Noël Peter B, Hoffmann Kenneth R, Kasodekar Snehal, Walczak Alan M, Schafer Sebastian
Toshiba Stroke Research Center, Department of Computer Science and Engineering, SUNY at Buffalo, Buffalo, New York 14214, USA.
Med Phys. 2006 Oct;33(10):3901-11. doi: 10.1118/1.2350705.
Stroke is one of the leading causes of death in the U.S. The treatment of stroke often involves vascular interventions in which devices are guided to the intervention site often through tortuous vessels based on two-dimensional (2-D) angiographic images. Three dimensional (3-D) vascular information may facilitate these procedures. Methods have been proposed for the self-calibrating determination of 3-D vessel trees from biplane and multiple plane images and the geometric relationships between the views (imaging geometries). For the biplane analysis, four or more corresponding points must be identified in the biplane images. For the multiple view technique, multiple vessels must be indicated and only the translation vectors relating the geometries are calculated. We have developed methods for the calculation of the 3-D vessel data and the full transformations relating the multiple views (rotations and translations) obtained during interventional procedures, and the technique does not require indication of corresponding points, but only the indication of a single vessel, e.g., the vessel of interest. Multiple projection views of vessel trees are obtained and transferred to the analysis computer. The vessel or vessels of interest are indicated by the user. Using the initial imaging geometry determined from the gantry information, 3-D vessel centerlines are calculated using the indicated centerlines in pairs of images. The imaging geometries are then iteratively adjusted and 3-D centerlines recalculated until the root-mean-square (rms) difference between the calculated 3-D centerlines is minimized. Simulations indicate that the 3-D centerlines can be accurately determined (to within 1 mm) even for errors in indication of the vessel endpoints as large as 5 mm. In phantom studies, the average rms difference between the pairwise calculated 3-D centerlines is approximately 7.5 mm prior to refinement (i.e., using the gantry information alone), whereas the average rms difference is usually below 1 mm after refinement. Accuracies and reliabilities of better than 1 mm were also determined by comparing centerlines determined using multiview and rotational angiography reconstruction and clinical data sets. These results indicate that the multiview approach will provide accurate and reliable 3-D centerlines for indicated vessel(s) without increasing the dose to the patient.
中风是美国主要的死因之一。中风的治疗通常涉及血管介入，在该过程中，设备常常基于二维血管造影图像，通过迂曲的血管被引导至介入部位。三维血管信息可能会有助于这些手术。已经有人提出了从双平面和多平面图像自校准确定三维血管树以及视图之间的几何关系（成像几何）的方法。对于双平面分析，必须在双平面图像中识别出四个或更多相应的点。对于多视图技术，必须指示多条血管，并且只计算与几何形状相关的平移向量。我们已经开发出了用于计算三维血管数据以及介入手术过程中获得的多视图之间的完全变换（旋转和平移）的方法，并且该技术不需要指示相应的点，而只需要指示一条血管，例如感兴趣的血管。获得血管树的多个投影视图并传输到分析计算机。用户指示感兴趣的一条或多条血管。利用从机架信息确定的初始成像几何，使用图像对中指示的中心线计算三维血管中心线。然后迭代调整成像几何并重新计算三维中心线，直到计算出的三维中心线之间的均方根（rms）差异最小化。模拟表明，即使血管端点指示误差高达5毫米，三维中心线也能被准确确定（误差在1毫米以内）。在体模研究中，在细化之前（即仅使用机架信息），成对计算的三维中心线之间的平均均方根差异约为7.5毫米，而细化之后平均均方根差异通常低于1毫米。通过比较使用多视图和旋转血管造影重建确定的中心线与临床数据集，还确定了优于1毫米的精度和可靠性。这些结果表明，多视图方法将为指示的血管提供准确可靠的三维中心线，而不会增加患者的辐射剂量。
