Scholarlink

Purpose <p>To evaluate the relationship between preoperative imaging features of endplate degeneration and incomplete fusion after LLIF and to establish a multivariable predictive model for preoperative risk stratification.</p> Methods <p>Patients who underwent LLIF between January 2021 and January 2025 were retrospectively reviewed. Preoperative MRI and CT were used to evaluate imaging features of endplate degeneration, including Modic classification, Schmorl’s node, endplate cartilage erosion, sub-endplate trabecular sclerosis, and bony endplate Hounsfield unit (HU). Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for incomplete fusion. A nomogram was constructed based on the final model, and its performance was evaluated using receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA).</p> Results <p>The mean age was 59.7 ± 9.5 years. At the 12-month follow-up, incomplete fusion, defined as BSF grade 1 pseudarthrosis or BSF grade 2 partial fusion, was observed in 33.3% (84/252) of patients. Multivariate analysis identified smoking history (OR 2.623, 95% CI 1.187–5.799, <i>p</i> = 0.017), osteoporosis (OR 2.231, 95% CI 1.002–4.967, <i>p</i> = 0.049), sub-endplate trabecular sclerosis (OR 7.598, 95% CI 1.498–17.545, <i>p</i> = 0.014), Modic type III changes (OR 7.290, 95% CI 1.853–16.679, <i>p</i> = 0.025), and elevated bony endplate HU (OR 5.454, 95% CI 1.032–15.822, <i>p</i> = 0.046) as independent predictors of incomplete fusion. The predictive model demonstrated good discrimination (AUC = 0.883).</p> Conclusions <p>Imaging features of endplate degeneration, particularly sub-endplate trabecular sclerosis, Modic type III changes, and elevated bony endplate HU, are independent predictors of incomplete fusion after LLIF. Incorporating these local structural factors with systemic risk factors may improve preoperative risk assessment.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Influence of endplate degeneration on fusion process in lateral lumbar interbody fusion

  • 期刊论文

  • 发表日期：

    2026年7月16日

查看全文
  • Han Wu,
  • Shaorong Li,
  • Yu Li,
  • Weijian Wang,
  • Jiaqi Li,
  • Jianshi Song,
  • Xiuqi Shan,
  • Yijian Guo,
  • Wei Zhang

摘要

Purpose

To evaluate the relationship between preoperative imaging features of endplate degeneration and incomplete fusion after LLIF and to establish a multivariable predictive model for preoperative risk stratification.

Methods

Patients who underwent LLIF between January 2021 and January 2025 were retrospectively reviewed. Preoperative MRI and CT were used to evaluate imaging features of endplate degeneration, including Modic classification, Schmorl’s node, endplate cartilage erosion, sub-endplate trabecular sclerosis, and bony endplate Hounsfield unit (HU). Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for incomplete fusion. A nomogram was constructed based on the final model, and its performance was evaluated using receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA).

Results

The mean age was 59.7 ± 9.5 years. At the 12-month follow-up, incomplete fusion, defined as BSF grade 1 pseudarthrosis or BSF grade 2 partial fusion, was observed in 33.3% (84/252) of patients. Multivariate analysis identified smoking history (OR 2.623, 95% CI 1.187–5.799, p = 0.017), osteoporosis (OR 2.231, 95% CI 1.002–4.967, p = 0.049), sub-endplate trabecular sclerosis (OR 7.598, 95% CI 1.498–17.545, p = 0.014), Modic type III changes (OR 7.290, 95% CI 1.853–16.679, p = 0.025), and elevated bony endplate HU (OR 5.454, 95% CI 1.032–15.822, p = 0.046) as independent predictors of incomplete fusion. The predictive model demonstrated good discrimination (AUC = 0.883).

Conclusions

Imaging features of endplate degeneration, particularly sub-endplate trabecular sclerosis, Modic type III changes, and elevated bony endplate HU, are independent predictors of incomplete fusion after LLIF. Incorporating these local structural factors with systemic risk factors may improve preoperative risk assessment.