Comparison of Three Types of Images for the Detection of Retinal Nerve Fiber Layer Defects

Exploring retinal conditions through blue light reflectance imaging

Blue light reflectance (BLR) imaging offers a non-invasive, cost-effective method for evaluating retinal structures by analyzing the reflectance and absorption characteristics of the inner retinal layers. By leveraging blue light's interaction with retinal tissues, BLR enhances visualization beyond the retinal nerve fiber layer, improving detection of structures such as the outer plexiform layer and macular pigment. Its diagnostic utility has been demonstrated in distinct retinal conditions, including hyperreflectance in early macular telangiectasia, hyporeflectance in non-perfused areas indicative of ischemia, identification of pseudodrusen patterns (notably the ribbon type), and detection of peripheral retinal tears and degenerative retinoschisis in eyes with reduced retinal pigment epithelial pigmentation. Best practices for image acquisition and interpretation are discussed, emphasizing standardization to minimize variability. Common artifacts and mitigation strategies are also addressed, ensuring image reliability. BLR's clinical utility, limitations, and future research directions are highlighted, particularly its potential in automated image analysis and quantitative assessment. Different BLR acquisition methods, such as fundus photography, confocal scanning laser ophthalmoscopy, and broad line fundus imaging, are evaluated for their respective advantages and limitations. As research advances, BLR's integration into multimodal workflows is expected to improve early detection and precise monitoring of retinal diseases.

Blue light reflectance imaging in non-perfusion areas detection: insights from multimodal analysis

DESIGN

A retrospective, cross-sectional image analysis using a convenience sample.

SUBJECTS

Five cases selected based on the availability of comprehensive imaging data.

METHODS

This study involved a retrospective review of images from five cases, focusing on the use of retinal monochromatic blue light reflectance (BLR) imaging to detect non-perfusion areas. Two cases of sickle-cell retinopathy demonstrated peripheral retinal non-perfusion identified through widefield fluorescein angiography. Three other cases-one with branch retinal vein occlusion, one with branch retinal artery occlusion, and one presenting paracentral acute middle maculopathy showed focal macular non-perfusion detected by structural OCT and OCTA. The areas of nonperfused retinal tissue, confirmed by fluorescein angiography, OCT, and OCTA, were then correlated with findings from the BLR image. This correlation aimed to identify any potential associations between these imaging modalities.

MAIN OUTCOME MEASURES

Enhance understanding of the utilization of retinal monochromatic BLR images as a non-perfusion biomarker.

RESULTS

The perfusion defects identified through fluorescein angiography were qualitatively correlated with hypo-reflective regions observed in the BLR images. A notable correlation was also observed between the OCTA deep capillary plexus findings and the BLR images. Additionally, areas of retinal thinning identified on structural OCT thickness maps corresponded with the hypo-reflective regions in the BLR images. This indicates the potential of BLR in identifying non-perfused retinal areas.

CONCLUSIONS

This study reinforces the evidence, through OCT, OCTA, and angiographic correlation, that the BLR can effectively identify areas of retinal non-perfusion in a non-invasive manner. Further research is warranted to assess the method's sensitivity, specificity, and limitations. While the interaction of blue light with the retina, leading to specular reflections and scattering, is established, this research represents a pioneering effort in suggesting which specific retinal structures may be implicated in this phenomenon. This novel insight opens avenues for deeper exploration into the underlying mechanisms and potential clinical applications of utilizing the BLR imaging technique for assessing retinal vascular abnormalities.

