Fast Segmentation of the Left Atrial Appendage in 3-D Transesophageal Echocardiographic Images
Fast Segmentation of the Left Atrial Appendage in 3-D Transesophageal Echocardiographic Images
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DOI：
10.1109/tuffc.2018.2872816
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发表时间：
2018-12-01
影响因子：
3.6
通讯作者：
D'hooge, Jan
中科院分区：
文献类型：
--
作者：
Morais, Pedro;Queiros, Sandro;D'hooge, Jan
左心房附件（LAA）通常被描述为“我们最致命的附件”，被认为是非瓣膜性心房颤动患者血栓栓塞的主要来源。目前，LAA闭塞可以作为治疗这些患者的一种方法，通过经皮输送装置阻塞LAA。然而，正确的设备尺寸并不简单，需要人工分析过程中的图像。这种方法是次优的，需要时间，并且专家之间的差异很大，这可能导致冗长的过程和过多的操作。提出了一种用于经食管超声心动图（TEE）三维图像的半自动LAA分割技术。具体而言，该方法基于一种新的分割管道，通过两阶段策略对曲线盲端模型进行优化：1)使用全局项的快速轮廓演化和2)基于区域能量的轮廓细化。为了降低其计算成本，使其对实际干预更有吸引力，采用了b样条显式活动曲面框架。这种新方法在20例患者的临床数据库中进行了评估。由两名观察员进行的人工分析被用作基础事实。三维分割结果证实了该方法的准确性、对参数变化的鲁棒性和计算吸引力，分割LAA的平均精度约为0.9 mm，耗时约14 s。此外，还发现了与观察者间可变性相当的性能。最后，评估了分割模型的优点，同时半自动提取临床测量值以进行设备选择，与目前的实践相比，显示出相似的准确性，但具有更高的可重复性。总体而言，本文提出的分割方法显示了改进LAA闭塞规划的潜力，显示了其在正常临床实践中的附加价值。
Left atrial appendage (LAA) has been generally described as "our most lethal attachment," being considered the major source of thromboembolism in patients with nonvalvular atrial fibrillation. Currently, LAA occlusion can be offered as a treatment for these patients, obstructing the LAA through a percutaneously delivered device. Nevertheless, correct device sizing is not straightforward, requiring manual analysis of peri-procedural images. This approach is suboptimal, time demanding, and highly variable between experts, which can result in lengthy procedures and excess manipulations. In this paper, a semiautomatic LAA segmentation technique for 3-D transesophageal echocardiography (TEE) images is presented. Specifically, the proposed technique relies on a novel segmentation pipeline where a curvilinear blind-ended model is optimized through a double stage strategy: 1) fast contour evolution using global terms and 2) contour refinement based on regional energies. To reduce its computational cost, and thus make it more attractive to real interventions, the B-spline explicit active surface framework was used. This novel method was evaluated in a clinical database of 20 patients. Manual analysis performed by two observers was used as ground truth. The 3-D segmentation results corroborated the accuracy, robustness to the variation of the parameters, and computationally attractiveness of the proposed method, taking approximately 14 s to segment the LAA with an average accuracy of similar to 0.9 mm. Moreover, a performance comparable to the interobserver variability was found. Finally, the advantages of the segmented model were evaluated, while semiautomatically extracting the clinical measurements for device selection, showing a similar accuracy but with a higher reproducibility when compared to the current practice. Overall, the proposed segmentation method shows potential for an improved planning of LAA occlusion, demonstrating its added value for normal clinical practice.