Thinning of the retinal nerve fiber layer (RNFL) is a recently discovered feature of Parkinson’s disease (PD). Its exact pathological mechanism is yet unknown. We aimed to determine whether morphological changes of the RNFL are limited to RNFL thinning or also comprise an altered internal structure of this layer. Therefore, we investigated RNFL thickness and applied the RNFL attenuation coefficient (RNFL-AC), a novel method derived from optical coherence tomography, in PD patients and healthy controls (HCs). In this pilot study, we included 20 PD patients and 20 HCs matched for age, sex, and ethnicity. An ophthalmologist investigated all participants thoroughly, and we acquired retinal images from both eyes of each participant with a Spectralis optical coherence tomography system. We obtained both the RNFL-AC and RNFL thickness from peripapillary RNFL scans for the entire RNFL, as well as for each quadrant separately. We found no significant differences in the average RNFL-AC or the RNFL-AC of the separate retinal quadrants between PD patients and the HC group. However, compared to the HC group, PD patients had a significantly thinner RNFL in the temporal retinal quadrant. RNFL thinning was found in the temporal quadrant in PD patients without a corresponding change in the RNFL-AC. These findings suggest a reduction in the number of RNFL axons (atrophy) without other major changes in the structural integrity of the remaining RNFL.

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The attenuation coefficient (AC) is a property related to the microstructure of tissue on a wavelength scale that can be estimated from optical coherence tomography (OCT) data. Since the OCT signal sensitivity is affected by the finite spectrometer/detector resolution called roll-off and the shape of the focused beam in the sample arm, ignoring these effects leads to severely biased estimates of AC. Previously, the signal intensity dependence on these factors has been modeled. In this paper, we study the dependence of the estimated AC on the beam-shape and focus depth experimentally. A method is presented to estimate the axial point spread function model parameters by fitting the OCT signal model for single scattered light to the averaged A-lines of multiple B-scans obtained from a homogeneous single-layer phantom. The estimated model parameters were used to compensate the signal for the axial point spread function and roll-off in order to obtain an accurate estimate of AC. The result shows a significant improvement in the accuracy of the estimation of AC after correcting for the shape of the OCT beam.@en

Optical coherence tomography (OCT) yields high-resolution, three-dimensional images of the retina. A better understanding of retinal nerve fiber bundle (RNFB) trajectories in combination with visual field data may be used for future diagnosis and monitoring of glaucoma. However, manual tracing of these bundles is a tedious task. In this work, we present an automatic technique to estimate the orientation of RNFBs from volumetric OCT scans. Our method consists of several steps, starting from automatic segmentation of the RNFL. Then, a stack of en face images around the posterior nerve fiber layer interface was extracted. The image showing the best visibility of RNFB trajectories was selected for further processing. After denoising the selected en face image, a semblance structure-oriented filter was applied to probe the strength of local linear structure in a discrete set of orientations creating an orientation space. Gaussian filtering along the orientation axis in this space is used to find the dominant orientation. Next, a confidence map was created to supplement the estimated orientation. This confidence map was used as pixel weight in normalized convolution to regularize the semblance filter response after which a new orientation estimate can be obtained. Finally, after several iterations an orientation field corresponding to the strongest local orientation was obtained. The RNFB orientations of six macular scans from three subjects were estimated. For all scans, visual inspection shows a good agreement between the estimated orientation fields and the RNFB trajectories in the en face images. Additionally, a good correlation between the orientation fields of two scans of the same subject was observed. Our method was also applied to a larger field of view around the macula. Manual tracing of the RNFB trajectories shows a good agreement with the automatically obtained streamlines obtained by fiber tracking.@en