Automated peroperative assessment of stents apposition from OCT pullbacks.

This study's aim was to control the stents apposition by automatically analyzing endovascular optical coherence tomography (OCT) sequences. Lumen is detected using threshold, morphological and gradient operators to run a Dijkstra algorithm. Wrong detection tagged by the user and caused by bifurcation, struts'presence, thrombotic lesions or dissections can be corrected using a morphing algorithm. Struts are also segmented by computing symmetrical and morphological operators. Euclidian distance between detected struts and wall artery initializes a stent's complete distance map and missing data are interpolated with thin-plate spline functions. Rejection of detected outliers, regularization of parameters by generalized cross-validation and using the one-side cyclic property of the map also optimize accuracy. Several indices computed from the map provide quantitative values of malapposition. Algorithm was run on four in-vivo OCT sequences including different incomplete stent apposition's cases. Comparison with manual expert measurements validates the segmentation׳s accuracy and shows an almost perfect concordance of automated results.

In vivo OCT coronary imaging augmented with stent reendothelialization score.

The aim of this study is to automatically assess reendothelialization of stents at an accuracy of down to a few microns by analyzing endovascular optical coherence tomography (OCT) sequences. Vessel wall and struts are automatically detected and complete distance map is then computed from sparse distances measured between wall and struts by thin-plate spline (TPS) interpolation. A reendothelialization score is mapped onto the geometry of the coronary artery segment. Accuracy and robustness are increased by taking into account the inhomogeneity of datapoints and integrating in the same framework orthogonalized forward selection of support points, optimal selection of regularization parameters by generalized cross-validation (GCV) and rejection of detection outliers. The comparison against manual expert measurements for a phantom study and 12 in vivo stents demonstrates no significant discordance with variability of the order of the strut thickness.