Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound
Development of a semi-automated method for mitral valve modeling with medial axis representation using 3D ultrasound
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DOI：
10.1118/1.3673773
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发表时间：
2012-02-01
期刊：
影响因子：
3.8
通讯作者：
Sehgal, Chandra M.
中科院分区：
文献类型：
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作者：
Pouch, Alison M.;Yushkevich, Paul A.;Sehgal, Chandra M.
目的：精确的二尖瓣三维建模有可能提高我们对二尖瓣形态的理解，特别是在二尖瓣反流（MR）的情况下。为了实现这一目标，作者开发了一种用户初始化的算法，用于从经食管3D超声（3D US）图像数据中重建瓣膜几何形状。方法：对14例经食道磁共振3D US图像进行半自动化图像分析。二尖瓣收缩期图像分析分为两个阶段：用户初始化分割和三维变形建模，具有连续的内侧表示（cm-rep）。半自动化分割开始于用户从3D美国数据生成的2D投影图像中识别阀门位置。然后使用水平集方法对二尖瓣小叶进行三维自动分割。其次，采用贝叶斯优化方法拟合双小块可变形介质模型进行二瓣膜分割；由此产生的cm-rep提供了二尖瓣的视觉重建，从中自动导出瓣膜形态的局部测量。从拟合的cm-rep中提取的特征包括环面积、环周长、环高度、节间宽度、隔侧长度、总帐篷体积和前帐篷体积百分比。将这些测量结果与专家手工跟踪得到的结果进行比较。将反流孔面积（ROA）测量值与MR严重程度的定性评估进行比较。根据拟合的cm-rep与目标分割之间的Dice重叠度评估cm-rep阀门形状表示的准确性。结果：半自动化图像分析得出的形态学特征和解剖ROA与3D US图像数据的手动追踪和临床放射学对MR严重程度的定性评估一致。拟合的厘米代表准确地捕获了瓣膜形状，并显示了不同程度MR严重程度的受试者之间瓣膜形态的患者特异性差异。当使用不同的cm-rep模板初始化模型拟合时，观察到Dice重叠和形态学测量的最小变化。结论：本研究展示了使用可变形的内侧模型，通过经食管3D US对二尖瓣几何形状进行半自动3D重建。该算法提供了二尖瓣叶的参数化几何表示，可用于评估临床超声图像中的二尖瓣形态。(C) 2012年美国医学物理学家协会。(DOI: 10.1118/1.3673773)
Purpose: Precise 3D modeling of the mitral valve has the potential to improve our understanding of valve morphology, particularly in the setting of mitral regurgitation (MR). Toward this goal, the authors have developed a user-initialized algorithm for reconstructing valve geometry from transesophageal 3D ultrasound (3D US) image data.Methods: Semi-automated image analysis was performed on transesophageal 3D US images obtained from 14 subjects with MR ranging from trace to severe. Image analysis of the mitral valve at midsystole had two stages: user-initialized segmentation and 3D deformable modeling with continuous medial representation (cm-rep). Semi-automated segmentation began with user-identification of valve location in 2D projection images generated from 3D US data. The mitral leaflets were then automatically segmented in 3D using the level set method. Second, a bileaflet deformable medial model was fitted to the binary valve segmentation by Bayesian optimization. The resulting cm-rep provided a visual reconstruction of the mitral valve, from which localized measurements of valve morphology were automatically derived. The features extracted from the fitted cm-rep included annular area, annular circumference, annular height, intercommissural width, septolateral length, total tenting volume, and percent anterior tenting volume. These measurements were compared to those obtained by expert manual tracing. Regurgitant orifice area (ROA) measurements were compared to qualitative assessments of MR severity. The accuracy of valve shape representation with cm-rep was evaluated in terms of the Dice overlap between the fitted cm-rep and its target segmentation.Results: The morphological features and anatomic ROA derived from semi-automated image analysis were consistent with manual tracing of 3D US image data and with qualitative assessments of MR severity made on clinical radiology. The fitted cm-reps accurately captured valve shape and demonstrated patient-specific differences in valve morphology among subjects with varying degrees of MR severity. Minimal variation in the Dice overlap and morphological measurements was observed when different cm-rep templates were used to initialize model fitting.Conclusions: This study demonstrates the use of deformable medial modeling for semi-automated 3D reconstruction of mitral valve geometry using transesophageal 3D US. The proposed algorithm provides a parametric geometrical representation of the mitral leaflets, which can be used to evaluate valve morphology in clinical ultrasound images. (C) 2012 American Association of Physicists in Medicine. [DOI: 10.1118/1.3673773]