终板Hounsfield单位相对于颈椎Hounsfield单位在预测颈椎前路椎间盘切除术和融合后沉降方面的优势。

IF 3.1 2区 医学 Q2 CLINICAL NEUROLOGY
Hannah A Levy, Maria D Astudillo Potes, Caden J Messer, Christopher A Magera, Zachariah W Pinter, Mohamad Bydon, Jeremy L Fogelson, Benjamin D Elder, Bradford L Currier, Ahmad N Nassr, Brett A Freedman, Brian A Karamian, Arjun S Sebastian
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引用次数: 0

摘要

目的:本研究旨在1)建立一种新的基于ct的终板骨密度评估方法(终板Hounsfield单位[EP-HU]), 2)分析EP-HU是否比椎体Hounsfield单位(HU)更能预测颈椎前路椎间盘切除术和融合(ACDF)后的沉降。方法:回顾性分析2018年至2020年间在学术中心接受一至三级ACDF伴钛体间支架治疗神经根病和/或脊髓病的所有成年患者。根据术前矢状CT扫描(左、右、中切面),用自由绘制工具划定2mm上下终板区域,以解释终板表面波动。所有CT切面上的上、下EP-HU取平均值计算EP-HU。通过仅限定小梁骨的轴向CT头颅、中段和尾端切口的平均值来确定颈椎HUs。在术后CT扫描的冠状面和矢状面切面上直接测量每个ACDF节段的颅端板和尾端板的体间下沉(1年),以确定最大下沉(下沉定义为≥2mm)。采用单变量和逐步logistic回归分析比较基于CT骨指标的沉陷。采用受试者工作特征(ROC)曲线分析,以EP-HUs和椎体HUs为基础确定沉降概率。结果:共纳入35例患者。67个不同的融合水平中有32个发生了下沉。下陷与年龄增大(p = 0.008)、糖尿病诊断(p = 0.015)和体间长度减小(p = 0.019)有关。EP-HUs与颈椎HUs有中度相关性(Pearson’s ρ = 0.63)。沉降与总EP-HUs的降低显著相关(沉降:475 HU,无沉降:543 HU;p = 0.019)和腰椎HUs降低(下沉:296 HU,无下沉:341 HU;P = 0.011)。ROC曲线分析确定了预测沉降的最佳EP-HU截止值为512.30(曲线下面积[AUC] = 0.701)。与沉降有关的椎体HUs的AUC为0.662。EP-HUs < 512.30预测沉降(OR 6.67, p = 0.001)独立于显著的人口统计学和外科因素。结论:CT颈椎ep - hu比椎体颈椎小梁hu更能预测ACDF后的沉陷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The superiority of endplate Hounsfield units relative to cervical vertebral Hounsfield units in predicting subsidence after anterior cervical discectomy and fusion.

Objective: The present investigation aimed to 1) develop a new CT-based assessment of endplate bone density (endplate Hounsfield unit [EP-HU]) and 2) analyze if EP-HU was a better predictor than vertebral Hounsfield unit (HU) for subsidence after anterior cervical discectomy and fusion (ACDF).

Methods: All adult patients who underwent one- to three-level ACDF with a titanium interbody for radiculopathy and/or myelopathy at an academic center between 2018 and 2020 were retrospectively identified. Based on preoperative sagittal CT scans (left, right, and middle cuts), 2-mm superior and inferior endplate regions were circumscribed with the free draw tool to account for endplate surface undulations. The average of the superior and inferior EP-HUs on all CT cuts was used to calculate EP-HU. Cervical vertebral HUs were determined from the average of axial CT cranial, middle, and caudal cuts circumscribing only trabecular bone. The interbody subsidence of the cranial and caudal endplates of each ACDF level was directly measured on the endplate-facing surface of both coronal and sagittal cuts of postoperative CT scans (at 1 year) to determine the maximum subsidence (subsidence defined as ≥ 2 mm). Univariate and stepwise logistic regression analyses were used to compare subsidence based on CT bone metrics. Receiver operating characteristic (ROC) curve analyses were used to determine the probability of subsidence based on EP-HUs and vertebral HUs.

Results: A total of 35 patients were included. Subsidence occurred at 32 of 67 unique fusion levels. Subsidence was associated with older age (p = 0.008), diabetes diagnosis (p = 0.015), and decreased interbody length (p = 0.019). EP-HUs exhibited moderate correlation with cervical vertebral HUs (Pearson's ρ = 0.63). Subsidence was significantly associated with decreased total EP-HUs (subsidence: 475 HU, no subsidence: 543 HU; p = 0.019) and decreased lumbar vertebral HUs (subsidence: 296 HU, no subsidence: 341 HU; p = 0.011). ROC curve analysis identified an optimal EP-HU cutoff of 512.30 (area under the curve [AUC] = 0.701) to predict subsidence. The AUC of the vertebral HUs with respect to subsidence was 0.662. EP-HUs < 512.30 predicted subsidence (OR 6.67, p = 0.001) independent of significant demographic and surgical factors.

Conclusions: CT cervical EP-HUs rather than vertebral cervical trabecular HUs may be more efficacious in predicting subsidence after ACDF.

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来源期刊
Journal of neurosurgery. Spine
Journal of neurosurgery. Spine 医学-临床神经学
CiteScore
5.10
自引率
10.70%
发文量
396
审稿时长
6 months
期刊介绍: Primarily publish original works in neurosurgery but also include studies in clinical neurophysiology, organic neurology, ophthalmology, radiology, pathology, and molecular biology.
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