INTEGRATING MACULAR OPTICAL COHERENCE TOMOGRAPHY WITH ULTRAWIDE-FIELD IMAGING IN A DIABETIC RETINOPATHY TELEMEDICINE PROGRAM USING A SINGLE DEVICE.

PURPOSE: To determine the effect of combined macular spectral-domain optical coherence tomography (SD-OCT) and ultrawide field retinal imaging (UWFI) within a telemedicine program. METHODS: Comparative cohort study of consecutive patients with both UWFI and SD-OCT. Ultrawide field retinal imaging and SD-OOCT were independently evaluated for diabetic macular edema (DME) and nondiabetic macular abnormality. Sensitivity and specificity were calculated with SD-OCT as the gold standard. RESULTS: Four hundred twenty-two eyes from 211 diabetic patients were evaluated. Diabetic macular edema severity by UWFI was as follows: no DME 93.4%, noncenter involved DME (nonciDME) 5.1%, ciDME 0.7%, ungradable DME 0.7%. SD-OCT was ungradable in 0.5%. Macular abnormality was identified in 34 (8.1%) eyes by UWFI and in 44 (10.4%) eyes by SD-OCT. Diabetic macular edema represented only 38.6% of referable macular abnormality identified by SD-OCT imaging. Sensitivity/specificity of UWFI compared with SD-OCT was 59%/96% for DME and 33%/99% for ciDME. Sensitivity/specificity of UWFI compared with SDOCT was 3%/98% for epiretinal membrane. CONCLUSION: Addition of SD-OCT increased the identification of macular abnormality by 29.4%. More than 58.3% of the eyes believed to have any DME on UWF imaging alone were false-positives by SD-OCT. The integration of SD-OCT with UWFI markedly increased detection and reduced false-positive assessments of DME and macular abnormality in a teleophthalmology program.

Comparison of Diabetic Retinopathy Lesions Identified Using Ultrawide Field Imaging and Optical Coherence Tomography Angiography.

INTRODUCTION: Optical coherence tomography (OCT) angiography (OCTA) has the potential to influence the diagnosis and management of diabetic eye disease. This study aims to determine the correlation between diabetic retinopathy (DR) findings on ultrawide field (UWF) color photography (UWF-CP), UWF fluorescein angiography (UWF-FA), and OCTA. METHODS: This is a cross-sectional, prospective study. One hundred and fourteen eyes from 57 patients with diabetes underwent mydriatic UWF-CP, UWF-FA, and OCTA. DR severity was assessed. Ischemic areas were identified on UWF-FA using ImageJ and the nonperfusion index (NPI) was calculated. Diabetic macular edema (DME) was assessed using OCT. Superficial capillary plexus vessel density (VD), vessel perfusion (VP), and foveal avascular zone (FAZ) area were automatically measured on OCTA. Pearson correlation coefficient between the imaging modalities was determined. RESULTS: Forty-five eyes were excluded due to non-DR findings or prior laser photocoagulation; 69 eyes were analyzed. DR severity was associated with larger NPI (r = 0.55944, p < 0.0001) even after distinguishing between cones (Cone Nonperfusion Index [CPI]: r = 0.55617, p < 0.0001) and rods (Rod Nonperfusion Index [RPI]: r = 0.55285, p < 0.0001). In eyes with nonproliferative DR (NPDR), NPI is correlated with DME (r = 0.51156, p = 0.0017) and central subfield thickness (CST) (r = 0.67496, p < 0.0001). UWF-FA macular nonperfusion correlated with NPI (r = 0.42899, p = 0.0101), CPI (r = 0.50028, p = 0.0022), and RPI (r = 0.49027, p = 0.0028). Central VD and VP correlated with the DME presence (r = 0.52456, p < 0.0001; r = 0.51952, p < 0.0001) and CST (r = 0.50133, p < 0.0001; r = 0.48731, p < 0.0001). Central VD and VP were correlated with macular nonperfusion (r = 0.44503, p = 0.0065; r = 0.44239, p = 0.0069) in eyes with NPDR. Larger FAZ was correlated with decreased central VD (r = -0.60089, p = 0.0001) and decreased central VP (r = -0.59224, p = 0.0001). CONCLUSION: UWF-CP, UWF-FA, and OCTA findings provide relevant clinical information on diabetic eyes. Nonperfusion on UWF-FA is correlated with DR severity and DME. OCTA metrics of the superficial capillary plexus correlate with the incidence of DME and macular ischemia.

Comparison of 2-Field and 5-Field Mydriatic Handheld Retinal Imaging in a Community-Based Diabetic Retinopathy Screening Program.

