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Radiographic findings involved in knee osteoarthritis progression are associated with pain symptom frequency and baseline disease severity: a population-level analysis using deep learning

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Knee Surgery, Sports Traumatology, Arthroscopy Aims and scope

Abstract

Purpose

To (1) develop a deep-learning (DL) algorithm capable of producing limb-length and knee-alignment measurements, and (2) determine the association between limb-length discrepancy (LLD), coronal-plane alignment, osteoarthritis (OA) severity, and patient-reported knee pain.

Methods

A multicenter, prospective patient cohort from the Osteoarthritis Initiative between 2004 and 2015 with full-limb standing radiographs at 12 month follow-up was included. A convolutional neural network was developed to automate measurements of the hip–knee–ankle (HKA) angle, femur, and tibia lengths, and LLD. At 12 month follow-up, patients reported their frequency of knee pain since enrollment and current level of knee pain.

Results

A total of 1011 patients (2022 knees, 52.3% female) with an average age of 61.2 ± 9.0 years were included. The algorithm performed 12,312 measurements in 5.4 h. ICC values of HKA and LLD ranged between 0.87 and 1.00 when compared against trained radiologist measurements. Knees producing pain most days of the month were significantly more varus (mean HKA:− 3.9° ± 2.8°) or valgus (mean HKA:2.8° ± 2.3°) compared to knees that did not produce any pain (p < 0.05). In varus knees, those producing pain on most days were part of the shorter limb compared to nonpainful knees (p < 0.05). Baseline Kellgren–Lawrence grade was significantly associated with HKA magnitude, LLD, and pain frequency at 12 month follow-up (p < 0.05 all).

Conclusion

A higher frequency of knee pain was associated with more severe coronal plane deformity, with valgus deviation being one degree less than varus on average, suggesting that the knee tolerates less valgus deformation before symptoms become more consistent. Knee pain frequency was also associated with greater LLD and baseline KL grade, suggesting an association between radiographically apparent joint degeneration and pain frequency.

Level of evidence

IV case series.

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Funding

No funding was received for this work.

Author information

Authors and Affiliations

  1. Department of Orthopedic Surgery, Hospital for Special Surgery, 535 East 70th Street, New York, NY, 10021, USA

    Kyle N. Kunze, Seong Jun Jang, David A. Mayman, Jonathan M. Vigdorchik, Seth A. Jerabek, Austin T. Fragomen & Peter K. Sculco

  2. Weill Cornell College of Medicine, New York, NY, USA

    Seong Jun Jang & Tim Li

  3. Adult Reconstruction and Joint Replacement Service, Hospital for Special Surgery, New York, NY, USA

    David A. Mayman, Jonathan M. Vigdorchik, Seth A. Jerabek & Peter K. Sculco

  4. Limb Lengthening and Complex Reconstruction Service, Hospital for Special Surgery, New York, NY, USA

    Austin T. Fragomen

Authors
  1. Kyle N. Kunze
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Contributions

KK: writing of initial manuscript, methodology, and supervision. SJ: writing of initial manuscript and data analysis. TL: data procurement and data analysis. DM, JV, PS, AF, and SJ: revision of initial manuscript and supervision.

Corresponding author

Correspondence to Kyle N. Kunze.

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Conflict of interest

Each author certifies that he or she has no commercial associations (e.g., consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article.

Ethical approval

This study was conducted using a public de-identified online database (Osteoarthritis Initiative) for secondary data analysis. The creation of the database was approved by the institutional review board at the respective institutions involved in the OAI.

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Supplementary Information

Below is the link to the electronic supplementary material.

167_2022_7213_MOESM1_ESM.jpg

Supplementary file1 Correlation plot between deep learning derived and radiologist derived measurements in all knees (JPG 661 KB)

167_2022_7213_MOESM2_ESM.jpg

Supplementary file2 Association between baseline KL grade and coronal plane alignment at one-year stratified by grade (JPG 660 KB)

Supplementary file3 Association between baseline KL grade and LLD at one-year stratified by grade (JPG 730 KB)

Supplementary file3 Association between baseline KL grade and LLD at one-year stratified by grade (JPG 730 KB)

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Kunze, K.N., Jang, S.J., Li, T. et al. Radiographic findings involved in knee osteoarthritis progression are associated with pain symptom frequency and baseline disease severity: a population-level analysis using deep learning. Knee Surg Sports Traumatol Arthrosc 31, 586–595 (2023). https://doi.org/10.1007/s00167-022-07213-x

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