Revealing Detailed Cartilage Function Through Nanoparticle Diffusion Imaging: A Computed Tomography & Finite Element Study.
Computational modeling
Constituent-specific behavior
Contrast-enhanced computed tomography
Dual-contrast agent
Osteoarthritis
Photon-counting detector
Journal
Annals of biomedical engineering
ISSN: 1573-9686
Titre abrégé: Ann Biomed Eng
Pays: United States
ID NLM: 0361512
Informations de publication
Date de publication:
16 Jul 2024
16 Jul 2024
Historique:
received:
12
01
2024
accepted:
23
05
2024
medline:
16
7
2024
pubmed:
16
7
2024
entrez:
16
7
2024
Statut:
aheadofprint
Résumé
The ability of articular cartilage to withstand significant mechanical stresses during activities, such as walking or running, relies on its distinctive structure. Integrating detailed tissue properties into subject-specific biomechanical models is challenging due to the complexity of analyzing these characteristics. This limitation compromises the accuracy of models in replicating cartilage function and impacts predictive capabilities. To address this, methods revealing cartilage function at the constituent-specific level are essential. In this study, we demonstrated that computational modeling derived individual constituent-specific biomechanical properties could be predicted by a novel nanoparticle contrast-enhanced computer tomography (CECT) method. We imaged articular cartilage samples collected from the equine stifle joint (n = 60) using contrast-enhanced micro-computed tomography (µCECT) to determine contrast agents' intake within the samples, and compared those to cartilage functional properties, derived from a fibril-reinforced poroelastic finite element model. Two distinct imaging techniques were investigated: conventional energy-integrating µCECT employing a cationic tantalum oxide nanoparticle (Ta
Identifiants
pubmed: 39012563
doi: 10.1007/s10439-024-03552-7
pii: 10.1007/s10439-024-03552-7
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Instrumentariumin Tiedesäätiö
ID : 190021
Organisme : Competitive State Research Funding of the Kuopio University Hospital Catchment Area
ID : 5041795
Organisme : Competitive State Research Funding of the Kuopio University Hospital Catchment Area
ID : 5063579
Organisme : Research Council of Finland
ID : 324529
Organisme : Research Council of Finland
ID : 357787
Organisme : Research Council of Finland
ID : 348410
Organisme : Regional Council of Pohjois-Savo
ID : A74798
Informations de copyright
© 2024. The Author(s).
Références
Bansal, P. N., N. S. Joshi, V. Entezari, M. W. Grinstaff, and B. D. Snyder. Contrast enhanced computed tomography can predict the glycosaminoglycan content and biomechanical properties of articular cartilage. Osteoarthr. Cartil. 18:184–191, 2010.
doi: 10.1016/j.joca.2009.09.003
Bansal, P. N., N. S. Joshi, V. Entezari, B. C. Malone, R. C. Stewart, B. D. Snyder, and M. W. Grinstaff. Cationic contrast agents improve quantification of glycosaminoglycan (GAG) content by contrast enhanced CT imaging of cartilage. J. Orthop. Res. 29:704–709, 2011.
pubmed: 21437949
doi: 10.1002/jor.21312
Bhattarai, A., J. T. J. Honkanen, K. A. H. Myller, M. Prakash, M. Korhonen, A. E. A. Saukko, T. N. Viré, A. Joukainen, A. N. Patwa, H. Kro, M. W. Grinstaff, and J. S. Jurvelin. Quantitative dual contrast CT technique for evaluation of articular cartilage properties. Ann. Biomed. Eng. 46:1038–1046, 2018.
pubmed: 29654384
doi: 10.1007/s10439-018-2013-y
Bhattarai, A., J. T. A. Mäkelä, B. Pouran, H. Kröger, H. Weinans, M. W. Grinstaff, J. Töyräs, and M. J. Turunen. Effects of human articular cartilage constituents on simultaneous diffusion of cationic and nonionic contrast agents. J. Orthop. Res. 39:771–779, 2021.
pubmed: 32767676
doi: 10.1002/jor.24824
Bhattarai, A., B. Pouran, J. T. A. Mäkelä, R. Shaikh, M. K. M. Honkanen, M. Prakash, H. Kröger, M. W. Grinstaff, H. Weinans, J. S. Jurvelin, and J. Töyräs. Dual contrast in computed tomography allows earlier characterization of articular cartilage over single contrast. J. Orthop. Res. 38:2230–2238, 2020.
