Effect of Optical Coherence Tomography Patterns on One-year Outcomes of Aflibercept Therapy for Diabetic Macular Edema

Özçalışkan, Şehnaz; Balcı, Sevcan; Karasu, Buğra; Artunay, Özgür

doi:10.29271/jcpsp.2020.02.149

Cited by 5 publications

(6 citation statements)

References 16 publications

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“…Kim et al 33 have reported that the DRT subtype had greater BCVA improvement after anti-VEGF at 6 and 12 months compared to CME and SRD subtypes. Several other studies have confirmed the same 33–36 . Few other studies have shown that the presence of subretinal fluid was predictive of better anatomical and visual outcomes to anti-VEGF 18 and dexamethasone implant 37 .…”

Section: Sdoct–based Classification Systems For Dme Subtypes – An Upd...mentioning

confidence: 73%

“…Several other studies have confirmed the same. [33][34][35][36] Few other studies have shown that the presence of subretinal fluid was predictive of better anatomical and visual outcomes to anti-VEGF 18 and dexamethasone implant. 37 However, 1 study did not record any significant differences between the 3 groups in terms of percentage change in CST or change in BCVA.…”

Section: Morphology Of Dmementioning

confidence: 99%

“…31 The morphological differences were shown to be useful in determining treatment outcome, despite the differences in baseline VA between the subtypes being insignificant. [32][33][34] Kim et al 33 have reported that the DRT subtype had greater BCVA improvement after anti-VEGF at 6 and 12 months compared to CME and SRD subtypes. Several other studies have confirmed the same.…”

Section: Morphology Of Dmementioning

confidence: 99%

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

Hui

Szeto

Tang

et al. 2022

Asia-Pacific Journal of Ophthalmology

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Optical coherence tomography (OCT) is an invaluable imaging tool in detecting and assessing diabetic macular edema (DME). Over the past decade, there have been different proposed OCT-based classification systems for DME. In this review, we present an update of spectraldomain OCT (SDOCT)-based DME classifications over the past 5 years. In addition, we attempt to summarize the proposed OCT qualitative and quantitative parameters from different classification systems in relation to disease severity, risk of progression, and treatment outcome. Although some OCT-based measurements were found to have prognostic value on visual outcome, there has been a lack of consensus or guidelines on which parameters can be reliably used to predict treatment outcomes. We also summarize recent literatures on the prognostic value of these parameters including quantitative measures such as macular thickness or volume, central subfield thickness or foveal thickness, and qualitative features such as the morphology of the vitreoretinal interface, disorganization of retinal inner layers, ellipsoid zone disruption integrity, and hyperreflective foci. In addition, we discuss that a framework to assess the validity of biomarkers for treatment outcome is essentially important in assessing the prognosis before deciding on treatment in DME. Finally, we echo with other experts on the demand for updating the current diabetic retinal disease classification.

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Section: Sdoct–based Classification Systems For Dme Subtypes – An Upd...mentioning

confidence: 73%

Section: Morphology Of Dmementioning

confidence: 99%

Section: Morphology Of Dmementioning

confidence: 99%

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

Hui

Szeto

Tang

et al. 2022

Asia-Pacific Journal of Ophthalmology

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“…After full-text screening, 41 articles were deemed eligible for planned analyses comparing CMT with VA and were included in the review. 9 – 49 The most common reasons for exclusion were a lack of participants and an incomplete dataset (eg, reporting percentage changes or for a fraction of participants only). Table 1 shows an overview of the included studies.…”

Section: Resultsmentioning

confidence: 99%

Relationship Between Macular Thickness and Visual Acuity in the Treatment of Diabetic Macular Edema With Anti-VEGF Therapy: Systematic Review

