Background context:

Studies have shown site-specific bone density measurements had more predictive value for complications than standard whole-region measurements. Recently, MRI-based assessments of the vertebral bone quality (VBQ) were introduced. However, there have been few studies that investigate the association between site-specific MRI bone assessment and osteoporosis related complications in patients undergoing lumbar interbody fusion. In this work, we created a novel site-specific MRI-based assessment of the endplate bone quality (EBQ) and assessed its predictive value for severe cage subsidence following standalone lateral lumbar interbody fusion (SA-LLIF).

Purpose:

To investigate the predictive value of a novel MRI based bone assessment for severe cage subsidence after SA-LLIF.

Study design/setting:

Retrospective cohort study PATIENT SAMPLE: Patients who underwent SA-LLIF from 2008-2019 at a single, academic institution with available preoperative lumbar CT and T1-weighted MRIs.

Outcome measures:

Association between EBQ and severe subsidence after SA-LLIF.

Methods:

We retrospectively reviewed the records of SA-LLIF patients treated between 2008-2019. EBQ was measured using preoperative non-contrast T1-weighted MRIs of the lumbar spine. EBQ was defined as the average value of signal intensity of both endplates divided by that of the cerebrospinal fluid space at the level of L3. Bivariate and multivariable analysis with generalized linear mixed models were performed and set binary severe subsidence as the outcome.

Results:

205 levels in 89 patients were included. 50 levels (24.4%) demonstrated severe subsidence. Bone mineral density measured by quantitative computed tomography was significantly lower in the subsidence group. Both VBQ and EBQ were significantly higher in the subsidence group. The EBQ plus Modic change (MC) model demonstrated that the effect of EBQ was independent of MC. In multivariate analyses adjusted with QCT-vBMD, EBQ showed significant association with cage subsidence whereas VBQ only showed a marginal trend. The EBQ based prediction model for severe subsidence showed better goodness of fit compared to the VBQ based model.

Conclusions:

High EBQ was an independent factor for severe cage subsidence after SA-LLIF and the EBQ-based model showed better goodness of fit compared to VBQ- or MC-based models. EBQ assessment prior to SA-LLIF may provide insight into a patient’s risk for severe subsidence.