pubmed: 32525582
doi: 10.1002/jor.24774
Didomenico, C. D., M. Lintz, and L. J. Bonassar. Molecular transport in articular cartilage—what have we learned from the past 50 years? Nat. Rev. Rheumatol. 14:393–403, 2018.
pubmed: 29899547
doi: 10.1038/s41584-018-0033-5
DiSilvestro, M. R., and J. K. F. Suh. A cross-validation of the biphasic poroviscoelastic model of articular cartilage in unconfined compression, indentation, and confined compression. J. Biomech. 34:519–525, 2001.
pubmed: 11266676
doi: 10.1016/S0021-9290(00)00224-4
Ebrahimi, M. Structure, Composition and Function of Human Tibiofemoral Joint Cartilage. Publications of the University of Eastern Finland Dissertations in Forestry and Natural Sciences No: 486, 2022, 13–64 pp.
Ebrahimi, M., M. A. J. Finnilä, A. Turkiewicz, M. Enhlund, S. Saarakkala, R. K. Korhonen, and P. Tanska. Elastic, dynamic viscoelastic and model-derived fibril-reinforced poroelastic mechanical properties of normal and osteoarthritic human femoral condyle cartilage. Ann. Biomed. Eng. 49:2622–2634, 2021.
pubmed: 34341898
pmcid: 8455392
doi: 10.1007/s10439-021-02838-4
Ebrahimi, M., S. Ojanen, A. Mohammadi, M. A. Finnilä, A. Joukainen, H. Kröger, S. Saarakkala, R. K. Korhonen, and P. Tanska. Elastic, viscoelastic and fibril-reinforced poroelastic material properties of healthy and osteoarthritic human tibial cartilage. Ann. Biomed. Eng. 47:953–966, 2019.
pubmed: 30690688
pmcid: 8494710
doi: 10.1007/s10439-019-02213-4
Ebrahimi, M., M. J. Turunen, M. A. Finnilä, A. Joukainen, H. Kröger, S. Saarakkala, R. K. Korhonen, and P. Tanska. Structure-function relationships of healthy and osteoarthritic human tibial cartilage: experimental and numerical investigation. Ann. Biomed. Eng. 48:2887–2900, 2020.
pubmed: 32648191
pmcid: 7723942
doi: 10.1007/s10439-020-02559-0
Evans, R. C., and T. M. Quinn. Solute diffusivity correlates with mechanical properties and matrix density of compressed articular cartilage. Arch. Biochem. Biophys. 442:1–10, 2005.
pubmed: 16157289
doi: 10.1016/j.abb.2005.07.025
Fowkes, M. M., P. D. N. Borges, F. Cacho-Nerin, P. E. Brennan, T. L. Vincent, and N. H. Lim. Imaging articular cartilage in osteoarthritis using targeted peptide radiocontrast agents. PLoS ONE. 17(5):e0268223, 2022.
pubmed: 35536857
pmcid: 9089912
doi: 10.1371/journal.pone.0268223
Freedman, J. D., H. Lusic, B. D. Snyder, and M. W. Grinstaff. Tantalum oxide nanoparticles for the imaging of articular cartilage using X-ray computed tomography: visualization of ex vivo/in vivo murine tibia and ex vivo human index finger cartilage. Angew. Chem. Int. Ed. 53:8406–8410, 2014.
doi: 10.1002/anie.201404519
Fripp, J., S. Crozier, S. K. Warfield, and S. Ourselin. Automatic segmentation of articular cartilage in magnetic resonance images of the knee. In: Medical Image Computing and Computer-Assisted Intervention, 2007, pp. 186–194.
