The Influence of Intersubject Variability in Ocular Anatomical Variables on the Mapping of Retinal Locations to the Retinal Nerve Fiber Layer and Optic Nerve Head

Lamparter, Julia; Russell, Richard A.; Zhu, Haogang; Asaoka, Ryo; Yamashita, Takehiro; Ho, Tuan A.; Garway-Heath, David F.

doi:10.1167/iovs.13-11902

Cited by 71 publications

(67 citation statements)

References 34 publications

(41 reference statements)

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“…Our findings concerning the overall variability and the influence of refraction and ONH inclination on the RNFB trajectories agreed well with other studies 1,8,10 and have been discussed in detail before. 6,7 To the best of our knowledge, the significant influence of the retinal blood vessel topography on the RNFB trajectories has not been addressed before.…”

Section: Discussionsupporting

confidence: 92%

“…8,9 The influence of anatomical variables including refraction, axial length, optic disc position, and optic disc dimensions on the RNFB trajectories has been studied as well. 7,8,10 Although significant factors were identified, the sources of the variability of the RNFB trajectories are not fully understood.It has been reported that the vascular and neuronal systems share many similarities. The blood vessels and nerves tend to develop in relative proximity, throughout the body of any species in general and in the primate retina in particular.…”

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confidence: 99%

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Influence of the Retinal Blood Vessel Topography on the Variability of the Retinal Nerve Fiber Bundle Trajectories in the Human Retina

Qiu

Schiefer

Nevalainen

et al. 2015

Invest. Ophthalmol. Vis. Sci.

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Citation: Qiu K, Schiefer J, Nevalainen J, Schiefer U, Jansonius NM. Influence of the retinal blood vessel topography on the variability of the retinal nerve fiber bundle trajectories in the human retina. Invest Ophthalmol Vis Sci. 2015;56:6320-6325. DOI:10.1167/ iovs.15-17450 PURPOSE. To determine the relationship between the retinal blood vessel topography and the retinal nerve fiber bundle (RNFB) trajectories in the human retina. METHODS.A previously collected dataset comprising 28 fundus photographs with traced RNFB trajectories was used. For all traced trajectories, the departure from our previously published RNFB trajectory model was calculated. Subsequently, we calculated, per subject, a ''mean departure'' for the superior-temporal and inferior-temporal region. We measured angles between a line connecting the optic nerve head (ONH) center and the fovea and lines connecting the ONH center and the crossings of the superior and inferior temporal arteries (arterial angles) and veins (venous angles) with circles around the ONH; circle radii were 25%, 50%, and 100% of the ONH center-to-fovea distance. We also defined two angles based on the location of the first arteriovenous crossing. Multiple linear regression analysis was performed with mean departure as dependent variable and refraction, ONH inclination, and vessel angles as independent variables.RESULTS. In the superior-temporal region, refraction (P ¼ 0.017), ONH inclination (P ¼ 0.021), and the arterial angle corresponding to the middle circle (P < 0.001) were significant determinants of mean departure. Explained variance was 0.54. In the inferior-temporal region, the arterial angle corresponding to the largest circle (P ¼ 0.002) was significant. Explained variance was 0.32. CONCLUSIONS.The retinal blood vessel topography explains a significant part of the RNFB trajectory variability but only if (1) the vessel topography is assessed at an appropriate distance from the ONH and (2) the superior and inferior hemifield are addressed independently.Keywords: retinal nerve fiber layer, retinal vessels, retinal vasculature G laucoma is one of the important causes of blindness, with irreversible damage to retinal ganglion cells, the retinal nerve fiber layer (RNFL), and the optic nerve as its pathological features. The detection of changes in these structures is part of the diagnostic armamentarium in glaucoma; a detailed anatomical knowledge of especially the retinal nerve fiber bundle (RNFB) trajectories is helpful to integrate information from each structure and to topographically correlate it with visual field data.In 2000, Garway-Heath et al. 1 reported nerve fiber bundle trajectories based on fundus photographs. Later, models based on axonal growth and maps based on the correspondence between optical coherence tomography thickness measurements and visual field data were published. [2][3][4][5] We developed a mathematical model describing the RNFB trajectories with their intersubject variability, based on fundus photographs. 6,7 A considerable variabili...

