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Cranial Reconstruction Evaluation - Comparison of European Statistical Shape Model Performance on Chinese Dataset

Marc Anton FüßingerMarc MetzgerRené Marcel RothweilerLeonard Simon BrandenburgStefan Schlager

出版	Universität, 2022
URL	http://books.google.com.hk/books?id=Pb9u0AEACAAJ&hl=&source=gbs_api

註釋Abstract: Purpose
Morphological variability of the skull is an important consideration for cranioplasty and implant design. Differences in morphology of the skull based on the ethnicity are known. In a previous study we could show the accuracy and benefits of virtual reconstructions based on a statistical shape model (SSM) for neurocranial defects. As the SSM is trained on European data, the question arises how well this model fares when dealing with patients with a different ethnic background. In this study we aim to evaluate the accuracy and applicability of our proposed method when deploying a cranial SSM generated from European data to estimate missing parts of the neurocranium in a Chinese population.

Methods
We used the same data and methods as in our previous study and compared the outcomes when applied to Chinese individuals. A large unilateral defect on the right side and a bilateral defect were created. The outer surface of the cranial table was reconstructed from CT scans, meshed with triangular elements, and registered to a template. Principal component analysis together with Thin Plate Spines (TPS) deformation was applied to quantify modes of variation. The mesh to mesh distances between the original defects ́ surfaces and the reconstructed surface were computed.

Results
Comparing the Chinese test group with the European control group, regarding the entire defect the analysis shows no significant difference for unilateral defects (test vs. control group/0.46 mm ± vs. 0.44 mm). Reconstruction of bilateral defects exhibited only in slightly higher prediction errors than those of unilateral defects (0.49 mm ± vs. 0.45 mm).

Conclusion
The proposed method shows a high accuracy that seems to be ethnical independent - with low error margins for virtual skull reconstruction and implant design