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Vibroarthrography for early detection of knee osteoarthritis using normalized frequency features

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Abstract

Vibroarthrography is a radiation-free and inexpensive method of assessing the condition of knee cartilage damage during extension-flexion movements. Acoustic sensors were placed on the patella and medial tibial plateau (two accelerometers) as well as on the lateral tibial plateau (a piezoelectric disk) to measure the structure-borne noise in 59 asymptomatic knees and 40 knees with osteoarthritis. After semi-automatic segmentation of the acoustic signals, frequency features were generated for the extension as well as the flexion phase. We propose simple and robust features based on relative high-frequency components. The normalized nature of these frequency features makes them insusceptible to influences on the signal gain, such as attenuation by fat tissue and variance in acoustic coupling. We analyzed their ability to serve as classification features for detection of knee osteoarthritis, including the effect of normalization and the effect of combining frequency features of all three sensors. The features permitted a distinction between asymptomatic and non-healthy knees. Using machine learning with a linear support vector machine, a classification specificity of approximately 0.8 at a sensitivity of 0.75 could be achieved. This classification performance is comparable to existing diagnostic tests and hence qualifies vibroarthrography as an additional diagnostic tool.

Acoustic frequency features were used to detect knee osteoarthritis at 80% specificity and 75% sensitivity.

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Authors and Affiliations

  1. Trauma Surgery Department, University Hospital of Munich, Munich, Germany

    Nima Befrui, Oussama Jarrousse, Tuan Nam Le, Walther H. W. Schulze & Simon Weidert

  2. Munich Innovation Labs, Grünwald, Germany

    Jens Elsner, Jacqueline Huvanandana, Oussama Jarrousse, Marcus Müller, Walther H. W. Schulze & Stefan Taing

  3. CPE GmbH, Willich, Germany

    Achim Flesser

  4. Evolunis UG (haftungsbeschränkt), Knesebeck, Germany

    Walther H. W. Schulze

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  1. Nima Befrui
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Correspondence to Jens Elsner.

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Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

The initial idea for this project and great support during the course of the study was provided by Dr. Jacek Czernicki, who helped with patient recruitment and with conducting the measurements. The authors would also like to thank Dr. Annie Horng for analyzing the MRI data to produce the pathological findings and further Dr. Michael Krüger-Franke for his valuable help with patient recruitment.

This work was co-funded by the German Federal Ministry for Economic Affairs and Energy under grant No. ZIM KF3177601KJ3.

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Befrui, N., Elsner, J., Flesser, A. et al. Vibroarthrography for early detection of knee osteoarthritis using normalized frequency features. Med Biol Eng Comput 56, 1499–1514 (2018). https://doi.org/10.1007/s11517-018-1785-4

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