Dataset Information

A computational modeling for the detection of diabetic retinopathy severity.

ABSTRACT: Prolonged diabetes ultimately leads to Diabetic Retinopathy (DR) which is one of the leading causes of preventable blindness in the world. Through advanced image analysis techniques are used for abnormalities detection in retina that define and correlate the severity of DR. A thorough study is done in this area in recent past years and on the basis of these studies we have developed a computer based prediction model that is used to determine the severity of DR. To identify severity DR, we have analyzed the human eye image. We have extracted some important features from human eye image i.e. Blood Artery, Optical disc, Exudates. Based on these image and data we have designed an automated system for the determination of DR severity. This automated DR severity assessment methods can be used to predict the clinical case and conditions when young clinicians would agree or disagree with their more experienced fellow members. The algorithms described in this study may be used in clinical practice to validate or invalidate the diagnoses. Algorithms or method developed here may also be used for pooling diagnostic knowledge for serving mankind. Here we have described a computational based low cost retinal diagnostic approach which can aid an ophthalmologist to quickly diagnose the various stages of DR. This system can accept retinal images and can successfully detect any pathological condition associated with DR.

SUBMITTER: Mishra PK

PROVIDER: S-EPMC4209363 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A computational modeling for the detection of diabetic retinopathy severity.

Mishra Pavan Kumar PK Sinha Abhijit A Teja Kaveti Ravi KR Bhojwani Nitin N Sahu Sagar S Kumar Awanish A

Bioinformation 20140930 9

Prolonged diabetes ultimately leads to Diabetic Retinopathy (DR) which is one of the leading causes of preventable blindness in the world. Through advanced image analysis techniques are used for abnormalities detection in retina that define and correlate the severity of DR. A thorough study is done in this area in recent past years and on the basis of these studies we have developed a computer based prediction model that is used to determine the severity of DR. To identify severity DR, we have a ...[more]

PMID: 25352722

Similar Datasets

Project description:BackgroundThe Early Treatment Diabetic Retinopathy Study Diabetic Retinopathy Severity Scale (DRSS) is a standard approach to measure diabetic retinopathy (DR) severity. Many clinical trials evaluating drug intervention for DR rely upon demonstration of a therapeutic effect through measurement of a 2- or 3-step improvement or progression on the DRSS; however, these binary endpoints require a relatively large sample size for a reliable estimate of therapeutic efficacy, especially when the SOC (eg, anti-VEGF) is used as a control. This study was designed to evaluate the sensitivity and statistical efficiency of detecting a drug effect in DR across different DRSS endpoints, and present alternative analytical approaches to enable smaller-size DR trials for detecting a reliable efficacy signal before moving into larger confirmatory DR trials.MethodsData from two randomized, double-blinded, controlled Phase III trials, that enrolled patients with decreased vision due to center-involved DME and the presence of macular edema documented on optical coherence tomography and simulated data, were used for this study. Changes in DRSS steps during a 3-month period from patients (n=205) with no active intervention were used to confirm the reliability of DRSS outcomes. A simulation study compared sensitivity and statistical efficiency across different DRSS endpoints.ResultsThe standard deviation of step change between baseline and month 3 DRSS across different steps at baseline were all within 1 step, confirming the reliability of DRSS measure by each step. Efficiency of detecting reliable therapeutic efficacy was augmented when treatment effect in improvement and progression was evaluated together; highest sensitivity was observed when change in DRSS steps was used directly as an endpoint.ConclusionDRSS step change may provide more robust sensitivity and statistical efficiency. It is therefore a more cost-effective endpoint for the detection of therapeutic efficacy signal in drug discoveries in DR.

