Optical Coherence Tomography Classification Systems for Diabetic Macular Edema and Their Associations With Visual Outcome and Treatment Responses - An Updated Review

Faricimab Treat-and-Extend for Diabetic Macular Edema: Two-Year Results from the Randomized Phase 3 YOSEMITE and RHINE Trials

PURPOSE

To evaluate the 2-year efficacy, durability, and safety of dual angiopoietin-2 and vascular endothelial growth factor (VEGF) A pathway inhibition with intravitreal faricimab according to a personalized treat-and-extend (T&E)-based regimen with up to every-16-week dosing in the YOSEMITE and RHINE (ClinicalTrials.gov identifiers, NCT03622580 and NCT03622593, respectively) phase 3 trials of diabetic macular edema (DME).

DESIGN

Randomized, double-masked, noninferiority phase 3 trials.

PARTICIPANTS

Adults with visual acuity loss (best-corrected visual acuity [BCVA] of 25-73 letters) due to center-involving DME.

METHODS

Patients were randomized 1:1:1 to faricimab 6.0 mg every 8 weeks, faricimab 6.0 mg T&E (previously referred to as personalized treatment interval), or aflibercept 2.0 mg every 8 weeks. The T&E up to every-16-week dosing regimen was based on central subfield thickness (CST) and BCVA change.

MAIN OUTCOME MEASURES

Included changes from baseline in BCVA and CST, number of injections, durability, absence of fluid, and safety through week 100.

RESULTS

In YOSEMITE and RHINE (n = 940 and 951, respectively), noninferior year 1 visual acuity gains were maintained through year 2; mean BCVA change from baseline at 2 years (weeks 92, 96, and 100 average) with faricimab every 8 weeks (YOSEMITE and RHINE, +10.7 letters and +10.9 letters, respectively) or T&E (+10.7 letters and +10.1 letters, respectively) were comparable with aflibercept every 8 weeks (+11.4 letters and +9.4 letters, respectively). The median number of study drug injections was lower with faricimab T&E (YOSEMITE and RHINE, 10 and 11 injections, respectively) versus faricimab every 8 weeks (15 injections) and aflibercept every 8 weeks (14 injections) across both trials during the entire study. In the faricimab T&E arms, durability was improved further during year 2, with > 60% of patients receiving every-16-week dosing and approximately 80% receiving every-12-week or longer dosing at week 96. Almost 80% of patients who achieved every-16-week dosing at week 52 maintained every-16-week dosing without an interval reduction through week 96. Mean CST reductions were greater (YOSEMITE/RHINE weeks 92/96/100 average: faricimab every 8 weeks -216.0/-202.6 µm, faricimab T&E -204.5/-197.1 µm, aflibercept every 8 weeks -196.3/-185.6 µm), and more patients achieved absence of DME (CST < 325 μm; YOSEMITE/RHINE weeks 92-100: faricimab every 8 weeks 87%-92%/88%-93%, faricimab T&E 78%-86%/85%-88%, aflibercept every 8 weeks 77%-81%/80%-84%) and absence of intraretinal fluid (YOSEMITE/RHINE weeks 92-100: faricimab every 8 weeks 59%-63%/56%-62%, faricimab T&E 43%-48%/45%-52%, aflibercept every 8 weeks 33%-38%/39%-45%) with faricimab every 8 weeks or T&E versus aflibercept every 8 weeks through year 2. Overall, faricimab was well tolerated, with a safety profile comparable with that of aflibercept.

CONCLUSIONS

Clinically meaningful visual acuity gains from baseline, anatomic improvements, and extended durability with intravitreal faricimab up to every 16 weeks were maintained through year 2. Faricimab given as a personalized T&E-based dosing regimen supports the role of dual angiopoietin-2 and VEGF-A inhibition to promote vascular stability and to provide durable efficacy for patients with DME.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Machine learning and optical coherence tomography-derived radiomics analysis to predict persistent diabetic macular edema in patients undergoing anti-VEGF intravitreal therapy

BACKGROUND

Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. This study aimed to develop and evaluate an OCT-omics prediction model for assessing anti-vascular endothelial growth factor (VEGF) treatment response in patients with DME.

