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A new sensing paradigm for the vibroacoustic detection of pedicle screw loosening

  • Matthias Seibold
  • , Bastian Sigrist
  • , Tobias Götschi
  • , Jonas Widmer
  • , Sandro Hodel
  • , Mazda Farshad
  • , Nassir Navab
  • , Philipp Fürnstahl
  • , Christoph J. Laux
  • University Hospital Balgrist
  • Technical University of Munich

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Abstract: The current clinical gold standard to assess the condition and detect loosening of pedicle screw implants is radiation-emitting medical imaging. However, solely based on medical imaging, clinicians are not able to reliably identify loose implants in a substantial amount of cases. To complement medical imaging for pedicle screw loosening detection, we propose a new methodology and paradigm for the radiation-free, non-destructive, and easy-to-integrate loosening detection based on vibroacoustic sensing. For the detection of a loose implant, we excite the vertebra of interest with a sine sweep vibration at the spinous process and use a custom highly sensitive piezo vibration sensor attached directly at the screw head to capture the propagated vibration characteristics which are analyzed using a detection pipeline based on spectrogram features and a SE-ResNet-18. To validate the proposed approach, we propose a novel, biomechanically validated simulation technique for pedicle screw loosening, conduct experiments using four human cadaveric lumbar spine specimens, and evaluate our algorithm in a cross-validation experiment. The proposed method reaches a sensitivity of 91.50±6.58% and a specificity of 91.10±2.27% for pedicle screw loosening detection.

Original languageEnglish
Pages (from-to)1001-1011
Number of pages11
JournalMedical & Biological Engineering & Computing
Volume63
Issue number4
DOIs
StatePublished - Apr 2025

Keywords

  • Computer-assisted diagnosis
  • Deep learning
  • Implant loosening detection
  • Pedicle screw
  • Spinal fusion surgery

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