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Identifying the Sources of Error When Using 3-Dimensional Printed Head Models with Surgical Navigation
Amirhossein Mehbodniya1, Mahmoud Moghavvemi2, Vairavan Narayanan3
1Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia.
World Neurosurgery
|October 23, 2019
Summary
Errors in 3D printed head models for surgical training can occur during preparation, printing, and registration. Automated registration techniques significantly improve accuracy, minimizing spatial errors for enhanced training utility.
Area of Science:
- Medical Imaging
- Surgical Training
- 3D Printing Technology
Background:
- Three-dimensional (3D) printed models are increasingly used for surgical training.
- Assessing the accuracy of these models is crucial for effective simulation.
Purpose of the Study:
- To evaluate sources of error in preparing, printing, and using 3D printed head models for training.
- To compare different registration methods for 3D printed models in surgical navigation.
Main Methods:
- Two 3D printed head models were created from patient imaging data with embedded markers.
- Three registration methods were tested: manual with original data, manual with scanned model data, and automatic with scanned model data.
- Errors were quantified by measuring the distance between the navigation probe and marker points.
Main Results:
- Preparation and printing errors were minimal, influenced by print orientation and postprocessing.
- Registration using scanned model data (1.082 mm) was more accurate than using original patient data (1.28 mm).
- Automated registration yielded the highest accuracy with the smallest error (0.74 mm).
Conclusions:
- Spatial accuracy errors are inherent in 3D fabricated models.
- Errors originate from fabrication, image registration, and the surgical registration process.
- Automated registration significantly enhances the spatial accuracy of 3D printed models for surgical training.