METHODS

A retrospective analysis of 113 eyes from 82 patients with DME was conducted. Comprehensive feature engineering was applied to clinical and optical coherence tomography (OCT) data. Logistic regression, support vector machine (SVM), and backpropagation neural network (BPNN) classifiers were trained using a training set of 79 eyes, and evaluated on a test set of 34 eyes. Clinical implications of the OCT-omics prediction model were assessed by decision curve analysis. Performance metrics (sensitivity, specificity, F1 score, and AUC) were calculated.

RESULTS

The logistic, SVM, and BPNN classifiers demonstrated robust discriminative abilities in both the training and test sets. In the training set, the logistic classifier achieved a sensitivity of 0.904, specificity of 0.741, F1 score of 0.887, and AUC of 0.910. The SVM classifier showed a sensitivity of 0.923, specificity of 0.667, F1 score of 0.881, and AUC of 0.897. The BPNN classifier exhibited a sensitivity of 0.962, specificity of 0.926, F1 score of 0.962, and AUC of 0.982. Similar discriminative capabilities were maintained in the test set. The OCT-omics scores were significantly higher in the non-persistent DME group than in the persistent DME group (p < 0.001). OCT-omics scores were also positively correlated with the rate of decline in central subfield thickness after treatment (Pearson's R = 0.44, p < 0.001).

CONCLUSION

The developed OCT-omics model accurately assesses anti-VEGF treatment response in DME patients. The model's robust performance and clinical implications highlight its utility as a non-invasive tool for personalized treatment prediction and retinal pathology assessment.

Explainable ensemble learning method for OCT detection with transfer learning

The accuracy and interpretability of artificial intelligence (AI) are crucial for the advancement of optical coherence tomography (OCT) image detection, as it can greatly reduce the manual labor required by clinicians. By prioritizing these aspects during development and application, we can make significant progress towards streamlining the clinical workflow. In this paper, we propose an explainable ensemble approach that utilizes transfer learning to detect fundus lesion diseases through OCT imaging. Our study utilized a publicly available OCT dataset consisting of normal subjects, patients with dry age-related macular degeneration (AMD), and patients with diabetic macular edema (DME), each with 15 samples. The impact of pre-trained weights on the performance of individual networks was first compared, and then these networks were ensemble using majority soft polling. Finally, the features learned by the networks were visualized using Grad-CAM and CAM. The use of pre-trained ImageNet weights improved the performance from 68.17% to 92.89%. The ensemble model consisting of the three CNN models with pre-trained parameters loaded performed best, correctly distinguishing between AMD patients, DME patients and normal subjects 100% of the time. Visualization results showed that Grad-CAM could display the lesion area more accurately. It is demonstrated that the proposed approach could have good performance of both accuracy and interpretability in retinal OCT image detection.

Application of optical coherence tomography angiography in the assessment of diabetic macular edema staging and laser photocoagulation efficacy

OBJECTIVE

This study aimed to analyze the effect of optical coherence tomography angiography (OCTA) on diabetic macular edema (DME) staging and assess the efficacy of laser photocoagulation.

METHODS

Eighty-six patients (141 eyes) with suspected DME who visited our hospital from August 2019 to March 2022 were selected and underwent fundus angiography and OCTA. The two examination methods were compared in terms of their efficacy in macular edema staging. Subsequently, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of OCTA in diagnosing DME were assessed using fundus angiography as the gold standard. In patients with clinically significant macular edema (CSME) treated with laser photocoagulation, the central concave non-perfused zone (FAZ), vascular density (VD), central macular retinal thickness (CRT), whole retinal blood flow density (FD-300), superficial capillary plexus (SCP), and deep capillary plexus (DCP) were measured using the OCTA 3 mm × 3 mm mode before treatment, at 3 months after treatment, and at 6 months after treatment. SCP, deep capillary plexus (DCP), blood flow density (VD), best corrected visual acuity (BCVA), and central retinal thickness (CRT) were recorded before treatment, 3 months after treatment, and 6 months after treatment. The correlation between BCVA and pre-treatment OCTA parameters at 6 months after treatment was analyzed using Pearson's correlation.

