Quantitative Endoscopic Measurement of Anatomy

描述(申请人提供)：视频内窥镜在诊断性和介入性临床应用中被广泛应用。然而，当前的视频内窥镜系统不支持观察解剖的重建和定量测量。然而，从视频图像测量和建模的能力具有许多潜在的临床应用，如确定肿瘤的大小，监控病变大小随时间的变化，或计算解剖的面积、大小或体积测量。同时，从视频图像重建算法的最新进展为创造定量内窥镜测量(QEM)系统的方法提供了机会。拟议项目的目标是确定QEM是否有可能作为常规的诊断或介入成像方式使用。为此，我们打算开发和评估一个原型系统，以满足特定的、急迫的临床需求：测量儿童呼吸道狭窄。这是QEM的理想测试应用，因为目前进行气道大小调整的方法是有创性的，而且其准确性有限。此外，提供一种新的、更准确的模式可能会使更好地监测和治疗这种疾病。因此，该项目的具体目标是： 1.目标1：研制临床可部署的内窥镜数据采集系统。 2.目标2：开发和验证用于计算跟踪视频内窥镜解剖表面几何属性的算法。 3.目的3：在受控临床环境下论证QEM的可行性。 最后，需要强调的是，虽然我们关注的是特定的临床环境，但这里描述的基本功能将产生更广泛的影响。光学和视频内窥镜设备广泛应用于诊断和外科手术的许多领域。轻松捕捉呼吸道、鼻窦腔等的完整几何形状的能力将为其他一些科学和临床研究打开大门。例如，将有可能进行重复成像以跟踪治疗效果，并执行目前依赖于更昂贵的CT或MR成像的办公室内诊断程序。 项目简介：拟议的项目将开发从内窥镜数据计算准确的解剖模型的方法。它将专门应用于一个高度相关的临床问题：幼儿呼吸道阻塞的大小。然而，在医学的许多领域中，进行简单、安全的解剖结构大小的可能性具有广泛的相关性。

DESCRIPTION (provided by applicant): Video endoscopy is widely used in both diagnostic and interventional clinical applications. However, current video endoscopy systems do not support reconstruction and quantitative measurement of viewed anatomy. Yet, the ability to measure and model from video images has a number of potential clinical applications such as sizing a tumor, monitoring the change in size of a lesion over time, or computing area, size, or volume measurements of anatomy. At the same time, recent advances in algorithms for reconstruction from video images offer the opportunity of creating methods for quantitative endoscopic measurement (QEM) systems. The goal of the proposed project is to determine whether QEM is potentially usable as a routine diagnostic or interventional imaging modality. To do so, we intend to develop and evaluate a prototype system in the context of a specific, acute clinical need: the measurement of stenosis in pediatric airways. This is an ideal test application for QEM, as the current method of performing airway sizing is invasive, and it has a limited degree of accuracy. Furthermore, providing a new, more accurate modality would potentially enable better monitoring and treatment of this disease. The specific aims for this project are thus: 1. Aim 1: Develop a clinically deployable endoscopic data collection system. 2. Aim 2: Develop and validate algorithms for computing geometric properties of anatomic surfaces from a tracked video endoscope. 3. Aim 3: Demonstrate the feasibility of QEM in a controlled clinical setting. Finally, it is important to emphasize that, while we are focused on a specific clinical setting, the basic capabilities described here will have a much broader impact. Optical and video endoscopic devices are widely used in many areas of diagnosis and surgery. The ability to easily capture the full geometry of airways, sinus cavities, and so forth will open the door to a number of other scientific and clinical investigations. For example, it would become possible to perform repeat imaging to track the effect of treatment, and to perform in-office diagnostic procedures that currently rely on more expensive CT or MR imaging. Project Narrative: The proposed project will develop methods for computing accurate models of anatomy from endoscopic data. It will be specifically applied to a clinical problem of high relevant: the sizing of airway obstructions in young children. However, the possibility of performing simple, safe sizing of anatomic structures has wide relevant in many areas of medicine.