Automated Planning With Multivariate Shape Descriptors for Fibular Transfer in Mandibular Reconstruction.

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.

Statistical Analysis of Interactive Surgical Planning Using Shape Descriptors in Mandibular Reconstruction with Fibular Segments.

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.

Sparse shape model for fibular transfer planning in mandibular reconstruction.

In this paper, we propose an automated preoperative planning method that estimates a plan fitted to the data of a new patient using a planned dataset of previous patients. Although mandibular reconstruction with fibular segments needs preoperative planning for the precise placement of segments, recent interactive planning software cannot secure objectivity of the planning and time-consuming trial-and-error processes are required. The proposed method employs sparse shape modeling; in this modeling, we select a subset of the data from a prepared preoperative planning dataset to make an example or instance of reconstruction via a linear combination of the data. We conduct experiments using the dataset planned by medical doctors and compare the instance estimated by the proposed method to the manual placement by these doctors.

Volumetric fibular transfer planning with shape-based indicators in mandibular reconstruction.

In preoperative planning for mandibular reconstructive surgery, it is necessary to determine the osteotomy lines for fibular shaping and the proper placement of fibular segments in the mandible. Although virtual surgical planning has been utilized in preoperative decision making, current software designs require manual operation and a trial-and-error process to refine the reconstruction plan. We have developed volumetric fibular transfer simulation software that can quickly design a preoperative plan based on direct volume manipulation and quantitative comparison with the patient's original mandible. We propose three quantitative shape indicators-volume ratio, contour error, and maximum projection-for symmetrical lesions of the mandible, and have implemented a parallel computation algorithm for the semiautomatic placement of fibular segments. Using this virtual planning software, we conducted a retrospective study of the computed tomography data from nine patients. We found that combining direct volume manipulation with real-time local search of placement improved the applicability of the planning system to optimize mandibular reconstruction.

Volumetric surgical planning system for fibular transfer in mandibular reconstruction.

This presentation introduces a new software design for virtual preoperative planning for free fibular transfer in mandibular reconstructive surgery. Direct volume resection and manipulation of superimposed fibular segments allow interactive editing of the surgical plan without the need for a surface modeling process. We also introduce three shape indicators: volume ratio, contour error and maximum projection for evaluating the reconstruction plan from geometrical aspects. The indicators significantly quantify the difference between 2-segment and 3-segment cases, and suggest optimization of preoperative planning while satisfying appropriate placement margins for fibular segments.