Assessing the validity of a cross-platform retinal image segmentation tool in normal and diseased retina

• Published in: Scientific reports 2021-11, Vol.11 (1), p.21784-21784, Article 21784
• Main Authors: Alex, Varsha, Motevasseli, Tahmineh, Freeman, William R., Jayamon, Jefy A., Bartsch, Dirk-Uwe G., Borooah, Shyamanga
• Format: Article
• Language: English
• Subjects: 692/308/409; 692/308/575; Computer programs; Eye; Humanities and Social Sciences; Humans; Image processing; Image Processing, Computer-Assisted - methods; multidisciplinary; Proprietary; Reproducibility of Results; Retina; Retina - anatomy & histology; Retina - diagnostic imaging; Retina - pathology; Retinal Diseases - diagnosis; Retinal Diseases - diagnostic imaging; Retinal Diseases - pathology; Science; Science (multidisciplinary); Segmentation; Software; Tomography, Optical Coherence - methods
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-01105-9

Comparing automated retinal layer segmentation using proprietary software (Heidelberg Spectralis HRA + OCT) and cross-platform Optical Coherence Tomography (OCT) segmentation software (Orion). Image segmentations of normal and diseased (iAMD, DME) eyes were performed using both softwares and then compared to the ‘gold standard’ of manual segmentation. A qualitative assessment and quantitative (layer volume) comparison of segmentations were performed. Segmented images from the two softwares were graded by two masked graders and in cases with difference, a senior retina specialist made a final independent decisive grading. Cross-platform software was significantly better than the proprietary software in the segmentation of NFL and INL layers in Normal eyes. It generated significantly better segmentation only for NFL in iAMD and for INL and OPL layers in DME eyes. In normal eyes, all retinal layer volumes calculated by the two softwares were moderate-strongly correlated except OUTLY. In iAMD eyes, GCIPL, INL, ONL, INLY, TRV layer volumes were moderate-strongly correlated between softwares. In eyes with DME, all layer volume values were moderate-strongly correlated between softwares. Cross-platform software can be used reliably in research settings to study the retinal layers as it compares well against manual segmentation and the commonly used proprietary software for both normal and diseased eyes.