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

Abstract

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.

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

“…Various OCT-based DME classification approaches, such as the “SAVE” classification [ 30 ] and “TCED-HFV” grading protocol [ 31 ] have been developed to quantitatively analyse changes in retinal structure, providing valuable insights for clinical decision-making. However, there remains a substantial gap in establishing consensus and guidelines for reliably predicting treatment outcomes using OCT parameters [ 32 ] Previous studies have explored various quantitative parameters, such as DRIL and ellipsoid zone/external limiting membrane integrity, as potential predictors of DME treatment response [ 14 , 33 ]. However, most studies of DRIL have been qualitative (presence or absence) or semi-quantitative (measuring absolute length or proportion), limiting their predictive power [ 12 ].…”

Alterations in the Choroidal Sublayers in Relationship to Severity and Progression of Diabetic Retinopathy

“…Future research may further explore the temporal relationship between retinal and choroidal microvascular changes in DR and validate whether choroidopathy precedes retinopathy in DM. Studies are also warranted to assess whether choroidal metrics could predict the development of PDR and DME, and even visual outcome and treatment response 90 .…”

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

“…DME is a multifactorial and complex disease driven by hypoxia, inflammation, hyperpermeability, and angiogenesis [ 5 , 6 ]. As a consequence, it is reasonable to hypothesize different DME phenotypes with different disease severity, risk of progression, and treatment outcomes [ 7 ]. Therefore, the assessment of the individual morphologic characteristics of DME may provide a better understanding of the pathophysiology of this disease, which, in turn, might help in the selection of the best treatment option in a personalized precision medicine approach [ 8 ].…”