Diagnostic assessment of glaucoma and non-glaucomatous optic neuropathies via optical texture analysis of the retinal nerve fibre layer

The clinical diagnostic evaluation of optic neuropathies relies on the analysis of the thickness of the retinal nerve fibre layer (RNFL) by optical coherence tomography (OCT). However, false positives and false negatives in the detection of RNFL abnormalities are common. Here we show that an algorithm integrating measurements of RNFL thickness and reflectance from standard wide-field OCT scans can be used to uncover the trajectories and optical texture of individual axonal fibre bundles in the retina and to discern distinctive patterns of loss of axonal fibre bundles in glaucoma, compressive optic neuropathy, optic neuritis and non-arteritic anterior ischaemic optic neuropathy. Such optical texture analysis can detect focal RNFL defects in early optic neuropathy, as well as residual axonal fibre bundles in end-stage optic neuropathy that were indiscernible by conventional OCT analysis and by red-free RNFL photography. In a diagnostic-performance study, optical texture analysis of the RNFL outperformed conventional OCT in the detection of glaucoma, as defined by visual-field testing or red-free photography. Our findings show that optical texture analysis of the RNFL for the detection of optic neuropathies is highly sensitive and specific.

Wedge Defects on Optical Coherence Tomography Angiography of the Peripapillary Retina in Glaucoma: Prevalence and Associated Clinical Factors

PRCIS

Among subjects with glaucoma, wedge-shaped defects on optical coherence tomography angiography (OCTA) were associated with disc hemorrhages (DH), paracentral visual field (VF) defects, increased cup-to-disc ratio (CDR), and thinner retinal nerve fiber layer (RNFL).

PURPOSE

To examine determinants of wedge defects on peripapillary OCTA in glaucoma.

MATERIALS AND METHODS

A total of 278 eyes of 186 subjects with mild to severe primary open-angle glaucoma underwent 6×6 spectral-domain OCTA imaging of the superficial peripapillary retina from 2016 to 2020 at an academic practice. Wedge defects were defined as focal microvasculature loss that extends outward from the optic nerve in an arcuate, wedge shape. Logistic regression models controlling for intereye correlation identified variables significantly associated with wedge defects. Eyes with profound microvasculature loss in both hemispheres were excluded. Candidate variables included: age, sex, race or ethnicity, diabetes, hypertension, follow-up duration, baseline untreated intraocular pressure, intraocular pressure at time of imaging, DH history, paracentral VF defects, CDR, central corneal thickness, spherical equivalent, VF mean deviation, RNFL thickness, and glaucoma stage.

RESULTS

Of 278 eyes, 126 (45.3%) had wedge defects in at least 1 hemisphere. In our multivariable logistic regression model, wedge defects were associated with DH history [odds ratio (OR): 3.19, 95% confidence interval (CI): 1.05-9.69, P=0.041], paracentral VF defects [OR: 4.38 (95% CI: 2.11-9.11), P<0.0001], larger CDR [OR: 1.27 (95% CI: 1.03-1.56), P=0.024, per 0.1 increase], and thinner RNFL [OR: 1.71 (95% CI: 1.25-2.34), P=0.0009, per 10 μm decrease].

CONCLUSION

DH history and paracentral VF defects were independently associated with wedge defects on OCTA, which was present in 45.3% of primary open-angle glaucoma patients. These findings may provide insight into glaucoma pathogenesis.

Sensitivity Detection of Retinal Nerve Fiber Layer in Glaucoma Based on High Level Semantic Image Fusion Algorithm

Glaucoma is currently recognized as a multifactorial, persistent and degenerative retinal disease. It mainly causes the loss of function and death of retinal ganglion cells in the optic nerve head area, and eventually leads to visual loss and blindness. Aiming at the segmentation and sensitivity detection of retinal nerve fiber layer (RNFL) in glaucoma, this paper mainly studies it based on high-level semantic image fusion algorithm. Firstly, the feature extracted by high-level semantic image fusion technology is used to train random forest classifier to segment retina to get rough position of the boundary of nerve fiber layer, then the first step of rough boundary is refined by boundary tracking algorithm to get the final result of retinal layer segmentation. In this algorithm, random forest classifier is used to find the boundary of single pixel width between layers of retina, and 12 features are used to train random forest classifier. Among them, relative gray feature and neighborhood feature can solve the problem of large segmentation error of uneven gray. By using high-level semantic image technology, the mean value and gradient features are extracted under multi-scale, and the relative gray difference features and neighborhood features are introduced, then the features are trained by random forest classifier. The trained classifier gives different labels to the unclassified features, and finally successfully segments the lower boundary of the retinal nerve fiber layer, which solves the sensitive segmentation and detection problem of the retinal nerve fiber layer with uneven pixel gray.

