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May 2008
Volume 49, Issue 13
Free
ARVO Annual Meeting Abstract   |   May 2008
Potentiality of Intraretinal Layer Segmentation to Locally Detect Early Retinal Changes in Patients With Diabetes Mellitus Using Optical Coherence Tomography
Author Affiliations & Notes
  • D. Cabrera Fernandez
    Bascom Palmer Eye Institute, University of Miami, Miami, Florida
  • G. M. Somfai
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary
  • E. Tátrai
    Yellow Twintip Order Order Top Top Twintip Yellow Department of Ophthalmology, Semmelweis University, Budapest, Hungary
  • S. Ranganathan
    Bascom Palmer Eye Institute, University of Miami, Miami, Florida
  • D. C. Yee
    Bascom Palmer Eye Institute, University of Miami, Miami, Florida
  • M. Ferencz
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary
  • W. E. Smiddy
    Order Yellow Yellow Top Twintip Top Order Twintip Bascom Palmer Eye Institute, University of Miami, Miami, Florida
  • Footnotes
    Top Twintip Yellow Order Order Twintip Yellow Top Commercial Relationships  D. Cabrera Fernandez, None; G.M. Somfai, None; E. Tátrai, None; S. Ranganathan, None; D.C. Yee, None; M. Ferencz, None; W.E. Smiddy, None.
  • Yellow Top Yellow Top Twintip Order Order Twintip Support  P30 EY014801, Research to Prevent Blindness and Zsigmond Diabetes Fund of the Hungarian Academy of Sciences
Investigative Ophthalmology & Visual Science May 2008, Vol.49, 2751. doi:
Abstract

Purpose: : To assess the ability of intraretinal layer segmentation to locally detect early retinal changes in diabetic patients.

Methods: : Six standard radial scans centered on the fovea were done by StratusOCTTM in 80 healthy eyes (35±13 years) and 28 eyes with diabetes mellitus (DM) with no or minimal diabetic retinopathy (MDR) (21 eyes no DR [DM; 31±7 years] and 7 eyes with minimal DR [MDR; 63±18]) on biomicroscopy. Automatic layer segmentation was performed using OCT Retinal Image Analysis software (OCTRIMA). Mean values of reflectance and retinal thickness (RT) of the macula, RNFL, GCL+IPL, INL, OPL, ONL, IS/OS and RPE in the fovea, pericentral and peripheral rings in the DM and MDR patients were compared with the mean values in healthy controls. Mean RT measurements in the groupsTop Top Yellow Yellow Order Twintip Order Twintip were compared using ANOVA followed by Dunnett-post hoc analysis. A modified p value of <0.001 was considered statistically significant.

Results: : No statistically significant thickness changes of the ONL, RPE Denim Midwash Evans Inexpensive Inexpensive Shorts Evans qaT6Ywtand macular RT were found in the fovea (R1). We found a significant reduction in the pericentral and peripheral regions of the RNFL (30.8±2.1 vs. 21.8±6.5µm and 56.6±4.8Twintip Yellow Top Yellow Twintip Order Order Top vs. 33.6±11.0µm, respectively, p<0.001 both cases), and a significant reduction in the GCL+IPL complex thickness in the pericentral region of the MDR group compared to controls (86.2±5.1µm vs. 72.2±8.8µm, p<0.001). Also, macular RT was significantly reduced in the pericentral ring of the MDR group compared to controls (308.5±9.3µm vs. 288.6±19.5µm, p<0.001). Local reflectance of each layer relative to each other was moderately stable within the retina for DM and control groups. However, this stable reflectance pattern was not present for the RNFL in eyes with MDR.

Conclusions: : We found reduced RNFL thickness in the pericentral and peripheral regions and reduced thickness of GCL+IPL complex in the pericentral region of the macula. Accordingly, macular RT was reduced in the pericentral region of the macula. Our results support the view of neurodegeneration in diabetes in the early stage of DR which seems to involve the RNFL and GCL layers mostly, leading to reduced macular thickness as reported previously. The strength of this study compared to other studies is the OCTRIMA subanalysis and quantification of the local variations of the intraretinal layers. Local measurement of the structural and optical properties of the retina by OCT appears to be a proper index for early DR detection.

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