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骨质疏松性腰椎中亨氏单位的侧别差异

Side specific differences of Hounsfield-Units in the osteoporotic lumbar spine.

作者信息

Metzner Florian, Reise Rebekka, Heyde Christoph-Eckhard, von der Höh Nicolas Heinz, Schleifenbaum Stefan

机构信息

ZESBO-Center for Research on Musculoskeletal Systems, Faculty of Medicine, Leipzig University, Leipzig, Germany.

Department of Orthopaedic Surgery, Traumatology and Plastic Surgery, University of Leipzig Medical Center, Leipzig, Germany.

出版信息

J Spine Surg. 2024 Jun 21;10(2):232-243. doi: 10.21037/jss-23-121. Epub 2024 Jun 11.

DOI:10.21037/jss-23-121
PMID:38974498
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11224781/
Abstract

BACKGROUND

Gold standard for determining bone density as a surrogate parameter of bone quality is measurement of bone mineral density (BMD) by dual energy X-ray absorptiometry (DXA), most commonly performed on the lumbar spine (L1-L4). Computed tomography (CT) data are often available for surgical planning prior to spine procedures, but currently this information is not standardized for bone quality assessment. Besides, measuring the Hounsfield-Units (HU) is also of great importance in the context of biomechanical studies. This study aims in comparing BMD from DXA and HU based on diagnostic CT scans. In addition, methods are presented to quantify local density variations within bones.

METHODS

One hundred and seventy-six vertebrae (L1-L4) from 44 body donors (age 84.0±8.7 years) were studied. DXA measurements were obtained on the complete vertebrae to determine BMD, as well as axial CT scans with a slice thickness of 1 mm. Using Mimics Innovation Suite image processing software (Materialise NV, Leuven, Belgium), two volumes (whole vertebra spongious bone) were formed for each vertebra, which in turn were divided in their left and right sides. From these total of six volumes, the respective mean HU was determined. HU of the whole vertebra and just spongious HU were compared with the BMD of the corresponding vertebrae. Side specific differences were calculated as relative values.

RESULTS

Whole bone and spongious HU correlated significantly (P>0.001; α=0.01) with BMD. A positive linear correlation was found, which was more pronounced for whole bone HU (R=0.72) than for spongious HU (R=0.62). When comparing the left and right sides within each vertebra, the HU was found to be 10% larger on average on one side compared to the opposite side. In some cases, the difference of left and right spongious bone can be up to 170%. There is a tendency for the side comparison to be larger for the spongious HU than for the whole vertebra.

CONCLUSIONS

Determination of HU from clinical CT scans is an important tool for assessing bone quality, primarily by including the cortical portion in the calculation of HU. Unlike BMD, HU can be used to distinguish precisely between individual regions. Some of the very large side-specific gradients of the HU indicate an enormous application potential for preoperative patient-specific planning.

摘要

背景

通过双能X线吸收法(DXA)测量骨矿物质密度(BMD)是将其作为骨质量替代参数来确定骨密度的金标准,最常测量的部位是腰椎(L1 - L4)。在脊柱手术前进行手术规划时,计算机断层扫描(CT)数据通常是可用的,但目前这些信息在骨质量评估方面尚未标准化。此外,在生物力学研究中测量亨氏单位(HU)也非常重要。本研究旨在基于诊断性CT扫描比较DXA测量的BMD和HU。此外,还介绍了量化骨内局部密度变化的方法。

方法

对44具尸体捐赠者(年龄84.0±8.7岁)的176个椎体(L1 - L4)进行了研究。在完整椎体上进行DXA测量以确定BMD,并进行层厚为1mm的轴向CT扫描。使用Mimics Innovation Suite图像处理软件(Materialise NV,比利时鲁汶),为每个椎体形成两个体积(整个椎体 松质骨),然后将其分为左右两侧。从这总共六个体积中,确定各自的平均HU。将整个椎体的HU和仅松质骨的HU与相应椎体的BMD进行比较。将左右两侧的差异计算为相对值。

结果

全骨和松质骨的HU与BMD显著相关(P>0.001;α = 0.01)。发现存在正线性相关,全骨HU的相关性(R = 0.72)比松质骨HU(R = 0.62)更明显。在比较每个椎体内的左右两侧时,发现一侧的HU平均比另一侧大10%。在某些情况下,左右松质骨的差异可达170%。松质骨HU的左右侧比较有比整个椎体更大的趋势。

结论

从临床CT扫描中确定HU是评估骨质量的重要工具,主要是通过在HU计算中纳入皮质部分。与BMD不同,HU可用于精确区分各个区域。HU的一些非常大的左右侧梯度表明其在术前针对患者个体的规划中具有巨大的应用潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/e87010165296/jss-10-02-232-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/1de4cbc507f8/jss-10-02-232-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/e9fdbbd5f43b/jss-10-02-232-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/f865cd2b2f14/jss-10-02-232-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/24a6c1200a04/jss-10-02-232-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/51ac04b757d4/jss-10-02-232-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/a49e3532375c/jss-10-02-232-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/788a8bd4f793/jss-10-02-232-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/75ee76cec142/jss-10-02-232-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/e87010165296/jss-10-02-232-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/1de4cbc507f8/jss-10-02-232-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/e9fdbbd5f43b/jss-10-02-232-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/f865cd2b2f14/jss-10-02-232-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/24a6c1200a04/jss-10-02-232-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/51ac04b757d4/jss-10-02-232-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/a49e3532375c/jss-10-02-232-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/788a8bd4f793/jss-10-02-232-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/75ee76cec142/jss-10-02-232-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b56/11224781/e87010165296/jss-10-02-232-f9.jpg

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