Novel utilisation of ultrawide-field fundus photography for detecting retinal nerve fibre layer defects in glaucomatous eyes

BACKGROUND/AIMS

Evaluation of the retinal nerve fibre layer (RNFL) is important for identifying glaucomatous damage. Ultrawide-field fundus photography (UWP) imaging is increasingly used in the ophthalmological field; however, it is unknown whether it can be used for detecting RNFL defects (RNFLDs). We investigated whether RNFLD can be detected with UWP images and compared the clinical effectiveness of three types of images for detecting RNFLD: conventional red-free RNFL photography (RFP), non-mydriatic UWP and digitally converted green separation of non-mydriatic UWP (G-UWP).

METHODS

Eyes with glaucoma or glaucoma suspect and normal control eyes meeting the eligibility criteria were consecutively enrolled from September 2019 to April 2020. Their conventional RFP, non-mydriatic UWP and G-UWP images were assessed for detecting RNFLD to evaluate the sensitivity and specificity for detecting RNFLD.

RESULTS

Three image sets of 196 participants (84 normal control, 25 glaucoma suspect and 87 glaucoma) were obtained. The sensitivity of G-UWP (94.6%; 95% CI 88.7 to 98.0) and RFP (92.9%; 95% CI 86.4 to 96.9) was higher than that of UWP (82.1%; 95% CI 73.8 to 88.7; p<0.05). The sensitivities of G-UWP and RFP are comparable. The specificity of G-UWP (78.6%; 95% CI 68.3 to 86.8) and UWP (75.0%; 95% CI 64.4 to 83.8) was comparable, but both were lower than that of RFP (98.8%; 95% CI 93.5 to 100.0; p<0.05).

CONCLUSION

Non-mydriatic UWP images can be used to detect RNFLD. Non-mydriatic G-UWP showed comparable sensitivity but lower specificity to conventional RFP. Non-mydriatic G-UWP could be used as a convenient and useful diagnostic tool for screening glaucoma in clinical settings.

Characteristics of diffuse retinal nerve fiber layer defects in red-free photographs as observed in optical coherence tomography en face images

Backgroud

To determine whether diffuse retinal nerve fiber layer (RNFL) defects, identified on red-free fundus photographs, could be identified on optical coherence tomography (OCT) en face structural images and to evaluate which factors are related to the different recognition patterns on en face images.

Methods

This retrospective, cross-sectional study included open-angle glaucoma eyes with diffuse RNFL defects in the inferior hemifield, identified in red-free photographs. The corresponding OCT en face structural images were divided into 3 groups: (1) no defect, (2) localized defect, and (3) diffuse defect. We compared the demographic and clinical ocular characteristics among the groups.

Results

A total of 209 eyes from 157 patients were included. The distribution of OCT en face images was: no defect, 25 eyes (11.96%); localized defect, 106 eyes (50.72%); diffuse defect, 78 eyes (37.32%). Logistic regression analysis revealed that eyes with greater mean deviation (P = 0.004) and thicker inferior RNFL (P = 0.008) would be included in the no defect and localized defect groups based on OCT en face images, rather than in the diffuse defect group.

Conclusion

Around half of diffuse RNFL defects identified in the red-free photographs appeared as localized defects in OCT en face images. Mild glaucomatous damage was related to no defect and localized defect groups, classified based on the OCT en face images, in eyes with diffuse photographic RNFL defects. OCT en face images may be helpful in further assessing diffuse RNFL defects seen in red-free photographs in eyes with open-angle glaucoma.

Capability of Ophthalmology Residents to Detect Glaucoma Using High-Dynamic-Range Concept versus Color Optic Disc Photography

BACKGROUND

Assessment of color disc photograph (C-DP) is affected by image quality, which decreases the ability to detect glaucoma. High-dynamic-range (HDR) imaging provides a greater range of luminosity. Therefore, the objective of this study was to evaluate the capability of ophthalmology residents to detect glaucoma using HDR-concept disc photography (HDR-DP) compared to C-DP.

