Decrease in the number of microaneurysms in diabetic macular edema after anti-vascular endothelial growth factor

Kenichiro Mori1, Shigeo Yoshida2, Yoshiyuki Kobayashi1

  • 1Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Abstract

Insights

Anti-vascular endothelial growth factor (VEGF) injections significantly reduced microaneurysms (MAs) in diabetic macular edema (DME) patients. Indocyanine green angiography (IA) may predict DME recurrence.

Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Diabetology

Background:

  • Diabetic macular edema (DME) is a leading cause of vision loss in diabetic patients.
  • Microaneurysms (MAs) are early indicators of diabetic retinopathy and contribute to DME.
  • Anti-vascular endothelial growth factor (VEGF) agents are a primary treatment for DME.

Purpose of the Study:

  • To evaluate the impact of intravitreal anti-VEGF agents on the number of microaneurysms (MAs) in eyes with DME.
  • To assess changes in MAs using fluorescein angiography (FA) and indocyanine green angiography (IA).
  • To explore the potential of IA in predicting DME recurrence.

Main Methods:

  • Retrospective analysis of 21 eyes from 16 patients with DME.
  • Patients received an initial loading dose of three monthly anti-VEGF injections, followed by a pro re nata regimen.
  • FA and IA imaging were performed at baseline and 6 months post-injection.

Main Results:

  • Significant reduction in MA counts across early-phase FA, late-phase FA, and late-phase IA (P < 0.0001).
  • Median MAs decreased from 6 to 2 (early FA), 3 to 1 (late FA), and 2 to 1 (late IA).
  • Higher baseline and 6-month MA counts on late-phase IA were observed in the recurrent DME group (P = 0.0185 and P = 0.009).

Conclusions:

  • Intravitreal anti-VEGF therapy effectively reduces MA burden in DME patients.
  • Late-phase IA detection of MAs may serve as a predictive biomarker for DME recurrence.
  • Further research is warranted to confirm IA's role in DME management and recurrence prediction.

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