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

• Published in: IEEE transactions on biomedical engineering 2017-08, Vol.64 (8), p.1772-1785
• Main Authors: Nakao, Megumi, Aso, Shimpei, Imai, Yuichiro, Ueda, Nobuhiro, Hatanaka, Toshihide, Shiba, Mao, Kirita, Tadaaki, Matsuda, Tetsuya
• Format: Article
• Language: English
• Subjects: Automated planning; Automation; Bone Transplantation - methods; Bones; Computational modeling; Computed tomography; Fibula - diagnostic imaging; Fibula - transplantation; fibular transfer surgery; Flaps; Humans; Image processing; Image reconstruction; Image segmentation; Imaging, Three-Dimensional - methods; Mandible; Mandible - diagnostic imaging; Mandible - surgery; mandibular reconstruction; Mandibular Reconstruction - methods; Medical personnel; Objective function; Pattern Recognition, Automated - methods; Planning; Preoperative Care - methods; Radiography, Dental - methods; Reconstructive Surgical Procedures - methods; Reproducibility of Results; Restoration; Sensitivity and Specificity; Shape; shape descriptor; Surgeons; Surgery; Surgery, Computer-Assisted - methods; surgical process modeling; Tomography, X-Ray Computed - methods; User-Computer Interface
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2016.2621742

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.