DESIGN

Cross-sectional study.

METHODS

Twenty subjects were classified by 3 glaucoma specialists as either glaucoma, glaucoma suspect, or control. All C-DPs were converted to HDR-DPs and randomly presented and assessed by 10 first-year ophthalmology residents. Sensitivity and specificity of glaucoma detection were compared.

RESULTS

The mean ± SD of averaged retinal nerve fiber layer (RNFL) thickness was 74.0 ± 6.1 μm, 100.2 ± 9.6 μm, and 105.8 ± 17.2 μm for glaucoma, glaucoma suspect, and controls, respectively. The diagnostic sensitivity of HDR-DP was higher than that of C-DP (87% versus 68%, mean difference: 19.0, 95% CI: 4.91 to 33.1; p = 0.014). Regarding diagnostic specificity, HDR-DP and C-DP yielded 46% and 75% (mean difference: 29.0, 95% CI: 13.4 to 44.6; p = 0.002).

CONCLUSIONS

HDR-DP statistically increased diagnostic sensitivity but not specificity. HDR-DP may be a screening tool for nonexpert ophthalmologists.

Predictive Value of HRT Stereometric Parameters and Blue-on-Yellow Perimetry Global Indices in Glaucoma-suspected Subjects

OBJECTIVE

To determine subtle changes of Heidelberg retina tomography (HRT) stereometric parameters and blue-on-yellow (B/Y) perimetry global indices for the early diagnosis of glaucoma in suspected subjects.

PATIENTS AND METHODS

Cross-sectional data on 174 eyes of 87 subjects from a larger cohort, attending the Glaucoma Department of the "G. Gennimatas" General Hospital of Athens from January 2004 to February 2014, were used in the study. Subjects were assigned to 3 groups: (a) "normals" not requiring treatment throughout the study (group 1), (b) suspects who developed glaucoma and required treatment during the study (group 2), and (c) patients with incipient glaucoma (group 3). Specific HRT and B/Y perimetry variables were compared among the 3 groups.

RESULTS

Significant differences were established for the following HRT parameters: "reference height" differed significantly between groups 1 and 2 and groups 1 and 3; "cup shape measure" differed significantly between groups 1 and 2 and groups 2 and 3. B/Y perimetry global index "mean deviation" significantly distinguished group 2 from groups 1 and 3.

CONCLUSIONS

The results of the present study suggest the predictive value of the HRT stereometric parameters "reference height" and "cup shape measure" and of the B/Y perimetry global index "mean deviation" in glaucoma-suspected subjects; further corroboration through longitudinal studies is warranted.

Diagnostic Accuracy of Nonmydriatic Fundus Photography for the Detection of Glaucoma in Diabetic Patients

Purpose. To determine the diagnostic accuracy for glaucoma of a set of criteria with nonmydriatic monoscopic fundus photography (NMFP) in diabetics. Methods. Diabetics recruited from a screening program for diabetic retinopathy and diabetic glaucoma patients recruited from our glaucoma unit were included. Any patient with evidence of diabetic retinopathy was excluded. Diabetic patients had to have no visual field defects to be included as controls. Glaucoma patients had to have a glaucomatous field defect in at least one eye to be included. One NMFP was taken per eye for all subjects. These photographs were evaluated by two masked glaucoma specialists for the presence of the following: bilateral cup to disc (C/D) ratio ≥0.6, notching or thinning of the neuroretinal rim, disc hemorrhages, and asymmetry in the C/D ratio between both eyes ≥0.2. This evaluation led to a dichotomous classification: if any of the above criteria was present, the patient was classified as glaucoma. If none were present, the patient was classified as normal. Results. 72 control subjects and 72 glaucoma patients were included. Evaluation of NMFP had a sensitivity of 79.17% and a specificity of 80.56% for specialist 1 and a sensitivity of 72.22% and a specificity of 88.88% for specialist 2 for the detection of glaucoma. The overall accuracy was 79.83% and 80.55%, respectively. Discussion. NMFP evaluation by a glaucoma specialist may be useful for the detection of glaucoma in diabetics.