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 language | English |
|---|---|
| Pages (from-to) | 1001-1011 |
| Number of pages | 11 |
| Journal | Medical & Biological Engineering & Computing |
| Volume | 63 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 2025 |
Keywords
- Computer-assisted diagnosis
- Deep learning
- Implant loosening detection
- Pedicle screw
- Spinal fusion surgery
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