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Section: Discussionsupporting

confidence: 92%

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confidence: 99%

Influence of the Retinal Blood Vessel Topography on the Variability of the Retinal Nerve Fiber Bundle Trajectories in the Human Retina

Qiu

Schiefer

Nevalainen

et al. 2015

Invest. Ophthalmol. Vis. Sci.

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“…Third, there are many factors which affect the trajectories of the retinal artery (e.g., the size, shape, and torsion of the eye). 24,25 The effect of the eye torsion was minimized by using a second-degree polynomial approach and by using the fovea-optic disc axis as a vertical landmark in measuring the retinal artery trajectory and NFLD angles. In addition, the magnification effect should not have altered angular measurements and trajectories.…”

Section: Discussionmentioning

confidence: 99%

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

Yamashita

Nitta

Sonoda

et al. 2015

Invest. Ophthalmol. Vis. Sci.

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“…It has been shown previously that several ocular parameters may have significant influence on the layout of the RNFL. 27 Although many of those parameters are currently not available for our study, it would be possible to include information on an individual eye's distance and angle between fovea and ONH into the model we used. Another factor to consider when comparing structural and functional measurements near the fovea is the displacement of ganglion cells.…”

Section: Discussionmentioning

confidence: 99%

Optimizing Structure–Function Relationship by Maximizing Correspondence Between Glaucomatous Visual Fields and Mathematical Retinal Nerve Fiber Models

Erler

Bryan

Eilers

et al. 2014

Invest. Ophthalmol. Vis. Sci.

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Citation: Erler NS, Bryan SR, Eilers PHC, Lesaffre EMEH, Lemij HG, Vermeer KA. Optimizing structure-function relationship by maximizing correspondence between glaucomatous visual fields and mathematical retinal nerve fiber models. Invest Ophthalmol Vis Sci. 2014;55:235055: -235755: . DOI:10.1167 PURPOSE. To introduce a method to optimize structural retinal nerve fiber layer (RNFL) models based on glaucomatous visual field data and to show how such an optimized model can be used to reduce noise in visual fields while probably preserving clinically important features. METHODS.Correlation coefficients between age-adjusted deviation values of pairs of visual field test locations were calculated from 103 visual fields of eyes with moderate glaucomatous damage. Distances between those test locations were defined for various parameters of a mathematical RNFL model. Then, the correspondence between the structural and functional data was defined by the spread, or variance, of the correlation coefficients for all distances. The model parameters that minimized this spread constituted the optimized model. To reduce noise in visual fields, the optimized model was used to smooth visual field data according to the RNFL's structure. The resulting fields were compared with visual fields that were smoothed based on the regular testing grid. RESULTS.The optimal parameters for the RNFL model reduced the variance of the correlation coefficients by 78% and were well within the range of parameters previously determined from fundus photographs. Smoothing the visual fields based on the optimized RNFL model strongly reduced noise while keeping important features.CONCLUSIONS. Mathematic RNFL models can be optimized based on visual field data, resulting in a strong structure-function relationship. Taking the RNFL's shape, as defined by such an optimized model, into account when smoothing visual fields results in better noise reduction while preserving important details.

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The Influence of Intersubject Variability in Ocular Anatomical Variables on the Mapping of Retinal Locations to the Retinal Nerve Fiber Layer and Optic Nerve Head

Cited by 71 publications

References 34 publications

Influence of the Retinal Blood Vessel Topography on the Variability of the Retinal Nerve Fiber Bundle Trajectories in the Human Retina

Influence of the Retinal Blood Vessel Topography on the Variability of the Retinal Nerve Fiber Bundle Trajectories in the Human Retina

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

Optimizing Structure–Function Relationship by Maximizing Correspondence Between Glaucomatous Visual Fields and Mathematical Retinal Nerve Fiber Models

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