INTRODUCTION: The purpose of this study was to compare 2-field (2F) and 5-field (5F) mydriatic handheld retinal imaging for the assessment of diabetic retinopathy (DR) severity in a community-based DR screening program (DRSP). METHODS: This was a prospective, cross-sectional diagnostic study, evaluating images of 805 eyes from 407 consecutive patients with diabetes acquired from a community-based DRSP. Mydriatic standardized 5F imaging (macula, disc, superior, inferior, temporal) with handheld retinal camera was performed. 2F (disc, macula), and 5F images were independently assessed using the International DR classification at a centralized reading center. Simple (K) and weighted (Kw) kappa statistics were calculated for DR. Sensitivity and specificity for referable DR ([refDR] moderate nonproliferative DR [NPDR] or worse) and vision-threatening DR ([vtDR] severe NPDR or worse) for 2F compared to 5F imaging were calculated. RESULTS: Distribution of DR severity by 2F/5F images (%): no DR 66.0/61.7, mild NPDR 10.7/14.4, moderate NPDR 7.9/8.1, severe NPDR 3.3/5.6, proliferative DR 5.6/4.6, ungradable 6.5/5.6. Exact agreement of DR grading between 2F and 5F was 81.7%, within 1-step 97.1% (K = 0.64, Kw = 0.78). Sensitivity/specificity for 2F compared 5F was refDR 0.80/0.97, vtDR 0.73/0.98. The ungradable images rate with 2F was 16.1% higher than with 5F (6.5 vs. 5.6%, p < 0.001). CONCLUSIONS: Mydriatic 2F and 5F handheld imaging have substantial agreement in assessing severity of DR. However, the use of mydriatic 2F handheld imaging only meets the minimum standards for sensitivity and specificity for refDR but not for vtDR. When using handheld cameras, the addition of peripheral fields in 5F imaging further refines the referral approach by decreasing ungradable rate and increasing sensitivity for vtDR.

Comparisons of Handheld Retinal Imaging with Optical Coherence Tomography for the Identification of Macular Pathology in Patients with Diabetes.

INTRODUCTION: Handheld retinal imaging cameras are relatively inexpensive and highly portable devices that have the potential to significantly expand diabetic retinopathy (DR) screening, allowing a much broader population to be evaluated. However, it is essential to evaluate if these devices can accurately identify vision-threatening macular diseases if DR screening programs will rely on these instruments. Thus, the purpose of this study was to evaluate the detection of diabetic macular pathology using monoscopic macula-centered images using mydriatic handheld retinal imaging compared with spectral domain optical coherence tomography (SDOCT). METHODS: Mydriatic 40°-60° macula-centered images taken with 3 handheld retinal imaging devices (Aurora [AU], SmartScope [SS], RetinaVue 700 [RV]) were compared with the Cirrus 6000 SDOCT taken during the same visit. Images were evaluated for the presence of diabetic macular edema (DME) on monoscopic fundus photographs adapted from Early Treatment Diabetic Retinopathy Study (ETDRS) definitions (no DME, noncenter-involved DME [non-ciDME], and center-involved DME [ciDME]). Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for each device with SDOCT as gold standard. RESULTS: Severity by ETDRS photos: no DR 33.3%, mild NPDR 20.4%, moderate 14.2%, severe 11.6%, proliferative 20.4%, and ungradable for DR 0%; no DME 83.1%, non-ciDME 4.9%, ciDME 12.0%, and ungradable for DME 0%. Gradable images by SDOCT (N = 217, 96.4%) showed no DME in 75.6%, non-ciDME in 9.8%, and ciDME in 11.1%. The ungradable rate for images (poor visualization in >50% of the macula) was AU: 0.9%, SS: 4.4%, and RV: 6.2%. For DME, sensitivity and specificity were similar across devices (0.5-0.64, 0.93-0.97). For nondiabetic macular pathology (ERM, pigment epithelial detachment, traction retinal detachment) across all devices, sensitivity was low to moderate (0.2-0.5) but highly specific (0.93-1.00). CONCLUSIONS: Compared to SDOCT, handheld macular imaging attained high specificity but low sensitivity in identifying macular pathology. This suggests the importance of SDOCT evaluation for patients suspected to have DME on fundus photography, leading to more appropriate referral refinement.

Effect of Accessible Nonmydriatic Retinal Imaging on Diabetic Retinopathy Surveillance Rates.

Purpose: To evaluate the impact on surveillance rates for diabetic retinopathy (DR) by providing nonmydriatic retinal imaging as part of comprehensive diabetes care at no cost to patients or insurers. Methods: A retrospective comparative cohort study was designed. Patients were imaged from April 1, 2016 to March 31, 2017 at a tertiary diabetes-specific academic medical center. Retinal imaging was provided without additional cost beginning October 16, 2016. Images were evaluated for DR and diabetic macular edema using standard protocol at a centralized reading center. Diabetes surveillance rates before and after no-cost imaging were compared. Results: A total of 759 and 2,080 patients respectively were imaged before and after offering no-cost retinal imaging. The difference represents a 274% increase in the number of patients screened. Furthermore, there was a 292% and 261% increase in the number of eyes with mild DR and referable DR, respectively. In the comparative 6-month period, 92 additional cases of proliferative DR were identified, estimated to prevent 6.7 cases of severe visual loss with annual cost savings of $180,230 (estimated yearly cost of severe vision loss per person: $26,900). In patients with referable DR, self-awareness was low, with no significant difference in the before and after groups (39.4% vs. 43.8%, p = 0.3725). Conclusions: Providing retinal imaging as part of comprehensive diabetes care substantially increased the number of patients identified by nearly threefold. The data suggest that the removal of out-of-pocket costs substantially increased patient surveillance rates, which may translate to improved long-term patient outcomes.

