A statistical shape model for estimating missing soft tissues of the face in a black South African population

dc.contributor.authorSwanepoel, Helene Francia
dc.contributor.authorMatthews, Harold S.
dc.contributor.authorClaes, Peter
dc.contributor.authorVandermeulen, Dirk
dc.contributor.authorOettle, Anna Catherina
dc.contributor.emailu27089691@tuks.ac.zaen_US
dc.date.accessioned2024-09-06T05:11:56Z
dc.date.available2024-09-06T05:11:56Z
dc.date.issued2024-07
dc.descriptionPrevious presentations: University of Cape Town Annual Face Science Symposium, Zoom virtual meeting, 8 November 2022.en_US
dc.description.abstractPURPOSE : Facial disfigurement may affect the quality of life of many patients. Facial prostheses are often used as an adjuvant to surgical intervention and may sometimes be the only viable treatment option. Traditional methods for designing soft-tissue facial prostheses are time-consuming and subjective, while existing digital techniques are based on mirroring of contralateral features of the patient, or the use of existing feature templates/models that may not be readily available. We aim to support the objective and semi-automated design of facial prostheses with primary application to midline or bilateral defect restoration where no contralateral features are present. Specifically, we developed and validated a statistical shape model (SSM) for estimating the shape of missing facial soft tissue segments, from any intact parts of the face. MATERIALS AND METHODS : An SSM of 3D facial variations was built from meshes extracted from computed tomography and cone beam computed tomography images of a black South African sample (n = 235) without facial disfigurement. Various types of facial defects were simulated, and the missing parts were estimated automatically by a weighted fit of each mesh to the SSM. The estimated regions were compared to the original regions using color maps and root-mean-square (RMS) distances. RESULTS : Root mean square errors (RMSE) for defect estimations of one orbit, partial nose, cheek, and lip were all below 1.71 mm. Errors for the full nose, bi-orbital defects, as well as small and large composite defects were between 2.10 and 2.58 mm. Statistically significant associations of age and type of defect with RMSE were observed, but not with sex or imaging modality. CONCLUSION : This method can support the objective and semi-automated design of facial prostheses, specifically for defects in the midline, crossing the midline or bilateral defects, by facilitating time-consuming and skill-dependent aspects of prosthesis design.en_US
dc.description.departmentAnatomyen_US
dc.description.librarianhj2024en_US
dc.description.sdgSDG-03:Good heatlh and well-beingen_US
dc.description.sponsorshipBakeng se Afrika.en_US
dc.description.urihttps://wileyonlinelibrary.com/journal/jopren_US
dc.identifier.citationSwanepoel, H.F., Matthews, H.S., Claes, P., Vandermeulen, D. & Oettle, A.C. A statistical shape model for estimating missing soft tissues of the face in a black South African population. Journal of Prosthodontics 2024; 33: 565–73. https://doi.org/10.1111/jopr.13746.en_US
dc.identifier.issn1059-941X (print)
dc.identifier.issn1532-849X (online)
dc.identifier.other10.1111/jopr.13746
dc.identifier.urihttp://hdl.handle.net/2263/98057
dc.language.isoenen_US
dc.publisherWileyen_US
dc.rights© 2024 by the American College of Prosthodontists. This is the pre-peer reviewed version of the following article : A statistical shape model for estimating missing soft tissues of the face in a black South African population. Journal of Prosthodontics 2024; 33: 565–73. https://doi.org/10.1111/jopr.13746. The definite version is available at : https://wileyonlinelibrary.com/journal/jopr.en_US
dc.subjectComputer-aided designen_US
dc.subjectFacial prosthesesen_US
dc.subjectFacial variationen_US
dc.subjectMidline defectsen_US
dc.subjectSoft-tissue facial defectsen_US
dc.subjectFacial disfigurementen_US
dc.subjectQuality of life (QoL)en_US
dc.subjectSDG-03: Good health and well-beingen_US
dc.titleA statistical shape model for estimating missing soft tissues of the face in a black South African populationen_US
dc.typePostprint Articleen_US

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