Validation of Optical Coherence Tomography Retinal Segmentation in Neurodegenerative Disease

This is the authors' abstract. We don't add key points for this paper.

PURPOSE: This study assessed agreement between an automated spectral-domain optical coherence tomography (SD-OCT) retinal segmentation software and manually corrected segmentation to validate its use in a prospective clinical study of neurodegenerative diseases (NDD). METHODS: The sample comprised 30 subjects with NDD, including vascular cognitive impairment, frontotemporal dementia, Parkinson's disease, and Alzheimer's disease. Macular SD-OCT scans were acquired and segmented using Heidelberg Spectralis. For the central foveal B scan of each eye, eight segmentation lines were examined to determine the proportion of each line that the software erroneously delineated. Errors in four lines were manually corrected in all B scans spanning a 6-mm circle centered on the foveola. Mean volume and thickness measurements for four retinal layers (total retina, retinal nerve fiber layer [RNFL], inner retinal layers, and outer retinal layers) were obtained before and after correction. Mean thickness differences ranged from -1.855 to 1.859 μm. CONCLUSIONS: Despite occasional small errors in software-generated retinal sublayer segmentation, agreement was excellent between software-derived and observer-corrected mean volume and thickness sublayer measurements. TRANSLATIONAL RELEVANCE: Automated SD-OCT segmentation software generates valid measurements of retinal layer volume and thickness in NDD subjects, thereby avoiding the need to manually correct nonobvious delineation errors.