ASSESSMENT OF FLUORESCEIN ANGIOGRAPHY NONPERFUSION IN EYES WITH DIABETIC RETINOPATHY USING ULTRAWIDE FIELD RETINAL IMAGING.

PURPOSE: Evaluate association of retinal nonperfusion (NP) on ultrawide field (UWF) fluorescein angiography (FA) with diabetic retinopathy (DR) severity and predominantly peripheral lesions (PPL). METHODS: Multicenter observational study, 652 eyes (361 participants) having nonproliferative DR (NPDR) without center-involved diabetic macular edema in at least one eye. Baseline 200° UWF-color and UWF-FA images were graded by a central reading center for color-PPL and FA-PPL, respectively. UWF-FA was graded for NP index within concentric zones: posterior pole (<10 mm from fovea), midperiphery (10-15 mm), and far periphery (>15 mm). RESULTS: Baseline Early Treatment Diabetic Retinopathy Study DR severity was 31.7% no DR/mild NPDR, 24.1% moderate NPDR, 14.0% moderately severe NPDR, 25.6% severe/very severe NPDR, and 4.6% proliferative DR. Worse DR severity was associated with increased NP index overall (P = 0.002), in the posterior pole (P < 0.001), midperiphery (P < 0.001), and far periphery (P = 0.03). On average, 29.6% of imaged retinal NP was in the posterior pole, 33.7% in midperiphery, and 36.7% in far periphery. Increased NP index was associated with FA-PPL (P < 0.001) but not with color-PPL (P = 0.65). CONCLUSION: Approximately, 70% of NP in diabetic eyes is located outside the posterior pole. Increased NP is associated with the presence of FA-PPL, suggesting UWF-FA may better predict future DR worsening than UWF-color alone.

Hemorrhage and/or Microaneurysm Severity and Count in Ultrawide Field Images and Early Treatment Diabetic Retinopathy Study Photography.

OBJECTIVE: To evaluate detection of hemorrhage and/or microaneurysm (H/Ma) using ultrawide field (UWF) retinal imaging as compared with standard Early Treatment Diabetic Retinopathy Study (ETDRS) 7-field photographs (ETDRS photos). DESIGN: Single-site comparative study of UWF images and ETDRS photos. PARTICIPANTS: One hundred twenty-six eyes of 69 patients with no diabetic retinopathy (DR) or mild or moderate nonproliferative DR (NPDR). METHODS: Stereoscopic 200° UWF images and stereoscopic 35mm 30° 7-field color photographs were acquired on the same visit. Images were graded for severity and distribution of H/Ma. H/Mas were counted in ETDRS fields 2 to 7 in both ETDRS photos and UWF images. H/Mas in the UWF peripheral fields were also counted. MAIN OUTCOME MEASURES: Kappa (κ) and weighted κ statistics for agreement. Number of H/Ma within and outside ETDRS fields identified in UWF images and ETDRS photos. RESULTS: Distribution of DR severity by ETDRS photos was 24 (19.0%) no DR, 48 (38.1%) mild NPDR, and 54 (42.9%) moderate NPDR. A total of 748 of 756 fields (98.9%) were gradable for H/Mas on ETDRS photos and UWF images. Simple κ/weighted κ statistics for severity of H/Ma: all fields 0.61/0.69, field 2 0.70/0.77, field 3 0.62/0.73, field 4 0.50/0.62, field 5 0.54/0.65, field 6 0.64/0.70, and field 7 0.58/0.63 with overall exact agreement in 81.3% and within 1 step in 97.9% of fields. A greater proportion of fields was graded a more severe H/Ma level in UWF images than in the corresponding ETDRS photos (UWF: 12.7% vs. ETDRS: 6.5%). Evaluating comparable areas in UWF images and ETDRS photos (fields 2-7), a mean of 42.8 H/Mas were identified using ETDRS photos and 48.8 in UWF images (P = 0.10). An additional mean of 21.3 H/Mas (49.8% increase, P < 0.0001) were identified in the peripheral fields of the UWF images. CONCLUSIONS: There is good to excellent agreement between UWF images and ETDRS photos in determining H/Ma severity, with excellent correlation of H/Ma counts within ETDRS photo fields. UWF peripheral fields identified 49.8% more H/Ma, suggesting a more severe H/Ma in 12.7% of eyes. Given the additional lesions detected in peripheral fields and the known risks associated with H/Ma and peripheral lesions, quantification of H/Ma using UWF images may provide a more accurate representation of DR disease activity and potential greater accuracy in predicting DR progression.

Identification of Diabetic Retinopathy and Ungradable Image Rate with Ultrawide Field Imaging in a National Teleophthalmology Program.

