The Wisconsin Epidemiologic Study of Diabetic Retinopathy

Klein, Ronald

doi:10.1001/archopht.1984.01040030398010

Cited by 1,564 publications

(298 citation statements)

References 29 publications

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“…Indeed, pericyte loss occurs prior to clinically discernible retinopathy. Although the mechanisms underlying the development of diabetic retinopathy and pericyte loss are unknown, hyperglycemia has been suggested as one ofthe most important causal factors (2). Once established, retinal vascular abnormalities are poorly reversed by euglycemic control (3).…”

supporting

confidence: 43%

Identification of multiple genes in bovine retinal pericytes altered by exposure to elevated levels of glucose by using mRNA differential display.

Aiello¹,

Robinson²,

Lin³

et al. 1994

Proc. Natl. Acad. Sci. U.S.A.

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Cell Culture. Bovine retinal pericytes were obtained from fresh eyes as described (12) and cultured in Dulbecco's modified Eagle's medium (DMEM; 5.5 mM glucose) with 20% (vol/vol) fetal bovine serum. Prior to RNA isolation, the pericytes were grown to confluence and shifted into DMEM plus 1% (vol/vol) calf serum with glucose levels of either 5.5 mM, 22 mM, or 5.5 mM with 16.5 mM mannitol. Media were changed daily for 7 days, and the cells were stimulated with DMEM plus 10% fetal bovine serum for 8 hr (30 hr for Western blots). Pericyte growth is inhibited under similar conditions (13). Bovine aortic endothelial and smooth muscle cells were obtained from calf aorta as described (14) and

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supporting

confidence: 43%

Identification of multiple genes in bovine retinal pericytes altered by exposure to elevated levels of glucose by using mRNA differential display.

Aiello¹,

Robinson²,

Lin³

et al. 1994

Proc. Natl. Acad. Sci. U.S.A.

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“…However, in doing so people with diabetes mellitus are placed at an increased risk for developing diabetes mellitus-related microvascular complications, the most common of which is diabetic retinopathy. 7,8 The current treatment recommendations for diabetic retinopathy are highly effective in preventing visual loss. [10][11][12] Early detection and accurate evaluation of diabetic retinopathy severity, co-ordinated medical care and prompt appropriate treatment represent an effective approach for diabetic eye care.…”

Section: Study Registrationmentioning

confidence: 44%

“…5 The characteristic lesions of diabetic retinopathy are presently estimated to affect nearly half of those diagnosed at any given time. [6][7][8][9] The advances in the medical management of diabetes mellitus have substantially increased patient survival and life expectancy. However, in doing so people with diabetes mellitus are placed at an increased risk for developing diabetes mellitus-related microvascular complications, the most common of which is diabetic retinopathy.…”

Section: Study Registrationmentioning

confidence: 46%

An observational study to assess if automated diabetic retinopathy image assessment software can replace one or more steps of manual imaging grading and to determine their cost-effectiveness

