Thoraxcenter, Delft, The Netherlands.
Catheter Cardiovasc Interv. 2009 Dec 1;74(7):1058-65. doi: 10.1002/ccd.22125.
Quantitative analysis of intracoronary optical coherence tomography (OCT) image data (QOCT) is currently performed by a time-consuming manual contour tracing process in individual OCT images acquired during a pullback procedure (frame-based method). To get an efficient quantitative analysis process, we developed a fully automatic three-dimensional (3D) lumen contour detection method and evaluated the results against those derived by expert human observers.
The method was developed using Matlab (The Mathworks, Natick, MA). It incorporates a graphical user interface for contour display and, in the selected cases where this might be necessary, editing. OCT image data of 20 randomly selected patients, acquired with a commercially available system (Lightlab imaging, Westford, MA), were pulled from our OCT database for validation.
A total of 4,137 OCT images were analyzed. There was no statistically significant difference in mean lumen areas between the two methods (5.03 + or - 2.16 vs. 5.02 + or - 2.21 mm(2); P = 0.6, human vs. automated). Regression analysis showed a good correlation with an r value of 0.99. The method requires an average 2-5 sec calculation time per OCT image. In 3% of the detected contours an observer correction was necessary.
Fully automatic lumen contour detection in OCT images is feasible with only a select few contours showing an artifact (3%) that can be easily corrected. This QOCT method may be a valuable tool for future coronary imaging studies incorporating OCT.
目前，通过在拉回过程中获取的单个 OCT 图像中的耗时手动轮廓跟踪过程（基于帧的方法）来对冠状动脉光学相干断层扫描（OCT）图像数据（QOCT）进行定量分析。为了获得高效的定量分析过程，我们开发了一种全自动的三维（3D）管腔轮廓检测方法，并将结果与专家人类观察者得出的结果进行了比较。
该方法是使用 Matlab（Mathworks，Natick，MA）开发的。它包含一个轮廓显示的图形用户界面，并在必要时选择进行编辑。从我们的 OCT 数据库中提取了 20 名随机患者的 OCT 图像数据，这些数据是使用商业上可用的系统（Lightlab Imaging，Westford，MA）获得的，用于验证。
总共分析了 4137 个 OCT 图像。两种方法之间的平均管腔面积没有统计学差异（5.03 ± 2.16 与 5.02 ± 2.21mm2；P = 0.6，人类与自动化）。回归分析显示出良好的相关性，r 值为 0.99。该方法平均需要 2-5 秒的计算时间/OCT 图像。在 3％的检测轮廓中，观察者需要进行校正。
仅使用少数几个显示伪影（3％）的轮廓，可以实现 OCT 图像中的全自动管腔轮廓检测，并且可以轻松进行校正。这种 QOCT 方法可能是未来包含 OCT 的冠状动脉成像研究的有价值工具。
