Functional characteristics of glaucoma related arcuate defects seen on OCT en face visualisation of the retinal nerve fibre layer.
Ontology highlight
ABSTRACT: Purpose
To assess continuity of perimetric defects corresponding to arcuate defects seen on optical coherence tomography (OCT) en face reflectance images of the retinal nerve fibre layer (RNFL) in patients with glaucoma.Methods
Seven patients with glaucoma who had arcuate structural defects on OCT RNFL en face images were recruited. Static suprathreshold stimuli were presented along different meridians to localise perimetric defects in the corresponding hemifield. Then two contrasts, one 6 dB greater than the other, were used with kinetic perimetry to assess the slope of the defect. Findings with kinetic and 24-2 perimetry were compared.Results
Static perimetry found that regions of perimetric abnormality spatially corresponded with the regions of en face RNFL hyporeflectivity. Kinetic perimetry found that the slopes of the edges of the defects ranged from 3-12 dB degree-1 , and that the functional abnormalities were continuous with the physiologic blind spot even when the 24-2 protocol only showed paracentral defects.Conclusions
Perimetric abnormalities and arcuate RNFL en face defects were spatially correspondent. Perimetric testing guided by OCT en face reflectance images can reveal greater functional detail of glaucomatous abnormality than 24-2 testing.
SUBMITTER: Ashimatey BS
PROVIDER: S-EPMC8248257 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Master Slave optical coherence tomography (MS-OCT) is an OCT method that does not require resampling of data and can be used to deliver en-face images from several depths simultaneously. As the MS-OCT method requires important computational resources, the number of multiple depth en-face images that can be produced in real-time is limited. Here, we demonstrate progress in taking advantage of the parallel processing feature of the MS-OCT technology. Harnessing the capabilities of graphics processing units (GPU)s, information from 384 depth positions is acquired in one raster with real time display of up to 40 en-face OCT images. These exhibit comparable resolution and sensitivity to the images produced using the conventional Fourier domain based method. The GPU facilitates versatile real time selection of parameters, such as the depth positions of the 40 images out of the set of 384 depth locations, as well as their axial resolution. In each updated displayed frame, in parallel with the 40 en-face OCT images, a scanning laser ophthalmoscopy (SLO) lookalike image is presented together with two B-scan OCT images oriented along rectangular directions. The thickness of the SLO lookalike image is dynamically determined by the choice of number of en-face OCT images displayed in the frame and the choice of differential axial distance between them.
| S-EPMC4574687 | biostudies-other
Project description:PurposeTo develop and evaluate a deep learning system for differentiating between eyes with and without glaucomatous visual field damage (GVFD) and predicting the severity of GFVD from spectral domain OCT (SD OCT) optic nerve head images.DesignEvaluation of a diagnostic technology.ParticipantsA total of 9765 visual field (VF) SD OCT pairs collected from 1194 participants with and without GVFD (1909 eyes).MethodsDeep learning models were trained to use SD OCT retinal nerve fiber layer (RNFL) thickness maps, RNFL en face images, and confocal scanning laser ophthalmoscopy (CSLO) images to identify eyes with GVFD and predict quantitative VF mean deviation (MD), pattern standard deviation (PSD), and mean VF sectoral pattern deviation (PD) from SD OCT data.Main outcome measuresDeep learning models were compared with mean RNFL thickness for identifying GVFD using area under the curve (AUC), sensitivity, and specificity. For predicting MD, PSD, and mean sectoral PD, models were evaluated using R2 and mean absolute error (MAE).ResultsIn the independent test dataset, the deep learning models based on RNFL en face images achieved an AUC of 0.88 for identifying eyes with GVFD and 0.82 for detecting mild GVFD significantly (P < 0.001) better than using mean RNFL thickness measurements (AUC = 0.82 and 0.73, respectively). Deep learning models outperformed standard RNFL thickness measurements in predicting all quantitative VF metrics. In predicting MD, deep learning models based on RNFL en face images achieved an R2 of 0.70 and MAE of 2.5 decibels (dB) compared with 0.45 and 3.7 dB for RNFL thickness measurements. In predicting mean VF sectoral PD, deep learning models achieved high accuracy in the inferior nasal (R2 = 0.60) and superior nasal (R2 = 0.67) sectors, moderate accuracy in inferior (R2 = 0.26) and superior (R2 = 0.35) sectors, and lower accuracy in the central (R2 = 0.15) and temporal (R2 = 0.12) sectors.ConclusionsDeep learning models had high accuracy in identifying eyes with GFVD and predicting the severity of functional loss from SD OCT images. Accurately predicting the severity of GFVD from SD OCT imaging can help clinicians more effectively individualize the frequency of VF testing to the individual patient.
