Literature DB >> 26198809

Estimating Lead Time Gained by Optical Coherence Tomography in Detecting Glaucoma before Development of Visual Field Defects.

Tammy M Kuang1, Chunwei Zhang2, Linda M Zangwill3, Robert N Weinreb3, Felipe A Medeiros4.   

Abstract

PURPOSE: To estimate the diagnostic accuracy and lead time gained by retinal nerve fiber layer (RNFL) thickness measurements from optical coherence tomography (OCT) for detecting glaucoma before the development of visual field defects.
DESIGN: Observational cohort study. PARTICIPANTS: The study group included 75 eyes of 75 patients suspected of having glaucoma. These eyes had normal standard automated perimetry (SAP) at baseline and demonstrated repeatable (3 consecutive) abnormal tests during a median follow-up of 6.3 years. A control group of 75 eyes of 75 healthy subjects matched by age and number of OCT tests during follow-up was included.
METHODS: The RNFL thickness measurements were obtained at the time of development of the earliest SAP defect (time 0) and also at times -1, -2, -3, and so forth, corresponding to 1 year, 2 years, 3 years, and so forth, before the development of field loss. The OCT measurements at corresponding intervals were analyzed for controls. Time-dependent receiver operating characteristic (ROC) curves were used to evaluate diagnostic accuracy of OCT. MAIN OUTCOME MEASURES: Areas and sensitivities of ROC curve at fixed specificities at different times before development of field loss.
RESULTS: At the date of conversion to the earliest visual field defect (time 0), mean ± standard deviation average RNFL thickness was 75.0±9.8 μm in glaucomatous eyes and 90.6±8.0 μm for controls (P < 0.001). Significant differences were seen up to 8 years before development of visual field defects (86.3±8.2 μm vs. 91.4±7.6 μm, respectively; P = 0.021). The ROC curve areas decreased with increasing times before detection of field defects. At times 0, -4, and -8 years, ROC curve areas were 0.87, 0.77, and 0.65, respectively. At 95% specificity, up to 35% of eyes had abnormal average RNFL thickness 4 years before development of visual field loss and 19% of eyes had abnormal results 8 years before field loss.
CONCLUSIONS: Assessment of RNFL thickness with OCT was able to detect glaucomatous damage before the appearance of visual field defects on SAP. In many subjects, significantly large lead times were seen when applying OCT as an ancillary diagnostic tool.
Copyright © 2015 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 26198809      PMCID: PMC4581949          DOI: 10.1016/j.ophtha.2015.06.015

Source DB:  PubMed          Journal:  Ophthalmology        ISSN: 0161-6420            Impact factor:   12.079


  40 in total

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2.  Comparison of ability of time-domain and spectral-domain optical coherence tomography to detect diffuse retinal nerve fiber layer atrophy.

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3.  Comparison of glaucoma diagnostic Capabilities of Cirrus HD and Stratus optical coherence tomography.

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Authors:  Gadi Wollstein; Joel S Schuman; Lori L Price; Ali Aydin; Paul C Stark; Ellen Hertzmark; Edward Lai; Hiroshi Ishikawa; Cynthia Mattox; James G Fujimoto; Lelia A Paunescu
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5.  Estimating the rate of retinal ganglion cell loss in glaucoma.

Authors:  Felipe A Medeiros; Linda M Zangwill; Douglas R Anderson; Jeffrey M Liebmann; Christopher A Girkin; Ronald S Harwerth; Marie-Josée Fredette; Robert N Weinreb
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9.  Spectral domain-optical coherence tomography to detect localized retinal nerve fiber layer defects in glaucomatous eyes.

Authors:  Gianmarco Vizzeri; Madhusudhanan Balasubramanian; Christopher Bowd; Robert N Weinreb; Felipe A Medeiros; Linda M Zangwill
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10.  Likelihood ratios for glaucoma diagnosis using spectral-domain optical coherence tomography.

Authors:  Renato Lisboa; Kaweh Mansouri; Linda M Zangwill; Robert N Weinreb; Felipe A Medeiros
Journal:  Am J Ophthalmol       Date:  2013-08-20       Impact factor: 5.258

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  35 in total

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2.  From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs.

Authors:  Felipe A Medeiros; Alessandro A Jammal; Atalie C Thompson
Journal:  Ophthalmology       Date:  2018-12-20       Impact factor: 12.079

Review 3.  Parameters of ocular fundus on spectral-domain optical coherence tomography for glaucoma diagnosis.

Authors:  Yu-Lin Tao; Li-Ming Tao; Zheng-Xuan Jiang; He-Ting Liu; Kun Liang; Mo-Han Li; Xuan-Sheng Zhu; Yan-Lin Ren; Bing-Jie Cui
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4.  Improving the Feasibility of Glaucoma Clinical Trials Using Trend-Based Visual Field Progression Endpoints.

Authors:  Zhichao Wu; David P Crabb; Balwantray C Chauhan; Jonathan G Crowston; Felipe A Medeiros
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5.  Vertical Macular Asymmetry Measures Derived From SD-OCT for Detection of Early Glaucoma.

Authors:  Farideh Sharifipour; Esteban Morales; Ji Woong Lee; JoAnn Giaconi; Abdelmonem A Afifi; Fei Yu; Joseph Caprioli; Kouros Nouri-Mahdavi
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Review 6.  [Unmet research and developmental needs in ophthalmology : A consensus-based road map of the European Vision Institute for 2019-2025].

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7.  The Association Between Clinical Features Seen on Fundus Photographs and Glaucomatous Damage Detected on Visual Fields and Optical Coherence Tomography Scans.

Authors:  Paula A Alhadeff; Carlos G De Moraes; Monica Chen; Ali S Raza; Robert Ritch; Donald C Hood
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8.  Association between Intraocular Pressure and Rates of Retinal Nerve Fiber Layer Loss Measured by Optical Coherence Tomography.

Authors:  Alberto Diniz-Filho; Ricardo Y Abe; Linda M Zangwill; Carolina P B Gracitelli; Robert N Weinreb; Christopher A Girkin; Jeffrey M Liebmann; Felipe A Medeiros
Journal:  Ophthalmology       Date:  2016-08-20       Impact factor: 12.079

9.  Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness.

Authors:  Dian Li; Franziska G Rauscher; Eun Young Choi; Mengyu Wang; Neda Baniasadi; Kerstin Wirkner; Toralf Kirsten; Joachim Thiery; Christoph Engel; Markus Loeffler; Tobias Elze
Journal:  Ophthalmology       Date:  2019-09-25       Impact factor: 12.079

10.  Attention-Guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association Using Volumetric Images.

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