Assessment of rates of structural change in glaucoma using imaging technologies

Mansouri, Kaweh; Leite, Mauro T.; Medeiros, Felipe A.; Leung, Christopher Kai-Shun; Weinreb, Robert N.

doi:10.1038/eye.2010.202

Cited by 67 publications

(54 citation statements)

References 68 publications

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“…13,22 Imaging-based quantitative measurements have diagnostic utility [23][24][25][26][27][28][29] and numerous publications support the ability of imaging-based measurements to identify glaucoma deterioration. [30][31][32][33][34][35][36][37][38][39][40] Progressive structural change has been shown to be useful as a predictor of subsequent VF loss. 41,42 The ability of imaging to detect deterioration has been compared with that of VF testing, controlling for the false-positive rate of the chosen progression criteria.…”

Section: Trial Registrationmentioning

confidence: 99%

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study

Garway-Heath

Zhu

Qian

et al. 2018

Health Technol Assess

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Background Progressive optic nerve damage in glaucoma results in vision loss, quantifiable with visual field (VF) testing. VF measurements are, however, highly variable, making identification of worsening vision (‘progression’) challenging. Glaucomatous optic nerve damage can also be measured with imaging techniques such as optical coherence tomography (OCT). Objective To compare statistical methods that combine VF and OCT data with VF-only methods to establish whether or not these allow (1) more rapid identification of glaucoma progression and (2) shorter or smaller clinical trials. Design Method ‘hit rate’ (related to sensitivity) was evaluated in subsets of the United Kingdom Glaucoma Treatment Study (UKGTS) and specificity was evaluated in 72 stable glaucoma patients who had 11 VF and OCT tests within 3 months (the RAPID data set). The reference progression detection method was based on Guided Progression Analysis™ (GPA) Software (Carl Zeiss Meditec Inc., Dublin, CA, USA). Index methods were based on previously described approaches [Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS), Permutation analyses Of Pointwise Linear Regression (PoPLR) and structure-guided ANSWERS (sANSWERS)] or newly developed methods based on Permutation Test (PERM), multivariate hierarchical models with multiple imputation for censored values (MaHMIC) and multivariate generalised estimating equations with multiple imputation for censored values (MaGIC). Setting Ten university and general ophthalmology units (UKGTS) and a single university ophthalmology unit (RAPID). Participants UKGTS participants were newly diagnosed glaucoma patients randomised to intraocular pressure-lowering drops or placebo. RAPID participants had glaucomatous VF loss, were on treatment and were clinically stable. Interventions 24-2 VF tests with the Humphrey Field Analyzer and optic nerve imaging with time-domain (TD) Stratus OCT™ (Carl Zeiss Meditec Inc., Dublin, CA, USA). Main outcome measures Criterion hit rate and specificity, time to progression, future VF prediction error, proportion progressing in UKGTS treatment groups, hazard ratios (HRs) and study sample size. Results Criterion specificity was 95% for all tests; the hit rate was 22.2% for GPA, 41.6% for PoPLR, 53.8% for ANSWERS and 61.3% for sANSWERS (all comparisons p ≤ 0.042). Mean survival time (weeks) was 93.6 for GPA, 82.5 for PoPLR, 72.0 for ANSWERS and 69.1 for sANSWERS. The median prediction errors (decibels) when the initial trend was used to predict the final VF were 3.8 (5th to 95th percentile 1.7 to 7.6) for PoPLR, 3.0 (5th to 95th percentile 1.5 to 5.7) for ANSWERS and 2.3 (5th to 95th percentile 1.3 to 4.5) for sANSWERS. HRs were 0.57 [95% confidence interval (CI) 0.34 to 0.90; p = 0.016] for GPA, 0.59 (95% CI 0.42 to 0.83; p = 0.002) for PoPLR, 0.76 (95% CI 0.56 to 1.02; p = 0.065) for ANSWERS and 0.70 (95% CI 0.53 to 0.93; p = 0.012) for sANSWERS. Sample size estimates were not reduced using methods including OCT data. PERM hit rates were between 8.3% and 17.4%. Treatment effects were non-significant in MaHMIC and MaGIC analyses; statistical significance was altered little by incorporating imaging. Limitations TD OCT is less precise than current imaging technology; current OCT technology would likely perform better. The size of the RAPID data set limited the precision of criterion specificity estimates. Conclusions The sANSWERS method combining VF and OCT data had a higher hit rate and identified progression more quickly than the reference and other VF-only methods, and produced more accurate estimates of the progression rate, but did not increase treatment effect statistical significance. Similar studies with current OCT technology need to be undertaken and the statistical methods need refinement. Trial registration Current Controlled Trials ISRCTN96423140. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 4. See the NIHR Journals Library website for further project information. Data analysed in the study were from the UKGTS. Funding for the UKGTS was provided through an unrestricted investigator-initiated research grant from Pfizer Inc. (New York, NY, USA), with supplementary funding from the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK. Imaging equipment loans were made by Heidelberg Engineering, Carl Zeiss Meditec and Optovue (Fremont, CA, USA). Pfizer, Heidelberg Engineering, Carl Zeiss Meditec and Optovue had no input into the design, conduct, analysis or reporting of any of the UKGTS findings or this work. The sponsor for both the UKGTS and RAPID data collection was Moorfields Eye Hospital NHS Foundation Trust. David F Garway-Heath, Tuan-Anh Ho and Haogang Zhu are partly funded by the NIHR Biomedical Research Centre based at Moorfields Eye Hospital and UCL Institute of Ophthalmology. David F Garway-Heath’s chair at University College London (UCL) is supported by funding from the International Glaucoma Association.

