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一种新型基于磁共振成像的特定部位骨质量评估(EBQ)在单纯侧路腰椎间融合术中预测严重 cage 下陷的价值。

The predictive value of a novel site-specific MRI-based bone quality assessment, endplate bone quality (EBQ), for severe cage subsidence among patients undergoing standalone lateral lumbar interbody fusion.

机构信息

Spine Care Institute, Hospital for Special Surgery, 535 East 70th Street, New York, NY 10021, USA.

Spine Care Institute, Hospital for Special Surgery, 535 East 70th Street, New York, NY 10021, USA; Department of Orthopaedic Surgery, Showa University School of Medicine, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8666 Japan.

出版信息

Spine J. 2022 Nov;22(11):1875-1883. doi: 10.1016/j.spinee.2022.07.085. Epub 2022 Jul 15.

DOI:10.1016/j.spinee.2022.07.085
PMID:35843534
Abstract

BACKGROUND CONTEXT

Studies have shown that site-specific bone density measurements had more predictive value for complications than standard whole-region measurements. Recently, MRI-based assessments of 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 to 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 and 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 analyses with generalized linear mixed models were performed and set binary severe subsidence as the outcome.

RESULTS

Two hundred five levels in 89 patients were included. Fifty 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 a 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 before SA-LLIF may provide insight into a patient's risk for severe subsidence.

摘要

背景

研究表明,与标准全区域测量相比,特定部位骨密度测量对并发症具有更高的预测价值。最近,引入了基于 MRI 的椎体骨质量(VBQ)评估。然而,很少有研究调查特定部位 MRI 骨评估与接受腰椎椎间融合术的患者的骨质疏松相关并发症之间的关系。在这项工作中,我们创建了一种新的基于特定部位 MRI 的终板骨质量(EBQ)评估方法,并评估了其对侧方腰椎椎间融合术(SA-LLIF)后严重 cage 下沉的预测价值。

目的

研究一种新的基于 MRI 的骨评估方法对 SA-LLIF 后严重 cage 下沉的预测价值。

研究设计/设置:回顾性队列研究。

患者样本

2008 年至 2019 年在一家单一的学术机构接受 SA-LLIF 治疗的患者,且术前均有腰椎 CT 和 T1 加权 MRI。

研究结果

在接受 SA-LLIF 治疗的患者中,EBQ 与术后严重下沉之间存在关联。

方法

我们回顾性地查阅了 2008 年至 2019 年接受 SA-LLIF 治疗的患者的记录。使用腰椎非对比 T1 加权 MRI 测量 EBQ。EBQ 定义为 L3 水平终板的平均信号强度除以脑脊液空间的信号强度。使用广义线性混合模型进行双变量和多变量分析,并将二元严重下沉设为结果。

结果

共纳入 89 例患者的 205 个节段。50 个节段(24.4%)出现严重下沉。下沉组的定量 CT 测量的骨密度明显较低。下沉组的 VBQ 和 EBQ 均明显较高。EBQ 加 Modic 改变(MC)模型表明,EBQ 的作用独立于 MC。在调整 QCT-vBMD 的多变量分析中,EBQ 与 cage 下沉有显著关联,而 VBQ 仅显示出边缘趋势。基于 EBQ 的严重下沉预测模型的拟合优度优于基于 VBQ 的模型。

结论

高 EBQ 是 SA-LLIF 后 cage 严重下沉的独立因素,基于 EBQ 的模型的拟合优度优于基于 VBQ 或 MC 的模型。SA-LLIF 前的 EBQ 评估可以深入了解患者严重下沉的风险。

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