RESULTS

Fundus angiography was performed in 86 patients (141 eyes) with suspected DME. Of the 141 eyes, 44 had no leakage, 52 had diffuse edema, 40 had focal macular edema, and 5 had eyes ischemia. A total of 97 eyes showed CSME on fundus angiography. Using fundus angiography as the gold standard, OCTA exhibited a sensitivity of 97.94 %, a specificity of 63.64 %, and an accuracy of 87.23 % in diagnosing CSME. The Kappa value between OCTA and fundus angiography was 0.674. The receiver operating characteristic curve revealed that the area under the curve (AUC) of OCTA in diagnosing CSME was 0.808 (95 % confidence interval: 0.717-0.899). The BCVA was higher, while the CRT was lower in CSME patients at 3 and 6 months after treatment (P<0.05). No significant difference was observed in the OCTA parameters in CSME patients at 3 months after treatment compared with that before treatment (P>0.05). Similarly, no significant difference was found in the FD300 of CSME patients at 6 months after treatment compared with that before treatment (P>0.05). However, the FAZ area, DCP-VD (overall, central concave, and paracentral concave), and SCP-VD (overall, central concave, and paracentral concave) were higher in CSME patients at 6 months after treatment compared with that before treatment (P<0.05). Pearson's correlation showed that BCVA was positively correlated with pre-treatment FAZ area, DCP-VD, and SCP-VD (r>0, P<0.05), and negatively associated with CRT (r<0, P<0.05).

CONCLUSION

OCTA exhibited high sensitivity and specificity in diagnosis and staging DME. It adeptly captures the microvascular and visual changes in the central macular recess before and after laser photocoagulation therapy, which can quantitatively guide the follow-up treatment of DME.

Risk Factors Associated with Diabetic Retinopathy with and without Macular Edema in Recently Diagnosed Patients with Type 2 Diabetes

Purpose

To evaluate the risk factors associated with diabetic macular edema (DME) in patients with a recent type 2 diabetes mellitus (T2DM) diagnosis.

Patients and Methods

We conducted a case-control study at a third-level hospital in Mexico City. We enrolled patients ≥18 years old, with T2DM less than five years of diagnosis, without disabling complications, and non-smokers. The control group was patients with diabetic retinopathy and without macular edema (DR-DME). Cases were patients with DR+DME. We measured fasting glucose, creatinine, lipid profile, urinary albumin/creatinine ratio (ACR), and HbA1c. An ophthalmological examination consisted of visual acuity measurement, digital three-field fundus photography with an automatic non-mydriatic camera, slit lamp, and Optical coherence tomography (OCT) examination.

Results

183 and 61 patients with DR-DME and DR+DME, respectively, were included in the analysis. The prevalence of mild DR was higher in the DR-DME group, but the frequencies of moderate and severe retinopathy were higher in the DR+DME group. Patients in the DR-DME group had better vision than those in the DR+DME group. Logistic regression analysis revealed that age (OR, 1.07), HbA1c (OR, 1.19), and Albumin-to-Creatinine Ratio (ACR) > 30 mg/g (OR, 3.37) were associated with an increased possibility of DME compared to DR-DME.

Conclusion

Our study provides insights into the association between risk factors and DME. We found a statistically strong association between HbA1c levels, age, and ACR. Patients with poor metabolic control should undergo an extensive medical examination to screen for DME, which may be related to the chronicity of DM and renal damage.

