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Related Experiment Video

Updated: Jun 7, 2025

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Exploring healthy knee kinematic phenotypes obtained through dynamic CT imaging: A cluster analysis study.

E H S Teule1, S A W van de Groes2, G Hannink3

  • 1Radboud University Medical Center, Orthopaedic Research Laboratory, Nijmegen, Netherlands (the); Radboud University Medical Center, Department of Plastic Surgery, Nijmegen, Netherlands (the).

Journal of Biomechanics
|November 10, 2024
PubMed
Summary

Dynamic Computed Tomography (CT) reveals two distinct knee kinematic phenotypes in healthy individuals. These findings offer crucial reference points for understanding knee joint variations and diagnosing pathologies.

Keywords:
Dynamic CTHealthy participantsK-means clusteringKinematic phenotypesKnee kinematics

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Area of Science:

  • Biomechanics
  • Medical Imaging
  • Orthopedics

Background:

  • Dynamic Computed Tomography (CT) is vital for assessing knee joint kinematics.
  • Significant variations in knee kinematics exist within healthy populations, complicating clinical integration.
  • A need exists for classifying healthy knee kinematics into homogenous phenotypes.

Purpose of the Study:

  • To identify and characterize distinct healthy knee kinematic phenotypes.
  • To utilize a clustering approach for analyzing dynamic CT data.
  • To establish reference phenotypes for healthy knee joint movement.

Main Methods:

  • 120 healthy knees underwent dynamic CT scanning during flexion and extension.
  • Eight tibiofemoral (TF) and patellofemoral kinematic parameters were extracted.
  • K-means clustering was applied to identify homogenous kinematic groups.

Main Results:

  • Two distinct kinematic clusters were identified, with 53 and 67 knees respectively.
  • Six of eight kinematic parameters showed statistically significant differences between clusters.
  • Cluster 1 displayed greater internal and adduction tibial rotation compared to Cluster 2.

Conclusions:

  • Two distinct healthy knee kinematic phenotypes were identified using dynamic CT.
  • These phenotypes highlight nuanced variations within a healthy cohort.
  • The identified phenotypes can serve as a reference for future studies on pathological knee kinematics.