Comparison of Time-Domain OCT and Fundus Photographic Assessments of Retinal Thickening in Eyes with Diabetic Macular Edema

Davis, Matthew D.; Bressler, Susan B.; Aiello, Lloyd Paul; Bressler, Neil M.; Browning, David J.; Flaxel, Christina J.; Fong, Donald S.; Foster, William; Glassman, Adam R.; Hartnett, M. Elizabeth; Kollman, Craig; Li, Helen K.; Qin, Haijing; Scott, Ingrid U.

doi:10.1167/iovs.07-1257

Cited by 78 publications

(59 citation statements)

References 13 publications

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“…Because of its non-contact, non-invasiveness and high resolution characteristics, OCT has become the most widely used optical technique in medical imaging. Especially, this technology has increasingly become a standard of care in ophthalmic imaging for the diagnosis and management of several ocular conditions and diseases such as age-related macular degeneration (AMD) [3,4], diabetic retinopathy [5,6] and glaucoma [7,8].…”

Section: Introductionmentioning

confidence: 99%

Characterizing relationship between optical microangiography signals and capillary flow using microfluidic channels

Choi

Wan

Chen

et al. 2016

Biomed. Opt. Express

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Optical microangiography (OMAG) is a powerful optical angiographic tool to visualize micro-vascular flow in vivo. Despite numerous demonstrations for the past several years of the qualitative relationship between OMAG and flow, no convincing quantitative relationship has been proven. In this paper, we attempt to quantitatively correlate the OMAG signal with flow. Specifically, we develop a simplified analytical model of the complex OMAG, suggesting that the OMAG signal is a product of the number of particles in an imaging voxel and the decorrelation of OCT (optical coherence tomography) signal, determined by flow velocity, interframe time interval, and wavelength of the light source. Numerical simulation with the proposed model reveals that if the OCT amplitudes are correlated, the OMAG signal is related to a total number of particles across the imaging voxel cross-section per unit time (flux); otherwise it would be saturated but its strength is proportional to the number of particles in the imaging voxel (concentration). The relationship is validated using microfluidic flow phantoms with various preset flow metrics. This work suggests OMAG is a promising quantitative tool for the assessment of vascular flow. Chen, and R. K. Wang, "Repeatability and reproducibility of optic nerve head perfusion measurements using optical coherence tomography angiography," J. Biomed. Opt. 21(6), 065002 (2016). 42. Z. Chu, J. Lin, C. Gao, C. Xin, Q. Zhang, C. L. Chen, L. Roisman, G. Gregori, P. J. Rosenfeld, and R. K. Wang, "Quantitative assessment of the retinal microvasculature using optical coherence tomography angiography," J.

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Section: Introductionmentioning

confidence: 99%

Characterizing relationship between optical microangiography signals and capillary flow using microfluidic channels

Choi

Wan

Chen

et al. 2016

Biomed. Opt. Express

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“…They are 1. the pixel's intensity value after preprocessing, 2. the standard deviation of the preprocessed intensity value, 3. the pixel's hue, 4. the number of edge pixel in a region around the pixel, 5. the average intensity of the pixel's cluster, 6. the size (measured in pixels) of the pixel's cluster, 7. the average intensity of the pixels in the neighborhood of the pixel's cluster, 8.…”

Section: Naive Bayesian Classifiermentioning

confidence: 99%

“…If the exudates extend into the macular area, vision loss can occur. In addition, the location of exudates based on macular position is important information for an ophthalmologist [5], [6]. They show the severity of disease, where exudates that appear closer to the macular indicate an increased severity of disease.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Automatic Exudate Detection between Machine Learning and Traditional Approaches

Sopharak

Uyyanonvara

Barman³

et al. 2009

IEICE Trans. Inf. & Syst.

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SUMMARYTo prevent blindness from diabetic retinopathy, periodic screening and early diagnosis are neccessary. Due to lack of expert ophthalmologists in rural area, automated early exudate (one of visible sign of diabetic retinopathy) detection could help to reduce the number of blindness in diabetic patients. Traditional automatic exudate detection methods are based on specific parameter configuration, while the machine learning approaches which seems more flexible may be computationally high cost. A comparative analysis of traditional and machine learning of exudates detection, namely, mathematical morphology, fuzzy c-means clustering, naive Bayesian classifier, Support Vector Machine and Nearest Neighbor classifier are presented. Detected exudates are validated with expert ophthalmologists' hand-drawn ground-truths. The sensitivity, specificity, precision, accuracy and time complexity of each method are also compared.

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“…(7,8) OCT and fundus photograph both provide complementary information and have moderate correlation in assessing retinal thickening in DMO. However, this cannot be a surrogate for VA, (9) as there is a wide range of acuity for a given degree of retinal oedema even following laser treatment. (9,10) This review aims to summarise recent findings from DRCR.net studies on the treatment of DMO.…”

Section: Introductionmentioning

confidence: 99%

“…However, this cannot be a surrogate for VA, (9) as there is a wide range of acuity for a given degree of retinal oedema even following laser treatment. (9,10) This review aims to summarise recent findings from DRCR.net studies on the treatment of DMO. The primary outcomes are Advances in the management of diabetic macular oedema based on evidence from the Diabetic Retinopathy Clinical Research Network reduction in thickening assessed by central subfield thickness (CST) on Stratus OCT-3 and improvement of VA on the ETDRS chart.…”

Section: Introductionmentioning

confidence: 99%

Advances in the management of diabetic macular oedema based on evidence from the Diabetic Retinopathy Clinical Research Network

Lim

Chia

Ah-kee

et al. 2015

smedj

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The Diabetic Retinopathy Clinical Research Network (DRCR.net) performs studies on new treatments for diabetic retinopathy. This review aims to summarise recent findings from DRCR.net studies on the treatment of diabetic macular oedema. We performed a PubMed search of articles from the DRCR.net, which included all studies pertaining to the treatment of diabetic maculopathy. The main outcome measures were retinal thickening as assessed by central subfield thickness on optical coherence tomography and improvement of visual acuity on the Early Treatment Diabetic Retinopathy Study (ETDRS) chart. Findings from each study were divided into modalities of treatment, namely photocoagulation, bevacizumab, triamcinolone, ranibizumab and vitrectomy. While modified ETDRS focal/grid laser remains the standard of care, intravitreal corticosteroids or anti-vascular endothelial growth factor agents have also proven to be effective, although they come with associated side effects. The choice of treatment modality for diabetic macular oedema is a clinical judgement call, and depends on the patient's clinical history and assessment.

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Comparison of Time-Domain OCT and Fundus Photographic Assessments of Retinal Thickening in Eyes with Diabetic Macular Edema

Abstract: There was a moderate correlation between OCT and FP assessments of RT in patients with DME and slightly less correlation of either measure with VA. OCT and FP provide complementary information but neither is a reliable surrogate for VA.

Cited by 78 publications

References 13 publications

Characterizing relationship between optical microangiography signals and capillary flow using microfluidic channels

Characterizing relationship between optical microangiography signals and capillary flow using microfluidic channels

Comparative Analysis of Automatic Exudate Detection between Machine Learning and Traditional Approaches

Advances in the management of diabetic macular oedema based on evidence from the Diabetic Retinopathy Clinical Research Network

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