Optical coherence tomography in the management of diabetic macular oedema

Diabetic macular oedema (DMO) is the major cause of visual impairment in people with diabetes. Optical coherence tomography (OCT) is now the most widely used modality to assess presence and severity of DMO. DMO is currently broadly classified based on the involvement to the central 1 mm of the macula into non-centre or centre involved DMO (CI-DMO) and DMO can occur with or without visual acuity (VA) loss. This classification forms the basis of management strategies of DMO. Despite years of research on quantitative and qualitative DMO related features assessed by OCT, these do not fully inform physicians of the prognosis and severity of DMO relative to visual function. Having said that, recent research on novel OCT biomarkers development and re-defined classification of DMO show better correlation with visual function and treatment response. This review summarises the current evidence of the association of OCT biomarkers in DMO management and its potential clinical importance in predicting VA and anatomical treatment response. The review also discusses some future directions in this field, such as the use of artificial intelligence to quantify and monitor OCT biomarkers and retinal fluid and identify phenotypes of DMO, and the need for standardisation and classification of OCT biomarkers to use in future clinical trials and clinical practice settings as prognostic markers and secondary treatment outcome measures in the management of DMO.

Microinvasive pars plana vitrectomy combined with internal limiting membrane peeling versus anti-VEGF intravitreal injection for treatment-naïve diabetic macular edema (VVV-DME study): study protocol for a randomized controlled trial

BACKGROUND

Diabetic macular edema (DME) is the main cause of vision loss in diabetic patients. Currently, anti-vascular endothelial growth factor (VEGF) intravitreal injection stands as the first-line therapy for DME. However, some patients exhibit insufficient response to anti-VEGF agents and often require multiple injections, imposing psychological and economic burdens. While microinvasive pars plana vitrectomy (PPV) has been shown to be safe and effective in treating refractory DME, scant research has explored its application to treatment-naïve DME. The purpose of this study is to determine whether early PPV combined with internal limiting membrane (ILM) peeling can lessen the therapeutic burden of DME patients, prevent vision loss, and maintain long-term stabilization of diabetic retinopathy.

METHODS

This is a single-center, prospective, parallel-group, non-inferiority randomized controlled trial involving 102 DME participants. Participants will be randomly assigned to either the study group (PPV combined with ILM peeling) or the control group (conbercept intravitreal injection (IVC)) at a 1:1 ratio, with a scheduled follow-up at 12 months post-operation. Comparative analysis of results between the two groups will be conducted at months 1, 3, 6, and 12 after the intervention. The primary outcomes involve evaluating the changes in central subfield thickness (CST) and best corrected visual acuity (BCVA). The secondary outcomes include assessment of optical coherence tomography (OCT) and OCT angiography (OCTA) biomarkers, re-treatment and adverse events rates, diabetic retinopathy (DR) development, cost-effectiveness analysis, and vision-related quality of life (VRQL).

DISCUSSION

Some patients do not respond well to anti-VEGF drugs and repeated intravitreal injections increase the treatment burden for patients. The VVV study aims to explore whether PPV combined with ILM peeling could become an initial treatment option for treatment-naïve DME patients.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05728476. Registered on 15 February 2023.

A Photodynamic Therapy Index for Central Serous Chorioretinopathy to Predict Visual Prognosis Using Pretreatment Factors

PURPOSE

This study aimed to establish a treatment index based on functional outcomes of photodynamic therapy (PDT) for central serous chorioretinopathy (CSC).

DESIGN

A retrospective clinical case-control study.

METHODS

This was a single-institute study. Eighty (80) eyes with CSC, who were treated by PDT and whose subretinal fluid resolves within 6 months were divided into two groups: those with poor visual outcome (PVO) (best-corrected visual acuity [BCVA] ≤ 0.5 6 months post-PDT), and the remaining eyes (better visual outcome [BVO]). The areas under the curve (AUC) and cutoff values from receiver operating characteristic curves were examined. These was used to predict the groups using pretreatment BCVA and the thickness of each retinochoroidal layer.