PURPOSE: To compare diabetic retinopathy (DR) identification and ungradable image rates between nonmydriatic ultrawide field (UWF) imaging and nonmydriatic multifield fundus photography (NMFP) in a large multistate population-based DR teleophthalmology program. DESIGN: Multiple-site, nonrandomized, consecutive, cross-sectional, retrospective, uncontrolled imaging device evaluation. PARTICIPANTS: Thirty-five thousand fifty-two eyes (17 526 patients) imaged using NMFP and 16 218 eyes (8109 patients) imaged using UWF imaging. METHODS: All patients undergoing Joslin Vision Network (JVN) imaging with either NMFP or UWF imaging from May 1, 2014, through August 30, 2015, within the Indian Health Service-JVN program, which serves American Indian and Alaska Native communities at 97 sites across 25 states, were evaluated. All retinal images were graded using a standardized validated protocol in a centralized reading center. MAIN OUTCOME MEASURES: Ungradable rate for DR and diabetic macular edema (DME). RESULTS: The ungradable rate per patient for DR and DME was significantly lower with UWF imaging compared with NMFP (DR, 2.8% vs. 26.9% [P < 0.0001]; DME, 3.8% vs. 26.2% [P < 0.0001]). Identification of eyes with either DR or referable DR (moderate nonproliferative DR or DME or worse) was increased using UWF imaging from 11.7% to 24.2% (P < 0.0001) and from 6.2% to 13.6% (P < 0.0001), respectively. In eyes with DR imaged with UWF imaging (n = 3926 eyes of 2402 patients), the presence of predominantly peripheral lesions suggested a more severe level of DR in 7.2% of eyes (9.6% of patients). CONCLUSIONS: In a large, widely distributed DR ocular telehealth program, as compared with NMFP, nonmydriatic UWF imaging reduced the number of ungradable eyes by 81%, increased the identification of DR nearly 2-fold, and identified peripheral lesions suggesting more severe DR in almost 10% of patients, thus demonstrating significant benefits of this imaging method for large DR teleophthalmology programs.

Operational Components of Telemedicine Programs for Diabetic Retinopathy.

Diabetic retinopathy is a leading cause of new-onset vision loss worldwide. Treatments supported by large clinical trials are effective in preserving vision, but many persons do not receive timely diagnosis and treatment of diabetic retinopathy, which is typically asymptomatic when most treatable. Telemedicine evaluation to identify diabetic retinopathy has the potential to improve access to care and improve outcomes, but incomplete implementation of published standards creates a risk to program utility and sustainability. In a prior article, we reviewed the literature regarding the impact of imaging device, number and size of retinal images, pupil dilation, type of image grader, and diagnostic accuracy on telemedicine assessment for diabetic retinopathy. This article reviews the literature regarding the impact of automated image grading, cost effectiveness, program standards, and quality assurance (QA) on telemedicine assessment of diabetic retinopathy. Telemedicine assessment of diabetic retinopathy has the potential to preserve vision, but greater attention to development and implementation of standards is needed to better realize its potential.

Clinical Components of Telemedicine Programs for Diabetic Retinopathy.

Diabetic retinopathy is a leading cause of new-onset vision loss worldwide. Treatments supported by large clinical trials are effective in preserving vision, but many persons do not receive timely diagnosis and treatment of diabetic retinopathy, which is typically asymptomatic when most treatable. Telemedicine evaluation to identify diabetic retinopathy has the potential to improve access to care, but there are no universal standards regarding camera choice or protocol for ocular telemedicine. We review the literature regarding the impact of imaging device, number and size of retinal images, pupil dilation, type of image grader, and diagnostic accuracy on telemedicine assessment for diabetic retinopathy. Telemedicine assessment of diabetic retinopathy has the potential to preserve vision, but further development of telemedicine specific technology and standardization of operations are needed to better realize its potential.

Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images.

Glaucoma is one of the leading causes of blindness worldwide. There is no cure for glaucoma but detection at its earliest stage and subsequent treatment can aid patients to prevent blindness. Currently, optic disc and retinal imaging facilitates glaucoma detection but this method requires manual post-imaging modifications that are time-consuming and subjective to image assessment by human observers. Therefore, it is necessary to automate this process. In this work, we have first proposed a novel computer aided approach for automatic glaucoma detection based on Regional Image Features Model (RIFM) which can automatically perform classification between normal and glaucoma images on the basis of regional information. Different from all the existing methods, our approach can extract both geometric (e.g. morphometric properties) and non-geometric based properties (e.g. pixel appearance/intensity values, texture) from images and significantly increase the classification performance. Our proposed approach consists of three new major contributions including automatic localisation of optic disc, automatic segmentation of disc, and classification between normal and glaucoma based on geometric and non-geometric properties of different regions of an image. We have compared our method with existing approaches and tested it on both fundus and Scanning laser ophthalmoscopy (SLO) images. The experimental results show that our proposed approach outperforms the state-of-the-art approaches using either geometric or non-geometric properties. The overall glaucoma classification accuracy for fundus images is 94.4% and accuracy of detection of suspicion of glaucoma in SLO images is 93.9 %.

