types, phenotypic maintenance of primary cells in cell culture, or engineering of materials for improved tissue interaction with medical implants. This challenge originates from the enormous design space for biomaterials, chemical and biochemical compounds, and incomplete knowledge of the guiding biological principles. To tackle this challenge, high-throughput platforms allow screening of multiple perturbations in one experimental setup. In this review, we provide an overview of screening platforms that are used in regenerative medicine. We discuss their fabrication techniques, and in silico tools to analyze the extensive data sets typically generated by these platforms.
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Affiliation(s)
- Steven Vermeulen
- Laboratory for Cell Biology-Inspired Tissue Engineering, MERLN Institute, University of Maastricht, Maastricht, the Netherlands; BioInterface Science Group, Department of Biomedical Engineering and Institute for Complex Molecular Systems, University of Eindhoven, Eindhoven, the Netherlands
| | - Jan de Boer
- BioInterface Science Group, Department of Biomedical Engineering and Institute for Complex Molecular Systems, University of Eindhoven, Eindhoven, the Netherlands.
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Haudenschild AK, Sherlock BE, Zhou X, Hu JC, Leach JK, Marcu L, Athanasiou KA. Non-destructive detection of matrix stabilization correlates with enhanced mechanical properties of self-assembled articular cartilage. J Tissue Eng Regen Med 2019; 13:637-648. [PMID: 30770656 DOI: 10.1002/term.2824] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 12/05/2018] [Accepted: 02/13/2019] [Indexed: 11/10/2022]
Abstract
Tissue engineers rely on expensive, time-consuming, and destructive techniques to monitor the composition, microstructure, and function of engineered tissue equivalents. A non-destructive solution to monitor tissue quality and maturation would greatly reduce costs and accelerate the development of tissue-engineered products. The objectives of this study were to (a) determine whether matrix stabilization with exogenous lysyl oxidase-like protein-2 (LOXL2) with recombinant hyaluronan and proteoglycan link protein-1 (LINK) would result in increased compressive and tensile properties in self-assembled articular cartilage constructs, (b) evaluate whether label-free, non-destructive fluorescence lifetime imaging (FLIm) could be used to infer changes in both biochemical composition and biomechanical properties, (c) form quantitative relationships between destructive and non-destructive measurements to determine whether the strength of these correlations is sufficient to replace destructive testing methods, and (d) determine whether support vector machine (SVM) learning can predict LOXL2-induced collagen crosslinking. The combination of exogenous LOXL2 and LINK proteins created a synergistic 4.9-fold increase in collagen crosslinking density and an 8.3-fold increase in tensile strength as compared with control (CTL). Compressive relaxation modulus was increased 5.9-fold with addition of LOXL2 and 3.4-fold with combined treatments over CTL. FLIm parameters had strong and significant correlations with tensile properties (R2 = 0.82; p < 0.001) and compressive properties (R2 = 0.59; p < 0.001). SVM learning based on FLIm-derived parameters was capable of automating tissue maturation assessment with a discriminant ability of 98.4%. These results showed marked improvements in mechanical properties with matrix stabilization and suggest that FLIm-based tools have great potential for the non-destructive assessment of tissue-engineered cartilage.