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Section: Trial Registrationmentioning

confidence: 99%

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study

Garway-Heath

Zhu

Qian

et al. 2018

Health Technol Assess

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“…23,24 In addition, IOP spontaneously varies from day to day. 25,26 The difficulty in gaining a true assessment of IOP fluctuation over time limits its ability to predict progressive glaucoma damage, 27 leaving us with progressive visual field 28 and structural damage 29,30 to the visual system as a primary diagnostic tool for treatment guidance. Currently there is no method available to assess the functional properties of the trabecular tissueproperties that are necessary to maintain IOP in a narrow range.…”

Section: Introductionmentioning

confidence: 99%

“…A perfusion system was used to control the mean IOP as well as to provide IOP sinusoidal transients (amplitude 3 mmHg, frequency 1 pulse/second) in all experiments. Measurements were carried out at seven graded mean IOPs (5,8,10,20,30,40, and 50 mm Hg). We demonstrate that PhS-OCT is sensitive enough to image/ visualize TM movement synchronous with the pulse-induced IOP transients, providing quantitative measurements of dynamic parameters such as velocity, displacement, and strain rate that are important for assessing the biomechanical compliance of the TM.…”

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confidence: 99%

Phase-sensitive optical coherence tomography characterization of pulse-induced trabecular meshwork displacement inex vivononhuman primate eyes

et al. 2012

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Abstract. Glaucoma is a blinding disease for which intraocular pressure (IOP) is the only treatable risk factor. The mean IOP is regulated through the aqueous outflow system, which contains the trabecular meshwork (TM). Considerable evidence indicates that trabecular tissue movement regulates the aqueous outflow and becomes abnormal during glaucoma; however, such motion has thus far escaped detection. The purpose of this study is to describe anovel use of a phase-sensitive optical coherence tomography (PhS-OCT) method to assess pulsedependent TM movement. For this study, we used enucleated monkey eyes, each mounted in an anterior segment holder. A perfusion system was used to control the mean IOP as well as to provide IOP sinusoidal transients (amplitude 3 mmHg, frequency 1 pulse/second) in all experiments. Measurements were carried out at seven graded mean IOPs (5,8,10,20,30,40, and 50 mm Hg). We demonstrate that PhS-OCT is sensitive enough to image/ visualize TM movement synchronous with the pulse-induced IOP transients, providing quantitative measurements of dynamic parameters such as velocity, displacement, and strain rate that are important for assessing the biomechanical compliance of the TM. We find that the largest TM displacement is in the area closest to Schlemm's canal (SC) endothelium. While maintaining constant ocular pulse amplitude, an increase of mean IOP results in a decrease of TM displacement and mean size of the SC. These results demonstrate that the PhS-OCT is a useful imaging technique capable of assessing functional properties necessary to maintain IOP in a healthy range, offering a new diagnostic alternative for glaucoma.

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“…Loss of axonal tissue in the RNFL has been reported to be one of the earliest detectable glaucomatous changes, which can proceed to morphological changes in the ONH and VF loss [8,9]. For this reason, many studies have focused on thinning of the RNFL and RNFLD using various imaging technologies [10,11]. It is therefore essential to obtain high quality RNFL images for early and accurate diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images

Ramaswamy

Lombardo

Devaney

2014

Biomed. Opt. Express

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Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM).

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Assessment of rates of structural change in glaucoma using imaging technologies

Cited by 67 publications

References 68 publications

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study

Phase-sensitive optical coherence tomography characterization of pulse-induced trabecular meshwork displacement inex vivononhuman primate eyes

Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images

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