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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

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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

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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:ImportanceStudies have not yet determined whether the distribution of lesions in the retinal periphery alters the association between the severity of diabetic retinopathy (DR) and macular vessel density.ObjectiveTo evaluate the association of DR lesion distribution with optical coherence tomography angiography (OCTA) metrics and DR severity.Design, setting, and participantsThis cross-sectional observational study was conducted at a tertiary care center for diabetic eye disease among 225 patients with type 1 or 2 diabetes who had undergone imaging between February 15, 2016, and December 31, 2019.ExposuresOptical coherence tomography angiography 3 × 3-mm macular scans and ultra-widefield color imaging.Main outcomes and measuresOptical coherence tomography angiography vessel density in the superficial capillary plexus, intermediate capillary plexus, and deep capillary plexus and choriocapillaris flow density. The severity of DR and the predominantly peripheral lesions (PPL) were evaluated from ultra-widefield color imaging.ResultsThe study evaluated 352 eyes (225 patients; 125 men [55.6%]; mean [SD] age, 52.1 [15.1] years), of which 183 eyes (52.0%) had mild nonproliferative diabetic retinopathy (NPDR), 71 eyes (20.2%) had moderate NPDR, and 98 eyes (27.8%) had severe NPDR or proliferative diabetic retinopathy (PDR). In eyes with no PPL (209 [59.4%]), the mean (SD) vessel density in the superficial capillary plexus (mild NPDR, 38.1% [4.7%]; moderate NPDR, 36.4% [4.6%]; severe NPDR or PDR, 34.1% [4.1%]; P < .001) and the deep capillary plexus (mild NPDR, 45.8% [3.0%]; moderate NPDR, 45.8% [2.2%]; severe NPDR or PDR, 44.5% [1.9%]; P = .002), as well as the mean (SD) choriocapillaris flow density (mild NPDR, 69.7% [6.2%]; moderate NPDR, 67.6% [5.6%]; severe NPDR or PDR, 67.1% [5.6%]; P = .01), decreased with increasing DR severity. These associations remained statistically significant even after correcting for age, signal strength index, spherical equivalent, duration of diabetes, type of diabetes, and correlation between eyes of the same patient. In eyes with PPL (143 [40.6%]), mean (SD) vessel density in the superficial capillary plexus (mild NPDR, 34.1% [4.1%]; moderate NPDR, 35.2% [4.1%]; severe NPDR or PDR, 36.0% [4.3%]; P = .42) and the deep capillary plexus (mild NPDR, 44.5% [1.7%]; moderate NPDR, 45.4% [1.4%]; severe NPDR or PDR, 44.9% [1.5%]; P = .81), as well as the mean (SD) choriocapillaris flow density (mild NPDR, 67.1% [5.6%]; moderate NPDR, 69.3% [4.6%]; severe NPDR or PDR, 68.3% [5.6%]; P = .49), did not appear to change with increasing DR severity.Conclusions and relevanceThese results suggest that central retinal vessel density is associated with DR severity in eyes without, but not with, PPL. These findings suggest a potential need to stratify future optical coherence tomography angiography studies of eyes with DR by the presence or absence of PPL. If DR onset and worsening are associated with the location of retinal nonperfusion, assessment of global retinal nonperfusion using widefield angiography may improve the ability to evaluate DR severity and risk of DR worsening over time.

Dataset Information

A computational modeling for the detection of diabetic retinopathy severity.

Publications

A computational modeling for the detection of diabetic retinopathy severity.

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