Author Response: Outer Retinal Bands.

Letters Author Response: Outer Retinal Bands We thank Richard F. Spaide 1 for his careful reading of our article, 2 and we welcome this opportunity to address some of his concerns. Given the complexity of the relevant concepts, we have chosen to present a summary of our findings followed by a list of Spaide’s relevant criticisms (in italic) along with our rebuttals. In the interest of brevity, we have chosen not to respond to criticisms that do not bear on the scientific impact of our article (e.g., the availability of raw, linear data in the Spectralis [Heidelberg Engineering, Heidelberg, Germany] software). In cross-sectional optical coherence tomography (OCT) images (B-scans) of the retina, several bands are seen in the outer retina. Our article sought to investigate one of these bands—‘‘band 2’’—which originates from a structure confined to photoreceptor cells. We aimed to quantitatively characterize this structure by resolving it within single cones and measuring its average thickness and its position with respect to the adjacent bands 1 and 3. We hypothesized that the outer retinal band 2 would be thinner than the inner segment ellipsoid (16– 20 lm) and that it would lie near the inner and outer segment (IS/OS) junction, approximately half way between the external limiting membrane (ELM) and cone outer segment tips (COST). We imaged four healthy eyes at two retinal locations (foveal and parafoveal) using adaptive optics (AO)-OCT, which permits three-dimensional resolution of cone photoreceptors. 3 From the resulting eight volumetric images, we segmented 9593 cones and measured the two parameters relevant to our hypotheses. We segmented each cone in three dimensions, using its lateral extent in en face projection and the locations of bands 1 and 3. Bands 1 and 3 were identified by identifying the A-lines comprising each cone and averaging them together to form the cone’s longitudinal reflectance profile (LRP). By quantifying cellular morphology on each of the 9593 cones, we found that band 2 has a thickness of 4.7 lm, corresponding to an object thickness of 3.5 lm or less, and that it lies approximately equidistant from the ELM and COST. These findings are consistent with the interpretation that band 2 arises from the junction between IS and OS, but inconsistent with the recent hypothesis 4 that the band arises from the IS ellipsoid. Spaide’s letter 1 raised seven significant criticisms of our methods and our interpretation of results. These are listed below, in order of perceived relative importance, along with our responses. Criticism 1: The mismatch between images of IS/OS and COST suggests that the cones were not segmented correctly. Our response: To measure cellular morphology, bands 1, 2, and 3 must be readily identifiable in the cone’s LRP. Spaide points out that the IS/OS and COST images in our figure 2 are not identical, and that these differences manifest in the transverse locations of peaks (his fig. 1) and mismatch between their en face projections (his fig. 2). Moreover, he points out that the ELM is not visible in our figure 5. He reasons that if we cannot identify structures in the images, we cannot provide accurate morphological measurements. First and most importantly, the AO-OCT B-scan to which he refers was a conceptual illustration, not data fit for further analysis. It is a single, unaveraged, unprocessed B-scan. It represents a transverse cut through the cones, but not necessarily through their centers, as they form a somewhat irregular mosaic that is not aligned to the imaging source’s scanned path across the retina. In short, each cone in the B- scan is represented by between one and five A-lines, significantly smaller than the 22 A-line volumetric image of each cone we used to compute an LRP. Worse, the image has lost four bits of dynamic range for publication. In the article, we described figure 5 as providing context for our results, and specifically not necessary for the scientific conclusions of the article, and that is because qualitative observations based on a single B-scan are of limited usefulness. Spaide does not describe precisely how he generated his figures 1 and 2. Given the diversity of methods for generating such images, we would prefer to deal with this question quantitatively. The Pearson correlation of the two original images in our figure 2 is 0.504 (see cross-correlation in attached Figure). Considering that this coefficient is computed over 19,370 pixels, the resulting P value is less than 10 -6 , which is consistent with the conclusion that the images originate from corresponding features. Due to bit-depth compression and smoothing, the publication images are even more highly correlated. Spaide is right that the images of IS/OS and COST are not identical, and this observation is confirmed by the fact that the Pearson correlation is less than 1.0. There are (at least) three possible reasons for the mismatch. First, it is known that the cone IS and OS diameter differ throughout most of the retina. There is now evidence that these differences affect the transverse waveguide modes supported by these respective segments, which can cause the IS/OS and COST reflections to differ, slightly in the fovea and dramatically in the periphery (Liu Z, Kocaoglu OP, Turner TL, Miller DT, manuscript submitted, 2015). 5 Second, because our main goal was characterization of band 2, focus of the system was optimized for that band, which may have contributed to differences in their appearance as well. Third, like all images, these have some random, uncorrelated noise. For any given cone, these factors may have caused differences in the lateral distribution of light at each layer, which explains the imperfect correspondence shown in his figure 2. The high statistical correspondence between the images (P < 10 - 6 ) suggests that although the noise and transverse modes may not be aligned, the bulk of the features in the images are. The low visibility of ELM in the B-scan is due, as Spaide recognized, to the linear scaling of the image, limited dynamic range of print images, and absence of any lateral integration of signal. After averaging a sufficient number of A- lines from each cone, the ELM was always identifiable in our experiment, in spite of its dark appearance in single B-scans. The ELM is comparably dark in Spaide’s own linearly scaled Spectralis B-scans, 4 even with the latter instrument’s greater optical blur, averaging, and postprocessing. Nevertheless, we are confident that his use of it as a morphological landmark was also justified. Criticism 2: Speckle and waveguiding made image analysis difficult. Our response: Spaide argues that averaging produces a smooth topography that ‘‘more accurately represents’’ the structure of interest. He is correct that averaging adjacent B- scans can reduce speckle contrast and increase signal, but this is true only if the extent of averaging is smaller than the structure of interest and larger than the speckle. This principle guided the design of our morphological analysis, in which we averaged all the A-lines originating from each cone (i.e., the structure of interest). We specifically avoided averaging Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc. www.iovs.org j ISSN: 1552-5783 Downloaded From: http://iovs.arvojournals.org/pdfaccess.ashx?url=/data/Journals/IOVS/933739/ on 02/10/2016