Abstract
BackgroundVarious 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.MethodsThe 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.ResultsEighty-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%.ConclusionsStatistical 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.
Highlights
Various medical fields rely on detailed anatomical knowledge of the distal radius
All morphometric parameters decreased from distal to proximal
Statistical 3D shape models of the distal radius can be generated using clinical computed tomography (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
Summary
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. Literature on the anatomy of the distal radius is limited to morphologic (shape) and morphometric (size) studies based on radiographs [8] or single computed tomography (CT) slices [9,10,11]. A well-established methodology in assessment of 3D anatomy and anatomical variances of bones are statistical shape models. These can be generated from a database of CT scans. Following 3D surface segmentation, a dense set of corresponding surface landmarks is generated for each bone Based on this information, 3D shape models can be calculated and the variation of each surface point within the population illustrated. The 3D shape models can be used to classify anatomical geometries into groups, for instance to determine gender of unidentified bones
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