Virtual reconstruction of bilateral midfacial defects by using statistical shape modeling

• Published in: Journal of cranio-maxillo-facial surgery 2019-07, Vol.47 (7), p.1054-1059
• Main Authors: Fuessinger, Marc Anton, Schwarz, Steffen, Neubauer, Joerg, Cornelius, Carl-Peter, Gass, Mathieu, Poxleitner, Philipp, Zimmerer, Ruediger, Metzger, Marc Christian, Schlager, Stefan
• Format: Article
• Language: English
• Subjects: 3D planning; Adult; Computer-assisted surgery (CAS); Dentistry; Humans; Imaging, Three-Dimensional; Models, Statistical; Orbital Fractures; Skull; Statistical shape model (SSM); Surgery, Computer-Assisted; Tomography, X-Ray Computed; Virtual defect reconstruction; Virtual planning
• ISSN: 1010-5182; 1878-4119
• DOI: 10.1016/j.jcms.2019.03.027

Mirroring and manual adaptation as the main virtual reconstruction method of midfacial defects is time demanding and ignores asymmetrical skull shapes. By using a statistical shape model (SSM), the reconstruction can be automatized and specified. The current study aims to show the ability of the SSM in the virtual reconstruction of artificial bilateral defects. Based on 131 pathologically unaffected CT scans of the adult midface region, an SSM was created. DICOM data were generated, segmented and registered on one mesh, which serves as template for the SSM. The SSM consists of the registered surface meshes and includes the shape variability of the cranial vault. Fractured or missing parts were calculated by the known shape variability of healthy midface data. Using 25 CT scans not included in the SSM, the precision of the reconstruction of virtually placed bilateral defects of the orbital floor (Group 1) and bilateral naso-orbital-ethmoid (NOE) fractures (Group 2). Distances to the corresponding parts of the intact skull were calculated to show the accuracy of the virtual reconstruction method. All defects could be reconstructed by using the SSM and GM technique. The analysis shows a high accuracy of the SSM-driven reconstruction, with a mean error of 0.75 ± 0.18 mm in group 1 and with a mean error of 0.81 ± 0.23 mm in group 2. The precision of the SSM-driven reconstruction is high and its application is easy for the clinician because of the automatization of the virtual reconstruction process in the field of computer-assisted surgery (CAS). Respecting of the natural asymmetry of the skull and the methods of GM are reasons for the high precision and the automatization of the new shown reconstruction workflow.