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Virtual reconstruction of midface defects using statistical shape models.
Journal of Cranio-maxillo-facial Surgery 2017 April
PURPOSE: This study evaluates the accuracy of a statistical shape model (SSM) for virtual fracture reconstruction of the lateral midface.
MATERIALS AND METHODS: A uniform bony defect of the right zygoma was created. A virtual reconstruction was performed by using the standard procedure of mirroring the unaffected to the affected side (Group I) and by using the statistical model based on 178 pathologically unaffected CT scans (Group II). The accuracy of the statistical shape model was evaluated in comparison to the present mirroring protocol. The reconstructed region was compared with the original bone evaluating the mean deviation of both surfaces.
RESULTS: All zygomas could be reconstructed with all methods. On the affected side the mean deviation was 1.10 mm ± 0.23 mm in group I and 0.85 mm ± 0.26 mm in group II. The differences between the groups were significant.
CONCLUSION: SSM offers a more precise reconstruction of midface defects than mirroring procedures. As an additional element SSM could automatize the CAS workflow in many respects.
MATERIALS AND METHODS: A uniform bony defect of the right zygoma was created. A virtual reconstruction was performed by using the standard procedure of mirroring the unaffected to the affected side (Group I) and by using the statistical model based on 178 pathologically unaffected CT scans (Group II). The accuracy of the statistical shape model was evaluated in comparison to the present mirroring protocol. The reconstructed region was compared with the original bone evaluating the mean deviation of both surfaces.
RESULTS: All zygomas could be reconstructed with all methods. On the affected side the mean deviation was 1.10 mm ± 0.23 mm in group I and 0.85 mm ± 0.26 mm in group II. The differences between the groups were significant.
CONCLUSION: SSM offers a more precise reconstruction of midface defects than mirroring procedures. As an additional element SSM could automatize the CAS workflow in many respects.
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