Skeletal Radiology

, Volume 48, Issue 1, pp 89–101 | Cite as

Baseline knee joint effusion and medial femoral bone marrow edema, in addition to MRI-based T2 relaxation time and texture measurements of knee cartilage, can help predict incident total knee arthroplasty 4–7 years later: data from the Osteoarthritis Initiative

  • Ursula Heilmeier
  • John Mbapte Wamba
  • Gabby B. Joseph
  • Karin Darakananda
  • Jennifer Callan
  • Jan Neumann
  • Thomas M. Link
Scientific Article



To evaluate if baseline pathological knee conditions as assessed via single features of the MR-based Whole-Organ Magnetic Resonance Imaging Scoring (WORMS), standard T2, and T2 gray-level co-occurrence matrix (GLCM) texture parameters of knee cartilage can serve as potential long-term radiological predictors of incident total knee arthroplasty (TKA) 4–7 years later.

Materials and methods

Baseline 3-T knee MRIs of 309 subjects from the Osteoarthritis Initiative (n = 81 TKA cases, with right-knee TKA 4–7 years after enrolment, and n = 228 TKA-free matched controls) were evaluated for the presence and severity of pathological knee conditions via modified WORMS. Knee cartilage was segmented and standard T2 cartilage and T2 GLCM texture measures (contrast, variance) were computed. Statistical analysis employed conditional logistic regression.


We found that a one-point increase on the joint effusion scale, the bone marrow edema scale or on the cartilage lesion scale at baseline predicted incident TKA (ORs: 2.45, 1.65, and 1.37 respectively (p ≤ 0.003)). For T2 cartilage measurements, we observed that in the lateral femur, a 1-SD increase in T2 relaxation time yielded a 28% increase in the odds of TKA (1.28 [1.09–1.643], p = 0.046). When looking at cartilage texture, we similarly noted that a 1-SD increase in the cartilage texture parameter “contrast” was associated with a 33–40% increased risk of incident TKA in the lateral femur and tibia (0.003 ≤ p ≤ 0.021), as was a 1-SD increase in the texture parameter “variance” in the lateral femur (p = 0.002).


Radiological evaluation of standard knee MR images via single WORMS features and T2 standard and texture analysis at baseline can help predict the patient’s individual risk for an incident TKA 4–7 years later.


Cartilage T2 relaxation time Magnetic resonance imaging Knee Total knee arthroplasty Osteoarthritis Predictive value of tests 



We would like to thank Felix Liu, John Lynch, and Nancy Lane for their valuable input and support. In addition, we would like to thank Prof. Nevitt and Prof. McCulloch for their statistical support.

Funds and grants

The study was supported by the Osteoarthritis Initiative, a public–private partnership comprising 5 NIH contracts (National Institute of Arthritis and Musculoskeletal and Skin Diseases contracts N01-AR-2-2258, N01-AR-2-2259, N01-AR-2-2260, N01-AR-2-2261, and N01-AR-2-2262), with research conducted by the Osteoarthritis Initiative Study Investigators. The study also received funding in part by the Intramural Research Program of the National Institute on Aging, NIH. Private funding partners involved are Merck Research, Novartis Pharmaceuticals, GlaxoSmithKline, and Pfizer; the private sector funding for the Osteoarthritis Initiative is orchestrated by the Foundation for the National Institutes of Health. This manuscript was prepared using an OAI public use data set and does not necessarily reflect the opinions or views of the OAI investigators, the NIH, or the private funding partners. The analyses were also funded through several grants awarded by NIH NIAMS (National Institute of Arthritis and Musculoskeletal and Skin Diseases): these were NIH U01-AR059507 (to TML), NIH P50-AR060752 (to TML) and NIH R01AR064771 (to TML).

Compliance with ethical standards

Conflicts of interest

The authors declare that they have no conflicts of interest.

Ethical approval

The OAI multicenter study is HIPAA-compliant and received approval by the institutional review boards at each clinical site. All study participants consented in writing to the study before study participation.


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Copyright information

© ISS 2018

Authors and Affiliations

  • Ursula Heilmeier
    • 1
  • John Mbapte Wamba
    • 1
  • Gabby B. Joseph
    • 1
  • Karin Darakananda
    • 1
  • Jennifer Callan
    • 1
  • Jan Neumann
    • 1
  • Thomas M. Link
    • 1
  1. 1.Musculoskeletal Quantitative Imaging Research Group, Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoUSA

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