Diabetic Retinopathy Severity and Peripheral Lesions Are Associated with Nonperfusion on Ultrawide Field Angiography.

PURPOSE: To assess whether the presence of peripheral nonperfusion on ultrawide field (UWF) fluorescein angiography (FA) is associated with diabetic retinopathy (DR) severity and the presence of predominantly peripheral lesions (PPLs). DESIGN: Single-site, cross-sectional, retrospective study. PARTICIPANTS: Sixty-eight eyes of 37 diabetic subjects with or without DR and no history of prior panretinal laser photocoagulation. METHODS: Both 200° UWF images and UWF FA images were acquired at the same visit. Early Treatment Diabetic Retinopathy Study (ETDRS) templates were overlaid digitally based on disc and macula location onto stereographically projected UWF images. Images were evaluated for the presence of PPLs, defined as more than 50% of the graded lesion located outside the ETDRS field in each of the 5 extended fields. The UWF-FA images were evaluated by 2 masked, independent graders for extent of retinal nonperfusion area (NPA) and nonperfusion index (NPI; nonperfused/total gradable area). MAIN OUTCOME MEASURES: Association of NPA and NPI with DR severity and presence of PPLs. RESULTS: Distribution of DR severity was as follows: no DR, 8.8% eyes; mild nonproliferative DR (NPDR), 17.6%; moderate NPDR, 32.4%; severe NPDR, 17.6%; proliferative DR (PDR), 19.1%; and high-risk PDR, 4.4%; with PPL present in 61.8%. There was strong intragrader (r = 0.95) and intergrader (r = 0.86) agreement for NPA. Presence of PPLs was associated with increased NPA (191.8 mm(2) vs. 306.1 mm(2); P = 0.0019) and NPI (0.25 vs. 0.43; P = 0.0003). These relationships remained significant after adjusting for DR severity and diabetes duration. In eyes without PDR (n = 52), increasing NPA and NPI was associated with worsening DR (NPA, P = 0.001; NPI, P = 0.0003). NPA and NPI were not associated with clinically significant macular edema (NPA, P = 0.99; NPI, P = 0.67), nor correlated with visual acuity (NPA, r = 0.14, P = 0.23; NPI, r = 0.24, P = 0.05). CONCLUSIONS: Following a standardized protocol, the evaluation of UWF FA for NPA and NPI is reproducible. Both parameters are correlated highly with the presence of PPLs and DR severity. Given that the presence and extent of PPLs have been associated with increased risks of DR progression, the clinical identification of PPLs may reflect closely the extent of nonperfusion and ischemia, thus accounting for the increased risk of progression.

Peripheral Lesions Identified on Ultrawide Field Imaging Predict Increased Risk of Diabetic Retinopathy Progression over 4 Years.

OBJECTIVE: To determine whether peripheral diabetic retinopathy (DR) lesions identified on ultrawide field (UWF) imaging are associated with increased DR progression. DESIGN: Prospective, longitudinal cohort. PARTICIPANTS: Two hundred eyes of 100 participants previously enrolled in a comparative instrument validation study. METHODS: Baseline mydriatic 7-standard field Early Treatment Diabetic Retinopathy Study (ETDRS) photographs and UWF images were obtained. On UWF images, DR lesions with a greater extent outside versus inside standard ETDRS fields were defined as predominantly peripheral lesions (PPLs). Follow-up ETDRS photographs were obtained 4.2±0.3 years after baseline. Baseline and follow-up DR severity were graded from ETDRS photographs. MAIN OUTCOME MEASURES: Rates of 2-step or more progression and progression to proliferative DR (PDR) in eyes with PPLs compared with eyes without PPLs identified on UWF imaging at baseline. RESULTS: In eyes without PDR (n = 109) at baseline, 56 (51%) had at least 1 field with PPLs and 43 (39%) had DR progression. Compared with eyes without PPLs, eyes with PPLs had a 3.2-fold increased risk of 2-step or more DR progression (6 [11%] vs. 19 [34%]; P = 0.005) and a 4.7-fold increased risk for progression to PDR (3 [6%] vs. 14 [25%]; P = 0.005). These findings remained statistically significant after adjusting for gender, diabetes type, diabetes duration, hemoglobin A1c (HbA1c) levels, and baseline DR severity. Increasing extent of fields with PPLs increased the risk for 2-step or more DR progression (P = 0.004) and progression to PDR (P = 0.009). CONCLUSIONS: Presence and increasing extent of PPLs were associated with increased risk of DR progression over 4 years, independent of baseline DR severity and HbA1c levels. Increasing extent of PPLs substantially increased the risk of DR progression and progression to PDR, especially with less severe DR at baseline. These findings demonstrate that detailed peripheral retinal evaluation provides important information that is necessary to assess completely the risk of DR progression.

Automated retinal image analysis for diabetic retinopathy in telemedicine.

