Developing cross-correlation as a method for microvessel imaging using clinical intravascular optical coherence tomography systems

Current clinical intravascular optical coherence tomography (IV-OCT) imaging systems have limited in-vivo flow imaging capability because of non-uniform catheter rotation and inadequate A-line scan density. Thus any flow-localisation method that seeks to identify sites of variation within the OCT image data-sets, whether that is in amplitude or phase, produces non-representative correlation (or variance) maps. In this study, both mean and the variation within a set of cross-correlation maps, for static OCT imaging was used to differentiate flow from nonflow regions. Variation was quantified by use of standard deviation. The advantage of this approach is its ability to image flow, even in the presence of motion artifacts. The ability of this technique to suppress noise and capture flow maps was demonstrated by imaging microflow in an ex-vivo porcine coronary artery model, by nailfold capillary imaging and in-vivo microvessel imaging from within the human coronary sinus.