Oral Presentation Sydney Spinal Symposium 2022

Smart orthopaedic implants: A targeted approach for continuous postoperative evaluation in the spine (#9)

Vivek Ramakrishna 1 2 3 , Uphar Chamoli 4 , Subhas C Mukhopadhyay 3 , Gangadhara Prusty 1 , Ashish D Diwan 5
  1. School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, NSW, Australia
  2. Spine Labs, St. George & Sutherland Clinical School, University of New South Wales, Sydney, NSW, Australia
  3. School of Engineering, Faculty of Science and Engineering, Macquarie University, Sydney, NSW, Australia
  4. St. George and Sutherland Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
  5. Spine Service, Department of Orthopaedic Surgery, St. George Hospital Campus, Kogarah, NSW, Australia

Aims

There are several complications associated with lumbar interbody fusion (LIF) surgery however, pseudarthrosis presents a multifaceted challenge in the postoperative management of the patient. Rates of pseudarthrosis at least one year after LIF surgery range from 3-20% in patients with healthy bone and 20-30% in patients with osteoporosis. Plain radiographs and fine-cut CT have high false positive rates and poor agreement between the two modalities. The aim of this study was to develop a proof-of-concept load-sensing interbody cage to determine whether it may be used to monitor fusion progression.

Methods

Amphenol P122 pressure sensors were bonded to printed circuit boards (PCBs), which connected to a Raspberry Pi microcontroller to convert and transmit the sensor outputs. The sensors were individually calibrated within their overload limits. A polyether ether ketone (PEEK) interbody cage was manufactured with CNC milling to fit the PCBs within. Silicone and poly (methyl methacrylate) (PMMA) were inserted in the graft regions to simulate early and full fusion. The load-sensing cage was loaded with distributed and eccentric loads up to 900N at 0.6mm/min between two pieces of synthetic bone with dimensions of lumbar vertebral bodies. A finite element analysis model was developed with identical conditions to the experimental setup.

Results

Under maximum load, the anterior sensors recorded a 56-58% reduction in pressure in the full fusion state compared to early fusion. Lateral regions measured a 36-37% stress reduction while the central location reduced by 45%. The two graft states were similarly distinguishable by sensor-recorded pressure at lower loads. The experimental results generally fell within the range of the average and maximum values obtained from simulation. The sensors more effectively detected left and right eccentric loads compared to anterior and posterior. Further, the load-sensing cage was able to detect changes in endplate stiffness.

Conclusion

The proof-of-concept load-sensing interbody cage is able to detect differences in fusion state, endplate stiffness, and loading conditions in this in vitro experimental setup. Future research should aim to improve the implantability of the device by reducing the number of sensors, improving durability, and optimising the sensing configuration.