Video-mosaicing of reflectance confocal images for examination of extended areas of skin in vivo

With cellular-level resolution comparable to histology, reflectance confocal microscopy (RCM) imaging is a promising approach both for diagnosis of skin cancer in vivo with high sensitivity and specificity1,2, and for pre- and intra-operative detection of cancer margins to guide treatment.3–5 However, RCM images are limited to a field of view (FOV) of 1 mm -by- 1 mm, much smaller than the typical size of skin lesions. Many diagnostic features cannot be reliably identified in such small FOVs. Moreover, clinicians rely heavily on visual context of the surrounding tissue to perform diagnoses. Thus, larger areas must be imaged to evaluate cellular and morphologic features with high accuracy and repeatability. To address this concern, mosaicing approaches, which increase the FOV by acquiring a matrix of adjacent images and stitching them together to display a large area, have been developed for confocal microscopy6. In standard mosaicing, images are acquired while mechanically translating the microscope lens relative to the skin along pre-determined linear (straight-line) trajectories. This approach was implemented in the RCM scanner used in the cited studies1–5, and, in fact, is now routinely used on patients. However, the mechanics of translation limit speed and coverage to pre-selected small rectangular-shaped areas, currently up to 8 mm-by-8 mm, imaged in ~4.5 minutes. Coverage and speed could be increased, of course, with larger and faster mechanical translation systems, but would add significant size and cost to RCM scanners, and would certainly not be practical for routine use on patients. Miniaturized confocal endoscopes have been developed that allow the operator flexible control for imaging in vivo, without the constraints of mechanical translation7,8 Similar flexibility is now possible for imaging skin with the recent advent of smaller and miniaturized handheld confocal microscopes9,10,11. The operator manually moves the microscope along a desired curvilinear trajectory, with the lens gently pressed against the tissue, while acquiring a video sequence of images. Video microscopy enables the operator to choose the trajectory in real-time, allowing adaptive coverage of areas that can be selected in real-time during acquisition. Thus, an area with any shape and size may be rapidly imaged, without the previous constraints of straight-line trajectories and rectangular coverage. However, observing a video, by itself, merely as a time-sequence of small FOVs, does not readily provide the necessary visual context from the surrounding tissue. In this paper, we present results from an approach for computationally transforming such videos into mosaics that display the entire imaged area. Algorithms for video-mosaicing have been developed in the fields of computational photography and computer vision12, and their use has previously been reported for confocal endoscopic imaging7,8.We report here application of video-mosaicing to reflectance confocal images of human skin lesions and margins in vivo.