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Spine

COMPARING THREE NUCLECTOMY TECHNIQUES: A HIGH-RESOLUTION MRI STUDY

The Society for Back Pain Research (SBPR) Annual General Meeting, ‘PANNING FOR GOLD’ 50+ Anniversary Meeting, Coventry, England, 30 June – 1 July 2022.



Abstract

Introduction

Nucleus replacement surgery has the potential to be an early treatment option for chronic lower back pain. The surgery involves removal (nuclectomy) and replacement of the native degenerated nucleus with a material designed to restore the disc's physiological properties. Multiple techniques have been considered to perform a nuclectomy, however the advantages and disadvantages of each are not well understood. The aim of this study was to quantitatively compare three nuclectomy techniques: automated-shaver, rongeurs, and laser.

Methods and results

Fifteen human vertebra-disc-vertebra lumbar specimens were split into three groups. Before and after nuclectomy axial mechanical tests were performed and T2-weighted 9.4T MRIs were acquired for each specimen. Using the automated-shaver and rongeur similar volumes of disc material were removed (2.51±1.10% and 2.76±1.39% of the total disc volume, respectively), whilst considerably less material was removed when using the laser (0.12±0.07%). Using the automated-shaver and rongeur significantly reduced the toe-region stiffness, while the linear region stiffness was significantly reduced only in the rongeur group. From the MRIs, more homogeneous cavities were seen in the center of the disc when using the automated shaver compared to rongeur, whilst laser ablation resulted in small, localized cavities.

Conclusion

Results suggest that the current laser parameters are not suitable for removal of large volumes of material unless the technique is optimised for this application. Both rongeurs and automated-shavers can be used to remove large volumes of material but the reduced risk of collateral damage to surrounding tissues suggests that an automated-shaver may be more suitable.

Conflicts of interest: No conflicts of interest

Sources of funding: Part of this work was funded by an Imperial College Research Fellowship for NN and an EPSRC DTP CASE Conversion Studentship for TR (EP/R513052/1).


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