Association of Machine Learning–Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis. Issue 9 (6th August 2021)
- Record Type:
- Journal Article
- Title:
- Association of Machine Learning–Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis. Issue 9 (6th August 2021)
- Main Title:
- Association of Machine Learning–Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis
- Authors:
- Brisson, Nicholas M.
Gatti, Anthony A.
Damm, Philipp
Duda, Georg N.
Maly, Monica R. - Abstract:
- Abstract : Objective: The relationship between in vivo knee load predictions and longitudinal cartilage changes has not been investigated. We undertook this study to develop an equation to predict the medial tibiofemoral contact force (MCF) peak during walking in persons with instrumented knee implants, and to apply this equation to determine the relationship between the predicted MCF peak and cartilage loss in patients with knee osteoarthritis (OA). Methods: In adults with knee OA (39 women, 8 men; mean ± SD age 61.1 ± 6.8 years), baseline biomechanical gait analyses were performed, and annualized change in medial tibial cartilage volume (mm 3 /year) over 2.5 years was determined using magnetic resonance imaging. In a separate sample of patients with force‐measuring tibial prostheses (3 women, 6 men; mean ± SD age 70.3 ± 5.2 years), gait data plus in vivo knee loads were used to develop an equation to predict the MCF peak using machine learning. This equation was then applied to the knee OA group, and the relationship between the predicted MCF peak and annualized cartilage volume change was determined. Results: The MCF peak was best predicted using gait speed, the knee adduction moment peak, and the vertical knee reaction force peak (root mean square error 132.88N; R 2 = 0.81, P < 0.001). In participants with knee OA, the predicted MCF peak was related to cartilage volume change (R 2 = 0.35, β = −0.119, P < 0.001). Conclusion: Machine learning was used to develop a novelAbstract : Objective: The relationship between in vivo knee load predictions and longitudinal cartilage changes has not been investigated. We undertook this study to develop an equation to predict the medial tibiofemoral contact force (MCF) peak during walking in persons with instrumented knee implants, and to apply this equation to determine the relationship between the predicted MCF peak and cartilage loss in patients with knee osteoarthritis (OA). Methods: In adults with knee OA (39 women, 8 men; mean ± SD age 61.1 ± 6.8 years), baseline biomechanical gait analyses were performed, and annualized change in medial tibial cartilage volume (mm 3 /year) over 2.5 years was determined using magnetic resonance imaging. In a separate sample of patients with force‐measuring tibial prostheses (3 women, 6 men; mean ± SD age 70.3 ± 5.2 years), gait data plus in vivo knee loads were used to develop an equation to predict the MCF peak using machine learning. This equation was then applied to the knee OA group, and the relationship between the predicted MCF peak and annualized cartilage volume change was determined. Results: The MCF peak was best predicted using gait speed, the knee adduction moment peak, and the vertical knee reaction force peak (root mean square error 132.88N; R 2 = 0.81, P < 0.001). In participants with knee OA, the predicted MCF peak was related to cartilage volume change (R 2 = 0.35, β = −0.119, P < 0.001). Conclusion: Machine learning was used to develop a novel equation for predicting the MCF peak from external biomechanical parameters. The predicted MCF peak was positively related to medial tibial cartilage volume loss in patients with knee OA. … (more)
- Is Part Of:
- Arthritis & rheumatology. Volume 73:Issue 9(2021)
- Journal:
- Arthritis & rheumatology
- Issue:
- Volume 73:Issue 9(2021)
- Issue Display:
- Volume 73, Issue 9 (2021)
- Year:
- 2021
- Volume:
- 73
- Issue:
- 9
- Issue Sort Value:
- 2021-0073-0009-0000
- Page Start:
- 1638
- Page End:
- 1645
- Publication Date:
- 2021-08-06
- Subjects:
- Arthritis -- Periodicals
Rheumatism -- Periodicals
616.72 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2326-5205 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/art.41735 ↗
- Languages:
- English
- ISSNs:
- 2326-5191
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1733.820000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24074.xml