A Novel Imaging Analysis Platform for Patients with Craniomaxillofacial Deformities

针对颅颌面畸形患者的新型影像分析平台

• 批准号: 9417942
• 负责人: James J Xia
• 金额: $ 48.18万
• 依托单位: METHODIST HOSPITAL RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-07 至 2021-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9417942
• 关键词: Algorithms; American; Anatomy; Atlases; Back; Cardiovascular Surgical Procedures; Cephalometry; Clinic; Clinical; Clinical Research; Communities; Computer Assisted; Computer software; Computers; Consultations; Deformity; Dental Care; Dentistry; Detection; Diagnosis; Diagnostic; Dimensions; Dose; Ensure; Evaluation; Exposure to; Face; Future; Goals; Head; Hour; Human; Image; Image Analysis; Image-Guided Surgery; Individual; Intervention; Jaw; Label; Learning; Manuals; Measurement; Measures; Methods; Modeling; Morphologic artifacts; Motivation; Nature; Noise; Operative Surgical Procedures; Oral; Orthodontics; Orthopedic Surgery procedures; Patient Care; Patients; Phase; Physicians' Offices; Plastic Surgical Procedures; Process; Quality of Care; Quantitative Evaluations; Radiation; Radiation exposure; Running; Scanning; Services; Shapes; Signal Transduction; Slice; Speed; Syncope; System; Technology; Three-Dimensional Image; Time; Tomography, Computed, Scanners; Tooth structure; Training; Validation; Visit; Work; X-Ray Computed Tomography; accurate diagnosis; base; care costs; cone-beam computed tomography; cost; craniofacial; craniomaxillofacial; design; detector; forest; imaging modality; improved; innovation; novel; open source; psychologic; public health relevance; simulation; three-dimensional modeling; tool; treatment planning; usability; user-friendly

 DESCRIPTION (provided by applicant): Our ultimate goal is to improve our ability to create and measure 3D models derived from cone-beam computed tomography (CBCT). Our main motivation is to improve quality and reduce costs in care of patients with craniomaxillofacial (CMF) deformities. The resulted innovations will also impact other fields. CMF deformities involve congenital and acquired deformities of the jaws and face. A large number of patients in the US and around the world suffered from CMF deformities. The evaluation of these patients includes an assessment of CMF form on 3D models that are traditionally generated from segmented spiral multi-slice CTs (MSCTs). These models are also used to plan their treatment. The purpose of segmentation is to separate different anatomical structures and to remove the artifacts on the CTs. Once 3D models are generated from the segmented CTs, anatomical and teeth landmarks are manually digitized for measurements. Finally, diagnosis and treatment planning are performed based on measurements. Although MSCT provides high- quality images and thus allows relatively fast and easy post processing, many concerns have been raised on excessive radiation exposure to patients. Therefore, more doctors are now using CBCT scanners in their offices. CBCT has less radiation and is inexpensive compared to the MSCT, but their use in generating 3D models is greatly limited by the poor image quality, i.e., low contrast / signal-to-noise ratio and artifacts. Thus, the existing automated segmentation algorithms developed for MSCT are incapable of practically segmenting CBCTs. The current solution to CBCT segmentation entails an arduous and lengthy process that involves labor-intensive manual editing of hundreds of slices. Besides, another arduous and inaccurate task in the assessment of CMF deformities is the digitization of anatomical landmarks on 3D models - the first step to quantify the deformities. Currently a typical 3D cephalometric and teeth analysis requires the manual digitization of more than 200 landmarks, which is time consuming and has limited accuracy. We hypothesize that the creation and measurement of high-quality 3D models can be significantly improved by developing innovative CBCT-friendly post processing tools. Therefore, in this renewal project, we propose to develop and validate a novel CBCT analysis platform to automate the process of CBCT segmentation and landmark digitization. The feasibility of our approaches has already been proven by our preliminary studies. Our innovative CBCT analysis platform will significantly improve the quality and reduce the cost of care to the individuals with CMF conditions. It will change our dental/CMF fields in effectively utilizing CBCT as a guide for on-the-fly diagnosis and treatment planning. With minimal user intervention, the computer will accurately and effectively do the work, which is currently artistically done by the labor-intensive human operators. The resulted innovations may also impact other fields in the future, e.g., orthopedic surgery and cardiovascular surgery where intraoperative whole-body CBCT is acquired for image-guided surgery and intervention.

 描述（由申请人提供）：我们的最终目标是提高我们创建和测量源自锥形束计算机断层扫描（CBCT）的3D模型的能力。我们的主要动机是提高颅颌面畸形患者的护理质量并降低成本。由此产生的创新也将影响其他领域。CMF畸形包括颌骨和面部的先天性和后天性畸形。美国和世界各地的大量患者患有CMF畸形。对这些患者的评价包括在传统上由分段螺旋多层CT（MSCT）生成的3D模型上评估CMF形式。这些模型也用于计划他们的治疗。分割的目的是分离不同的解剖结构并去除CT上的伪影。一旦从分割的CT生成3D模型，解剖和牙齿标志被手动数字化用于测量。最后，根据测量结果进行诊断和治疗计划。尽管多层螺旋CT提供了高质量的图像，因此允许相对快速和容易的后处理，但已经提出了对患者过度辐射暴露的许多担忧。因此，越来越多的医生现在在办公室使用CBCT扫描仪。与MSCT相比，CBCT具有更少的辐射并且便宜，但是它们在生成3D模型中的使用受到差的图像质量的极大限制，即，低对比度/信噪比和伪影。因此，为MSCT开发的现有自动分割算法不能实际分割CBCT。CBCT分割的当前解决方案需要一个艰巨而漫长的过程，涉及数百个切片的劳动密集型手动编辑。此外，CMF畸形评估的另一项艰巨而不准确的任务是3D模型上解剖标志的数字化-量化畸形的第一步。目前，典型的3D头影测量和牙齿分析 需要对200多个地标进行人工数字化，这是耗时的并且具有有限的准确性。我们假设，通过开发创新的CBCT友好的后处理工具，可以显着改善高质量3D模型的创建和测量。因此，在这个更新项目中，我们建议开发和验证一个新的CBCT分析平台，以自动化CBCT分割和标志数字化的过程。我们的方法的可行性已经被我们的初步研究所证实。我们创新的CBCT分析平台将显著提高CMF患者的护理质量并降低护理成本。它将改变我们的牙科/CMF领域有效利用CBCT 作为即时诊断和治疗计划的指南。在最少的用户干预下，计算机将准确有效地完成工作，目前这些工作是由劳动密集型的人类操作员完成的。由此产生的创新也可能在未来影响其他领域，例如，骨科手术和心血管手术，其中采集术中全身CBCT用于图像引导手术和干预。