4.7 Article

A Novel Method to Simulate the Progression of Collagen Degeneration of Cartilage in the Knee: Data from the Osteoarthritis Initiative

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SCIENTIFIC REPORTS
卷 6, 期 -, 页码 -

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NATURE PUBLISHING GROUP
DOI: 10.1038/srep21415

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资金

  1. European Research Council under the European Union's Seventh Framework Programme (FP)/ERC [281180]
  2. Kuopio and Oulu University Hospitals (VTR) [5041752, K33745]
  3. Finnish Cultural Foundation North Savo regional fund [65142194]
  4. Sigrid Juselius Foundation
  5. Academy of Finland [286526]
  6. Swedish Research Council [2011-5064]
  7. Swedish Foundation for Strategic Research [IB13-0021]
  8. Swedish Foundation for Strategic Research (SSF) [IB13-0021] Funding Source: Swedish Foundation for Strategic Research (SSF)

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We present a novel algorithm combined with computational modeling to simulate the development of knee osteoarthritis. The degeneration algorithm was based on excessive and cumulatively accumulated stresses within knee joint cartilage during physiological gait loading. In the algorithm, the collagen network stiffness of cartilage was reduced iteratively if excessive maximum principal stresses were observed. The developed algorithm was tested and validated against experimental baseline and 4-year follow-up Kellgren-Lawrence grades, indicating different levels of cartilage degeneration at the tibiofemoral contact region. Test groups consisted of normal weight and obese subjects with the same gender and similar age and height without osteoarthritic changes. The algorithm accurately simulated cartilage degeneration as compared to the Kellgren-Lawrence findings in the subject group with excess weight, while the healthy subject group's joint remained intact. Furthermore, the developed algorithm followed the experimentally found trend of cartilage degeneration in the obese group (R-2 = 0.95, p < 0.05; experiments vs. model), in which the rapid degeneration immediately after initiation of osteoarthritis (0-2 years, p < 0.001) was followed by a slow or negligible degeneration (2-4 years, p > 0.05). The proposed algorithm revealed a great potential to objectively simulate the progression of knee osteoarthritis.

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