Tufail

Kapetanakis

Salas-Vega

et al. 2016

Health Technol Assess

105

128

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Background Diabetic retinopathy screening in England involves labour-intensive manual grading of retinal images. Automated retinal image analysis systems (ARIASs) may offer an alternative to manual grading. Objectives To determine the screening performance and cost-effectiveness of ARIASs to replace level 1 human graders or pre-screen with ARIASs in the NHS diabetic eye screening programme (DESP). To examine technical issues associated with implementation. Design Observational retrospective measurement comparison study with a real-time evaluation of technical issues and a decision-analytic model to evaluate cost-effectiveness. Setting A NHS DESP. Participants Consecutive diabetic patients who attended a routine annual NHS DESP visit. Interventions Retinal images were manually graded and processed by three ARIASs: iGradingM (version 1.1; originally Medalytix Group Ltd, Manchester, UK, but purchased by Digital Healthcare, Cambridge, UK, at the initiation of the study, purchased in turn by EMIS Health, Leeds, UK, after conclusion of the study), Retmarker (version 0.8.2, Retmarker Ltd, Coimbra, Portugal) and EyeArt (Eyenuk Inc., Woodland Hills, CA, USA). The final manual grade was used as the reference standard. Arbitration on a subset of discrepancies between manual grading and the use of an ARIAS by a reading centre masked to all grading was used to create a reference standard manual grade modified by arbitration. Main outcome measures Screening performance (sensitivity, specificity, false-positive rate and likelihood ratios) and diagnostic accuracy [95% confidence intervals (CIs)] of ARIASs. A secondary analysis explored the influence of camera type and patients’ ethnicity, age and sex on screening performance. Economic analysis estimated the cost per appropriate screening outcome identified. Results A total of 20,258 patients with 102,856 images were entered into the study. The sensitivity point estimates of the ARIASs were as follows: EyeArt 94.7% (95% CI 94.2% to 95.2%) for any retinopathy, 93.8% (95% CI 92.9% to 94.6%) for referable retinopathy and 99.6% (95% CI 97.0% to 99.9%) for proliferative retinopathy; and Retmarker 73.0% (95% CI 72.0% to 74.0%) for any retinopathy, 85.0% (95% CI 83.6% to 86.2%) for referable retinopathy and 97.9% (95% CI 94.9 to 99.1%) for proliferative retinopathy. iGradingM classified all images as either ‘disease’ or ‘ungradable’, limiting further iGradingM analysis. The sensitivity and false-positive rates for EyeArt were not affected by ethnicity, sex or camera type but sensitivity declined marginally with increasing patient age. The screening performance of Retmarker appeared to vary with patient’s age, ethnicity and camera type. Both EyeArt and Retmarker were cost saving relative to manual grading either as a replacement for level 1 human grading or used prior to level 1 human grading, although the latter was less cost-effective. A threshold analysis testing the highest ARIAS cost per patient before which ARIASs became more expensive per appropriate outcome than human grading, when used to replace level 1 grader, was Retmarker £3.82 and EyeArt £2.71 per patient. Limitations The non-randomised study design limited the health economic analysis but the same retinal images were processed by all ARIASs in this measurement comparison study. Conclusions Retmarker and EyeArt achieved acceptable sensitivity for referable retinopathy and false-positive rates (compared with human graders as reference standard) and appear to be cost-effective alternatives to a purely manual grading approach. Future work is required to develop technical specifications to optimise deployment and address potential governance issues. Funding The National Institute for Health Research (NIHR) Health Technology Assessment programme, a Fight for Sight Grant (Hirsch grant award) and the Department of Health’s NIHR Biomedical Research Centre for Ophthalmology at Moorfields Eye Hospital and the University College London Institute of Ophthalmology.

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“…The criteria for inclusion in the study were a history of sudden onset of severe hyperglycemia and weight loss, spontaneous sustained ketosis or ketonuria, age between 18 to 45 years, living with diabetes mellitus (to allow enough time for the development of diabetic retinal disease), and freedom from any other endocrine and metabolic disease, as well as nondiabetic renal, liver and cardiac disease. In this study, we included 10 persons with diabetes for at least 10 years and without retinopathy, i.e., early treatment diabetic retinopathy study level 1 (Klein et al, 1984). This was confirmed by examination by indirect ophthalmoscopy and biomicroscopy.…”

Section: Study Populationsupporting

confidence: 45%

Algorithm for predicting macular dysfunction based on moment invariants classification of the foveal avascular zone in functional retinal images

Arthur

Silva

et al. 2017

Res. Biomed. Eng.

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Introduction: A new method for segmenting and quantifying the macular area based on morphological alternating sequential filtering (ASF) is proposed. Previous studies show that persons with diabetes present alterations in the foveal avascular zone (FAZ) prior to the appearance of retinopathy. Thus, a proper characterization of FAZ using a method of automatic classification and prediction is a supportive and complementary tool for medical evaluation of the macular region, and may be useful for possible early treatment of eye diseases in persons without diabetic retinopathy. Methods: We obtained high-resolution retinal images using a non-invasive functional imaging system called Retinal Function Imager to generate a series of combined capillary perfusion maps. We filtered sequentially the macular images to reduce the complexity by ASF. Then we segmented the FAZ using watershed transform from an automatic selection of markers. Using Hu's moment invariants as a descriptor, we can automatically classify and categorize each FAZ. Results: The FAZ differences between non-diabetic volunteers and diabetic subjects were automatically distinguished by the proposed system with an accuracy of 81%. Conclusion: This is an innovative method to classify FAZ using a fully automatic algorithm for segmentation (based on morphological operators) and for the classification (based on descriptor formed by Hu's moments) despite the presence of edema or other structures. This is an alternative tool for eye exams, which may contribute to the analysis and evaluation of FAZ morphology, promoting the prevention of macular impairment in diabetics without retinopathy.

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The Wisconsin Epidemiologic Study of Diabetic Retinopathy

Cited by 1,564 publications

References 29 publications

Identification of multiple genes in bovine retinal pericytes altered by exposure to elevated levels of glucose by using mRNA differential display.

Identification of multiple genes in bovine retinal pericytes altered by exposure to elevated levels of glucose by using mRNA differential display.

An observational study to assess if automated diabetic retinopathy image assessment software can replace one or more steps of manual imaging grading and to determine their cost-effectiveness

Algorithm for predicting macular dysfunction based on moment invariants classification of the foveal avascular zone in functional retinal images

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