Contrast-to-Noise Ratios for Assessing the Detection of Progression in the Various Stages of Glaucoma

Majoor, Juleke Eugenie Anne; Vermeer, Koenraad A.; Andrinopoulou, Eleni‐Rosalina; Lemij, Hans G

doi:10.1167/tvst.8.3.8

Cited by 7 publications

(8 citation statements)

References 31 publications

(45 reference statements)

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“…Optical coherence tomography (OCT) can detect glaucomatous damage to retinal ganglion cells and is more sensitive than SAP in detecting early glaucoma ( 29 , 30 ). OCT nerve fiber layer measurements are more sensitive to detecting early damage than optic nerve head (ONH), macular and confocal scanning laser ophthalmoscope measurements ( 31 , 32 ).…”

Section: Discussionmentioning

confidence: 99%

Slowed Saccadic Reaction Times in Seemingly Normal Parts of Glaucomatous Visual Fields

et al. 2021

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Purpose: In eye movement perimetry, peripheral stimuli are confirmed by goal-directed eye movements toward the stimulus. The saccadic reaction time (SRT) is regarded as an index of visual field responsiveness, whereas in standard automated perimetry (SAP), the visual field sensitivity is tested. We investigated the relation between visual field sensitivity and responsiveness in corresponding locations of the visual field in healthy controls and in patients with mild, moderate and advanced glaucoma.Materials and Methods: Thirty-four healthy control subjects and 42 glaucoma patients underwent a 54-point protocol in eye movement perimetry (EMP) and a 24-2 SITA standard protocol in a Humphrey Field Analyzer. The visual field points were stratified by total deviation sensitivity loss in SAP into 6 strata. A generalized linear mixed model was applied to determine the influence of the various factors.Results: The generalized linear mixed model showed that the mean SRT increased with increasing glaucoma severity, from 479 ms in the control eyes to 678 ms in the eyes of patients with advanced glaucoma (p < 0.001). Mean SRTs significantly increased with increasing SAP sensitivity loss. Even at the locations where no sensitivity loss was detected by SAP (total deviation values greater or equal than 0 dB), we found lengthened SRTs in mild, moderate and advanced glaucoma compared to healthy controls (p < 0.05) and in moderate and advanced glaucoma compared to mild glaucoma (p < 0.05). At locations with total deviation values between 0 and −3 dB, −3 and −6 dB and −6 and −12 dB, we found similar differences.Conclusions: The lengthened SRT in areas with normal retinal sensitivities in glaucomatous eyes, i.e., planning and execution of saccades to specific locations, precede altered sensory perception as assessed with SAP. Better understanding of altered sensory processing in glaucoma might allow earlier diagnosis of emerging glaucoma.

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Section: Discussionmentioning

confidence: 99%

Slowed Saccadic Reaction Times in Seemingly Normal Parts of Glaucomatous Visual Fields

et al. 2021

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“…Development in retinal imaging modalities (especially OCT) is making rapid strides in providing the objective visualization arXiv:2010.03872v1 [cs.CV] 8 Oct 2020 of early, mild, and severe ocular complications [4], particularly for the glaucoma [5], the second leading cause of irreversible blindness worldwide. Moreover, the detection and monitoring of glaucoma by measuring the velocity of RNFL thickness loss has been significantly highlighted in many recent stateof-the-art studies [6], [7].…”

Section: A Clinical Studiesmentioning

confidence: 99%

“…However, observing the degeneration of RGCs through optic nerve head (ONH) SD-OCT scans can provide a superior and objective indication of early glaucoma, resulting in the timely prevention of non-recoverable visual impairments. Furthermore, due to the unprecedented clinical significance of retinal OCT examination [5]- [7], many researchers have developed autonomous systems to objectively screen glaucoma (especially in early-stage) using retinal OCT scans [17]. Moreover, Almobarak et al [18] manually segmented ONH structures from SD-OCT scans to analyze pathological variations in healthy and glaucomatous pathologies.…”

Section: B Automated Glaucomatous Analysismentioning

confidence: 99%

“…For a block of n consecutive convolution layers within the network having the dilation rate 'r' where n > r, the dilation factors in the proposed framework are generated through round(r − n 2 + i) where i varies from 0 to n − 1. For example, for a block containing 5 cascaded convolution layers having the dilation rate r = 3, the dilation factors will be [1,2,3,4,5], meaning that the first convolution layer within the block will perform ). Similarly, the green pixels (in layer 4) are computed through brown pixels in layer 3, brown pixels are computed through red pixels in layer 2 and red pixels are computed through dark blue pixels in layer 1.…”

Section: B Hybrid Convolution Frameworkmentioning

confidence: 99%

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Clinically Verified Hybrid Deep Learning System for Retinal Ganglion Cells Aware Grading of Glaucomatous Progression

Raja¹,

Hassan

Akram³

et al. 2021

IEEE Trans. Biomed. Eng.

