Enhanced Navigation for Endoscopic Sinus Surgery Through Video Analysis

通过视频分析增强内窥镜鼻窦手术导航

• 批准号: 8508940
• 负责人: GREGORY Donald HAGER
• 金额: $ 45.52万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-12 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8508940
• 关键词: Affect; Algorithms; Anatomic Surface; Anatomic structures; Anatomy; Area; Cadaver; Carotid Arteries; Clinical; Clinical Investigator; Computational algorithm; Data; Development; Effectiveness; Endoscopes; Endoscopy; Engineering; Evaluation; Goals; Healthcare Systems; Image; Imagery; Imaging Device; In Situ; Judgment; Laparoscopy; Lead; Location; Measures; Medical; Methodology; Methods; Modeling; Morbidity - disease rate; Names; Navigation System; Nursing Faculty; Operative Surgical Procedures; Optic Nerve; Orthopedic Surgery procedures; Outcome; Patients; Procedures; Process; Radiation; Resolution; Retinal Cone; Safety; Scanning; Shapes; Sinus; Staging; Structure; Surface; Surgeon; Surgical Error; Time; Translating; Translational Research; Translations; United States; Vertebral column; Vision; Work; X-Ray Computed Tomography; base; clinical practice; clinically relevant; comparative; cost; craniofacial; experience; improved; innovation; intraoperative imaging; millimeter; neurosurgery; optical imaging; patient safety; prototype; reconstruction; skills; tool

DESCRIPTION (provided by applicant): This project will provide new registration and visualization tools for functional endoscopic sinus surgery (FESS) using widely available high-definition endoscopic video. These tools will provide higher accuracy navigation accuracy to the surgeon, and will make it possible to accurately measure change as surgery progresses. The key innovation in the project is the integration of algorithms for computational vision with traditional navigation methods to provide these enhancements. The algorithms will be evaluated retrospectively on video and navigation data acquired during FESS procedures. The project has four specific aims: Aim 1: Develop video-CT registration algorithms that are accurate to CT resolution. Aim 2: Develop methods for surface shape estimation from endoscopic images. Aim 3: Perform comparative evaluation of video-CT-based navigation on patient data. Aim 4: Assess the accuracy and reliability of intraoperative surface estimation on patient data. The significance of improved navigation is to 1) enhancement patient safety and outcomes by reducing potential complications and radiation exposure, and 2) to reduce cost by improving clinical workflow and clarity of intraoperative visualization. In the United States, it is estimate that there are more than 200,000 sinus surgery procedures performed annually. All of these are performed under endoscopic guidance, and a large fraction can or could employ surgical navigation. Thus, even moderate improvements in outcome and workflow efficiency can lead to significant benefits to both patients and the health care system. The innovation of the proposed approach is the use of the images from the endoscope itself as the basis for: 1) registration to pre-operative or intra-operative volumes, and 2) reconstruction of anatomic surfaces. Prior work has demonstrated that these problems are both solvable. The project will combine the efforts of an experienced team consisting of engineering and clinical faculty, and will focus on translation of the research to clinically relevant data. The methodology of the project will be to develop and validate algorithms extensively on cadaver models with the goal of achieving 0.5 mm accuracy for both registration and surface reconstruction. Once these goals are achieved, the algorithms will be assessed on patient data acquired during FESS procedures. Although aimed at FESS, the proposed methods are widely applicable to other areas of endoscopy and laparoscopy.

描述（由申请人提供）：该项目将使用广泛可用的高清内窥镜视频为功能性内窥镜鼻窦手术（FESS）提供新的配准和可视化工具。这些工具将为外科医生提供更高精度的导航精度，并将使其能够随着手术的进行而准确测量变化。该项目的关键创新是将计算视觉算法与传统导航方法相结合，以提供这些增强功能。将根据FESS手术期间采集的视频和导航数据对算法进行回顾性评价。 该项目有四个具体目标：目标1：开发视频CT配准算法，精确到CT分辨率。目标2：开发用于从内窥镜图像估计表面形状的方法。目标3：对患者数据进行基于视频CT的导航的比较评价。目的4：评估术中表面估计对患者数据的准确性和可靠性。 改进导航的意义在于：1）通过减少潜在并发症和辐射暴露来提高患者安全性和结局，2）通过改善临床工作流程和术中可视化的清晰度来降低成本。在美国，据估计每年进行超过200，000例鼻窦手术。所有这些都是在内窥镜引导下进行的，并且很大一部分可以或可以采用手术导航。因此，即使是结果和工作流程效率的适度改善也可以为患者和医疗保健系统带来显著的益处。 所提出的方法的创新在于使用来自内窥镜本身的图像作为以下的基础：1）与术前或术中体积的配准，以及2）解剖表面的重建。先前的工作已经证明，这些问题都是可以解决的。该项目将联合收割机的努力，一个经验丰富的团队组成的工程和临床教师，并将重点放在翻译的研究，临床相关的数据。 该项目的方法将是制定和 在尸体模型上广泛验证算法，目标是实现0.5 mm的配准和表面重建精度。一旦达到这些目标，将根据FESS手术期间采集的患者数据评估算法。 虽然针对FESS，但所提出的方法广泛适用于内窥镜和腹腔镜的其他领域。