Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.
Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.
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DOI：
10.1007/978-3-319-66182-7_85
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发表时间：
2017-09
期刊：
影响因子：
--
通讯作者：
Yushkevich PA
中科院分区：
文献类型：
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作者：
Pouch AM;Aly AH;Lai EK;Yushkevich N;Stoffers RH;Gorman JH 4th;Cheung AT;Gorman JH 3rd;Gorman RC;Yushkevich PA
经食管超声心动图是术前评估缺血性二尖瓣反流 (IMR) 的二尖瓣的主要成像方式。虽然超声心动图对 IMR 二尖瓣的 3D 形态有众所周知的见解，例如环状扩张和小叶栓系，但人们对瓣膜动力学的量化如何为 IMR 的手术治疗提供信息或预测疾病的短期复发了解较少。作为填补这一知识空白的一步，我们提出了一种新颖的框架，用于实时 3D 超声心动图 (rt-3DE) 中二尖瓣的 4D 分割和几何建模。该框架集成了多图谱标签融合和基于模板的医学建模，以生成瓣膜动力学的定量描述模型。这项工作的新颖之处在于，通过使用分组标签融合和卡尔曼滤波，在分割和建模阶段强制执行 rt-3DE 分割的时间一致性。该算法根据 10 名患者的 rt-3DE 数据系列进行评估：其中 5 名患者二尖瓣形态正常，5 名患者患有严重 IMR。在这 10 个数据系列中，总共 207 个单独的 3DE 图像，每个 3DE 分割都针对手动跟踪进行了验证，并证明了分割之间的时间一致性。最终目标是生成瓣膜动力学的准确且一致的表示，可以直观和定量地提供对正常和病理瓣膜功能的洞察。
Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.