A study of the effectiveness of ultrasound imaging in the early detection of cartilage degeneration in the knee joint of athletes

  • Ling Tang Department of Ultrasonography, Xiangya Hospital of Central South University, Changsha 410008, China
Keywords: ultrasound imaging technique; knee joint; VAS score; MRI assessment; cartilage degeneration
Article ID: 980

Abstract

Knee injury is one of the common sports injuries, this paper aims to analyze the performance of ultrasound imaging technology in the assessment of early detection of athletes with knee pain, to provide a reliable assessment index for clinical diagnosis and treatment and an index for judging the efficacy. To analyze the causes of cartilage degeneration in athletes’ knee joints, and to evaluate and compare the ultrasound imaging method with the commonly used clinical assessment (Visual Analogue Scale (VAS) score, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score) and imaging assessment (Digital Radiography(DR), Magnetic Resonance Imaging (MRI)) for knee osteoarthritis according to the advantageous performance of ultrasound imaging technology in the examination of knee joint diseases. The correlation between ultrasound assessment and VAS score and WOMAC score, as well as DR assessment and MRI assessment were obtained, respectively. To investigate the value of ultrasonography in the evaluation of patients with osteoarthritis of the knee. The ultrasound scores of the knee were positively correlated with the VAS scores and WOMAC scores, with correlation coefficients of 0.891 and 0.902, respectively. The correlation coefficients of ultrasound ratings with DR ratings and MRI ratings were 0.876 and 0.895, respectively (both > 0.75), which were good correlations.

References

1. Stetter, B. J., Ringhof, S., Krafft, F. C., Sell, S., & Stein, T. (2019). Estimation of knee joint forces in sport movements using wearable sensors and machine learning. Sensors, 19(17), 3690.

2. Kadhim, F. M., Chiad, J. S., &Takhakh, A. M. (2018, December). Design and manufacturing knee joint for smart transfemoral prosthetic. In IOP conference series: materials science and engineering (Vol. 454, p. 012078). IOP Publishing.

3. Lluch, E., Dueñas, L., Falla, D., Baert, I., Meeus, M., Sanchez-Frutos, J., & Nijs, J. (2018). Preoperative pain neuroscience education combined with knee joint mobilization for knee osteoarthritis: a randomized controlled trial. The Clinical journal of pain, 34(1), 44-52.

4. Beidokhti, H. N., Janssen, D., van de Groes, S., Hazrati, J., Van den Boogaard, T., &Verdonschot, N. (2017). The influence of ligament modelling strategies on the predictive capability of finite element models of the human knee joint. Journal of biomechanics, 65, 1-11.

5. Ghai, S., Driller, M. W., & Masters, R. S. (2018). The influence of below-knee compression garments on knee-joint proprioception. Gait & posture, 60, 258-261.

6. Harput, G. (2020). Kinesiology of the knee joint. In Comparative Kinesiology of the Human Body (pp. 393-410). Academic Press.

7. Zhou, Z., Zhao, G., Kijowski, R., & Liu, F. (2018). Deep convolutional neural network for segmentation of knee joint anatomy. Magnetic resonance in medicine, 80(6), 2759-2770.

8. Tan, J. S., Tippaya, S., Binnie, T., Davey, P., Napier, K., Caneiro, J. P., ... & Campbell, A. (2022). Predicting knee joint kinematics from wearable sensor data in people with knee osteoarthritis and clinical considerations for future machine learning models. Sensors, 22(2), 446.

9. Tran, J., Peng, P. W., Lam, K., Baig, E., Agur, A. M., &Gofeld, M. (2018). Anatomical study of the innervation of anterior knee joint capsule: implication for image-guided intervention. Regional Anesthesia & Pain Medicine, 43(4), 407-414.

10. Ferket, B. S., Feldman, Z., Zhou, J., Oei, E. H., Bierma-Zeinstra, S. M., & Mazumdar, M. (2017). Impact of total knee replacement practice: cost effectiveness analysis of data from the Osteoarthritis Initiative. bmj, 356.

11. Vaienti, E., Scita, G., Ceccarelli, F., &Pogliacomi, F. (2017). Understanding the human knee and its relationship to total knee replacement. Acta Bio Medica: AteneiParmensis, 88(Suppl 2), 6.

