Flow 3D+T Image Reconstruction Algorithms for Enhanced Cerebral Angiography

描述（由申请人提供）：这项R21研究旨在促进增强时空图像重建和分析，以实现更安全的神经血管手术。目前的术中脑血管造影图像是二维投影，需要操作员进行实时判读。在对时间敏感的环境中，操作员必须在2D X射线血管造影投影延时图像和复杂的血管内脉管系统3D结构之间进行心理映射，以便检测和定位介入期间可能出现的近端和远端血栓栓塞事件。在介入治疗（如颈动脉支架植入术或动脉瘤弹簧圈栓塞术）期间未能检测到部分或完全阻塞性凝块，可能导致下游脑组织血流中断，从而导致缺血性卒中。目前可用的术中断层扫描3D血管图不包含局部血流信息。期望的动态3D（3D+T）图像目前不可用，因为：1）对于可用的基于X射线的断层摄影单元而言，穿过脉管系统的血流太快，以及2）如果这种技术可用，则将使患者经受相当大的额外辐射暴露和造影剂注射。检测术中血栓栓塞事件将使他们的治疗能够避免中风。成功检测的可能性又将显著受益于以下能力：1）重建3D+T图像以从多个视角真实的时间估计和监测血流，2）获得节段血流和区域灌注的定量信息，以及3）检测和定位手术引起的时空变化和血流异常（例如，形成或栓塞的血栓或斑块碎片、内膜夹层或医源性血管痉挛），前提是这种能力及时发生，而无需额外的干扰人为干预或对患者的辐射暴露。为了解决这些问题，我们开发了（目标1）一个变分能量公式的同时平滑和分割，融合在一个统一的方式先验信息和测量数据。该方法同时在整个脉管系统上发展流动，并避免误差向下游传播和累积。接下来，将开发用于从血流模式中提取信息的分析方法，以检测和定位位于未直接成像区域的异常。将使用体模数据测试重建和异常检测以及定位算法，以证明处理模糊性的能力，然后使用来自包含模拟动态分支闭塞的血流模型的实验室数据。还将通过回顾性分析从既往手术中收集的3D和动态2D（2D+T）图像（具有已知不良事件，如血栓栓塞）来确认算法。这些结果将构成将该方法扩展到算法优化和前瞻性临床评价的基础。 公共卫生相关性：很难从二维X射线图像中解释我们体内的情况。它们并不总是很好地揭示体内血液流动的性质，也不总是很好地揭示血液凝块的可能发生。这项研究通过为放射科医生和外科医生提供血管中血流的三维图像来克服这一限制。这些图像更容易解释，更具揭示性，并将使医生能够检测，定位和采取行动纠正凝块等异常情况，以及进行更安全，更快速的手术，从而挽救生命和金钱。

DESCRIPTION (provided by applicant): This R21 research aims to contribute to enhanced spatiotemporal image reconstruction and analysis to achieve safer neurovascular procedures. Current intra-procedural cerebral angiographic images are two-dimensional projections, which require demanding real-time interpretation by the operator. In a time-sensitive environment, the operator must perform the mental mapping between 2D X-Ray angiographic projection time lapse images and the complex 3D structure of the cerebrovasculature in order, among other, to detect and locate proximal and distal thromboembolic events that may have arisen during an intervention. Failure to detect partially or completely obstructive clots during an intervention such as carotid stenting or aneurysm coiling, could result in blood flow interruption to downstream brain tissue leading to ischemic stroke. Currently available intra-procedural tomographic 3D vascular maps do not contain local blood flow information. Desired dynamic 3D (3D+T) images are currently unavailable because: 1) blood flow across the vasculature is too rapid for available X-ray based tomography units, and 2) such technology, were it available, would subject the patient to considerable additional radiation exposure and contrast agent injection. Detecting intra-procedural thromboembolic events would enable their treatment to avoid a stroke. The likelihood of successful detection in turn would significantly benefit from the ability to 1) reconstruct 3D+T images to estimate and monitor blood flow in real time from multiple perspectives, 2) obtain quantitative information of segmental blood flow and regional perfusion, and 3) detect and locate procedure-induced spatio-temporal changes and blood flow anomalies (e.g. formed or embolized thrombus or plaque fragment, intimal dissection, or iatrogenic vasospasm), provided that this capability occurs in a timely fashion without additional distracting human intervention or radiation exposure to the patient. To address these issues, we developed (Aim 1) a variational energy formulation for simultaneous smoothing and segmentation that fuses in a unified fashion prior information and measurement data. This approach simultaneously evolves flow over the entire vasculature and avoids propagation and accumulation of errors downstream. Next, analytical methods will be developed for extracting information from blood flow patterns to enable the detection and localization of abnormalities situated in areas not directly imaged. Both the reconstruction and anomaly detection and localization algorithms will be tested using phantom data to demonstrate the ability to deal with ambiguity, followed by benchtop data from the flow model incorporating simulated dynamic branch occlusions. The algorithms will also be validated by retrospective analysis of 3D and dynamic 2D (2D+T) images collected from previous procedures with known adverse events such as thromboembolism. The results will form the basis for expansion of this approach to algorithm optimization and prospective clinical evaluation. PUBLIC HEALTH RELEVANCE: It is difficult to interpret from two-dimensional X-ray images what is inside our body. They do not reveal always so well the nature of the blood flow inside the body, nor the possible occurrence of blood clots. This research overcomes this limitation by providing radiologists and surgeons with three-dimensional images of blood flow in vessels. These images are easier to interpret, more revealing and will make it possible for doctors to detect, locate and take actions to correct abnormalities such as clots, as well as perform a safer and faster surgery thus saving lives and money.