Drilling Condition Identification Based on Sound Pressure Signal in Anterior Cervical Discectomy Surgery

Med Sci Monit. 2019 Sep 2:25:6574-6580. doi: 10.12659/MSM.917676.

Abstract

BACKGROUND In anterior cervical discectomy and fusion (ACDF) surgery, drilling operation causes a high risk of tissue injury. This study aimed to present a novel feedback system based on sound pressure signals to identify drilling condition during ACDF. MATERIAL AND METHODS ACDF surgery was performed on the C4/5 segments of 6 porcine cervical specimens. The annulus fibrosus, endplate cartilage, sub-endplate cortical bone, and posterior longitudinal ligament (PLL) were drilled until penetration using a 2-mm high-speed burr. Sound pressure signals were collected using a microphone and dynamic signal analyzer. The recorded signals of different tissues were proceeded with lifting wavelet transform for extracting harmonic components. The frequencies of harmonic components are 1, 2, 3, 4, and 5 times higher than the motor frequency. The magnitude of harmonic components was calculated to identify different drilling conditions, along a broad spectrum of frequencies (1-5 kHz). For statistical analysis, one-way ANOVA (analysis of variance) and post hoc test (Dunnett's T3) were performed. RESULTS Very good demarcation was found among the signal magnitudes of different drilling conditions. Different drilling conditions do not present the same rate of variation of frequency. Differences in magnitude among all drilling conditions were statistically significant at certain frequency points (p<0.05). In 3 cases, one tissue could not be identified with respect to another (annulus fibrosus and endplate cartilage at 2 kHz, PLL and penetration at 3 kHz, annulus fibrosus and sub-endplate cortical bone at 5 kHz, p>0.05). CONCLUSIONS Sound pressure signals may provide an auxiliary feedback system for enhancing drilling operation in ACDF surgery, especially in minimally invasive surgery.

MeSH terms

  • Animals
  • Cervical Vertebrae / surgery*
  • Diskectomy*
  • Female
  • Male
  • Pressure*
  • Sound*
  • Swine
  • Wavelet Analysis