Quantitative Endoscopic Measurement of Anatomy

描述（由申请人提供）：视频内窥镜广泛用于诊断和介入临床应用。然而，当前的视频内窥镜检查系统不支持所观察的解剖结构的重建和定量测量。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，例如确定肿瘤的大小，监测病变大小随时间的变化，或计算解剖结构的面积、大小或体积测量。同时，从视频图像重建算法的最新进展提供了创建定量内窥镜测量（QEM）系统的方法的机会。拟议项目的目标是确定QEM是否可能用作常规诊断或介入成像模式。为此，我们打算开发和评估一个原型系统的背景下，一个特定的，急性的临床需求：在小儿气道狭窄的测量。这是QEM的理想测试应用，因为当前进行气道测量的方法是有创的，并且其准确度有限。此外，提供一种新的、更准确的模式将有可能更好地监测和治疗这种疾病。因此，该项目的具体目标是： 1.目的1：开发一个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特性的算法。 3.目的3：证明QEM在受控临床环境中的可行性。 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用于诊断和手术的许多领域。能够轻松捕获气道、窦腔等的完整几何形状，将为许多其他科学和临床研究打开大门。例如，可以进行重复成像以跟踪治疗效果，并进行目前依赖于更昂贵的CT或MR成像的办公室诊断程序。 项目叙述：拟议的项目将开发从内窥镜数据计算准确解剖模型的方法。它将专门应用于一个高度相关的临床问题：幼儿气道阻塞的大小。然而，对解剖结构进行简单、安全的尺寸测量的可能性在许多医学领域具有广泛的相关性。

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.