Literature DB >> 25563763

Quantitative comparison of macular segmentation performance using identical retinal regions across multiple spectral-domain optical coherence tomography instruments.

Sebastian M Waldstein1, Bianca S Gerendas1, Alessio Montuoro1, Christian Simader1, Ursula Schmidt-Erfurth1.   

Abstract

PURPOSE: Comparison of optical coherence tomography (OCT) segmentation performance regarding technical accuracy and clinical relevance.
METHODS: 29 eyes were imaged prospectively with Spectralis (Sp), Cirrus (Ci), 3D-OCT 2000 (3D) and RS-3000 (RS) OCTs. Raw data were evaluated in validated custom software. A 1 mm diameter subfield, centred on the fovea, was investigated to compare identical regions for each case. Segmentation errors were corrected on each B-scan enclosed in this subfield. Proportions of wrongly segmented A-scans were noted for inner and outer retinal boundaries. Centre point thickness (CPT) and central macular thickness (CMT) were compared before and after correction.
RESULTS: Segmentation errors occurred in 77% and affected on average 29% of A-scans, resulting in mean differences of 24/13 µm (CPT/CMT). The incidence of segmentation errors was 48% (Sp), 79% (Ci), 86% (3D) and 93% (RS), p<0.001. Mean proportions of A-scans with wrong outer retinal boundary were 30% (Sp), 9% (Ci), 23% (3D) and 10% (RS), p=0.006; proportions for the inner retinal boundary were 11% (Sp), 12% (Ci), 6% (3D) and 21% (RS), p=0.034. Mean deviations in CPT/CMT were 41/28 µm (Sp), 17/11 µm (Ci), 30/13 µm (3D) and 18/8 µm (RS), p=0.409/0.477.
CONCLUSIONS: By comparison of identical regions, substantial differences were detected between the tested OCT devices regarding technical accuracy and clinical impact. Spectralis showed lowest error incidence but highest error impact. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Entities:  

Keywords:  Diagnostic tests/Investigation; Imaging; Macula; Retina

Mesh:

Year:  2015        PMID: 25563763     DOI: 10.1136/bjophthalmol-2014-305573

Source DB:  PubMed          Journal:  Br J Ophthalmol        ISSN: 0007-1161            Impact factor:   4.638


  10 in total

1.  Robust total retina thickness segmentation in optical coherence tomography images using convolutional neural networks.

Authors:  Freerk G Venhuizen; Bram van Ginneken; Bart Liefers; Mark J J P van Grinsven; Sascha Fauser; Carel Hoyng; Thomas Theelen; Clara I Sánchez
Journal:  Biomed Opt Express       Date:  2017-06-16       Impact factor: 3.732

2.  Directional Optical Coherence Tomography Reveals Reliable Outer Nuclear Layer Measurements.

Authors:  Kevin K Tong; Brandon J Lujan; Yixiu Zhou; Meng C Lin
Journal:  Optom Vis Sci       Date:  2016-07       Impact factor: 1.973

3.  Detection of Diabetic Macular Edema in Optical Coherence Tomography Image Using an Improved Level Set Algorithm.

Authors:  Zhenhua Wang; Wenping Zhang; Yanan Sun; Mudi Yao; Biao Yan
Journal:  Biomed Res Int       Date:  2020-04-30       Impact factor: 3.411

4.  Association of Macular Thickness With Age and Age-Related Macular Degeneration in the Carotenoids in Age-Related Eye Disease Study 2 (CAREDS2), An Ancillary Study of the Women's Health Initiative.

Authors:  Tyler Etheridge; Zhe Liu; Marine Nalbandyan; Spencer Cleland; Barbara A Blodi; Julie A Mares; Steven Bailey; Robert Wallace; Karen Gehrs; Lesley F Tinker; Ronald Gangnon; Amitha Domalpally
Journal:  Transl Vis Sci Technol       Date:  2021-02-05       Impact factor: 3.283

5.  Volume Averaging of Spectral-Domain Optical Coherence Tomography Impacts Retinal Segmentation in Children.

Authors:  Carmelina Trimboli-Heidler; Kelly Vogt; Robert A Avery
Journal:  Transl Vis Sci Technol       Date:  2016-08-18       Impact factor: 3.283

6.  Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease.

Authors:  Jing Wu; Sebastian M Waldstein; Alessio Montuoro; Bianca S Gerendas; Georg Langs; Ursula Schmidt-Erfurth
Journal:  Int J Biomed Imaging       Date:  2016-08-31

7.  Stepwise segmentation error correction in optical coherence tomography angiography images of patients with diabetic macular edema.

Authors:  Khalil Ghasemi Falavarjani; Reza Mirshahi; Shahriar Ghasemizadeh; Mahsa Sardarinia
Journal:  Ther Adv Ophthalmol       Date:  2020-08-27

8.  Physiological changes in retinal layers thicknesses measured with swept source optical coherence tomography.

Authors:  Elisa Viladés; Amaya Pérez-Del Palomar; José Cegoñino; Javier Obis; María Satue; Elvira Orduna; Luis E Pablo; Marta Ciprés; Elena Garcia-Martin
Journal:  PLoS One       Date:  2020-10-14       Impact factor: 3.240

9.  Validation and Clinical Applicability of Whole-Volume Automated Segmentation of Optical Coherence Tomography in Retinal Disease Using Deep Learning.

Authors:  Marc Wilson; Reena Chopra; Megan Z Wilson; Charlotte Cooper; Patricia MacWilliams; Yun Liu; Ellery Wulczyn; Daniela Florea; Cían O Hughes; Alan Karthikesalingam; Hagar Khalid; Sandra Vermeirsch; Luke Nicholson; Pearse A Keane; Konstantinos Balaskas; Christopher J Kelly
Journal:  JAMA Ophthalmol       Date:  2021-09-01       Impact factor: 7.389

10.  Quantitative Analysis of OCT for Neovascular Age-Related Macular Degeneration Using Deep Learning.

Authors:  Gabriella Moraes; Dun Jack Fu; Marc Wilson; Hagar Khalid; Siegfried K Wagner; Edward Korot; Daniel Ferraz; Livia Faes; Christopher J Kelly; Terry Spitz; Praveen J Patel; Konstantinos Balaskas; Tiarnan D L Keenan; Pearse A Keane; Reena Chopra
Journal:  Ophthalmology       Date:  2020-09-24       Impact factor: 12.079

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.