Fully automatic three‐dimensional quantitative analysis of intracoronary optical coherence tomography

Objectives and background : 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. Methods : 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. Results : 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 ± 2.16 vs. 5.02 ± 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. Conclusion : 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. © 2009 Wiley‐Liss, Inc.