Automated cortical bone segmentation for multirow-detector CT imaging with validation and application to human studies
Automated cortical bone segmentation for multirow-detector CT imaging with validation and application to human studies
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DOI：
10.1118/1.4923753
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发表时间：
2015-08-01
期刊：
影响因子：
3.8
通讯作者：
Saha, Punam K.
中科院分区：
文献类型：
--
作者：
Li, Cheng;Jin, Dakai;Saha, Punam K.
目的：皮质骨支持和保护人体骨骼功能，在确定骨骼强度和骨折风险方面发挥着重要作用。使用多行探测器 CT (MD-CT) 成像在外周部位进行皮质骨分割对于骨强度和骨折风险的体内评估非常有用。该任务的主要挑战来自有限的空间分辨率、低信噪比、皮质孔的存在以及小梁骨和皮质骨之间过渡的结构复杂性。提出了一种用于体内 MD-CT 成像的远端胫骨皮质骨分割的自动算法，并检查了其性能和应用。方法：该算法分两个主要步骤完成 - (1) 骨填充、对齐和感兴趣区域计算，(2) 皮质骨分割。第一步之后，执行以下任务序列来完成皮质骨分割：（1）检测骨髓空间和可能的孔隙，（2）计算皮质骨厚度，检测退缩点，并确认和填充真实孔隙，（3）检测骨内边界和勾画皮质骨。介绍了几种数字拓扑和几何技术的有效概括，并提出了一种用于皮质骨分割的全自动算法。结果：在人体 MD-CT 扫描中观察到，在皮质骨的手动轮廓体积一致性方面，准确度为 95.1%，而在配准后的高分辨率显微 CT 成像上，与手动轮廓相比，准确度为 88.5%。尸体重复扫描获得的组内相关系数为 0.98。进行了一项试点研究来描述皮质骨特性的性别差异。这项研究涉及来自爱荷华州骨骼发育研究的 51 名女性和 46 名男性参与者（年龄：19-20 岁）。这项初步研究的结果表明，平均而言，在调整身高和体重差异后，与女性相比，男性的皮质较厚（前部区域的平均差为 0.33 mm，效果大小为 0.92），骨矿物质密度较低（后部区域的平均差为 -28.73 mg/cm(3)，效果大小为 1.35）。 结论：所提出的算法适用于胫骨远端 MD-CT 成像中皮质骨的全自动分割。和再现性。对一项试点研究数据的分析表明，皮质骨指数可以量化 MD-CT 成像中皮质骨的性别差异。需要应用于更大的人群，包括那些骨骼受损的人群。 (C) 2015 年美国医学物理学家协会。
Purpose: Cortical bone supports and protects human skeletal functions and plays an important role in determining bone strength and fracture risk. Cortical bone segmentation at a peripheral site using multirow-detector CT (MD-CT) imaging is useful for in vivo assessment of bone strength and fracture risk. Major challenges for the task emerge from limited spatial resolution, low signal-to-noise ratio, presence of cortical pores, and structural complexity over the transition between trabecular and cortical bones. An automated algorithm for cortical bone segmentation at the distal tibia from in vivo MD-CT imaging is presented and its performance and application are examined.Methods: The algorithm is completed in two major steps-(1) bone filling, alignment, and region-of-interest computation and (2) segmentation of cortical bone. After the first step, the following sequence of tasks is performed to accomplish cortical bone segmentation-(1) detection of marrow space and possible pores, (2) computation of cortical bone thickness, detection of recession points, and confirmation and filling of true pores, and (3) detection of endosteal boundary and delineation of cortical bone. Effective generalizations of several digital topologic and geometric techniques are introduced and a fully automated algorithm is presented for cortical bone segmentation.Results: An accuracy of 95.1% in terms of volume of agreement with manual outlining of cortical bone was observed in human MD-CT scans, while an accuracy of 88.5% was achieved when compared with manual outlining on postregistered high resolution micro-CT imaging. An intraclass correlation coefficient of 0.98 was obtained in cadaveric repeat scans. A pilot study was conducted to describe gender differences in cortical bone properties. This study involved 51 female and 46 male participants (age: 19-20 yr) from the Iowa Bone Development Study. Results from this pilot study suggest that, on average after adjustment for height and weight differences, males have thicker cortex (mean difference 0.33 mm and effect size 0.92 at the anterior region) with lower bone mineral density (mean difference -28.73 mg/cm(3) and effect size 1.35 at the posterior region) as compared to females.Conclusions: The algorithm presented is suitable for fully automated segmentation of cortical bone in MD-CT imaging of the distal tibia with high accuracy and reproducibility. Analysis of data from a pilot study demonstrated that the cortical bone indices allow quantification of gender differences in cortical bone from MD-CT imaging. Application to larger population groups, including those with compromised bone, is needed. (C) 2015 American Association of Physicists in Medicine.