RESULT

Twenty-one (21) eyes were in the PVO group and 59 eyes in the BVO group were included. The AUCs were 0.959 for BCVA, 0.959 for the thickness from the internal limiting membrane to the external limiting membrane (IET), 0.820 for the thickness from the external limiting membrane to the photoreceptor outer segment layer, 0.715 for the subfoveal retinal thickness, and 0.515 for the subfoveal choroidal thickness. The BCVA and IET cut-off values were 0.267 logMAR and 71.5 µm, respectively. Using the combination of the cutoff values of BCVA and IET, the highest values for the sensitivity, specificity, positive predictive value, and negative predictive value were 95.2%, 94.9%, 85.0%, and 98.0%, respectively.

CONCLUSION

The combination of pre-PDT BCVA and IET in CSC can accurately predict the post-treatment visual prognosis. These values could be used as a treatment index of PDT for CSC.

The Disorganization of Retinal Inner Layers Is Correlated to Müller Cells Impairment in Diabetic Macular Edema: An Imaging and Omics Study

The disorganization of retinal inner layers (DRIL) is an optical coherence tomography (OCT) biomarker strictly associated with visual outcomes in patients with diabetic macular edema (DME) whose pathophysiology is still unclear. The aim of this study was to characterize in vivo, using retinal imaging and liquid biopsy, DRIL in eyes with DME. This was an observational cross-sectional study. Patients affected by center-involved DME were enrolled. All patients underwent spectral domain optical coherence tomography (SD-OCT) and proteomic analysis of aqueous humor (AH). The presence of DRIL at OCT was analyzed by two masked retinal experts. Fifty-seven biochemical biomarkers were analyzed from AH samples. Nineteen eyes of nineteen DME patients were enrolled. DRIL was present in 10 patients (52.63%). No statistically significant difference was found between DME eyes with and without DRIL, considering the AH concentration of all the analyzed biomarkers except for glial fibrillary acidic protein (GFAP), a biomarker of Müller cells dysfunction (p = 0.02). In conclusion, DRIL, in DME eyes, seems to strictly depend on a major dysfunction of Müller cells, explaining its role not only as imaging biomarker, but also as visual function Müller cells-related parameter.

Validation of an Automated Artificial Intelligence Algorithm for the Quantification of Major OCT Parameters in Diabetic Macular Edema

Artificial intelligence (AI) and deep learning (DL)-based systems have gained wide interest in macular disorders, including diabetic macular edema (DME). This paper aims to validate an AI algorithm for identifying and quantifying different major optical coherence tomography (OCT) biomarkers in DME eyes by comparing the algorithm to human expert manual examination. Intraretinal (IRF) and subretinal fluid (SRF) detection and volumes, external limiting-membrane (ELM) and ellipsoid zone (EZ) integrity, and hyperreflective retina foci (HRF) quantification were analyzed. Three-hundred three DME eyes were included. The mean central subfield thickness was 386.5 ± 130.2 µm. IRF was present in all eyes and confirmed by AI software. The agreement (kappa value) (95% confidence interval) for SRF presence and ELM and EZ interruption were 0.831 (0.738–0.924), 0.934 (0.886–0.982), and 0.936 (0.894–0.977), respectively. The accuracy of the automatic quantification of IRF, SRF, ELM, and EZ ranged between 94.7% and 95.7%, while accuracy of quality parameters ranged between 99.0% (OCT layer segmentation) and 100.0% (fovea centering). The Intraclass Correlation Coefficient between clinical and automated HRF count was excellent (0.97). This AI algorithm provides a reliable and reproducible assessment of the most relevant OCT biomarkers in DME. It may allow clinicians to routinely identify and quantify these parameters, offering an objective way of diagnosing and following DME eyes.