Relationship Between Location of Retinal Nerve Fiber Layer Defect and Curvature of Retinal Artery Trajectory in Eyes With Normal Tension Glaucoma

Yamashita, Takehiro; Nitta, Koji; Sonoda, Shozo; Sugiyama, Kazuhisa; Sakamoto, Taiji

doi:10.1167/iovs.15-17119

Cited by 11 publications

(11 citation statements)

References 24 publications

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“…This finding is not only important to understand retinal structure in eyes with myopia, but also to understand the development of structural changes in eyes with glaucoma. In myopic early-stage glaucomatous eyes, RNFL defects often appear at the paracentral area, and we have shown that RNFL defects locate closer to the papillo-macular bundle as AL increases 31 . This finding has also been reported in an independent study 32 .…”

Section: Discussionmentioning

confidence: 61%

The relationship between retinal nerve fibre layer thickness profiles and CorvisST tonometry measured biomechanical properties in young healthy subjects

Murata

Nakakura²,

Nakao

et al. 2017

Sci Rep

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We previously reported that a shallow circumpapillary retinal nerve fiber layer (cpRNFL) peak angle as measured by optical coherence tomography (OCT) suggests the temporal retina is stretched around the optic disc from the papillo-macular bundle (Yamashita T et al. Investigative Ophthalmol Vis Sci 2013). The purpose of the current study was to investigate the relationship between CorvisST tonometry (CST) corneal measurements, axial length (AL) and the change in OCT-measured cpRNFL peak angle, in young healthy subjects. OCT and CST measurements were carried out in 97 eyes of 97 young healthy volunteers. The relationship between cpRNFL peak angle and 12 CST parameters, adjusted for AL, was investigated using linear modelling. The mean ± standard deviation cpRNFL peak angle of the 97 healthy volunteers was 130.6 ± 25.4 (range: 77.8 to 207.0) degrees. The optimal linear model to explain cpRNFL peak angle (chosen from 216 different models) included three CST variables related to the speed and size of energy absorption (namely, A1 time, A1 length and A2 time), in addition to AL. In eyes with longer AL and shorter energy absorption in CST measurement, temporal retina is stretched around the optic disc from the papillo-macular bundle, as suggested by a shallow cpRNFL peak angle.

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Section: Discussionmentioning

confidence: 61%

The relationship between retinal nerve fibre layer thickness profiles and CorvisST tonometry measured biomechanical properties in young healthy subjects

Murata

Nakakura²,

Nakao

et al. 2017

Sci Rep

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“…The fovea is located between these two peaks/margins, so the retina stretches more horizontally and/or vertically in some eyes due to tension on the fovea, resulting in a greater distance between these two peaks where the retinal vessel trajectories are measured. This results in a thinner retina . The x and y coordinates of the marked points were automatically detected in MATLAB and were converted to new coordinates by shifting the origin to the center of the optic disk.…”

Section: Methodsmentioning

confidence: 99%

Examination of retinal vascular trajectory in schizophrenia and bipolar disorder

Appaji

Nagendra

Chako

et al. 2019

Psychiatry Clin Neurosci

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Aim: Evidence suggests microvascular dysfunction (wider retinal venules and narrower arterioles) in schizophrenia (SCZ) and bipolar disorder (BD). The vascular development is synchronous with neuronal development in the retina and brain. The retinal vessel trajectory is related to retinal nerve fiber layer thinning and cerebrovascular abnormalities in SCZ and BD and has not yet been examined. Hence, in this study we examined the retinal vascular trajectory in SCZ and BD in comparison with healthy volunteers (HV).Methods: Retinal images were acquired from 100 HV, SCZ patients, and BD patients, respectively, with a non-mydriatic fundus camera. Images were quantified to obtain the retinal arterial and venous trajectories using a validated, semiautomated algorithm. Analysis of covariance and regression analyses were conducted to examine group differences. A supervised machine-learning ensemble of bagged-trees method was used for automated classification of trajectory values.Results: There was a significant difference among groups in both the retinal venous trajectory (HV: 0.17 AE 0.08; SCZ: 0.25 AE 0.17; BD: 0.27 AE 0.20; P < 0.001) and the arterial trajectory (HV: 0.34 AE 0.15; SCZ: 0.29 AE 0.10; BD: 0.29 AE 0.11; P = 0.003) even after adjusting for age and sex (P < 0.001). On post-hoc analysis, the SCZ and BD groups differed from the HV on retinal venous and arterial trajectories, but there was no difference between SCZ and BD patients. The machine learning showed an accuracy of 86% and 73% for classifying HV versus SCZ and BD, respectively.Conclusion: Smaller trajectories of retinal arteries indicate wider and flatter curves in SCZ and BD. Considering the relation between retinal/cerebral vasculatures and retinal nerve fiber layer thinness, the retinal vascular trajectory is a potential marker for SCZ and BD. As a relatively affordable investigation, retinal fundus photography should be further explored in SCZ and BD as a potential screening measure.

