In Vivo Supervised Analysis of Stent Reendothelialization From Optical Coherence Tomography
In Vivo Supervised Analysis of Stent Reendothelialization From Optical Coherence Tomography
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DOI：
10.1109/tmi.2009.2037755
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发表时间：
2010-03-01
影响因子：
10.6
通讯作者：
Sarry, Laurent
中科院分区：
文献类型：
--
作者：
Kauffmann, Claude;Motreff, Pascal;Sarry, Laurent
本研究的目的是通过分析血管内光学相干断层扫描 (OCT) 序列，以交互方式评估支架的再内皮化，精度低至几微米。通过使用形态、梯度和对称算子与主动轮廓模型相结合，自动检测血管壁和支架支柱；发出警报要求用户监督由血栓性病变或夹层引起的一些极端不规则的几何形状。然后根据墙壁和支柱之间测量的稀疏距离计算完整的距离图。缺失值通过薄板样条 (TPS) 函数进行插值。通过考虑数据点的不均匀性并在同一框架中集成支持点的正交前向选择、通过广义交叉验证优化正则化参数选择以及拒绝检测异常值，可以提高准确性和鲁棒性。对模拟数据、模型采集和 11 个典型体内 OCT 序列进行验证。与手动专家测量的比较表明 OCT 分辨率数量级的偏差（小于 10 μm）和支柱宽度数量级的标准偏差（小于 150 μm）。
The aim of this study is to interactively assess reendothelialization of stents at an accuracy of down to a few micrometer by analyzing endovascular optical coherence tomography (OCT) sequences. Vessel wall and stent struts are automatically detected by using morphological, gradient, and symmetry operators coupled with active contour models; alerts are issued to ask for user supervision over some extreme irregular geometries caused by thrombotic lesions or dissections. A complete distance map is then computed from sparse distances measured between wall and struts. Missing values are interpolated by thin-plate spline (TPS) functions. Accuracy and robustness are increased by taking into account the inhomogeneity of data points and integrating in the same framework orthogonalized forward selection of support points, optimal selection of regularization parameters by generalized cross-validation, and rejection of detection outliers. Validation is performed on simulated data, phantom acquisitions and 11 typical in vivo OCT sequences. The comparison against manual expert measurements demonstrates a bias of the order of OCT resolution (less than 10 mu m) and a standard deviation of the order of the strut width (less than 150 mu m).