Wang

Hou

et al. 2022

Journal of VitreoRetinal Diseases

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Purpose: To examine the relationship between central macular thickness (CMT) measured by optical coherence tomography (OCT) and visual acuity (VA) in patients with center-involving diabetic macular edema (DME) receiving antivascular endothelial growth factor (anti-VEGF) treatment. Methods: Peer-reviewed articles from 2016 to 2020 reporting intravitreal injections of bevacizumab, ranibizumab, or aflibercept that provided data on pretreatment (baseline) and final retinal thickness (CMT) and visual acuity (VA) were identified. The relationship between relative changes was assessed via a linear random-effects regression model controlling for treatment group. Results: No significant association between the logarithm of the minimum angle of resolution (logMAR) VA and CMT was found in 41 eligible studies evaluating 2667 eyes. The observed effect estimate was a 0.12 increase (95% CI, −0.124 to 2.47) in logMAR VA per 100 µm reduction in CMT after treatment change. There were no significant differences in logMAR VA between the anti-VEGF treatment groups. Conclusions: There was no statistically significant relationship between the change in logMAR VA and change in CMT as well as no significant effect of the type of anti-VEGF treatment on the change in logMAR VA. Although OCT analysis, including measurements of CMT, will continue to be an integral part of the management of DME, further exploration is needed on additional anatomic factors that might contribute to visual outcomes.

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“…Precise classification of DME based on the pathological basis under the DME phenotype will undoubtedly contribute to the correct treatment decision making and prognosis prediction. Some retinal experts propose to classify DME into 3 types based on OCT morphological changes of fluid accumulation in DME, 48 namely: (1) type I, diffuse retinal thickening type (DRT), whose mechanism is the disruption of the intraretinal blood barrier (iBRB) due to inflammation and oxidative stress, resulting in increased retinal vascular permeability and ultimately fluid accumulation in the retinal neuroepithelium to form DRT 49 ; (2) type II, cystoid macular 53,54 In addition, DRT has a shorter symptoms duration, a better visual prognosis, and a lower central macular thickness (CMT) than CME. 54,55 DRT and SRD types of DME are also more responsive to anti-VEGF therapy than CME types.…”

Section: Application Of Ai In Dme Precision Evaluationmentioning

confidence: 99%

Application of Artificial Intelligence in Precision Medicine for Diabetic Macular Edema

Zhang

et al. 2023

Asia-Pacific Journal of Ophthalmology

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Diabetic macular edema (DME) is the primary cause of central vision impairment in patients with diabetes and the leading cause of preventable blindness in working-age people. With the advent of optical coherence tomography and antivascular endothelial growth factor (anti-VEGF) therapy, the diagnosis, evaluation, and treatment of DME were greatly revolutionized in the last decade. However, there is tremendous heterogeneity among DME patients, and 30%–50% of DME patients do not respond well to anti-VEGF agents. In addition, there is no evidence-based and universally accepted administration regimen. The identification of DME patients not responding to anti-VEGF agents and the determination of the optimal administration interval are the 2 major challenges of DME, which are difficult to achieve with the coarse granularity of conventional health care modality. Therefore, more and more retina specialists have pointed out the necessity of introducing precision medicine into the management of DME and have conducted related studies in recent years. One of the most frontier methods is the targeted extraction of individualized disease features from optical coherence tomography images based on artificial intelligence technology, which provides precise evaluation and risk classification of DME. This review aims to provide an overview of the progress of artificial intelligence-enabled precision medicine in automated screening, precise evaluation, prognosis prediction, and follow-up monitoring of DME. Further, the challenges ahead of real-world applications and the future development of precision medicine in DME will be discussed.

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Effect of Optical Coherence Tomography Patterns on One-year Outcomes of Aflibercept Therapy for Diabetic Macular Edema

Abstract: Objective: To evaluate the outcomes of aflibercept based on different morphologic patterns on optical coherence tomography (OCT) for diabetic macular edema (DME).

Cited by 5 publications

References 16 publications

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

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

Relationship Between Macular Thickness and Visual Acuity in the Treatment of Diabetic Macular Edema With Anti-VEGF Therapy: Systematic Review

Application of Artificial Intelligence in Precision Medicine for Diabetic Macular Edema

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