There will be an estimated 552 million persons with diabetes globally by the year 2030. Over half of these individuals will develop diabetic retinopathy, representing a nearly insurmountable burden for providing diabetes eye care. Telemedicine programmes have the capability to distribute quality eye care to virtually any location and address the lack of access to ophthalmic services. In most programmes, there is currently a heavy reliance on specially trained retinal image graders, a resource in short supply worldwide. These factors necessitate an image grading automation process to increase the speed of retinal image evaluation while maintaining accuracy and cost effectiveness. Several automatic retinal image analysis systems designed for use in telemedicine have recently become commercially available. Such systems have the potential to substantially improve the manner by which diabetes eye care is delivered by providing automated real-time evaluation to expedite diagnosis and referral if required. Furthermore, integration with electronic medical records may allow a more accurate prognostication for individual patients and may provide predictive modelling of medical risk factors based on broad population data.

Visual outcomes from pars plana vitrectomy versus combined pars plana vitrectomy, phacoemulsification, and intraocular lens implantation in patients with diabetes.

PURPOSE: To compare visual acuity outcomes and diabetic retinopathy progression after pars plana vitrectomy (PPV) versus combined pars plana vitrectomy and phacoemulsification (PPVCE) in patients with diabetes. METHODS: Retrospective review of 222 consecutive diabetic patients undergoing PPV or PPVCE. RESULTS: A total of 251 eyes of 222 patients were evaluated (PPV = 122, PPVCE = 129). Four-year follow-up was 64% (161 eyes). Overall, patients undergoing PPVCE had better preoperative visual acuity (PPVCE = 20/80, PPV = 20/160, P = 0.03). At 4-year follow-up, visual acuity improved (PPV = +22, PPVCE = +11 letters) compared with baseline in both groups. After correcting for baseline differences in visual acuity, no statistically significant difference in final visual acuity was observed (PPVCE = 20/32, PPV = 20/50, P = 0.09). Results did not differ substantially by surgical indication (vitreous hemorrhage, traction retinal detachment, epiretinal membrane, and/or diabetic macular edema). Cataract progression occurred in 64%, and cataract surgery was performed in 39% of phakic eyes undergoing PPV. Rates of diabetic retinopathy progression, vitreous hemorrhage, and retinal detachment were not statistically different. Neovascular glaucoma developed in 2 patients (2%) after PPV and 6 patients (8%) after PPVCE (P = 0.07). CONCLUSION: In diabetic patients, equivalent visual acuity improvement over 4 years was observed after PPV or PPVCE. Visual outcomes and retinopathy progression rates were not significantly different after either intervention, suggesting that PPVCE may be appropriate when indicated in patients with diabetes.

Macula vs periphery in diabetic retinopathy: OCT-angiography and ultrawide field fluorescein angiography imaging of retinal non perfusion.

OBJECTIVES: To investigate the association between peripheral non-perfusion index (NPI) on ultrawide-field fluorescein angiography (UWF-FA) and quantitative OCT-Angiography (OCT-A) metrics in the macula. METHODS: In total, 48 eyes with UWF-colour fundus photos (CFP), UWF-FA (California, Optos) and OCT-A (Spectralis, Heidelberg) were included. OCT-A (3 × 3 mm) was used to determine foveal avascular zone (FAZ) parameters and vessel density (VD), perfusion density (PD), fractal dimension (FD) on superficial capillary plexus (SCP). NPI's extent and distribution was determined on UWF-FA within fovea centred concentric rings corresponding to posterior pole (<10 mm), mid-periphery (10-15 mm), and far-periphery (>15 mm) and within the total retinal area, the central macular field (6×6 mm), ETDRS fields and within each extended ETDRS field (P3-P7). RESULTS: Macular PD was correlated to NPI in total area of retina (Spearman ρ = 0.69, p < 0.05), posterior pole (ρ = 0.48, p < 0.05), mid-periphery (ρ = 0.65, p < 0.05), far-periphery (ρ = 0.59, p < 0.05), P3-P7 (ρ = 0,55 at least, p < 0.05 for each), central macula (ρ = 0.47, p < 0.05), total area in ETDRS (ρ = 0.55, p < 0.05). Macular VD and FD were correlated to NPI of total area of the retina (ρ = 0.60 and 0.61, p < 0.05), the mid-periphery (ρ = 0.56, p < 0.05) and far-periphery (ρ = 0.60 and ρ = 0.61, p < 0.05), and in P3-P7 (p < 0.05). FAZ perimeter was significantly corelated to NPI at posterior pole and central macular area (ρ = 0.37 and 0.36, p < 0.05), and FAZ area to NPI in central macular area (ρ = 0.36, p < 0.05). CONCLUSIONS: Perfusion macular metrics on OCT-A correlated with UWF-FA's non-perfusion (NP), particularly in the retina's mid and far periphery, suggesting that OCT-A might be a useful non-invasive method to estimate peripheral retinal NP.

Disparities Between Teleretinal Imaging Findings and Patient-Reported Diabetic Retinopathy Status and Follow-up Eye Care Interval: A 10-Year Prospective Study.

