Journal of Orthopaedic Surgery and Research (Apr 2024)

Preoperative MRI-based endplate quality: a novel tool for predicting cage subsidence after anterior cervical spine surgery

  • Yuan Tuo,
  • Kaiyuan Lin,
  • Junsong Yang,
  • Sibo Wang,
  • Haimiti Abudouaini

DOI
https://doi.org/10.1186/s13018-024-04716-w
Journal volume & issue
Vol. 19, no. 1
pp. 1 – 9

Abstract

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Abstract Purpose The objective of this study was to examine the predictive value of a newly developed MRI-based Endplate Bone Quality (EBQ) in relation to the development of cage subsidence following anterior cervical discectomy and fusion (ACDF). Methods Patients undergoing ACDF for degenerative cervical diseases between January 2017 and June 2022 were included. Correlation between EBQ scores and segmental height loss was analyzed using Pearson’s correlation. ROC analyses were employed to ascertain the EBQ cut-off values that predict the occurrence of cage subsidence. Multivariate logistic regression analyses were conducted to identify the risk factors associated with postoperative cage subsidence. Results 23 individuals (14.56%) exhibited the cage subsidence after ACDF. In the nonsubsidence group, the average EBQ and lowest T-score were determined to be 4.13 ± 1.14 and − 0.84 ± 1.38 g/cm2 respectively. In contrast, the subsidence group exhibited a mean EBQ and lowest T-score of 5.38 ± 0.47 (p < 0.001) and − 1.62 ± 1.34 g/cm2 (p = 0.014), respectively. There was a significant positive correlation (r = 0.798**) between EBQ and the segmental height loss. The EBQ threshold of 4.70 yielded optimal sensitivity (73.9%) and specificity (93.3%) with AUC of 0.806. Furthermore, the lowest T-score (p = 0.045, OR 0.667) and an elevated cervical EBQ score (p < 0.001, OR 8.385) were identified as significant risk factors for cage subsidence after ACDF. Conclusions The EBQ method presents itself as a promising and efficient tool for surgeons to assess patients at risk of cage subsidence and osteoporosis prior to cervical spine surgery, utilizing readily accessible patient data.

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