Planning of mandibular reconstructions based on statistical shape models
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The reconstruction of large continuity defects of the mandible is a challenging task, especially when the shape of the missing part is not known prior to operation. Today, the surgical planning is based mainly on visual judgment and the individual skills and experience of the surgeons. The objective of the current study was to develop a computer-based method that is capable of proposing a reconstruction shape from a known residual mandible part.
The volumetric data derived from 60 CT scans of mandibles were used as the basis for the novel numerical procedure. To find a standardized representation of the mandible shapes, a mesh was elaborated that follows the course of anatomical structures with a specially developed topology of quadrilaterals. These standard meshes were transformed with defined mesh modifications toward each individual mandible surface to allow for further statistical evaluations. The data were used to capture the inter-individual shape variations that were considered as random field variations and mathematically evaluated with principal component analysis. With this information of the mandibular shape variations, an algorithm was developed that proposes shapes for reconstruction planning based on given residual mandible geometry parts.
The accuracy of the novel method was evaluated on six different virtually defined continuity defects that were each created on three mandibles that were not part of the initial database. Virtual reconstructions showed sufficient accuracy of the algorithm for the planning of surgical reconstructions, with average deviations toward the actual geometry of \(1.82 \pm 0.11\) mm for small missing parts and 5 mm for large hemi-lateral defects.
The presented algorithm may be a valuable tool for the planning of mandibular reconstructions. The proposed shapes can be used as templates for computer-aided manufacturing, e.g., with 3D printing devices that use biocompatible materials.
KeywordsMandible Reconstruction Morphology Scaffolds Random field variations 3D printing
We acknowledge financial support of the present study by the German Federal Ministry of Education and Research (Grant No. 13GW0016C). Furthermore, the support of DYNARDO Austria GmbH for providing licenses of the software tools Statistics on Structures and optiSLang is gratefully acknowledged.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards (Approval No. 2596/09, Technische Universität München, Germany).
For this type of study, formal consent is not required.
Human and animal rights
This article does not contain any studies with human participants or animals performed by any of the authors.
- 11.Lamecker H, Zachow S, Wittmers A, Weber B, Hege H, Isholtz B, Stiller M (2006) Automatic segmentation of mandibles in low-dose CT-data. Int J Comput Assist Radiol Surg 1:393Google Scholar
- 14.Gollmer ST, Buzug TM (2012) Fully automatic shape constrained mandible segmentation from cone-beam CT data. In: 2012 9th IEEE international symposium on biomedical imaging (ISBI), pp 1272–1275Google Scholar
- 16.Reichert JC, Cipitria A, Epari DR, Saifzadeh S, Krishnakanth P, Berner A, Woodruff MA, Schell H, Mehta M, Schuetz MA, Duda GN, Hutmacher DW (2012) A tissue engineering solution for segmental defect regeneration in load-bearing long bones. Sci Transl Med 4(141):141ra93. doi: 10.1126/scitranslmed.3003720
- 21.Modabber A, Ayoub N, Möhlhenrich SC, Goloborodko E, Sönmez TT, Ghassemi M, Loberg C, Lethaus B, Ghassemi A, Hölzle F (2014) The accuracy of computer-assisted primary mandibular reconstruction with vascularized bone flaps: iliac crest bone flap versus osteomyocutaneous fibula flap. Med Devices Evid Res 7:211–217CrossRefGoogle Scholar
- 26.Sorkine O, Cohen-Or D, Lipman Y, Alexa M, Rössl C, Seidel H-P (2004) Laplacian surface editing. In: Eurographics symposium on geometry processing, pp 175–184Google Scholar
- 29.Wolff S (2014) Robustness evaluation in sheet metal forming using statistics on structures (SoS) and optiSLang. In: Proceedings 32nd German ANSYS and CADFEM users’ meetingGoogle Scholar
- 30.Wolff S (2013) Simulation of random fields in structural design. In: 11th international probabilistic workshopGoogle Scholar
- 31.Kroon DJ (2011) Segmentation of the mandibular canal in cone-beam CT data. PhD thesis Universiteit TwenteGoogle Scholar
- 32.Kainmueller D, Lamecker H, Seim H, Zachow S (2009) Multi-object segmentation of head bones. In: MICCAI workshop head and neck auto-segmentation challenge, pp 1–11Google Scholar
- 35.Wendland H (2004) Scattered data approximation: Cambridge monographs on applied and computational mathematics. Cambridge University Press, CambridgeGoogle Scholar
- 38.Bucher C (2009) Computational analysis of randomness in structural mechanics: structures and infrastructures book series, 1st edn. CRC Press, Boca Raton, FLGoogle Scholar
- 39.Nunes RF, Will J, Bayer V, Chittepu K (2009) Robustness Evaluation of brake systems concerned to squeal noise problem. In: Proceedings of the 7th Weimar optimization and stochastic days, pp 1–20Google Scholar
- 40.Roos D, Einzinger J, Bayer V (2009) Robust design optimization applied to structural, thermal and fluid analysis including manufacturing tolerances. In: Proceedings of the Weimar optimization and stochastic daysGoogle Scholar
- 41.Jewer DD, Boyd JB, Manktelow RT, Zuker RM, Rosen IB, Gullane PJ, Rotstein LE, Freeman JE (1989) Orofacial and mandibular reconstruction with the iliac crest free flap: a review of 60 cases and a new method of classification. Plast Reconstr Surg 84:391–403 (discussion 404–405) PubMedCrossRefGoogle Scholar
- 42.Skadłubowicz P, Król Z, Wróbel Z, Hefti F, Krieg A (2009) Using of statistical shape models for pelvis reconstruction in the oncologic surgery. J Med Informatics Technol 13:151–156Google Scholar
- 51.Bou-Sleiman H, Iizuka T, Nolte L-P, Reyes M (2013) Population-based design of mandibular fixation plates with bone quality and morphology considerations. Ann Biomed Eng 41(2):377–384Google Scholar
- 52.Raith S, Varga V, Steiner T, Hölzle F, Fischer H (2016) Computational geometry assessment for morphometric analysis of the mandible. Comput Methods Biomech Biomed Eng:1–8. doi: 10.1080/10255842.2016.1196196