OBJECTIVE: To assess self-reported awareness of diabetic retinopathy (DR) and concordance of eye examination follow-up compared with findings from concurrent retinal images. RESEARCH DESIGN AND METHODS: We conducted a prospective observational 10-year study of 26,876 consecutive patients with diabetes who underwent retinal imaging during an endocrinology visit. Awareness and concordance were evaluated using questionnaires and retinal imaging. RESULTS: Awareness information and gradable images were available in 25,360 patients (94.3%). Severity of DR by imaging was as follows: no DR (n = 14,317; 56.5%), mild DR (n = 6,805; 26.8%), or vision-threatening DR (vtDR; n = 4,238; 16.7%). In the no, mild, and vtDR groups, 96.7%, 88.5%, and 54.9% of patients, respectively, reported being unaware of any prior DR. When DR was present, reporting no prior DR was associated with shorter diabetes duration, milder DR, last eye examination >1 year before, no dilation, no scheduled appointment, and less specialized provider (all P < 0.001). Among patients with vtDR, 41.2%, 58.1%, and 64.2% did not report being aware of any DR and follow-up was concordant with current DR severity in 66.7%, 41.3%, and 25.4% (P < 0.001) of patients when prior examination was performed by a retinal specialist, nonretinal ophthalmologist, or optometrist (P < 0.001), respectively. CONCLUSIONS: Substantial discrepancies exist between DR presence, patient awareness, and concordance of follow-up across all DR severity levels. These discrepancies are present across all eye care provider types, with the magnitude influenced by provider type. Therefore, patient self-report should not be relied upon to reflect DR status. Modification of medical care and education models may be necessary to enhance retention of ophthalmic knowledge in patients with diabetes and ensure accurate communication between all health care providers.

Accuracy of Integrated Artificial Intelligence Grading Using Handheld Retinal Imaging in a Community Diabetic Eye Screening Program.

Purpose: To evaluate mydriatic handheld retinal imaging performance assessed by point-of-care (POC) artificial intelligence (AI) as compared with retinal image graders at a centralized reading center (RC) in identifying diabetic retinopathy (DR) and diabetic macular edema (DME). Design: Prospective, comparative study. Subjects: Five thousand five hundred eighty-five eyes from 2793 adult patients with diabetes. Methods: Point-of-care AI assessment of disc and macular handheld retinal images was compared with RC evaluation of validated 5-field handheld retinal images (disc, macula, superior, inferior, and temporal) in identifying referable DR (refDR; defined as moderate nonproliferative DR [NPDR], or worse, or any level of DME) and vision-threatening DR (vtDR; defined as severe NPDR or worse, or any level of center-involving DME [ciDME]). Reading center evaluation of the 5-field images followed the international DR/DME classification. Sensitivity (SN) and specificity (SP) for ungradable images, refDR, and vtDR were calculated. Main Outcome Measures: Agreement for DR and DME; SN and SP for refDR, vtDR, and ungradable images. Results: Diabetic retinopathy severity by RC evaluation: no DR, 67.3%; mild NPDR, 9.7%; moderate NPDR, 8.6%; severe NPDR, 4.8%; proliferative DR, 3.8%; and ungradable, 5.8%. Diabetic macular edema severity by RC evaluation was as follows: no DME (80.4%), non-ciDME (7.7%), ciDME (4.4%), and ungradable (7.5%). Referable DR was present in 25.3% and vtDR was present in 17.5% of eyes. Images were ungradable for DR or DME in 7.5% by RC evaluation and 15.4% by AI. There was substantial agreement between AI and RC for refDR (κ = 0.66) and moderate agreement for vtDR (κ = 0.54). The SN/SP of AI grading compared with RC evaluation was 0.86/0.86 for refDR and 0.92/0.80 for vtDR. Conclusions: This study demonstrates that POC AI following a defined handheld retinal imaging protocol at the time of imaging has SN and SP for refDR that meets the current United States Food and Drug Administration thresholds of 85% and 82.5%, but not for vtDR. Integrating AI at the POC could substantially reduce centralized RC burden and speed information delivery to the patient, allowing more prompt eye care referral. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Automated Machine Learning for Predicting Diabetic Retinopathy Progression From Ultra-Widefield Retinal Images.

