Novel Patellofemoral Ligament Modelling to Detect Anterior Knee Pain After Total Knee Arthroplasty

4 pages•Published: March 8, 2024

Andrew Shimmin, Ishaan Jagota, Brett Fritsch, David Parker, Joshua Twiggs and Brad Miles

Abstract

Up to 35% of total knee arthroplasty (TKA) patients experience short term anterior knee pain (AKP) and up to 20% of non-revised knees experience anterior knee pain in the long term. Patellofemoral pain is the primary cause of AKP and accounts for over 8% of revision TKA procedures in Australia. This study introduces a geometric patello- femoral ligament analysis model which was used to differentiate between patients with and without post-operative anterior knee pain.
All patients received pre- and post-operative CT scans and lateral flexed radiograph. The CT scans were segmented and landmarked before being registered to the flexed radiographs. The antero-posterior (AP) of the medial and lateral patellar edge relative to the medial and lateral femoral epicondyles were measured pre- operatively, post-operatively as well as the difference between the two states. These measurements were analysed for their impacts on patient outcome using the Kujala score.
Both medial and lateral antero-posterior patellofemoral offsets had statistically significant, moderate inverse correlations with the overall Kujala score. However, no statistically significant relationship was observed between the post- operative Kujala score and the pre-operative AP offsets or the change in AP offset between the pre- and post-operative states.
The results suggest that a higher medial or lateral post-operative patellofemoral AP offset, potentially due to the overstuffing of the patellofemoral joint, may result in inferior patient outcomes and residual AKP. Overall, it is imperative to consider the possible causes of post-operative AKP and models should be developed to inform surgeons in a clinical setting.

Keyphrases: anterior knee pain, computational modelling, patellofemoral joint, patellofemoral ligament, postoperative outcome, tka, total knee arthroplasty

In: Joshua W Giles (editor). Proceedings of The 22nd Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, vol 6, pages 82-85.

Links:	https://easychair.org/publications/paper/6ffW
	https://doi.org/10.29007/8fds

BibTeX entry

@inproceedings{CAOS2023:Novel_Patellofemoral_Ligament_Modelling,
  author    = {Andrew Shimmin and Ishaan Jagota and Brett Fritsch and David Parker and Joshua Twiggs and Brad Miles},
  title     = {Novel Patellofemoral Ligament Modelling to Detect Anterior Knee Pain After Total Knee Arthroplasty},
  booktitle = {Proceedings of The 22nd Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery},
  editor    = {Joshua W Giles},
  series    = {EPiC Series in Health Sciences},
  volume    = {6},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5305},
  url       = {/publications/paper/6ffW},
  doi       = {10.29007/8fds},
  pages     = {82-85},
  year      = {2024}}

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