Fugazzola, M., M. T. Nissinen, J. Jäntti, J. Tuppurainen, S. Plomp, N. Te Moller, J. T. A. Mäkelä, and R. van Weeren. Composition, architecture and biomechanical properties of articular cartilage in differently loaded areas of the equine stifle. Equine Vet. J. 56(3):573–585, 2023.
pubmed: 37376723
doi: 10.1111/evj.13960
Halonen, K. S., M. E. Mononen, J. S. Jurvelin, J. Töyräs, and R. K. Korhonen. Importance of depth-wise distribution of collagen and proteoglycans in articular cartilage—a 3D finite element study of stresses and strains in human knee joint. J. Biomech. 46:1184–1192, 2013.
pubmed: 23384762
doi: 10.1016/j.jbiomech.2012.12.025
Honkanen, M. K. M., H. Matikka, J. T. J. Honkanen, A. Bhattarai, M. W. Grinstaff, A. Joukainen, H. Kröger, J. S. Jurvelin, and J. Töyräs. Imaging of proteoglycan and water contents in human articular cartilage with full-body CT using dual contrast technique. J. Orthop. Res. 37:1059–1070, 2019.
pubmed: 30816584
pmcid: 6594070
doi: 10.1002/jor.24256
Honkanen, M. K. M., A. E. A. Saukko, M. J. Turunen, R. Shaikh, M. Prakash, G. Lovric, A. Joukainen, H. Kröger, M. W. Grinstaff, and J. Töyräs. Synchrotron MicroCT reveals the potential of the dual contrast technique for quantitative assessment of human articular cartilage composition. J. Orthop. Res. 38:563–573, 2020.
pubmed: 31535728
doi: 10.1002/jor.24479
Honkanen, M. K. M., A. E. A. Saukko, M. J. Turunen, W. Xu, G. Lovric, J. T. J. Honkanen, M. W. Grinstaff, V. P. Lehto, and J. Töyräs. Triple contrast CT method enables simultaneous evaluation of articular cartilage composition and segmentation. Ann. Biomed. Eng. 48:556–567, 2020.
pubmed: 31576504
doi: 10.1007/s10439-019-02362-6
Huttu, M. R. J., J. Puhakka, J. T. A. Mäkelä, Y. Takakubo, V. Tiitu, S. Saarakkala, Y. T. Konttinen, I. Kiviranta, and R. K. Korhonen. Cell-tissue interactions in osteoarthritic human hip joint articular cartilage. Connect. Tissue Res. 55:282–291, 2014.
pubmed: 24702070
doi: 10.3109/03008207.2014.912645
Jäntti, J., A. Joenathan, M. Fugazzola, J. Tuppurainen, J. T. J. Honkanen, J. Töyräs, R. van Weeren, B. D. Snyder, M. W. Grinstaff, H. Matikka, and J. T. A. Mäkelä. Cationic tantalum oxide nanoparticle contrast agent for micro computed tomography reveals articular cartilage proteoglycan distribution and collagen architecture alterations. Osteoarthr. Cartil. 32:299–309, 2024.
doi: 10.1016/j.joca.2023.11.020
Jäntti, J., A. Joenathan, M. Fugazzola, R. van Weeren, B. D. Synder, M. W. Grinstaff, J. Töyräs, H. Matikka, and J. T. Mäkelä. Tantalum oxide nanoparticles for contrast enhanced computed tomography imaging of cartilage. Osteoarthr. Cartil. 30:S277, 2022.
doi: 10.1016/j.joca.2022.02.374
Julkunen, P., T. Harjula, J. Iivarinen, J. Marjanen, K. Seppänen, T. Närhi, J. Arokoski, M. J. Lammi, P. A. Brama, J. S. Jurvelin, and H. J. Helminen. Biomechanical, biochemical and structural correlations in immature and mature rabbit articular cartilage. Osteoarthr. Cartil. 17:1628–1638, 2009.
doi: 10.1016/j.joca.2009.07.002
Julkunen, P., T. Harjula, J. Marjanen, H. J. Helminen, and J. S. Jurvelin. Comparison of single-phase isotropic elastic and fibril-reinforced poroelastic models for indentation of rabbit articular cartilage. J. Biomech. 42:652–656, 2009.
pubmed: 19193381
doi: 10.1016/j.jbiomech.2008.12.010
Julkunen, P., P. Kiviranta, W. Wilson, J. S. Jurvelin, and R. K. Korhonen. Characterization of articular cartilage by combining microscopic analysis with a fibril-reinforced finite-element model. J. Biomech. 40:1862–1870, 2007.
pubmed: 17052722
doi: 10.1016/j.jbiomech.2006.07.026
Julkunen, P., W. Wilson, H. Isaksson, J. S. Jurvelin, W. Herzog, and R. K. Korhonen. A review of the combination of experimental measurements and fibril-reinforced modeling for investigation of articular cartilage and chondrocyte response to loading. Comput. Math. Methods Med.2013:326150, 2013.
pubmed: 23653665
pmcid: 3638701
doi: 10.1155/2013/326150
Juntunen, M. A. K. Technical and algorithmic approaches for medical photon counting computed tomography in the example of coronary artery calcium quantification. Acta Univ. Oul. D 1592, 2020.
