Literature DB >> 25860862

Characteristic correlations of the structure-function relationship in different glaucomatous disc types.

Kazuko Omodaka1, Naoko Takada, Takuhiro Yamaguchi, Hidetoshi Takahashi, Makoto Araie, Toru Nakazawa.   

Abstract

PURPOSE: To investigate the influence of the optic disc type on the overall and regional correlation between structure and function in open angle glaucoma (OAG).
METHODS: We divided 144 eyes of 144 patients with OAG into four groups according to Nicolela et al.'s classification of optic disc type: focal ischemic (FI), myopic glaucomatous (MY), senile sclerotic (SS), and generalized enlargement (GE). We measured the circumpapillary retinal nerve fiber layer thickness (cpRNFLT) with the 3D OCT-2000 and the mean deviation (MD) with the Humphrey Field Analyzer in each group and determined the influence of the disc type on these parameters with the Spearman rank correlation.
RESULTS: We found that cpRNFLT and MD were significantly correlated in the MY (r = 0.61, P < 0.001), GE (r = 0.62, P < 0.001), and SS groups (r = 0.52, P = 0.002), but not in the FI group (r = 0.25, P = 0.130). The region of the optic disc with the highest correlation coefficient between structure and function differed according to the disc type.
CONCLUSIONS: The correlation between cpRNFLT and MD varied according to the optic disc morphology in OAG. This suggests that different disc types have characteristic regional variations in the correlation between structure and function. The disc type should therefore be considered in investigations of the correlation between structure and function in glaucoma.

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Year:  2015        PMID: 25860862     DOI: 10.1007/s10384-015-0379-z

Source DB:  PubMed          Journal:  Jpn J Ophthalmol        ISSN: 0021-5155            Impact factor:   2.447


  35 in total

1.  Monitoring glaucoma progression.

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Journal:  Prog Brain Res       Date:  2008       Impact factor: 2.453

2.  Retinal nerve fiber layer analysis: relationship between optical coherence tomography and red-free photography.

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3.  Use of sequential Heidelberg retina tomograph images to identify changes at the optic disc in ocular hypertensive patients at risk of developing glaucoma.

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4.  Comparison of the GDx VCC scanning laser polarimeter, HRT II confocal scanning laser ophthalmoscope, and stratus OCT optical coherence tomograph for the detection of glaucoma.

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Journal:  Arch Ophthalmol       Date:  2004-06

5.  Clinically detectable nerve fiber atrophy precedes the onset of glaucomatous field loss.

Authors:  A Sommer; J Katz; H A Quigley; N R Miller; A L Robin; R C Richter; K A Witt
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6.  Heidelberg retina tomograph parameters of the optic disc in eyes with progressive retinal nerve fibre layer defects.

Authors:  Ville Saarela; P Juhani Airaksinen
Journal:  Acta Ophthalmol       Date:  2008-09       Impact factor: 3.761

7.  Structure-function relationship between the octopus perimeter cluster mean sensitivity and sector retinal nerve fiber layer thickness measured with the RTVue optical coherence tomography and scanning laser polarimetry.

Authors:  Farzaneh Naghizadeh; Anita Garas; Péter Vargha; Gábor Holló
Journal:  J Glaucoma       Date:  2014-01       Impact factor: 2.503

8.  An evaluation of optic disc and nerve fiber layer examinations in monitoring progression of early glaucoma damage.

Authors:  H A Quigley; J Katz; R J Derick; D Gilbert; A Sommer
Journal:  Ophthalmology       Date:  1992-01       Impact factor: 12.079

9.  Various glaucomatous optic nerve appearances: clinical correlations.

Authors:  M T Nicolela; S M Drance
Journal:  Ophthalmology       Date:  1996-04       Impact factor: 12.079

10.  Significant correlations between optic nerve head microcirculation and visual field defects and nerve fiber layer loss in glaucoma patients with myopic glaucomatous disk.

Authors:  Yu Yokoyama; Naoko Aizawa; Naoki Chiba; Kazuko Omodaka; Masahiko Nakamura; Takaaki Otomo; Shunji Yokokura; Nobuo Fuse; Toru Nakazawa
Journal:  Clin Ophthalmol       Date:  2011-12-07
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  8 in total

Review 1.  [Secondary diseases in high myopia].

Authors:  F Ziemssen; W Lagrèze; B Voykov
Journal:  Ophthalmologe       Date:  2017-01       Impact factor: 1.059

2.  Correlation Between Enlargement of Retinal Nerve Fiber Defect Angle in En Face Imaging and Visual Field Progression.

Authors:  Naoki Takahashi; Kazuko Omodaka; Arata Nakazawa; Tsutomu Kikawa; Takahiro Ninomiya; Naoki Kiyota; Satoru Tsuda; Noriko Himori; Masahiro Akiba; Toru Nakazawa
Journal:  Transl Vis Sci Technol       Date:  2022-06-01       Impact factor: 3.048

3.  Rates of Retinal Nerve Fiber Layer Thinning in Distinct Glaucomatous Optic Disc Phenotypes in Early Glaucoma.

Authors:  Ryan Caezar C David; Sasan Moghimi; Eren Ekici; Jiun L Do; Huiyuan Hou; James A Proudfoot; Alireza Kamalipour; Takashi Nishida; Christopher A Girkin; Jeffrey M Liebmann; Robert N Weinreb
Journal:  Am J Ophthalmol       Date:  2021-04-25       Impact factor: 5.488

4.  OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients.

Authors:  Naoko Takada; Kazuko Omodaka; Tsutomu Kikawa; Airi Takagi; Akiko Matsumoto; Yu Yokoyama; Yukihiro Shiga; Kazuichi Maruyama; Hidetoshi Takahashi; Masahiro Akiba; Toru Nakazawa
Journal:  PLoS One       Date:  2016-08-24       Impact factor: 3.240

5.  Classification of optic disc shape in glaucoma using machine learning based on quantified ocular parameters.

Authors:  Kazuko Omodaka; Guangzhou An; Satoru Tsuda; Yukihiro Shiga; Naoko Takada; Tsutomu Kikawa; Hidetoshi Takahashi; Hideo Yokota; Masahiro Akiba; Toru Nakazawa
Journal:  PLoS One       Date:  2017-12-19       Impact factor: 3.240

6.  Glaucoma Diagnosis with Machine Learning Based on Optical Coherence Tomography and Color Fundus Images.

Authors:  Guangzhou An; Kazuko Omodaka; Kazuki Hashimoto; Satoru Tsuda; Yukihiro Shiga; Naoko Takada; Tsutomu Kikawa; Hideo Yokota; Masahiro Akiba; Toru Nakazawa
Journal:  J Healthc Eng       Date:  2019-02-18       Impact factor: 2.682

7.  Hierarchical deep learning models using transfer learning for disease detection and classification based on small number of medical images.

Authors:  Guangzhou An; Masahiro Akiba; Kazuko Omodaka; Toru Nakazawa; Hideo Yokota
Journal:  Sci Rep       Date:  2021-03-01       Impact factor: 4.379

8.  Comparison of Machine-Learning Classification Models for Glaucoma Management.

Authors:  Guangzhou An; Kazuko Omodaka; Satoru Tsuda; Yukihiro Shiga; Naoko Takada; Tsutomu Kikawa; Toru Nakazawa; Hideo Yokota; Masahiro Akiba
Journal:  J Healthc Eng       Date:  2018-06-19       Impact factor: 2.682

  8 in total

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