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(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质量和降低护理颅颌面(CMF)畸形患者的成本。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获得性畸形。美国和世界各地的大量患者患有CMF畸形。对这些患者的评估包括对传统上由分段螺旋多层螺旋CT(MSCT)生成的3D模型的CMF形式的评估。这些模型也被用来计划他们的治疗。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，解剖和牙齿地标就被手动数字化以进行测量。最后，根据测量结果进行诊断和治疗计划。虽然MSCT提供了高质量的图像，因此可以相对快速和容易地进行后处理，但人们对患者过度辐射的问题提出了许多担忧。因此，现在越来越多的医生在办公室里使用CBCT扫描仪。与MSCT相比，CBCT具有辐射小、价格便宜的优点，但其在生成3D模型方面的应用受到低对比度/信噪比和伪影等图像质量的极大限制。因此，现有的针对MSCT的自动分割算法不能对CBCT进行实际分割。目前的CBCT分割解决方案需要费力而漫长的过程，需要对数百个切片进行劳动密集型人工编辑。此外，CMF畸形评估中另一项艰巨而不准确的任务是对3D模型上的解剖地标进行数字化-这是量化畸形的第一步。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，耗时长，精度有限。我们假设，通过开发创新的CBCT友好的后处理工具，可以显著改善高质量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分割和地标数字化的过程。我们的初步研究已经证明了我们方法的可行性。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。它将改变我们在有效利用CBCT方面的牙科/CMF领域 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这项工作，这项工作目前是由劳动密集型的人类操作员艺术地完成的。由此产生的创新也可能影响未来的其他领域，例如整形外科和心血管外科，在这些领域，术中全身CBCT被获取用于图像引导手术和介入。