Robust Quantitative Assessment of Trabecular Microarchitecture in Extremity Cone-Beam CT Using Optimized Segmentation Algorithms.
Robust Quantitative Assessment of Trabecular Microarchitecture in Extremity Cone-Beam CT Using Optimized Segmentation Algorithms.
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使用优化的分割算法对四肢锥束 CT 中的小梁微结构进行稳健的定量评估。
DOI：
10.1117/12.2293346
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Zbijewski,W
中科院分区：
文献类型：
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作者：
Brehler,M;Cao,Q;Moseley,KF;Osgood,G;Morris,C;Demehri,S;Yorkston,J;Siewerdsen,JH;Zbijewski,W
目的：由于传统骨科成像模式的分辨率有限，骨微结构的体内评价仍然具有挑战性。我们研究平板探测器四肢锥形束CT（CBCT）在骨小梁定量分析中的性能。为了实现精细松质骨结构的精确形态测量，先进的CBCT预处理和分割algorithms developed.Methods：该研究涉及35个穿甲骨活检样本在肢体CBCT（体素大小75 μm，成像剂量~13 mGy）和金标准μCT（体素大小7.67 μm）上成像。CBCT图像分割使用（i）全局大津阈值法，（ii）Bernsen局部阈值法，（iii）Bernsen局部阈值法与附加的基于直方图的全局预阈值法，以及（iv）与（iii）相同但结合使用拉普拉斯金字塔的对比度增强法。结果：局部阈值法结合全局预阈值法和Laplacian对比增强法的CBCT分割效果优于其他CBCT分割方法。使用该最佳分割方案，肢体CBCT和μCT之间实现了强相关性，BV/TV的Pearson系数为0.93，Tb.Th为0.89，Tb.Sp为0.91，Tb.N为0.88（所有结果均具有统计学显著性）。与使用大津算法的简单全局CBCT分割相比，先进的分割方法在Tb.Th的相关系数方面提高了约20%，在Tb.Sp的相关系数方面提高了约50%。这促使肢体CBCT在骨健康的体内评价中的临床应用不断发展，例如在早期骨关节炎和骨质疏松症中。
Purpose: In-vivo evaluation of bone microarchitecture remains challenging because of limited resolution of conventional orthopaedic imaging modalities. We investigate the performance of flat-panel detector extremity Cone-Beam CT (CBCT) in quantitative analysis of trabecular bone. To enable accurate morphometry of fine trabecular bone architecture, advanced CBCT pre-processing and segmentation algorithms are developed.Methods: The study involved 35 transilliac bone biopsy samples imaged on extremity CBCT (voxel size 75 μm, imaging dose ~13 mGy) and gold standard μCT (voxel size 7.67 μm). CBCT image segmentation was performed using (i) global Otsu’s thresholding, (ii) Bernsen’s local thresholding, (iii) Bernsen’s local thresholding with additional histogram-based global pre-thresholding, and (iv) the same as (iii) but combined with contrast enhancement using a Laplacian Pyramid. Correlations between extremity CBCT with the different segmentation algorithms and gold standard μCT were investigated for measurements of Bone Volume over Total Volume (BV/TV), Trabecular Thickness (Tb.Th), Trabecular Spacing (Tb.Sp), and Trabecular Number (Tb.N).Results: The combination of local thresholding with global pre-thresholding and Laplacian contrast enhancement outperformed other CBCT segmentation methods. Using this optimal segmentation scheme, strong correlation between extremity CBCT and μCT was achieved, with Pearson coefficients of 0.93 for BV/TV, 0.89 for Tb.Th, 0.91 for Tb.Sp, and 0.88 for Tb.N (all results statistically significant). Compared to a simple global CBCT segmentation using Otsu’s algorithm, the advanced segmentation method achieved ~20% improvement in the correlation coefficient for Tb.Th and ~50% improvement for Tb.Sp.Conclusions: Extremity CBCT combined with advanced image pre-processing and segmentation achieves high correlation with gold standard μCT in measurements of trabecular microstructure. This motivates ongoing development of clinical applications of extremity CBCT in in-vivo evaluation of bone health e.g. in early osteoarthritis and osteoporosis.