Research shows that neurodegeneration occurs early in the diabetic retinopathy (DR) disease process, manifesting as structural, functional and molecular changes even in the absence of visible microvascular abnormalities.1 OCT is one diagnostic tool that shows promise for detecting these changes early, with a new study finding it can detect thinning of the inner retinal layers before diabetic retinopathy becomes visible.2
The researchers used swept-source OCT (SS-OCT) to compare the macular thickness and retinal nerve fiber layer between age-matched pregnant patients with gestational diabetes, non-pregnant women with Type 2 diabetes without DR and healthy non-pregnant women.
Mean best-corrected visual acuity, IOP, age and mean subfoveal choroidal thickness were similar across all three groups. The mean central macular thickness measurements were:
- Gestational diabetes group: 215.3 ± 10.83μm
- Type 2 diabetes group: 220.58 ± 21.62μm
- Controls: 230.03 ± 21.24μm
The researchers found that, compared with the control group, the retinal nerve fiber layer was slightly thinner only in the inferior zone of the two study groups. They also observed a statistically significant difference in thickness of all sectors of the ganglion cell layer among all groups, with non-pregnant Type 2 diabetes patients exhibiting the lowest values.
The researchers suggest that, “SS-OCT plays an important role in detecting retinal neurodegenerative changes and choroidal thickness induced by gestational and Type 2 diabetes before the development of retinopathy.”
1. Garcia-Ramírez M, Hernández C, Villarroel M, et al. Interphotoreceptor retinoid-binding protein (IRBP) is downregulated at early stages of diabetic retinopathy. Diabetologica. 2009;52:12:2633-41.
2. Chhablani J, Sharma A, Goud A, et al. Neurodegeneration in type 2 diabetes: Evidence from spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2015;56:11:6333-8.
3. Akpolat C, Kurt MM, Evliyaoglu F, et al. Analysis of retinal neurodegeneration in gestational and type 2 diabetes using swept-source optical coherence tomography.