Incorporating Prior Knowledge of Surgical Devices in CBCT-Guided Interventions

描述(申请人提供)：锥束CT(CBCT)在影像引导程序中的应用越来越多，包括脊柱融合和全髋关节置换术等矫形外科手术。由于术中成像特别可能包括断层扫描视野内的外科设备(例如，工具、植入物或假体)，并且这些组件具有已知的组成、大小和形状，因此存在在重建方法中集成此类信息的独特机会。研究人员开发了一种新的基于模型的方法，称为已知分量重建(KCR)，它利用已知的衰减分布，对由已知分量(具有未知姿势)组成的对象进行建模，以及未知的背景解剖结构。这是一种将先验对象知识结合到重建框架中的新范例，在该框架中，该算法联合估计背景衰减和记录已知分量。这项技术特别适合于丢失数据和低信噪比的情况，这在金属设备的介入性成像中很常见。传统的重建方法容易出现严重的金属条纹伪影(特别是在低剂量下)，在设备近端的图像质量最差，这往往正是对图像质量要求最高的感兴趣区域(例如，可视化附近的关键结构或植入物的界面)。初步研究表明，九广铁路基本上能够消除与金属有关的伪影，并允许将物体可视化，直到工具或植入物的边界。我们假设，一个基于广义KCR框架的集成系统和已知设备组件库可以在外科植入物附近提供无伪影重建，促进介入CBCT中高精度的设备放置和剂量减少协议。提出了以下具体目标：1)为九铁建立一个概括性的分析框架。研究包括开发用于介入性CBCT的完整物理模型，利用九广铁路独特的组件知识集成，以及采用可变形转换模型以允许广泛类别的不确切已知组件(例如，脊柱融合中的固定杆在实施特定脊柱弯曲的过程中变形)。2.)为九广铁路建立一个综合系统。这一发展包括从CAD文件或物理设备生成高保真的参数化元件模型的方法、计算效率高的算法和硬件，以及根据九广铁路联合计算的元件注册来评估装置布局中的几何精度的工具。3.)在临床前实验和模拟程序中评估九广铁路。工作包括一系列系统的实验，使用具有多个组件的幻影和身体，可变形的结构，以及强调噪音、剂量、物体大小和植入物大小限制的条件。结果指标将包括定量成像性能指标、医生评分和登记误差分析，以及这些指标与最小剂量获取方案的关系。

DESCRIPTION (provided by applicant): Cone-beam CT (CBCT) is finding increased use in image-guided procedures, including orthopaedic surgeries such as spine fusion and total hip arthroplasty. Since intraoperative imaging is particularly likely to include surgical devices (e.g. tools, implants, or prostheses) within the tomographic field-of-view and these components have known composition, size, and shape, there is a unique opportunity to integrate such information in a re- construction approach. The investigators have developed a novel model-based approach called known- component reconstruction (KCR) that leverages known attenuation distributions, modeling an object comprised of known components (with unknown pose), as well as an unknown background anatomy. This is a new paradigm for incorporating prior object knowledge into a reconstruction framework where the algorithm jointly estimates both the background attenuation and the registers the known components. The technique is particularly well-suited to missing data and low signal-to-noise, as is common in interventional imaging due to metallic devices. Traditional reconstruction approaches are prone to severe metal streak artifacts (especially at low doses) with the poorest image quality in locations proximal to the device, which is often precisely the area of interest with the greatest image quality demands (e.g. visualization of nearby critical structures or interfaces of implants). Preliminary studies demonstrate that KCR is able to essentially eliminate artifacts associated with metal and allows for visualization of the object right up to the boundary of the tool or implant. We hypothesize tha an integrated system based on a generalized KCR framework with a library of known device components can provide artifact-free reconstructions in proximity to surgical implants, facilitatin high- precision device placement and dose reduction protocols in interventional CBCT. The following Specific Aims are proposed: 1.) Build a generalized analytic framework for KCR. Studies include development of a complete physics model for interventional CBCT, leveraging KCR's unique integration of component know- ledge, and adopting a deformable transformation model to allow for a broad class of inexactly known components (e.g., fixation rods in spine fusions that are deformed during a procedure to enforce a specific spine curvature). 2.) Create an integrated system for KCR. The development includes methods for generation of high- fidelity parameterized component models from CAD files or physical devices, computationally efficient algorithms and hardware, and tools for assessment of geometric accuracy in device placement from the component registration computed jointly in KCR. 3.) Evaluate KCR in pre-clinical experiments and simulated procedures. Work includes a systematic series of experiments using phantoms and cadavers with multiple components, deformable constructs, and conditions that stress the limits of noise, dose, object size, and implant size. Outcome measures will include quantitative imaging performance metrics, physician scoring, and registration error analysis, as well as the relation of these metrics to minimum-dose acquisition protocols.