12. Price, A. J., Alvand, A., Troelsen, A., Katz, J. N., Hooper, G., Gray, A., ... & Beard, D. (2018). Knee replacement. The Lancet, 392(10158), 1672-1682.

13. Eitner, A., Pester, J., Vogel, F., Marintschev, I., Lehmann, T., Hofmann, G. O., & Schaible, H. G. (2017). Pain sensation in human osteoarthritic knee joints is strongly enhanced by diabetes mellitus. Pain, 158(9), 1743-1753.

14. Guo, R., Lu, G., Qin, B., & Fei, B. (2018). Ultrasound imaging technologies for breast cancer detection and management: a review. Ultrasound in medicine & biology, 44(1), 37-70.

15. Wang, Y., Ge, X., Ma, H., Qi, S., Zhang, G., & Yao, Y. (2021). Deep learning in medical ultrasound image analysis: a review. IEEE Access, 9, 54310-54324.

16. Lee, W., & Roh, Y. (2017). Ultrasonic transducers for medical diagnostic imaging. Biomedical engineering letters, 7(2), 91-97.

17. Javlanovich, D., Zafar, Y., Karimov, B., Gaybullaev, S. O. U., &Mirzakulov, M. M. U. (2022). Ultrasonic and radiological picture in the combination of chronic venous insufficiency and osteoarthritis of the knee joints. Academic research in educational sciences, 3(5), 945-956.

18. Amandullaevich, A. Y., Zafarjanovich, U. Z., &Isroilovich, T. T. (2022). ULTRASONIC EXAMINATION OF INJURIES OF THE KNEE JOINT. Yosh TadqiqotchiJurnali, 1(4), 338-346.

19. D’Agostino, V., Sorriento, A., Cafarelli, A., Donati, D., Papalexis, N., Russo, A., ... & Spinnato, P. (2024). Ultrasound imaging in knee osteoarthritis: current role, recent advancements, and future perspectives. Journal of Clinical Medicine, 13(16), 4930.

20. Liu, B., Xu, H. Y., Zhang, R., Han, L., Li, Y., & Sun, X. F. (2023). An Update on Clinical Utility of Musculoskeletal Ultrasonography in Knee Osteoarthritis. Journal of Ultrasound in Medicine, 42(7), 1413-1422.

21. You, K., & Cao, H. (2020). Application of Medical Ultrasound in Rehabilitation of Knee Joint Injury. InvestigaciónClínica, 61(1), 22-30.

22. Vasilev, V. A., Ivanisenko, A. V., Konovalova, I. I., &Lukashuk, A. F. (2020). Possibilities of ultrasound examination of the knee joint in the diagnosis of Hoffa’s disease. Genij Ortopedii, 26(1), 44-49.

23. Chen, S. B., Lin, S. B., Li, Y. Q., & Liu, Y. T. (2020). Characteristics of musculoskeletal ultrasound versus X-ray in their differential diagnosis of knee osteoarthritis. Int. J. Clin. Exp. Med, 13, 8734-8739.

24. Yuxing Xu & Chao Zhang. (2024). Prediction of lateral neck metastasis in patients with papillary thyroid cancer with suspicious lateral lymph ultrasonic imaging based on central lymph node metastasis features.. Oncology letters(4),472.

25. ZhengdongLi,XuepingJiang,Meng Zhang &Tiaoyin Zhu. (2024). Ultrasonic imaging assisted by Phase Coherence and Synthetic Aperture Focusing Technology. Journal of Physics: Conference Series(1),012176-012176.

26. LexiuXu,YifangLi,QinzhenShi,Yunyun Zhang & Dean Ta. (2024). Full-waveform ultrasonic imaging for bone. Journal of Physics: Conference Series(1),012005-012005.

Published
2025-01-10
How to Cite
Tang, L. (2025). A study of the effectiveness of ultrasound imaging in the early detection of cartilage degeneration in the knee joint of athletes. Molecular & Cellular Biomechanics, 22(1), 980. https://doi.org/10.62617/mcb980
Section
Article