RESUMO
OBJECTIVE: This paper introduces methods to automate preoperative planning of fibular segmentation and placement for mandibular reconstruction with fibular flaps. METHODS: Preoperative virtual planning for this type of surgery has been performed by manual adjustment of many parameters, or based upon a single feature of the reconstruction. We propose a novel planning procedure formulated as a nonconvex minimization problem of an objective function using the multilateral shape descriptors. RESULTS: A retrospective study was designed and 120 reconstruction plans were reproduced using computed tomography images with oral surgeons. The proposed automated planning model was quantitatively compared with both the existing model and the surgeons' plans. CONCLUSION: The results show that the developed framework attains stable automated planning that agrees with the surgeons' decisions. SIGNIFICANCE: This method addresses tradeoff problems between symmetric reconstruction and restoration of the native contour of the mandible.
Assuntos
Transplante Ósseo/métodos , Fíbula/transplante , Mandíbula/cirurgia , Reconstrução Mandibular/métodos , Cirurgia Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodos , Fíbula/diagnóstico por imagem , Humanos , Imageamento Tridimensional/métodos , Mandíbula/diagnóstico por imagem , Reconhecimento Automatizado de Padrão/métodos , Cuidados Pré-Operatórios/métodos , Radiografia Dentária/métodos , Procedimentos de Cirurgia Plástica/métodos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Interface Usuário-ComputadorRESUMO
This study was performed to quantitatively analyze medical knowledge of, and experience with, decision-making in preoperative virtual planning of mandibular reconstruction. Three shape descriptors were designed to evaluate local differences between reconstructed mandibles and patients' original mandibles. We targeted an asymmetrical, wide range of cutting areas including the mandibular sidepiece, and defined a unique three-dimensional coordinate system for each mandibular image. The generalized algorithms for computing the shape descriptors were integrated into interactive planning software, where the user can refine the preoperative plan using the spatial map of the local shape distance as a visual guide. A retrospective study was conducted with two oral surgeons and two dental technicians using the developed software. The obtained 120 reconstruction plans show that the participants preferred a moderate shape distance rather than optimization to the smallest. We observed that a visually plausible shape could be obtained when considering specific anatomical features (e.g., mental foramen. mandibular midline). The proposed descriptors can be used to multilaterally evaluate reconstruction plans and systematically learn surgical procedures.