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Affiliation(s)
- Anne K Haudenschild
- Department of Biomedical Engineering, University of California Davis, Davis, CA, USA
| | - Benjamin E Sherlock
- Department of Biomedical Engineering, University of California Davis, Davis, CA, USA
| | - Xiangnan Zhou
- Department of Biomedical Engineering, University of California Davis, Davis, CA, USA
| | - Jerry C Hu
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA
| | - J Kent Leach
- Department of Biomedical Engineering, University of California Davis, Davis, CA, USA.,Department of Orthopaedic Surgery, University of California Davis Medical Center, Sacramento, CA, USA
| | - Laura Marcu
- Department of Biomedical Engineering, University of California Davis, Davis, CA, USA
| | - Kyriacos A Athanasiou
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA
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Fleck AK, Kruger U, Carlson K, Waltz C, McCallum SA, Lucas Lu X, Wan LQ. Zonal variation of MRI-measurable parameters classifies cartilage degradation. J Biomech 2017; 65:176-184. [DOI: 10.1016/j.jbiomech.2017.10.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Revised: 08/29/2017] [Accepted: 10/15/2017] [Indexed: 01/26/2023]
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Reiter DA, Magin RL, Li W, Trujillo JJ, Pilar Velasco M, Spencer RG. Anomalous T2 relaxation in normal and degraded cartilage. Magn Reson Med 2015; 76:953-62. [PMID: 26336966 DOI: 10.1002/mrm.25913] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2015] [Revised: 08/11/2015] [Accepted: 08/11/2015] [Indexed: 11/05/2022]
Abstract
PURPOSE To compare the ordinary monoexponential model with three anomalous relaxation models-the stretched Mittag-Leffler, stretched exponential, and biexponential functions-using both simulated and experimental cartilage relaxation data. METHODS Monte Carlo simulations were used to examine both the ability of identifying a given model under high signal-to-noise ratio (SNR) conditions and the accuracy and precision of parameter estimates under more modest SNR as would be encountered clinically. Experimental transverse relaxation data were analyzed from normal and enzymatically degraded cartilage samples under high SNR and rapid echo sampling to compare each model. RESULTS Both simulation and experimental results showed improvement in signal representation with the anomalous relaxation models. The stretched exponential model consistently showed the lowest mean squared error in experimental data and closely represents the signal decay over multiple decades of the decay time (e.g., 1-10 ms, 10-100 ms, and >100 ms). The stretched exponential parameter αse showed an inverse correlation with biochemically derived cartilage proteoglycan content. CONCLUSION Experimental results obtained at high field suggest potential application of αse as a measure of matrix integrity. Simulation reflecting more clinical imaging conditions, indicate the ability to robustly estimate αse and distinguish between normal and degraded tissue, highlighting its potential as a biomarker for human studies. Magn Reson Med 76:953-962, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- David A Reiter
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Richard L Magin
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Weiguo Li
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Juan J Trujillo
- Departamento de Análisis Matemático, Universidad de La Laguna, La Laguna, Tenerife, Spain
| | - M Pilar Velasco
- Departamento de Matemática, Estadística e Investigación Operativa, Centro Universitario de la Defensa Universidad de Zaragoza, Zaragoza, Spain
| | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
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Neu CP. Functional imaging in OA: role of imaging in the evaluation of tissue biomechanics. Osteoarthritis Cartilage 2014; 22:1349-59. [PMID: 25278049 PMCID: PMC4185127 DOI: 10.1016/j.joca.2014.05.016] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2014] [Revised: 05/06/2014] [Accepted: 05/17/2014] [Indexed: 02/02/2023]
Abstract
Functional imaging refers broadly to the visualization of organ or tissue physiology using medical image modalities. In load-bearing tissues of the body, including articular cartilage lining the bony ends of joints, changes in strain, stress, and material properties occur in osteoarthritis (OA), providing an opportunity to probe tissue function through the progression of the disease. Here, biomechanical measures in cartilage and related joint tissues are discussed as key imaging biomarkers in the evaluation of OA. Emphasis will be placed on the (1) potential of radiography, ultrasound, and magnetic resonance imaging to assess early tissue pathomechanics in OA, (2) relative utility of kinematic, structural, morphological, and biomechanical measures as functional imaging biomarkers, and (3) improved diagnostic specificity through the combination of multiple imaging biomarkers with unique contrasts, including elastography and quantitative assessments of tissue biochemistry. In comparison to other modalities, magnetic resonance imaging provides an extensive range of functional measures at the tissue level, with conventional and emerging techniques available to potentially to assess the spectrum of preclinical to advance OA.
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Affiliation(s)
- C P Neu
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.