Importance: Machine learning (ML) algorithms have the potential to identify eyes with early diabetic retinopathy (DR) at increased risk for disease progression. Objective: To create and validate automated ML models (autoML) for DR progression from ultra-widefield (UWF) retinal images. Design, Setting and Participants: Deidentified UWF images with mild or moderate nonproliferative DR (NPDR) with 3 years of longitudinal follow-up retinal imaging or evidence of progression within 3 years were used to develop automated ML models for predicting DR progression in UWF images. All images were collected from a tertiary diabetes-specific medical center retinal image dataset. Data were collected from July to September 2022. Exposure: Automated ML models were generated from baseline on-axis 200° UWF retinal images. Baseline retinal images were labeled for progression based on centralized reading center evaluation of baseline and follow-up images according to the clinical Early Treatment Diabetic Retinopathy Study severity scale. Images for model development were split 8-1-1 for training, optimization, and testing to detect 1 or more steps of DR progression. Validation was performed using a 328-image set from the same patient population not used in model development. Main Outcomes and Measures: Area under the precision-recall curve (AUPRC), sensitivity, specificity, and accuracy. Results: A total of 1179 deidentified UWF images with mild (380 [32.2%]) or moderate (799 [67.8%]) NPDR were included. DR progression was present in half of the training set (590 of 1179 [50.0%]). The model's AUPRC was 0.717 for baseline mild NPDR and 0.863 for moderate NPDR. On the validation set for eyes with mild NPDR, sensitivity was 0.72 (95% CI, 0.57-0.83), specificity was 0.63 (95% CI, 0.57-0.69), prevalence was 0.15 (95% CI, 0.12-0.20), and accuracy was 64.3%; for eyes with moderate NPDR, sensitivity was 0.80 (95% CI, 0.70-0.87), specificity was 0.72 (95% CI, 0.66-0.76), prevalence was 0.22 (95% CI, 0.19-0.27), and accuracy was 73.8%. In the validation set, 6 of 9 eyes (75%) with mild NPDR and 35 of 41 eyes (85%) with moderate NPDR progressed 2 steps or more were identified. All 4 eyes with mild NPDR that progressed within 6 months and 1 year were identified, and 8 of 9 (89%) and 17 of 20 (85%) with moderate NPDR that progressed within 6 months and 1 year, respectively, were identified. Conclusions and Relevance: This study demonstrates the accuracy and feasibility of automated ML models for identifying DR progression developed using UWF images, especially for prediction of 2-step or greater DR progression within 1 year. Potentially, the use of ML algorithms may refine the risk of disease progression and identify those at highest short-term risk, thus reducing costs and improving vision-related outcomes.

Peripheral lesions identified by mydriatic ultrawide field imaging: distribution and potential impact on diabetic retinopathy severity.

OBJECTIVE: To assess diabetic retinopathy (DR) as determined by lesions identified using mydriatic ultrawide field imaging (DiSLO200; Optos plc, Scotland, UK) compared with Early Treatment Diabetic Retinopathy Study (ETDRS) 7-standard field film photography. DESIGN: Prospective comparative study of DiSLO200, ETDRS 7-standard field film photographs, and dilated fundus examination (DFE). PARTICIPANTS: A total of 206 eyes of 103 diabetic patients selected to represent all levels of DR. METHODS: Subjects had DiSLO200, ETDRS 7-standard field film photographs, and DFE. Images were graded for severity and distribution of DR lesions. Discrepancies were adjudicated, and images were compared side by side. MAIN OUTCOME MEASURES: Distribution of hemorrhage and/or microaneurysm (H/Ma), venous beading (VB), intraretinal microvascular abnormality (IRMA), and new vessels elsewhere (NVE). Kappa (κ) and weighted κ statistics for agreement. RESULTS: The distribution of DR severity by ETDRS 7-standard field film photographs was no DR 12.5%; nonproliferative DR mild 22.5%, moderate 30%, and severe/very severe 8%; and proliferative DR 27%. Diabetic retinopathy severity between DiSLO200 and ETDRS film photographs matched in 80% of eyes (weighted κ = 0.74,κ = 0.84) and was within 1 level in 94.5% of eyes. DiSLO200 and DFE matched in 58.8% of eyes (weighted κ = 0.69,κ = 0.47) and were within 1 level in 91.2% of eyes. Forty eyes (20%) had DR severity discrepancies between DiSLO200 and ETDRS film photographs. The retinal lesions causing discrepancies were H/Ma 52%, IRMA 26%, NVE 17%, and VB 4%. Approximately one-third of H/Ma, IRMA, and NVE were predominantly outside ETDRS fields. Lesions identified on DiSLO200 but not ETDRS film photographs suggested a more severe DR level in 10% of eyes. Distribution in the temporal, superotemporal, inferotemporal, superonasal, and inferonasal fields was 77%, 72%, 61%, 65%, and 59% for H/Ma, respectively (P<0.0001); 22%, 24%, 21%, 28%, and 22% for VB, respectively (P = 0.009); 52%, 40%, 29%, 47%, and 36% for IRMA, respectively (P<0.0001), and 8%, 4%, 4%, 8%, and 5% for NVE, respectively (P = 0.03). All lesions were more frequent in the temporal fields compared with the nasal fields (P<0.0001). CONCLUSIONS: DiSLO200 images had substantial agreement with ETDRS film photographs and DFE in determining DR severity. On the basis of DiSLO200 images, significant nonuniform distribution of DR lesions was evident across the retina. The additional peripheral lesions identified by DiSLO200 in this cohort suggested a more severe assessment of DR in 10% of eyes than was suggested by the lesions within the ETDRS fields. However, the implications of peripheral lesions on DR progression within a specific ETDRS severity level over time are unknown and need to be evaluated prospectively.