Juntunen, M. A. K., S. I. Inkinen, J. H. Ketola, A. Kotiaho, M. Kauppinen, A. Winkler, and M. T. Nieminen. Framework for photon counting quantitative material decomposition. IEEE Trans. Med. Imaging. 39:35–47, 2020.
pubmed: 31144630
doi: 10.1109/TMI.2019.2914370
Kokkonen, H. T., J. Mäkelä, K. A. M. Kulmala, L. Rieppo, J. S. Jurvelin, V. Tiitu, H. M. Karjalainen, R. K. Korhonen, V. Kovanen, and J. Töyräs. Computed tomography detects changes in contrast agent diffusion after collagen cross-linking typical to natural aging of articular cartilage. Osteoarthr. Cartil. 19:1190–1198, 2011.
doi: 10.1016/j.joca.2011.07.008
Korhonen, R. K., M. S. Laasanen, J. Töyräs, R. Lappalainen, H. J. Helminen, and J. S. Jurvelin. Fibril reinforced poroelastic model predicts specifically mechanical behavior of normal, proteoglycan depleted and collagen degraded articular cartilage. J. Biomech. 36:1373–1379, 2003.
pubmed: 12893046
doi: 10.1016/S0021-9290(03)00069-1
Laasanen, M. S., J. Töyräs, R. K. Korhonen, J. Rieppo, S. Saarakkala, M. T. Nieminen, J. Hirvonen, and J. S. Jurvelin. Biomechanical properties of knee articular cartilage. Biorheology. 40:133–140, 2003.
pubmed: 12454397
Lawson, T., A. Joenathan, A. Patwa, B. D. Snyder, and M. W. Grinstaff. Tantalum oxide nanoparticles for the quantitative contrast-enhanced computed tomography of ex vivo human cartilage: assessment of biochemical composition and biomechanics. ACS Nano. 15:19175–19184, 2021.
pubmed: 34882411
doi: 10.1021/acsnano.1c03375
Leddy, H. A., and F. Guilak. Site-specific molecular diffusion in articular cartilage measured using fluorescence recovery after photobleaching. Ann. Biomed. Eng. 31:753–760, 2003.
pubmed: 12971608
doi: 10.1114/1.1581879
Li, L. P., M. D. Buschmann, and A. Shirazi-Adl. A fibril reinforced nonhomogeneous poroelastic model for articular cartilage: inhomogeneous response in unconfined compression. J. Biomech. 33:1533–1541, 2000.
pubmed: 11006376
doi: 10.1016/S0021-9290(00)00153-6
Li, L. P., and W. Herzog. Arthroscopic evaluation of cartilage degeneration using indentation testing—influence of indenter geometry. Clin. Biomech. 21:420–426, 2006.
doi: 10.1016/j.clinbiomech.2005.12.010
Li, L. P., J. Soulhat, M. D. Buschmann, and A. Shirazi-Adl. Nonlinear analysis of cartilage in unconfined ramp compression using a fibril reinforced poroelastic model. Clin. Biomech. 14:673–682, 1999.
doi: 10.1016/S0268-0033(99)00013-3
Lipshitz, H., R. Etheredge 3rd., and M. J. Glimcher. Changes in the hexosamine content and swelling ratio of articular cartilage as functions of depth from the surface. J. Bone Jt. Surg. Am. 58:1149–1153, 1976.
doi: 10.2106/00004623-197658080-00021
Mäkelä, J. Dissertations in forestry and natural sciences: structural and functional alterrations of articular cartilage in osteoarthritis. 2016.
