Literature DB >> 28146240

Diagnostic Power of Lamina Cribrosa Depth and Curvature in Glaucoma.

Seung Hyen Lee1, Tae-Woo Kim1, Eun Ji Lee1, Michaël J A Girard2, Jean Martial Mari3.   

Abstract

Purpose: To compare the capability of the lamina cribrosa depth (LCD) and lamina cribrosa (LC) curvature in discriminating between eyes with primary open-angle glaucoma (POAG) and healthy eyes.
Methods: Seventy-seven eyes of 77 patients with POAG and 77 eyes of 77 healthy subjects who were matched for age, sex, and axial length were included. The LCD and lamina cribrosa curvature index (LCCI) were measured in B-scan images obtained using swept-source optical coherence tomography at seven locations spaced equidistantly across the vertical optic disc diameter. The mean values of the measurements made at seven points of the LC were defined as the average LCD and LCCI.
Results: The average LCD (527.0 ± 116.4 vs. 413.3 ± 80.4 μm, P < 0.001) and average LCCI (10.97 ± 2.59 vs. 6.81 ± 1.43, P < 0.001) were significantly larger in POAG eyes than in the matched healthy subjects (all seven locations, P < 0.001). The area under the receiver operating characteristic curve (AUC) was significantly larger for the LCCI than the LCD (0.921 vs. 0.784, P < 0.001). The intraocular pressure was positively associated with average LCD and LCCI in healthy subjects (P = 0.021 and P < 0.001, respectively) and POAG patients (P = 0.011 and P < 0.001, respectively). Male sex was associated with larger average LCCI (P = 0.013) and LCD (P = 0.008) in POAG. Conclusions: The LCCI had significantly better discriminating capability between POAG and healthy eyes than LCD. This finding suggests that the LCCI may serve better than the LCD for improved glaucoma management.

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Year:  2017        PMID: 28146240     DOI: 10.1167/iovs.16-20802

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  22 in total

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2.  Deep learning based noise reduction method for automatic 3D segmentation of the anterior of lamina cribrosa in optical coherence tomography volumetric scans.

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3.  Nonlinear distortion correction for posterior eye segment optical coherence tomography with application to tree shrews.

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4.  Predictive Modeling of Long-Term Glaucoma Progression Based on Initial Ophthalmic Data and Optic Nerve Head Characteristics.

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5.  Histologic validation of optical coherence tomography-based three-dimensional morphometric measurements of the human optic nerve head: Methodology and preliminary results.

Authors:  Massimo A Fazio; Stuart K Gardiner; Luigi Bruno; Meredith Hubbard; Gianfranco Bianco; Udayakumar Karuppanan; Jihee Kim; Mustapha El Hamdaoui; Rafael Grytz; J Crawford Downs; Christopher A Girkin
Journal:  Exp Eye Res       Date:  2021-01-28       Impact factor: 3.467

6.  The influence of different intraocular pressure on lamina cribrosa parameters in glaucoma and the relation clinical implication.

Authors:  Jian Wu; Yifan Du; Jiaying Li; Xiaowei Fan; Caixia Lin; Ningli Wang
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7.  Deep Learning for Glaucoma Detection and Identification of Novel Diagnostic Areas in Diverse Real-World Datasets.

Authors:  Erfan Noury; Suria S Mannil; Robert T Chang; An Ran Ran; Carol Y Cheung; Suman S Thapa; Harsha L Rao; Srilakshmi Dasari; Mohammed Riyazuddin; Dolly Chang; Sriharsha Nagaraj; Clement C Tham; Reza Zadeh
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8.  Thin minimal rim width at Bruch's membrane opening is associated with glaucomatous paracentral visual field loss.

Authors:  Elise V Taniguchi; Eleftherios I Paschalis; Dejiao Li; Kouros Nouri-Mahdavi; Stacey C Brauner; Scott H Greenstein; Angela V Turalba; Janey L Wiggs; Louis R Pasquale; Lucy Q Shen
Journal:  Clin Ophthalmol       Date:  2017-12-08

9.  Characterization of Prelaminar Wedge-Shaped Defects in Primary Open-Angle Glaucoma.

Authors:  Carolina A Chiou; Mengyu Wang; Elise V Taniguchi; Rafaella Nascimento E Silva; Anna Khoroshilov; Dian Li; Haobing Wang; Scott H Greenstein; Stacey C Brauner; Angela V Turalba; Louis R Pasquale; Lucy Q Shen
Journal:  Curr Eye Res       Date:  2020-10-27       Impact factor: 2.555

10.  Lamina Cribrosa Morphology Predicts Progressive Retinal Nerve Fiber Layer Loss In Eyes with Suspected Glaucoma.

Authors:  Jeong-Ah Kim; Tae-Woo Kim; Robert N Weinreb; Eun Ji Lee; Michaël J A Girard; Jean Martial Mari
Journal:  Sci Rep       Date:  2018-01-15       Impact factor: 4.379

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