A Three-Dimensional Statistical Average Skull: Application of Biometric Morphing in Generating Missing Anatomy
Tara Lynn Teshima1, Vaibhav Patel, James G Mainprize
1*Division of Plastic Surgery, Sunnybrook Health Sciences Centre, University of Toronto †Medical Imaging Research, Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
The Journal of Craniofacial Surgery
|June 27, 2015
Summary
Researchers developed a statistical 3D virtual skull model from a normative dataset. This model aids in reconstructing missing craniofacial anatomy for surgical planning and evaluation.
Area of Science:
- Craniomaxillofacial Surgery
- Medical Imaging
- Computational Anatomy
Background:
- Three-dimensional (3D) modeling is increasingly used in craniomaxillofacial surgery.
- Development is limited by the absence of a normative 3D anatomical dataset and a statistical mean 3D virtual model.
Purpose of the Study:
- To develop and validate a protocol for generating a statistical 3D virtual skull model.
- To create a normative 3D dataset of adult skulls for this purpose.
Main Methods:
- Processed 200 adult skull CT images using thin-plate spline geometric morphometrics.
- Developed a protocol for 3D skull landmarking and data reduction using 21 anthropometric points.
- Validated the statistical average 3D skull by reconstructing cranial defects and comparing to original skulls.
Main Results:
- Generated a normative database of 33 adult human skulls.
- Created a statistical average 3D skull.
- Demonstrated a root mean square error (RMSE) of 0.74 mm for defect restoration using the average skull, significantly better than the worst match (4.4 mm) and comparable to the best match (0.58 mm).
Conclusions:
- The statistical average craniofacial surface topography is a valuable tool.
- It can assist in deriving missing anatomy in complex craniofacial defects.
- It aids in evaluating the morphologic outcomes of surgical interventions.
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