| S-EPMC8063221 | biostudies-literature
Project description:PurposeThe assessment of retinal nerve fiber layer defects (RNFLDs) is a useful part of glaucoma care. Here, we obtained en-face images of retinal layers below the inner limiting membrane (ILM) with swept source-optical coherence tomography (SS-OCT), and measured RNFLD angle with new software.MethodsThis study included 105 eyes of 105 normal tension glaucoma (NTG) patients (age, 59.8 ± 13.2). Exclusion criteria were best-corrected visual acuity < 0.5, axial length > 28 mm, non-glaucoma ocular disease, and systemic disease affecting the visual field. We obtained 12 x 9 mm 3D volume scans centered on the macula with SS-OCT (DRI OCT-1, Topcon), and from these scans, created 3 averaged en-face images, each comprising 7 horizontal en-face images (total thickness: 18.2 μm). We labeled these averaged images, according to their depth below the ILM, as en-face images 1 (shallowest), 2 (middle) and 3 (deepest). In each image, a circle was drawn centered on the disc, with a radius of half the distance between the centers of the disc and macula. The investigator marked points where the edge of the RNFLD intersected this circle, and RNFLD angle (RNFLDA) was calculated with new software. Finally, we analyzed the association between RNFLDA, cpRNFLT, weighted RGC count (wrgc) and Humphrey field analyzer (HFA)-measured mean deviation (MD) and hemifield total deviation (TD), both overall and in each hemifield.ResultsEn-face image 2 had the highest interclass reproducibility for measuring RNFLDA (intra-rater intraclass correlation coefficient (ICC): 0.988, inter-rater ICC: 0.962). The correlation coefficients with RNFLDA were: HFA MD, -0.60; superior TD, -0.73; inferior TD, -0.69; overall cpRNFLT, -0.27; superior hemifield cpRNFLT, -0.39; and inferior hemifield cpRNFLT, -0.53 (all p<0.001).ConclusionsRNFLDA measured in SS-OCT images had high reproducibility and was correlated to glaucoma severity. Our new method may be a valuable future part of glaucoma care.
| S-EPMC5659603 | biostudies-literature
Project description:To estimate the floor of retinal nerve fibre layer (RNFL) thickness measurements and the corresponding retinal sensitivity loss in glaucoma.Visual field (VF), Spectralis RNFL (83 patients and 37 healthy subjects) and RTVue RNFL data obtained separately (56 patients and 36 healthy subjects) were reviewed. Global and quadrant residual layer thicknesses and corresponding VF losses were estimated using two Bayesian change point models.The respective residual thicknesses from change point model 1 (CPM1) on Spectralis and RTVue (respectively) were 49.9 and 70.6?µm globally, 57.1 and 83.7?µm superiorly, 55.2 and 79.0?µm inferiorly, 43.1 and 60.5?µm nasally, and 40.1 and 59.5?µm temporally. Corresponding VF losses ranged between -25.1 and -21.7?dB (Spectralis) and between -21.8 and -3.4?dB (RTVue). From CPM2, RNFL thinning reached horizontal asymptotes at VF losses between -18.0 and -10.7?dB (Spectralis) and between -12.1 and -2.5?dB (RTVue). There were no significant differences between postchange point residual layer thicknesses from CPM1 and CPM2 on Spectralis (37.0-50.8?µm vs 38.3-56.0?µm) and RTVue (60.6-80.5?µm vs 58.4-88.8?µm).Global RNFL thinning reaches the floor at a smaller VF loss level with Spectralis than with RTVue. The nasal and temporal quadrants retain thinner residual layers than superior and inferior quadrant RNFL. Measuring RNFL below their minimums will not yield useful clinical information.
