Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
Med Phys. 2012 Feb;39(2):933-50. doi: 10.1118/1.3673773.
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.
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.
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.
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.
二尖瓣的精确 3D 建模有可能提高我们对瓣膜形态的理解，特别是在二尖瓣反流（MR）的情况下。为此，作者开发了一种用户初始化算法，用于从经食管 3D 超声（3D US）图像数据中重建瓣膜几何形状。
对 14 例 MR 从微量到重度的患者进行经食管 3D US 图像的半自动图像分析。二尖瓣在收缩中期的图像分析有两个阶段：用户初始化分割和使用连续中轴表示（cm-rep）的 3D 可变形建模。半自动分割首先从 3D US 数据生成的 2D 投影图像中用户识别瓣位置。然后使用水平集方法在 3D 中自动分割二尖瓣叶。其次，通过贝叶斯优化将双叶瓣可变形中轴模型拟合到二值瓣分割。所得的 cm-rep 提供了二尖瓣的可视化重建，从中自动得出了瓣膜形态的局部测量值。从拟合的 cm-rep 中提取的特征包括瓣环面积、瓣环周长、瓣环高度、房室沟宽度、隔侧长度、总遮篷容积和前遮篷容积百分比。将这些测量值与专家手动追踪获得的测量值进行比较。反流口面积（ROA）测量值与 MR 严重程度的定性评估进行比较。cm-rep 对瓣膜形状表示的准确性通过拟合的 cm-rep 与其目标分割之间的 Dice 重叠来评估。
半自动图像分析得出的形态特征和解剖 ROA 与 3D US 图像数据的手动追踪以及对不同 MR 严重程度患者的临床放射学定性评估一致。拟合的 cm-rep 准确地捕捉到了瓣膜形状，并在不同 MR 严重程度的患者中表现出了瓣膜形态的个体差异。当使用不同的 cm-rep 模板初始化模型拟合时，Dice 重叠和形态测量的变化最小。
本研究证明了使用可变形中轴建模来使用经食管 3D US 进行二尖瓣几何形状的半自动 3D 重建。所提出的算法提供了二尖瓣叶的参数几何表示，可以用于评估临床超声图像中的瓣膜形态。
