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

Research output: Contribution to journalArticlepeer-review

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. Graphical abstract: (Figure presented.)

Original languageEnglish
JournalMedical & Biological Engineering & Computing
DOIs
StateAccepted/In press - 2024

Keywords

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

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