| S-EPMC4441828 | biostudies-literature
Project description:Localised retinal nerve fibre layer defects (RNFLDs) are reported to indicate the degree of glaucomatous damage but can also be sequelae of retinal vascular insufficiency as a result of systemic vascular factors. We investigated the association between RNFLDs and cardiovascular risk factors. RNFLDs were detected in 440 (29.2%) of 1508 subjects. The presence of RNFLDs was associated with higher HbA1c (odds ratio [OR] 1.289, p?<?0.001), higher 24-h mean systolic blood pressure (SBP; OR 1.013, p?<?0.005), and lower estimated glomerular filtration rate (eGFR; OR 0.995, p?<?0.005). An increasing number of RNFLDs was correlated with higher SBP (r?=?0.186, p?<?0.001), higher HbA1c (r?=?0.128, p?<?0.010), lower eGFR (r?=?-0.112, p?<?0.020), and younger age (r?=?-0.303, p?<?0.001). Subjects with RNFLDs had a higher predicted 10-year risk of atherosclerotic cardiovascular disease than did those without RNFLDs (9.7% vs 7.9%, p?=?0.008 in middle-aged subjects, 25.6% vs 23.2%, p?=?0.040 in older subjects). In conclusion, RNFLDs are associated with SBP, eGFR, and HbA1c. Concomitant cardiovascular risk factors should be considered when evaluating patients with localised RNFLDs.
| S-EPMC6920147 | biostudies-literature
Project description:PurposeTo evaluate the accuracy and reliability in differentiating retinal arteries from veins using widefield optical coherence tomography angiography (OCTA).MethodsTen healthy eyes and 12 eyes from diabetic patients were included. Foveal-centered swept-source OCTA images (12 × 12 mm) were obtained using the PLEX Elite 9000. Vessels were graded as arteries or veins by two independent, masked readers. Arteriovenous crossings were also evaluated in healthy eyes. The vessel identification gold standard was defined using color fundus photographs (CFP) for normal eyes and both CFP and fluorescein angiography for diabetic eyes. Grading accuracy was compared to the gold standard and reliability between readers assessed.ResultsThe study evaluated 538 vessels (119 first order, 110 second, 309 third) in healthy eyes and 645 vessels (184 first order, 159 second, 302 third). In healthy eyes, the average accuracies identifying all, first-, second-, and third-order vessels were 98.61%, 99.16%, 100%, and 98.06%, respectively. Cohen's κ between graders in all vessels was 0.948. In diabetic eyes, the average accuracies identifying vessels were 96.90%, 99.46%, 97.77%, and 94.85%, respectively. Cohen's κ between graders for all vessels was 0.888. For crossing identification, the average accuracy and Cohen's κ were low (60.71% and 0.659, respectively).ConclusionsEn face OCTA allows for accurate and reliable artery and vein identification; for small branches and crossings, identification by en face OCTA alone may be less accurate and reliable.Translational relevanceArteries and veins can be differentiated on OCTA, assisting in clinically identifying pathology as arterial or venous side.
| S-EPMC6602142 | biostudies-literature
Project description:PURPOSE:To compare the diagnostic ability of wide-field swept-source optical coherence tomography (SS-OCT) retinal nerve fiber layer (RNFL) maps with spectral-domain OCT (SD-OCT) maps for detection of preperimetric (PPG) and early glaucoma (EG). PATIENTS AND METHODS:One hundred and forty-six eyes, including 37 healthy eyes, 38 eyes with PPG, and 71 eyes with EG, were analyzed. The patients underwent both SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec, Dublin, CA, USA) and wide-field SS-OCT scanning (DRI-OCT-1 Atlantis; Topcon, Tokyo, Japan). By SD-OCT, circumpapillary RNFL and macular ganglion cell analyses were performed. SS-OCT provides a wide-field RNFL thickness map and a SuperPixel map, which are composed of an RNFL deviation map of the peripapillary area and a deviation map of the composition of the ganglion cell layer with the inner plexiform layer and RNFL [GC-IPL+RNFL] in the macular area. The ability to discriminate PPG and EG from healthy eyes was assessed according to sensitivity, specificity and area under the receiver operating characteristic curve for parameters and criteria provided by SD-OCT and wide-field SS-OCT scanning. RESULTS:The wide-field RNFL thickness map obtained by SS-OCT showed the highest sensitivity to PPG and EG (92.1 and 97.2%, respectively) as compared with the other, SD-OCT criteria. The wide-field RNFL thickness map showed PPG-diagnostic performance comparable to the SD-OCT RNFL thickness and GC-IPL deviation maps (p?=?0.453 and 0.180), and PPG-diagnostic performance superior to the SD-OCT RNFL deviation and GC-IPL thickness maps (p?=?0.003 and 0.039). In EG, the wide-field RNFL thickness and SuperPixel maps showed diagnostic performance comparable to the SD-OCT thickness and deviation maps (p?=?0.065 to 0.100), except for the GC-IPL thickness map (p?=?0.004). CONCLUSIONS:The wide-field SS-OCT RNFL thickness maps showed a diagnostic ability for distinguishing PPG and EG from healthy eyes that was similar to that of SD-OCT. In the clinical setting, these maps can be effective for detection of early-glaucomatous changes.
