Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (4/4 displayed)

  • 2023Machine Learning Prediction of Collagen Fiber Orientation and Proteoglycan Content From Multiparametric Quantitative MRI in Articular Cartilage10citations
  • 2004Prediction of biomechanical properties of articular cartilage with quantitative magnetic resonance imaging116citations
  • 2003Structure-function relationships in enzymatically modified articular cartilage118citations
  • 2000Quantitative MR microscopy of enzymatically degraded articular cartilagecitations

Places of action

Chart of shared publication
Casula, Victor
1 / 1 shared
Liimatainen, Timo
1 / 1 shared
Nykänen, Olli
1 / 4 shared
Nissi, Mikko J.
1 / 3 shared
Ketola, Juuso H. J.
1 / 1 shared
Mirmojarabian, Seyed Amir
1 / 1 shared
Töyräs, Juha
3 / 28 shared
Jurvelin, Jukka S.
3 / 11 shared
Helminen, Heikki J.
3 / 3 shared
Laasanen, Mikko S.
1 / 1 shared
Silvennoinen, Johanna
2 / 2 shared
Rieppo, Jarno
2 / 3 shared
Korhonen, Rami K.
1 / 6 shared
Kovanen, Vuokko
1 / 2 shared
Hyttinen, Mika M.
1 / 1 shared
Hakumäki, Juhana M.
1 / 1 shared
Chart of publication period
2023
2004
2003
2000

Co-Authors (by relevance)

  • Casula, Victor
  • Liimatainen, Timo
  • Nykänen, Olli
  • Nissi, Mikko J.
  • Ketola, Juuso H. J.
  • Mirmojarabian, Seyed Amir
  • Töyräs, Juha
  • Jurvelin, Jukka S.
  • Helminen, Heikki J.
  • Laasanen, Mikko S.
  • Silvennoinen, Johanna
  • Rieppo, Jarno
  • Korhonen, Rami K.
  • Kovanen, Vuokko
  • Hyttinen, Mika M.
  • Hakumäki, Juhana M.
OrganizationsLocationPeople

article

Prediction of biomechanical properties of articular cartilage with quantitative magnetic resonance imaging

  • Töyräs, Juha
  • Nieminen, Miika T.
  • Jurvelin, Jukka S.
  • Helminen, Heikki J.
  • Laasanen, Mikko S.
  • Silvennoinen, Johanna
Abstract

Quantitative magnetic resonance imaging (MRI) is the most potential non-invasive means for revealing the structure, composition and pathology of articular cartilage. Here we hypothesize that cartilage mechanical properties as determined by the macromolecular framework and their interactions can be accessed by quantitative MRI. To test this, adjacent cartilage disk pairs (n = 32) were prepared from bovine proximal humerus and patellofemoral surfaces. For one sample, the tissue Young's modulus, aggregate modulus, dynamic modulus and Poisson's ratio were determined in unconfined compression. The adjacent disk was studied at 9.4T to determine the tissue T relaxation time, sensitive to the integrity of the collagen network, and T relaxation time in the presence of Gd-DTPA, a technique developed for the estimation of cartilage proteoglycan (PG) content. Quantitative MRI parameters were able to explain up to 87% of the variations in certain biomechanical parameters. Correlations were further improved when data from the proximal humerus was assessed separately. MRI parameters revealed a topographical variation similar to that of mechanical parameters. Linear regression analysis revealed that Young's modulus of cartilage may be characterized more completely by combining both collagen- and PG-sensitive MRI parameters. The present results suggest that quantitative MRI can provide important information on the mechanical properties of articular cartilage. The results are encouraging with respect to functional imaging of cartilage, although in vivo applicability may be limited by the inferior resolution of clinical MRI instruments.

Topics
  • impedance spectroscopy
  • surface
  • Poisson's ratio