Thickness of Intraretinal Layers in Patients with Type 2 Diabetes Mellitus Depending on a Concomitant Diabetic Neuropathy: Results of a Cross-Sectional Study Using Deviation Maps for OCT Data Analysis

Ruby Kala Prakasam,Diethelm Tschöpe,Aleksandra Matuszewska-Iwanicka,Hans-Joachim Hettlich,Martin Röhlig,Dagmar-Christiane Fischer,Heidrun Schumann,Rudolf F Guthoff,Bernd Stratmann,Oliver Stachs

doi:10.3390/biomedicines8070190

Abstract

Optical coherence tomography (OCT) supports the detection of thickness changes in intraretinal layers at an early stage of diabetes mellitus. However, the analysis of OCT data in cross-sectional studies is complex and time-consuming. We introduce an enhanced deviation map-based analysis (MA) and demonstrate its effectiveness in detecting early changes in intraretinal layer thickness in adults with type 2 diabetes mellitus (T2DM) compared to common early treatment diabetic retinopathy study (ETDRS) grid-based analysis (GA). To this end, we obtained OCT scans of unilateral eyes from 33 T2DM patients without diabetic retinopathy and 40 healthy controls. The patients were categorized according to concomitant diabetic peripheral neuropathy (DN). The results of MA and GA demonstrated statistically significant differences in retinal thickness between patients and controls. Thinning was most pronounced in total retinal thickness and the thickness of the inner retinal layers in areas of the inner macular ring, selectively extending into areas of the outer macular ring and foveal center. Patients with clinically proven DN showed the strongest thinning of the inner retinal layers. MA showed additional areas of thinning whereas GA tended to underestimate thickness changes, especially in areas with localized thinning. We conclude that MA enables a precise analysis of retinal thickness data and contributes to the understanding of localized changes in intraretinal layers in adults with T2DM.

Highlights

Optical coherence tomography (OCT) [1] is an established method for detecting early signs of neurodegenerative changes in patients with diabetes mellitus (DM)
We demonstrated a new map-based analysis using comparative color-coded deviation maps (DevMs), which helped us to understand the distribution of local thickness changes between two different study groups with greater spatial specificity
To test our visual analytics (VA) software for OCT data analysis, we recruited a group of type 2 diabetes mellitus (T2DM) patients and assembled a control group of comparable age

Summary

Introduction

Optical coherence tomography (OCT) [1] is an established method for detecting early signs of neurodegenerative changes in patients with diabetes mellitus (DM). In pediatric and adult DM patients at an early stage or even before any manifestation of clinical signs of microangiopathy (e.g., diabetic retinopathy (DR)) Such changes are thought to serve as biomarkers for the identification of patients at risk of developing DR. The process of boundary identification and segmentation is followed by the generation of topographical color-coded thickness maps by measuring every single point of OCT data While these color-coded thickness maps are spatially informative, it is hard to relate such data to the widely used early treatment diabetic retinopathy study (ETDRS) grid [8]. The inner and outer rings are divided into four quadrants (nasal, temporal, superior and inferior) To date, this grid-based analysis has been frequently used for the comparison of OCT findings between groups [3,9]. Subtle and localized thickness differences within one cell are likely to be overlooked due to data averaging

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