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基于自动区域生长的新鲜冷冻人腕骨标本小梁骨结构分割。

Automated region growing-based segmentation for trabecular bone structure in fresh-frozen human wrist specimens.

机构信息

Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, SE-58185, Sweden.

Department of Radiology and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, SE-58185, Sweden.

出版信息

BMC Med Imaging. 2024 May 1;24(1):101. doi: 10.1186/s12880-024-01281-w.

Abstract

Bone strength depends on both mineral content and bone structure. Measurements of bone microstructure on specimens can be performed by micro-CT. In vivo measurements are reliably performed by high-resolution peripheral computed tomography (HR-pQCT) using dedicated software. In previous studies from our research group, trabecular bone properties on CT data of defatted specimens from many different CT devices have been analyzed using an Automated Region Growing (ARG) algorithm-based code, showing strong correlations to micro-CT.The aim of the study was to validate the possibility of segmenting and measuring trabecular bone structure from clinical CT data of fresh-frozen human wrist specimens. Data from micro-CT was used as reference. The hypothesis was that the ARG-based in-house built software could be used for such measurements.HR-pQCT image data at two resolutions (61 and 82 µm isotropic voxels) from 23 fresh-frozen human forearms were analyzed. Correlations to micro-CT were strong, varying from 0.72 to 0.99 for all parameters except trabecular termini and nodes. The bone volume fraction had correlations varying from 0.95 to 0.98 but was overestimated compared to micro-CT, especially at the lower resolution. Trabecular separation and spacing were the most stable parameters with correlations at 0.80-0.97 and mean values in the same range as micro-CT.Results from this in vitro study show that an ARG-based software could be used for segmenting and measuring 3D trabecular bone structure from clinical CT data of fresh-frozen human wrist specimens using micro-CT data as reference. Over-and underestimation of several of the bone structure parameters must however be taken into account.

摘要

骨强度取决于矿物质含量和骨结构。可以通过微计算机断层扫描 (micro-CT) 对标本的骨微观结构进行测量。高分辨率外周计算机断层扫描 (HR-pQCT) 可使用专用软件进行可靠的体内测量。在我们研究小组的先前研究中,已经使用基于自动区域生长 (ARG) 算法的代码分析了来自许多不同 CT 设备的脱脂标本 CT 数据中的小梁骨特性,该代码与微 CT 具有很强的相关性。该研究的目的是验证从新鲜冷冻人腕部标本的临床 CT 数据中分割和测量小梁骨结构的可能性。使用微 CT 数据作为参考。假设可以使用基于 ARG 的内部构建软件进行此类测量。分析了来自 23 个新鲜冷冻人前臂的两种分辨率(61 和 82 µm 各向同性体素)的 HR-pQCT 图像数据。与微 CT 的相关性很强,除了小梁末端和节点外,所有参数的相关性均为 0.72 至 0.99。骨体积分数的相关性在 0.95 至 0.98 之间,但与微 CT 相比被高估,尤其是在较低分辨率下。小梁分离和间距是最稳定的参数,相关性在 0.80-0.97 之间,平均值与微 CT 相同。这项体外研究的结果表明,基于 ARG 的软件可用于从新鲜冷冻人腕部标本的临床 CT 数据中分割和测量 3D 小梁骨结构,并以微 CT 数据作为参考。但是,必须考虑到几个骨结构参数的高估和低估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3855/11061919/ee482a37f851/12880_2024_1281_Fig1_HTML.jpg

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