March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
Predictive Power Of Novel Biomarkers For Early Retinopathy Development In The Diabetic Macula
Author Affiliations & Notes
  • Delia DeBuc
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • Wei Gao
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • Erika Tatrai
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary
  • Lenke Laurik
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary
  • Boglarka Varga
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary
  • Veronika Olvedy
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary
  • Aniko Somogyi
    Department of Internal Medicine, Semmelweis University, Budapest, Hungary
  • William E. Smiddy
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • Gabor M. Somfai
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary
  • Footnotes
    Commercial Relationships  Delia DeBuc, US 61/139,082 (P); Wei Gao, None; Erika Tatrai, None; Lenke Laurik, None; Boglarka Varga, None; Veronika Olvedy, None; Aniko Somogyi, None; William E. Smiddy, None; Gabor M. Somfai, None
  • Footnotes
    Support  NIH/NEI-EY020607; JDRF 2007-727, NIH Center Core Grant P30EY014801, Research to Prevent Blindness Unrestricted Grant, Department of Defense (DOD- Grant#W81XWH-09-1-0675)
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 805. doi:
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      Delia DeBuc, Wei Gao, Erika Tatrai, Lenke Laurik, Boglarka Varga, Veronika Olvedy, Aniko Somogyi, William E. Smiddy, Gabor M. Somfai; Predictive Power Of Novel Biomarkers For Early Retinopathy Development In The Diabetic Macula. Invest. Ophthalmol. Vis. Sci. 2012;53(14):805.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : To assess the diagnostic power of novel biomarkers based on thickness, texture and optical measures of the backscattered signal from layered retinal structures in diabetic eyes.

Methods: : A total of 155 eligible eyes from 99 participants (74 healthy eyes (34±12 yrs), 38 eyes with type 1 diabetes mellitus (DM) with no retinopathy (35±10 yrs) and 43 eyes with mild diabetic retinopathy (MDR, 43±17 yrs) on biomicroscopy) were included in the study. Diagnostic parameters, such as thickness, rough dimension, contrast, reflectivity, total reflectance and layer index, were extracted from OCT images and evaluated to test their suitability as predictors of early diabetic retinopathy. ANOVA followed by Newman-Keuls post-hoc analyses were used to test for differences between groups (p <0.001 statistically significant). Receiver operating characteristic (ROC) curves were constructed to describe the ability of each parameter to discriminate between MDR eyes with DM and healthy eyes. Discriminative diagnostic characteristics of the ROC curve, such as the c-statistic, sensitivity, specificity, and positive likelihood ratio (PLR), were analyzed.

Results: : The maximum discrimination (MD) value for the intraretinal thickness of 0.87 for the OPL and 0.74 for the GCL+IPL complex was obtained at a thickness≤ 38.14 µm and 75.43 µm, respectively. This implies there is an 87% (74%) probability the diabetic subject will have an abnormal OPL (GCL+IPL) thickness. At this value, the sensitivity for the OPL (GCL+IPL) is 89.2% (74.3%) with a specificity of 79.10% (65.10%). The PLR for OPL (GCL+IPL) is 4.3 (2.1), which increase the probability of early retinopathy development about 25% (15%), respectively. Similarly, the MD value for rough dimension of 0.90 for the GCL+IPL complex was obtained at a value ≤ 1.67. At this value, the sensitivity for the GCL+IPL complex is 91.9% with a specificity of 81.4%. The PLR for GCL+IPL complex is 4.9, which increase the probability of early retinopathy development about 30%. Total reflectance and layer index also showed MD values for all layers except RPE and INL (only for layer index) with an average PLR of 2.0, which increase the probability of early retinopathy development about 15%.

Conclusions: : In this study, the total reflectance, rough dimension, thickness and layer index displayed the most powerful diagnostic utility for detecting early changes in the diabetic retina. Our results showed that looking for abnormality in the GCL+IPL complex, OPL and OS could detect DR earlier. Compared to the standard thickness measurements provided by OCT devices, the combination of thickness, texture and optical measurements were significantly better at discriminating MDR eyes from healthy normal and DM eyes.

Keywords: diabetic retinopathy • imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • image processing 
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