Nose Reconstruction

Konofaos, Petros; Wallace, Robert D.

doi:10.1007/978-3-030-78028-9_15

Tips and Tricks in Plastic Surgery 2021

DOI: 10.1007/978-3-030-78028-9_15

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Nose Reconstruction

Petros Konofaos

Robert D. Wallace

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2023

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“…The restoration of ocular loss continues to lack a viable solution. The surgical reconstruction of ear 14 and nose 15 defects also presents unique challenges. Successfully addressing defects of these features by accurately replicating their intricate three‐dimensional geometry requires complex surgical techniques and the availability of appropriate donor tissues 16,17 …”

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confidence: 99%

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

Swanepoel,

Matthews,

Claes

et al. 2023

Journal of Prosthodontics

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PurposeFacial 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 MethodsAn 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.ResultsRoot 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.ConclusionThis 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.This article is protected by copyright. All rights reserved

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mentioning

confidence: 99%

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

Swanepoel,

Matthews,

Claes

et al. 2023

Journal of Prosthodontics

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Nose Reconstruction

Cited by 1 publication

References 21 publications

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

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

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