Mäkelä, J. T. A., S.-K. Han, W. Herzog, and R. K. Korhonen. Very early osteoarthritis changes sensitively fluid flow properties of articular cartilage. J. Biomech. 48:3369–3376, 2015.
pubmed: 26159056
doi: 10.1016/j.jbiomech.2015.06.010
Mäkelä, J. T. A., M. R. J. Huttu, and R. K. Korhonen. Structure–function relationships in osteoarthritic human hip joint articular cartilage. Osteoarthr. Cartil. 20:1268–1277, 2012.
doi: 10.1016/j.joca.2012.07.016
Malda, J., K. E. M. Benders, T. J. Klein, J. C. de Grauw, M. J. L. Kik, D. W. Hutmacher, D. B. F. Saris, P. R. van Weeren, and W. J. A. Dhert. Comparative study of depth-dependent characteristics of equine and human osteochondral tissue from the medial and lateral femoral condyles. Osteoarthr. Cartil. 20:1147–1151, 2012.
doi: 10.1016/j.joca.2012.06.005
Maroudas, A. Distribution and diffusion of solutes in articular cartilage. Biophys. J. 10:365–379, 1970.
pubmed: 4245322
pmcid: 1367772
doi: 10.1016/S0006-3495(70)86307-X
Maroudas, A. Biophysical chemistry of cartilaginous tissues with special reference to solute and fluid transport. Biorheology. 12:233–248, 1975.
pubmed: 1106795
doi: 10.3233/BIR-1975-123-416
Meng, H., Q. Quan, X. Yuan, Y. Zheng, J. Peng, Q. Guo, A. Wang, and S. Lu. Diffusion of neutral solutes within human osteoarthritic cartilage: effect of loading patterns. J. Orthop. Transl. 22:58–66, 2020.
Mohammadi, A., K. A. H. Myller, P. Tanska, J. Hirvasniemi, S. Saarakkala, J. Töyräs, R. K. Korhonen, and M. E. Mononen. Rapid CT-based estimation of articular cartilage biomechanics in the knee joint without cartilage segmentation. Ann. Biomed. Eng. 48:2965–2975, 2020.
pubmed: 33179182
pmcid: 7723937
doi: 10.1007/s10439-020-02666-y
Mononen, M. E., M. K. Liukkonen, and R. K. Korhonen. Utilizing atlas-based modeling to predict knee joint cartilage degeneration: data from the osteoarthritis initiative. Ann. Biomed. Eng. 47:813–825, 2019.
pubmed: 30547410
doi: 10.1007/s10439-018-02184-y
Mononen, M. E., P. Tanska, H. Isaksson, and R. K. Korhonen. New algorithm for simulation of proteoglycan loss and collagen degeneration in the knee joint: data from the osteoarthritis initiative. J. Orthop. Res. 36:1673–1683, 2018.
pubmed: 29150953
doi: 10.1002/jor.23811
Myller, K. A. H., J. T. J. Honkanen, J. S. Jurvelin, S. Saarakkala, J. Töyräs, and S. P. Väänänen. Method for segmentation of knee articular cartilages based on contrast-enhanced CT images. Ann. Biomed. Eng. 46:1756–1767, 2018.
pubmed: 30132213
doi: 10.1007/s10439-018-2081-z
Nieminen, H. J., T. Ylitalo, S. Karhula, J. P. Suuronen, S. Kauppinen, R. Serimaa, E. Hæggström, K. P. H. Pritzker, M. Valkealahti, P. Lehenkari, M. Finnilä, and S. Saarakkala. Determining collagen distribution in articular cartilage using contrast-enhanced micro-computed tomography. Osteoarthr. Cartil. 23:1613–1621, 2015.
doi: 10.1016/j.joca.2015.05.004
Nimer, E., R. Schneiderman, and A. Maroudas. Diffusion and partition of solutes in cartilage under static load. Biophys. Chem. 106:125–146, 2003.
pubmed: 14556902
doi: 10.1016/S0301-4622(03)00157-1
Nissinen, M. T., N. Hänninen, M. Prakash, J. T. A. Mäkelä, M. J. Nissi, J. Töyräs, M. T. Nieminen, R. K. Korhonen, and P. Tanska. Functional and structural properties of human patellar articular cartilage in osteoarthritis. J. Biomech.126:110634, 2021.
