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使用光学相干断层扫描技术对人类软骨退变进行三维成像与分析。

Three-dimensional imaging and analysis of human cartilage degeneration using Optical Coherence Tomography.

作者信息

Nebelung Sven, Brill Nicolai, Marx Ulrich, Quack Valentin, Tingart Markus, Schmitt Robert, Rath Björn, Jahr Holger

机构信息

Department of Orthopaedics, Aachen University Hospital, Aachen, Germany.

出版信息

J Orthop Res. 2015 May;33(5):651-9. doi: 10.1002/jor.22828. Epub 2015 Mar 13.

Abstract

Optical Coherence Tomography (OCT) is an evolving imaging technology allowing non-destructive imaging of cartilage tissue at near-histological resolution. This study investigated the diagnostic value of real time 3-D OCT in comparison to conventional 2-D OCT in the comprehensive grading of human cartilage degeneration. Fifty-three human osteochondral samples were obtained from eight total knee arthroplasties. OCT imaging was performed by either obtaining a single two-dimensional cross-sectional image (2-D OCT) or by collecting 100 consecutive parallel 2-D OCT images to generate a volumetric data set of 8 × 8 mm (3-D OCT). OCT images were assessed qualitatively according to a modified version of the DJD classification and quantitatively by algorithm-based evaluation of surface irregularity, tissue homogeneity, and signal attenuation. Samples were graded according to the Outerbridge classification and statistically analyzed by one-way ANOVA, Kruskal Wallis and Tukey's or Dunn's post-hoc tests. Overall, the generation of 3-D volumetric datasets and their multiple reconstructions such as rendering, surface topography, parametric, and cross-sectional views proved to be of potential diagnostic value. With increasing distance to the mid-sagittal plane and increasing degeneration, score deviations increased, too. In conclusion, 3-D imaging of cartilage with image analysis algorithms adds considerable potential diagnostic value to conventional OCT diagnostics.

摘要

光学相干断层扫描(OCT)是一种不断发展的成像技术,能够以接近组织学的分辨率对软骨组织进行无损成像。本研究调查了实时三维OCT与传统二维OCT相比在人类软骨退变综合分级中的诊断价值。从8例全膝关节置换术中获取了53个人骨软骨样本。通过获取单个二维横截面图像(二维OCT)或收集100个连续的平行二维OCT图像以生成8×8毫米的体积数据集(三维OCT)来进行OCT成像。根据改良版的DJD分类对OCT图像进行定性评估,并通过基于算法的表面不规则性、组织同质性和信号衰减评估进行定量评估。根据Outerbridge分类对样本进行分级,并通过单因素方差分析、Kruskal Wallis检验以及Tukey或Dunn事后检验进行统计分析。总体而言,三维体积数据集的生成及其多种重建方式,如渲染、表面形貌、参数和横截面视图,被证明具有潜在的诊断价值。随着距矢状中平面距离的增加和退变程度的加重,评分偏差也会增加。总之,利用图像分析算法对软骨进行三维成像为传统OCT诊断增添了相当大的潜在诊断价值。

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