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Normal and malaligned talonavicular fusion alters cadaveric foot pressure and kinematics.

Elizabeth P WahlWilliam D LinEric C WhittakerBrian K CookBruce J SangeorzanWilliam R Ledoux
Published in: Journal of orthopaedic research : official publication of the Orthopaedic Research Society (2024)
Talonavicular (TN) fusion is a common treatment for TN arthritis or deformity correction. There is incongruous evidence regarding remaining motion at the talocalcaneal and calcaneocuboid joints after TN fusion. Additionally, the effects of a malaligned TN fusion are not well understood and alignment of the fusion may be important for overall foot integrity. This project assessed the kinematic and kinetic effects of neutral and malaligned TN fusions. Ten cadaveric feet were tested on a gait simulator in four conditions: unfused, fused in neutral, fused in varus, and fused in valgus. The fusions were simulated with external fixation hardware. An eight-camera motion analysis system and a 10-segment foot model generated kinematic data, and a pressure mat captured pressure data. Simulated TN fusion was achieved in eight feet. From unfused to fused-neutral, range of motion (ROM) was not eliminated in the adjacent joints, but the positions of the joints changed significantly throughout stance phase. Furthermore, the ROM increased at the tibiotalar joint. Plantar pressure and center of pressure shifted laterally with neutral fusion. The malalignments marginally affected the ROM but changed joint positions throughout stance phase. Pressure patterns were shifted laterally in varus malalignment and medially in valgus malalignment. The residual motion and the altered kinematics at the joints in the triple joint complex after TN fusion may subsequently increase the incidence of arthritis. Clinical significance: This study quantifies the effects of talonavicular fusion and malalignment on the other joints of the triple joint complex.
Keyphrases
  • rheumatoid arthritis
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  • high speed
  • electronic health record
  • machine learning
  • big data
  • high resolution
  • deep learning
  • ultrasound guided
  • convolutional neural network