| Title |
Analysis of the three-dimensional anatomical variance of the distal radius using 3D shape models
|
|---|---|
| Published in |
BMC Medical Imaging, March 2017
|
| DOI | 10.1186/s12880-017-0193-9 |
| Pubmed ID | |
| Authors |
Sebastian F. Baumbach, Jakob Binder, Alexander Synek, Fabian G. Mück, Yan Chevalier, Ekkehard Euler, Georg Langs, Lukas Fischer |
| Abstract |
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. 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. 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%. 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. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 2% |
| Unknown | 47 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 17% |
| Researcher | 8 | 17% |
| Student > Bachelor | 7 | 15% |
| Student > Ph. D. Student | 6 | 13% |
| Other | 3 | 6% |
| Other | 4 | 8% |
| Unknown | 12 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 23% |
| Engineering | 10 | 21% |
| Computer Science | 2 | 4% |
| Agricultural and Biological Sciences | 2 | 4% |
| Nursing and Health Professions | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 16 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 March 2017.
All research outputs
#17,881,664
of 22,958,253 outputs
Outputs from BMC Medical Imaging
#338
of 603 outputs
Outputs of similar age
#221,229
of 307,900 outputs
Outputs of similar age from BMC Medical Imaging
#3
of 7 outputs
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