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Irrechukwu ON, Von Thaer S, Frank EH, Lin PC, Reiter DA, Grodzinsky AJ, Spencer RG. Prediction of cartilage compressive modulus using multiexponential analysis of T(2) relaxation data and support vector regression. NMR IN BIOMEDICINE 2014; 27:468-77. [PMID: 24519878 PMCID: PMC4608539 DOI: 10.1002/nbm.3083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2013] [Revised: 12/04/2013] [Accepted: 01/07/2014] [Indexed: 05/14/2023]
Abstract
Evaluation of mechanical characteristics of cartilage by magnetic resonance imaging would provide a noninvasive measure of tissue quality both for tissue engineering and when monitoring clinical response to therapeutic interventions for cartilage degradation. We use results from multiexponential transverse relaxation analysis to predict equilibrium and dynamic stiffness of control and degraded bovine nasal cartilage, a biochemical model for articular cartilage. Sulfated glycosaminoglycan concentration/wet weight (ww) and equilibrium and dynamic stiffness decreased with degradation from 103.6 ± 37.0 µg/mg ww, 1.71 ± 1.10 MPa and 15.3 ± 6.7 MPa in controls to 8.25 ± 2.4 µg/mg ww, 0.015 ± 0.006 MPa and 0.89 ± 0.25MPa, respectively, in severely degraded explants. Magnetic resonance measurements were performed on cartilage explants at 4 °C in a 9.4 T wide-bore NMR spectrometer using a Carr-Purcell-Meiboom-Gill sequence. Multiexponential T2 analysis revealed four water compartments with T2 values of approximately 0.14, 3, 40 and 150 ms, with corresponding weight fractions of approximately 3, 2, 4 and 91%. Correlations between weight fractions and stiffness based on conventional univariate and multiple linear regressions exhibited a maximum r(2) of 0.65, while those based on support vector regression (SVR) had a maximum r(2) value of 0.90. These results indicate that (i) compartment weight fractions derived from multiexponential analysis reflect cartilage stiffness and (ii) SVR-based multivariate regression exhibits greatly improved accuracy in predicting mechanical properties as compared with conventional regression.
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Affiliation(s)
- Onyi N. Irrechukwu
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
| | - Sarah Von Thaer
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
| | - Eliot H. Frank
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Ping-Chang Lin
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
| | - David A. Reiter
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
| | - Alan J. Grodzinsky
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Richard G. Spencer
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
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Appel AA, Anastasio MA, Larson JC, Brey EM. Imaging challenges in biomaterials and tissue engineering. Biomaterials 2013; 34:6615-30. [PMID: 23768903 PMCID: PMC3799904 DOI: 10.1016/j.biomaterials.2013.05.033] [Citation(s) in RCA: 167] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2013] [Accepted: 05/18/2013] [Indexed: 12/11/2022]
Abstract
Biomaterials are employed in the fields of tissue engineering and regenerative medicine (TERM) in order to enhance the regeneration or replacement of tissue function and/or structure. The unique environments resulting from the presence of biomaterials, cells, and tissues result in distinct challenges in regards to monitoring and assessing the results of these interventions. Imaging technologies for three-dimensional (3D) analysis have been identified as a strategic priority in TERM research. Traditionally, histological and immunohistochemical techniques have been used to evaluate engineered tissues. However, these methods do not allow for an accurate volume assessment, are invasive, and do not provide information on functional status. Imaging techniques are needed that enable non-destructive, longitudinal, quantitative, and three-dimensional analysis of TERM strategies. This review focuses on evaluating the application of available imaging modalities for assessment of biomaterials and tissue in TERM applications. Included is a discussion of limitations of these techniques and identification of areas for further development.