| S-EPMC6137103 | biostudies-literature
Project description:ObjectiveTo examine microcystic inner nuclear layer (INL) changes in glaucomatous eyes and to determine associated factors.DesignRetrospective, cross-sectional, observational study.MethodsTwo hundred seventeen eyes of 133 patients with primary open angle glaucoma (POAG), 41 eyes of 32 patients with preperimetric glaucoma and 181 normal eyes of 117 subjects were ultimately included. Microcystic INL lesions were examined with infrared fundus images and with 19 vertical spectral domain optical coherence tomography (SD-OCT) images in the macular area.ResultsMicrocystic INL changes were observed in 6.0% of eyes with POAG, but none of the normal eyes or eyes with preperimetric glaucoma showed microcystic INL changes. The proportion of eyes with advanced glaucoma was significantly larger (P = 0.013) in eyes with microcystic lesions than without. The visual field mean deviation (MD) slope was also significantly worse (P = 0.027) in eyes with microcystic lesions. No significant differences were observed in age, sex, refraction, axial length, intraocular pressure, or MD value between eyes with and without microcystic INL lesions. In several cases, microcystic INL lesions occurred along with glaucomatous visual field progression. The retinal nerve fiber layer (RNFL) thickness (P = 0.013) and ganglion cell layer (GCL) + inner plexiform layer thickness (P = 0.023) were significantly lower in areas with microcystic lesions than without. The INL was also significantly thicker (P = 0.002) in areas with microcystic lesions.ConclusionsMicrocystic INL lesions in glaucomatous eyes are closely associated with RNFL and GCL thinning and correlated with worse MD slope. These INL lesions may indicate focal and progressive damage in glaucoma.
| S-EPMC4467090 | biostudies-literature
Project description:Automated measurements of the retinal nerve fiber layer thickness on circular OCT B-Scans provide physicians additional parameters for glaucoma diagnosis. We propose a novel retinal nerve fiber layer segmentation algorithm for frequency domain data that can be applied on scans from both normal healthy subjects, as well as glaucoma patients, using the same set of parameters. In addition, the algorithm remains almost unaffected by image quality. The main part of the segmentation process is based on the minimization of an energy function consisting of gradient and local smoothing terms. A quantitative evaluation comparing the automated segmentation results to manually corrected segmentations from three reviewers is performed. A total of 72 scans from glaucoma patients and 132 scans from normal subjects, all from different persons, composed the database for the evaluation of the segmentation algorithm. A mean absolute error per A-Scan of 2.9 µm was achieved on glaucomatous eyes, and 3.6 µm on healthy eyes. The mean absolute segmentation error over all A-Scans lies below 10 µm on 95.1% of the images. Thus our approach provides a reliable tool for extracting diagnostic relevant parameters from OCT B-Scans for glaucoma diagnosis.
| S-EPMC3018129 | biostudies-literature
Project description:Recent reports show varying results regarding peripapillary retinal nerve fibre layer (RNFL) thickness after intraocular pressure (IOP)-lowering glaucoma surgery. We hypothesised that different levels of the preoperative IOP influence RNFL thickness. A total of 60 patients (60 eyes) with glaucoma, who underwent glaucoma surgery and had a stable postoperative mean IOP < 22 mmHg, were enrolled. The RNFL thickness was measured using spectral domain optical coherence tomography, before and at 3-6 months after surgery. The preoperative peak IOP, 37.4 ± 10.8 mmHg, decreased to a postoperative mean IOP of 14.8 ± 3.5 mmHg (p < 0.001). The average RNFL thickness was significantly reduced from 75.6 ± 17.7 μm to 70.2 ± 15.8 μm (p < 0.001). In subgroup analyses, only patients with a preoperative peak IOP ≥ median value (37 mmHg) exhibited significant RNFL thinning (9.7 ± 6.6 μm, p < 0.001) associated with a higher preoperative peak IOP (r = 0.475, p = 0.008). The RNFL thinning was evident for a few months after glaucoma surgery in patients with a higher preoperative peak IOP, although the postoperative IOP was stable.
| S-EPMC6761197 | biostudies-literature