The ultimate goal of this project is to develop an open source novel imaging informatics platform, the AnatomicAligner, to improve the surgical planning method for craniomaxillofacial (CMF) surgery and subsequently to improve the treatment outcome of the patients with CMF deformities. CMF surgery involves the correction of congenital and acquired deformities of the skull and face. Due to the complex nature of the CMF skeleton, it requires extensive presurgical planning. Unfortunately, the traditional planning methods, e.g. prediction tracings and simulating surgery on stone models have remained unchanged over the last 50 years. Many unwanted surgical outcomes are the result of these deficient methods. To solve these problems, we have developed a Computer-Aided Surgical Simulation (CASS) system. Although it still needs significant improvements, the use of CASS has eliminated most of the limitations of the traditional methods. Unfortunately, it also creates a new problem that the digital establishment of dental occlusion becomes significantly more difficult. The dental articulation is an important step during the planning process to correct preexisting malocclusions or to surgically reestablish a new occlusion. The current gold standard is to utilize stone dental models and hand-articulate them on an articulator. Unfortunately, the same is not true in virtual world. These dental arches are 3D images. When the digital teeth are moved towards each other, they are not stopped by collision and continue to move through each other, which do not occur in real world. In order to completely solve these problems, it is critical to develop a new system that will integrate fully automated process of dental articulation and significantly improved our CASS technologies. Our hypotheses are that the occlusion can be digitally and automatically established in a computer planning system, and the computer-generated occlusion is as precise as the occlusion established by hand-articulating a set of stone models (the current gold standard). In order to prove our hypotheses, we are proposing three Specific Aims to develop and validate a novel imaging informatics platform, the AnatomicAligner, for CMF surgery. The system is innovative because for the first time, doctors will be able to efficiently and accurately plan the entire surgery in the computer, including automated establishment of dental occlusion. The new technical contributions include: 1) a robust 3D segmentation-based approach to achieve the initial digital dental model alignment;and 2) novel approaches for automated final digital articulation. The significance of this project is that the AnatomicAligner system will produce a paradigm shift in CMF planning. Surgeons will be able to completely abandon the problematic traditional methods for a more accurate, faster and cost effective method. The success of AnatomicAligner will lead to a new class of imaging informatics platform for CMF surgery. This platform can also be transformed to orthopedic surgery and other medical specialties. Once completed, the software (both source codes and executables) will be freely downloaded from internet by research community.
In the surgical planning process of craniomaxillofacial surgeries, the articulation of dental models is an important step to correct preexisting malocclusions or to reestablish a new occlusion after it is disrupted by trauma, pathology or surgery. The traditional standard is to utilize stone dental models and articulate them by hand on an articulator. In order to solve the problems associated with the traditional planning methods and incorporate automated digital dental articulation for surgical planning, we are proposing to develop and validate an open source imaging informatics platform, the AnatomicAligner, for craniomaxillofacial surgery.
|Zhang, Guangming; Xia, James J; Liebschner, Michael et al. (2016) Improved Rubin-Bodner model for the prediction of soft tissue deformations. Med Eng Phys 38:1369-1375|
|Zhang, Xiaoyan; Tang, Zhen; Liebschner, Michael A K et al. (2016) An eFace-Template Method for Efficiently Generating Patient-Specific Anatomically-Detailed Facial Soft Tissue FE Models for Craniomaxillofacial Surgery Simulation. Ann Biomed Eng 44:1656-71|
|Gateno, J; Jajoo, A; Nicol, M et al. (2016) The primal sagittal plane of the head: a new concept. Int J Oral Maxillofac Surg 45:399-405|
|Wang, Li; Gao, Yaozong; Shi, Feng et al. (2016) Automated segmentation of dental CBCT image with prior-guided sequential random forests. Med Phys 43:336|
|Li, B; Shen, S G; Yu, H et al. (2016) A new design of CAD/CAM surgical template system for two-piece narrowing genioplasty. Int J Oral Maxillofac Surg 45:560-6|
|Gateno, Jaime; Alfi, David; Xia, James J et al. (2015) A Geometric Classification of Jaw Deformities. J Oral Maxillofac Surg 73:S26-31|
|Wang, Li; Ren, Yi; Gao, Yaozong et al. (2015) Estimating patient-specific and anatomically correct reference model for craniomaxillofacial deformity via sparse representation. Med Phys 42:5809-16|
|Zhang, Jun; Gao, Yaozong; Wang, Li et al. (2015) Automatic Craniomaxillofacial Landmark Digitization via Segmentation-guided Partially-joint Regression Forest Model and Multi-scale Statistical Features. IEEE Trans Biomed Eng :|
|Xia, J J; Gateno, J; Teichgraeber, J F et al. (2015) Algorithm for planning a double-jaw orthognathic surgery using a computer-aided surgical simulation (CASS) protocol. Part 1: planning sequence. Int J Oral Maxillofac Surg 44:1431-40|
|Zhang, Jian; Xia, James; Li, Jianfu et al. (2015) Reconstruction-based Digital Dental Occlusion of the Partially Edentulous Dentition. IEEE J Biomed Health Inform :|
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