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“…The curvature of the RA trajectory was quantified by fitting it to a second-degree polynomial equation as described in detail elsewhere. [18][19][20] The RA and the center of the optic discs were identified in the CFPs. The fovea-to-disc axis in the CFPs was rotated to a vertical position.…”

Section: Measurement Of Retinal Artery Trajectorymentioning

confidence: 99%

“…We began this project to determine whether we can approach the conclusion of AI using only known parameters with a theme to distinguish the sex from ocular CFPs. Thus far, there have been numerous studies using various parameters of the ocular function and biometry, [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] and the parameters used in this study were derived from them. If these factors are useful for distinguishing the sex, we may be able to understand the conclusions by Poplin et al 5 We found that a combination of known clinical parameters in the CFPs are useful in identifying the sex of the individual whose CFPs were being analyzed.…”

Section: Introductionmentioning

confidence: 99%

Factors in Color Fundus Photographs That Can Be Used by Humans to Determine Sex of Individuals

Yamashita

Asaoka

Terasaki

et al. 2020

Trans. Vis. Sci. Tech.

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Purpose: Artificial intelligence (AI) can identify the sex of an individual from color fundus photographs (CFPs). However, the mechanism(s) involved in this identification has not been determined. This study was conducted to determine the information in CFPs that can be used to determine the sex of an individual. Methods:Prospective observational cross-sectional study of 112 eyes of 112 healthy volunteers. The following characteristics of CFPs were analyzed: the color of peripapillary area expressed by the mean values of red, green, and blue intensities, and the tessellation expressed by the tessellation fundus index (TFI). The optic disc ovality ratio, papillomacular angle, retinal artery trajectory, and retinal vessel angles were also quantified. Their differences between the sexes were assessed by Mann-Whitney U tests. Regularized binomial logistic regression was used to select the decisive factors. In addition, its discriminative performance was evaluated through the leave-one-out cross validation. Results:The mean age of 76 men and 36 women was 25.8 years. The regularized binomial logistic regression delivered the optimal model for sex selected variables of peripapillary temporal green and blue intensities, temporal TFI, supratemporal TFI, optic disc ovality ratio, artery trajectory, and supratemporal retinal artery angle. With this approach, the discrimination accuracy rate was 77.9%. Conclusions:Human-assessed characteristics of CFPs are useful in investigating the new theme proposed by AI, the sex of an individual.Translational Relevance: This is the first report to approach the thinking process of AI by humans and can be a new approach to medical AI research.

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Relationship Between Location of Retinal Nerve Fiber Layer Defect and Curvature of Retinal Artery Trajectory in Eyes With Normal Tension Glaucoma

Cited by 11 publications

References 24 publications

The relationship between retinal nerve fibre layer thickness profiles and CorvisST tonometry measured biomechanical properties in young healthy subjects

The relationship between retinal nerve fibre layer thickness profiles and CorvisST tonometry measured biomechanical properties in young healthy subjects

Examination of retinal vascular trajectory in schizophrenia and bipolar disorder

Factors in Color Fundus Photographs That Can Be Used by Humans to Determine Sex of Individuals

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