Project description:ImportanceModerate to substantial agreement between Early Treatment Diabetic Retinopathy Study (ETDRS) 7-field imaging and ultrawide-field (UWF) imaging has been suggested in single-center studies. Comparing images obtained by multiple centers could increase confidence that UWF images can be used reliably in place of ETDRS imaging in future clinical trials.ObjectiveTo compare diabetic retinopathy (DR) severity from modified ETDRS 7-field imaging and UWF imaging.Design, setting, and participantsThis preplanned, cross-sectional analysis included modified ETDRS 7-field images obtained using the Diabetic Retinopathy Clinical Research Network acquisition protocol and UWF images obtained captured with the Optos 200Tx system (Optos, PLC) from adult participants (≥18 years old) with type 1 or type 2 diabetes. Both image types were evaluated by trained graders masked to clinical data. Data collection occurred from February 2015 to December 2015, and data analysis from June 2016 to December 2017.Main outcomes and measuresAgreement between UWF images, UWF images masked to include only the ETDRS 7-field area, and ETDRS 7-field images were calculated using κ statistics.ResultsA total of 764 eyes from 385 participants were included; participants had a median (IQR) age of 62.2 (53.6-69.2) years, 194 (50.4%) were women, and 256 (66.5%) were white. Of 742 eyes with both ETDRS 7-field images and UWF masked images graded, 359 (48.4% [95% CI, 44.4%-52.4%]) eyes had exact agreement, and 653 eyes (88.0% [95% CI, 85.2%-90.3%]) agreed within 1 step (weighted κ, 0.51 [95% CI, 0.44-0.58]). After open adjudication by an independent senior grader of all images with more than a 2-step discrepancy, perfect agreement was found in 435 eyes (59.0% [95% CI, 55.1%-62.8%]) and agreement within 1 step in 714 eyes (96.9% [95% CI, 95.1%-98.0%]; κ, 0.77 [95% CI, 0.73-0.82]). Ability of the imaging modalities to detect retinopathy severity in an individual eye was considered similar in 59 eyes (50.9% [95% CI, 41.3%-60.4%]), better for ETDRS 7-field imaging in 22 eyes (19.0% [95% CI, 12.5%-27.7%]), and better for UWF-masked images in 31 eyes (26.7% [95% CI 18.8%-36.5%]). Comparing UWF masked and unmasked images, 94 of 751 eyes (12.5%) had DR graded as at least 1 step more severe on UWF unmasked images vs UWF masked images. Predominantly peripheral DR lesions were present in 308 of 751 eyes (41.0%); this suggested increased DR severity by 2 or more steps in 34 eyes (11.0%).Conclusions and relevanceImaging by the ETDRS 7-field and UWF imaging systems have moderate to substantial agreement when determining the severity of DR within the 7 standard fields. Disparities in an individual eye are equivalently distributed between imaging modalities and can be better or worse on 1 or the other. Longitudinal follow-up will evaluate the primary outcome of this study to determine if peripheral retinal findings are associated with future retinopathy outcomes.

Project description:PurposeEstimate effects of ranibizumab on diabetic retinopathy (DR) severity in US Hispanic and non-Hispanic white persons with center-involved diabetic macular edema (DME) causing vision impairment for whom ranibizumab treatment would be considered.Patients and methodsThis model simulated DR severity outcomes over 2 years in the better-seeing eye using US census, National Health and Nutrition Examination Survey, Wisconsin Epidemiologic Study of Diabetic Retinopathy, and Los Angeles Latino Eye Study data. Baseline DR severity estimated from Diabetic Retinopathy Clinical Research Network trial data. Changes in DR severity after 2 years, with/without monthly ranibizumab (0.3 or 0.5 mg), were estimated from Phase III clinical trial data (RIDE/RISE) using a 2-dimensional Monte Carlo simulation model. Number of patients over a 2-year period for whom 1) DR severity worsening was avoided, 2) DR severity improved, and 3) selected clinical events related to proliferative DR (PDR) occurred, was estimated.ResultsAn estimated 37,274 US Hispanic and non-Hispanic white persons were projected to have DR with center-involved DME and be eligible for ranibizumab treatment. The number of persons with moderately severe non-proliferative DR (NPDR) or less severe DR at baseline who would worsen to PDR and experience a PDR complication over 2 years would be reduced from 437 with no ranibizumab to 19 with ranibizumab (95% reduction; 95% simulation interval [SI], 79-100%). The number of persons with severe NPDR or less severe DR at baseline who would be expected to improve by ≥2 DR severity levels over 2 years would increase from 1706 with no ranibizumab to 13,042 with ranibizumab (682% increase; 95% SI, 478-967%).ConclusionThis model estimates that ranibizumab treatment in US Hispanic and non-Hispanic white patients with center-involved DME causing vision impairment would potentially reduce the number of patients with worsening DR and potentially increase the number with DR improvements.

Dataset Information

A computational modeling for the detection of diabetic retinopathy severity.

Publications

A computational modeling for the detection of diabetic retinopathy severity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure