Analysis of the three-dimensional anatomical variance of the distal radius using 3D shape models
Analysis of the three-dimensional anatomical variance of the distal radius using 3D shape models
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DOI：
10.1186/s12880-017-0193-9
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发表时间：
2017-03-09
影响因子：
2.7
通讯作者：
Fischer, Lukas
中科院分区：
文献类型：
--
作者：
Baumbach, Sebastian F.;Binder, Jakob;Fischer, Lukas
背景：各种医学领域依赖于桡骨远端的详细解剖学知识。目前的研究仅限于二维分析，并通过不同的测量位置进行偏倚。目的是1）生成桡骨远端的3D形状模型并调查3D形状的变化，2）生成和评估标准化切面中的形态测量学，以及3）测试模型的分类准确性。方法：对当地放射学数据库进行筛选，以获得CT扫描完整的桡骨。1)对数据集进行分割并生成3D表面模型。计算统计3D形状模型（总体、性别和侧别），并通过评价模式数量评估3D形状变化。2)分配解剖标志并用于定义垂直于主轴的三个标准化横截面切割平面。为平均形状模型和每个单独半径生成切割平面。对于每个切割平面，计算并比较以下形态测量参数：最大宽度和深度、周长和面积。3)整体形状模型被用来评估预测值（留一交叉验证）的性别和侧identification在研究population.Results：八十六半径（45左，44%女性，40 +/- 18岁）。1)总体而言，成功生成了侧部和性别特异性统计3D模型。第一种模式解释了总方差的37%。与右侧桡骨（模式数量：6女性/ 6男性）相比，左侧桡骨具有更高的形状变化（模式数量：20女性/ 23男性）。2)可以使用解剖标志来定义标准化切割平面。所有形态测量参数从远端到近端逐渐降低。男性半径大于女性半径，两侧差异无统计学意义。3)结论：利用临床CT数据集可以生成桡骨远端的统计学三维形状模型。这些模型可用于评估总体骨方差，定义和分析标准化切割平面，并识别未知样本的性别。这些数据突出了形状模型在评估人体骨骼的3D解剖结构和解剖变异方面的潜力。
Background: Various medical fields rely on detailed anatomical knowledge of the distal radius. Current studies are limited to two-dimensional analysis and biased by varying measurement locations. The aims were to 1) generate 3D shape models of the distal radius and investigate variations in the 3D shape, 2) generate and assess morphometrics in standardized cut planes, and 3) test the model's classification accuracy.Methods: The local radiographic database was screened for CT-scans of intact radii. 1) The data sets were segmented and 3D surface models generated. Statistical 3D shape models were computed (overall, gender and side separate) and the 3D shape variation assessed by evaluating the number of modes. 2) Anatomical landmarks were assigned and used to define three standardized cross-sectional cut planes perpendicular to the main axis. Cut planes were generated for the mean shape models and each individual radius. For each cut plane, the following morphometric parameters were calculated and compared: maximum width and depth, perimeter and area. 3) The overall shape model was utilized to evaluate the predictive value (leave one out cross validation) for gender and side identification within the study population.Results: Eighty-six radii (45 left, 44% female, 40 +/- 18 years) were included. 1) Overall, side and gender specific statistical 3D models were successfully generated. The first mode explained 37% of the overall variance. Left radii had a higher shape variance (number of modes: 20 female / 23 male) compared to right radii (number of modes: 6 female / 6 male). 2) Standardized cut planes could be defined using anatomical landmarks. All morphometric parameters decreased from distal to proximal. Male radii were larger than female radii with no significant side difference. 3) The overall shape model had a combined median classification probability for side and gender of 80%.Conclusions: Statistical 3D shape models of the distal radius can be generated using clinical CT-data sets. These models can be used to assess overall bone variance, define and analyze standardized cut-planes, and identify the gender of an unknown sample. These data highlight the potential of shape models to assess the 3D anatomy and anatomical variance of human bones.