pubmed: 34454206
doi: 10.1016/j.jbiomech.2021.110634
Orozco, G. A., A. S. A. Eskelinen, J. P. Kosonen, M. S. Tanaka, M. Yang, T. M. Link, B. Ma, X. Li, A. J. Grodzinsky, R. K. Korhonen, and P. Tanska. Shear strain and inflammation-induced fixed charge density loss in the knee joint cartilage following ACL injury and reconstruction: a computational study. J. Orthop. Res. 40:1505–1522, 2022.
pubmed: 34533840
doi: 10.1002/jor.25177
Paakkari, P., S. I. Inkinen, M. K. M. Honkanen, M. Prakash, R. Shaikh, M. T. Nieminen, M. W. Grinstaff, J. T. A. Mäkelä, J. Töyräs, and J. T. J. Honkanen. Quantitative dual contrast photon-counting computed tomography for assessment of articular cartilage health. Sci. Rep. 11:5556, 2021.
pubmed: 33692379
pmcid: 7946949
doi: 10.1038/s41598-021-84800-x
Pedoia, V., X. Li, F. Su, N. Calixto, and S. Majumdar. Fully automatic analysis of the knee articular cartilage T1ρ relaxation time using voxel-based relaxometry. J. Magn. Reson. Imaging. 43:970–980, 2016.
pubmed: 26443990
doi: 10.1002/jmri.25065
Räsänen, L. P., M. E. Mononen, E. Lammentausta, M. T. Nieminen, J. S. Jurvelin, and R. K. Korhonen. Three dimensional patient-specific collagen architecture modulates cartilage responses in the knee joint during gait. Comput. Methods Biomech. Biomed. Eng. 19:1225–1240, 2016.
doi: 10.1080/10255842.2015.1124269
Saukko, A. E. A., J. T. J. Honkanen, W. Xu, S. P. Väänänen, J. S. Jurvelin, V.-P. Lehto, and J. Töyräs. Dual contrast CT method enables diagnostics of cartilage injuries and degeneration using a single CT image. Ann. Biomed. Eng. 45:2857–2866, 2017.
pubmed: 28924827
doi: 10.1007/s10439-017-1916-3
Saukko, A. E. A., M. J. Turunen, M. K. M. Honkanen, G. Lovric, V. Tiitu, J. T. J. Honkanen, M. W. Grinstaff, J. S. Jurvelin, and J. Töyräs. Simultaneous quantitation of cationic and non-ionic contrast agents in articular cartilage using synchrotron MicroCT imaging. Sci. Rep. 9:7118, 2019.
pubmed: 31068614
pmcid: 6506503
doi: 10.1038/s41598-019-43276-6
Torzilli, P. A., J. M. Arduino, J. D. Gregory, and M. Bansal. Effect of proteoglycan removal on solute mobility in articular cartilage. J. Biomech. 30:895–902, 1997.
pubmed: 9302612
doi: 10.1016/S0021-9290(97)00059-6
van der Voet, A. A comparison of finite element codes for the solution of biphasic poroelastic problems. Proc. Inst. Mech. Eng. H. 211:209–211, 1997.
pubmed: 9184461
Wilson, W., C. C. Van Donkelaar, B. Van Rietbergen, K. Ito, and R. Huiskes. Stresses in the local collagen network of articular cartilage: a poroviscoelastic fibril-reinforced finite element study. J. Biomech. 37:357–366, 2004.
pubmed: 14757455
doi: 10.1016/S0021-9290(03)00267-7
Wilson, W., C. C. Van Donkelaar, B. Van Rietbergen, K. Ito, and R. Huiskes. Erratum to “Stresses in the local collagen network of articular cartilage: a poroviscoelastic fibril-reinforced finite element study” [Journal of Biomechanics 37 (2004) 357–366] and “A fibril-reinforced poroviscoelastic swelling model for articular cartilage.” J. Biomech. 38:2138–2140, 2005.
doi: 10.1016/j.jbiomech.2005.04.024
Zhang, K., W. Lu, and P. Marziliano. Automatic knee cartilage segmentation from multi-contrast MR images using support vector machine classification with spatial dependencies. Magn. Reson. Imaging. 31:1731–1743, 2013.
pubmed: 23867282
doi: 10.1016/j.mri.2013.06.005