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Glaucoma is the second leading cause of blindness worldwide. Glaucomatous progression can be easily monitored by analyzing the degeneration of retinal ganglion cells (RGCs). Many researchers have screened glaucoma by measuring cup-to-disc ratios from fundus and optical coherence tomography scans. However, this paper presents a novel strategy that pays attention to the RGC atrophy for screening glaucomatous pathologies and grading their severity. Methods:The proposed framework encompasses a hybrid convolutional network that extracts the retinal nerve fiber layer, ganglion cell with the inner plexiform layer and ganglion cell complex regions, allowing thus a quantitative screening of glaucomatous subjects. Furthermore, the severity of glaucoma in screened cases is objectively graded by analyzing the thickness of these regions. Results: The proposed framework is rigorously tested on publicly available Armed Forces Institute of Ophthalmology (AFIO) dataset, where it achieved the F1 score of 0.9577 for diagnosing glaucoma, a mean dice coefficient score of 0.8697 for extracting the RGC regions and an accuracy of 0.9117 for grading glaucomatous progression. Furthermore, the performance of the proposed framework is clinically verified with the markings of four expert ophthalmologists, achieving a statistically significant Pearson correlation coefficient of 0.9236. Conclusion: An automated assessment of RGC degeneration yields better glaucomatous screening and grading as compared to the state-ofthe-art solutions. Significance: An RGC-aware system not only screens glaucoma but can also grade its severity and here we present an end-to-end solution that is thoroughly evaluated on a standardized dataset and is clinically validated for analyzing glaucomatous pathologies.

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“…In a previous study, we used contrast-to-noise ratios (CNRs) to determine which technology, OCT or SAP, was more sensitive for detecting glaucomatous progression in the various stages of the disease. 5 The CNR was defined as the change in magnitude of a parameter between two consecutive glaucoma stages (contrast) divided by the measurement variability of that parameter in those stages (noise). Because the ratio is dimensionless, it enables a direct comparison between the different types of measurements (structural and functional) for their sensitivity to detect progression.…”

Section: Introductionmentioning

confidence: 99%

Contrast-to-Noise Ratios to Evaluate the Detection of Glaucomatous Progression in the Superior and Inferior Hemiretina

Majoor

Vermeer²,

Lemij

2022

Trans. Vis. Sci. Tech.

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Purpose To determine the sensitivity of optical coherence tomography (OCT) and standard automated perimetry (SAP) for detecting glaucomatous progression in the superior and inferior hemiretina. Methods We calculated contrast-to-noise ratios (CNRs) for OCT retinal nerve fiber layer (RNFL) thickness of hemiretinas and for SAP mean total deviation (MTD) of the corresponding hemifields from longitudinal data (205 eyes, 125 participants). The glaucoma stage for each hemiretina was based on the corresponding hemifield's MTD. Contrast was defined as the difference of the parameter between two consecutive glaucoma stages, whereas noise was the measurement variability of the parameter in those stages. The higher the CNR of a parameter, the more sensitive it is to detecting progression in the transition between successive stages. Results There were no statistically significant differences for the RNFL CNR and MTD CNR between superior and inferior hemiretinas. As the glaucoma stage of the opposite hemiretina worsened, the MTD CNR in the transition from moderate to advanced glaucoma significantly increased. The RNFL CNR in the transition from mild to moderate glaucoma significantly decreased in case of advanced glaucoma in the opposite hemiretina. Conclusions Similar to full retinas, detecting conversion to glaucoma in hemiretinas is more sensitive with OCT than SAP, whereas with more advanced disease, SAP is more sensitive for detecting progression. More importantly, the sensitivity for detecting progression in one hemiretina with either technique depends on the glaucoma severity in the opposite hemiretina. Translational Relevance Monitoring glaucomatous progression with either OCT or SAP partly depends on the glaucoma severity in the opposite hemiretina.

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Contrast-to-Noise Ratios for Assessing the Detection of Progression in the Various Stages of Glaucoma

Cited by 7 publications

References 31 publications

Slowed Saccadic Reaction Times in Seemingly Normal Parts of Glaucomatous Visual Fields

Slowed Saccadic Reaction Times in Seemingly Normal Parts of Glaucomatous Visual Fields

Clinically Verified Hybrid Deep Learning System for Retinal Ganglion Cells Aware Grading of Glaucomatous Progression

Contrast-to-Noise Ratios to Evaluate the Detection of Glaucomatous Progression in the Superior and Inferior Hemiretina

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