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Affiliation(s)
- Alyssa A. Appel
- Department of Biomedical Engineering, Illinois Institute of Technology, 3255 South Dearborn St, Chicago, IL 60616, USA
- Research Service, Hines Veterans Administration Hospital, Hines, IL, USA
| | - Mark A. Anastasio
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Jeffery C. Larson
- Department of Biomedical Engineering, Illinois Institute of Technology, 3255 South Dearborn St, Chicago, IL 60616, USA
- Research Service, Hines Veterans Administration Hospital, Hines, IL, USA
| | - Eric M. Brey
- Department of Biomedical Engineering, Illinois Institute of Technology, 3255 South Dearborn St, Chicago, IL 60616, USA
- Research Service, Hines Veterans Administration Hospital, Hines, IL, USA
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Kotecha M, Klatt D, Magin RL. Monitoring cartilage tissue engineering using magnetic resonance spectroscopy, imaging, and elastography. TISSUE ENGINEERING PART B-REVIEWS 2013; 19:470-84. [PMID: 23574498 DOI: 10.1089/ten.teb.2012.0755] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
A key technical challenge in cartilage tissue engineering is the development of a noninvasive method for monitoring the composition, structure, and function of the tissue at different growth stages. Due to its noninvasive, three-dimensional imaging capabilities and the breadth of available contrast mechanisms, magnetic resonance imaging (MRI) techniques can be expected to play a leading role in assessing engineered cartilage. In this review, we describe the new MR-based tools (spectroscopy, imaging, and elastography) that can provide quantitative biomarkers for cartilage tissue development both in vitro and in vivo. Magnetic resonance spectroscopy can identify the changing molecular structure and alternations in the conformation of major macromolecules (collagen and proteoglycans) using parameters such as chemical shift, relaxation rates, and magnetic spin couplings. MRI provides high-resolution images whose contrast reflects developing tissue microstructure and porosity through changes in local relaxation times and the apparent diffusion coefficient. Magnetic resonance elastography uses low-frequency mechanical vibrations in conjunction with MRI to measure soft tissue mechanical properties (shear modulus and viscosity). When combined, these three techniques provide a noninvasive, multiscale window for characterizing cartilage tissue growth at all stages of tissue development, from the initial cell seeding of scaffolds to the development of the extracellular matrix during construct incubation, and finally, to the postimplantation assessment of tissue integration in animals and patients.
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Affiliation(s)
- Mrignayani Kotecha
- Department of Bioengineering, University of Illinois at Chicago , Chicago, Illinois
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Kotecha M, Ravindran S, Schmid TM, Vaidyanathan A, George A, Magin RL. Application of sodium triple-quantum coherence NMR spectroscopy for the study of growth dynamics in cartilage tissue engineering. NMR IN BIOMEDICINE 2013; 26:709-17. [PMID: 23378198 PMCID: PMC3634872 DOI: 10.1002/nbm.2916] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2012] [Revised: 10/23/2012] [Accepted: 12/09/2012] [Indexed: 06/01/2023]
Abstract
We studied the tissue growth dynamics of tissue-engineered cartilage at an early growth stage after cell seeding for four weeks using sodium triple-quantum coherence NMR spectroscopy. The following tissue-engineering constructs were studied: 1) bovine chondrocytes cultured in alginate beads; 2) bovine chondrocytes cultured as pellets (scaffold-free chondrocyte pellets); and 3) human marrow stromal cells (HMSCs) seeded in collagen/chitosan based biomimetic scaffolds. We found that the sodium triple-quantum coherence spectroscopy could differentiate between different tissue-engineered constructs and native tissues based on the fast and slow components of relaxation rate as well as on the average quadrupolar coupling. Both fast (Tf ) and slow (Ts ) relaxation times were found to be longer in chondrocyte pellets and biomimetic scaffolds compared to chondrocytes suspended in alginate beads and human articular cartilage tissues. In all cases, it was found that relaxation rates and motion of sodium ions measured from correlation times were dependent on the amount of macromolecules, high cell density and anisotropy of the cartilage tissue-engineered constructs. Average quadrupolar couplings were found to be lower in the engineered tissue compared to native tissue, presumably due to the lack of order in collagen accumulated in the engineered tissue. These results support the use of sodium triple-quantum coherence spectroscopy as a tool to investigate anisotropy and growth dynamics of cartilage tissue-engineered constructs in a simple and reliable way.
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Affiliation(s)
- Mrignayani Kotecha
- Department of Bioengineering, University of Illinois at Chicago, IL 60607, USA.
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