July 2020
Volume 61, Issue 9
Open Access
ARVO Imaging in the Eye Conference Abstract  |   July 2020
Automated central macular fluid volume quantification provides a higher diagnostic accuracy than central macular thickness measurement for diabetic macular edema
Author Affiliations & Notes
  • Qisheng You
    Casey Eye Institute, OHSU, Portland, Oregon, United States
  • kotaro tsuboi
    Casey Eye Institute, OHSU, Portland, Oregon, United States
  • Yukun Guo
    Casey Eye Institute, OHSU, Portland, Oregon, United States
  • Jie Wang
    Casey Eye Institute, OHSU, Portland, Oregon, United States
  • Christina J. Flaxel
    Casey Eye Institute, OHSU, Portland, Oregon, United States
  • Steven T. Bailey
    Casey Eye Institute, OHSU, Portland, Oregon, United States
  • David Huang
    Casey Eye Institute, OHSU, Portland, Oregon, United States
  • Yali Jia
    Casey Eye Institute, OHSU, Portland, Oregon, United States
  • Thomas Hwang
    Casey Eye Institute, OHSU, Portland, Oregon, United States
  • Footnotes
    Commercial Relationships   Qisheng You, None; kotaro tsuboi, None; Yukun Guo, None; Jie Wang, None; Christina Flaxel, None; Steven Bailey, None; David Huang, OptoVue (P), OptoVue (F), OptoVue (C); Yali Jia, OptoVue (F), OptoVue (P); Thomas Hwang, None
  • Footnotes
    Support  Grants R01 EY024544, R01 EY027833, and P30 EY010572 from the National Institutes of Health, an unrestricted departmental funding grant and William & Mary Greve Special Scholar Award from Research to Prevent Blindness, New York.
Investigative Ophthalmology & Visual Science July 2020, Vol.61, PP0021. doi:
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      Qisheng You, kotaro tsuboi, Yukun Guo, Jie Wang, Christina J. Flaxel, Steven T. Bailey, David Huang, Yali Jia, Thomas Hwang; Automated central macular fluid volume quantification provides a higher diagnostic accuracy than central macular thickness measurement for diabetic macular edema. Invest. Ophthalmol. Vis. Sci. 2020;61(9):PP0021.

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

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Abstract

Purpose : To assess the diagnostic accuracy of automated central macular fluid volume (CMFV) quantification for diabetic macular edema (DME).

Methods : All participants underwent comprehensive clinical examinations, 6x6-mm horizontal 19-line macular structural optical coherence tomography (OCT) raster scans and 6x6-mm macular OCT angiography (OCTA) volumetric scans. Two retinal fellows reviewed structural raster OCT scans independently and diagnosed DME if intraretinal or subretinal fluid was detected in central 1-mm region. A retinal specialist arbitrated cases with discrepancy. Mean central macular thickness (CMT) within central 1mm circle was measured on structural OCT scans. A deep-learning based algorithm automatically detected CMFV within central 1mm circle on 6x6-mm OCTA scans.

Results : We enrolled 1 eye each of 202 diabetic patients (90 men) with a mean age of 60 years. DME was diagnosed in 88 eyes. (Table1) The intraclass correlation for DME diagnosis of the two fellows was 0.888. The area under the receiver operating characteristic curve (AROC) of CMFV for diagnosis of DME was 0.904, significantly larger (P=0.03) than AROC of CMT 0.837. (Fig 1.) The sensitivity at 95% specificity of CMFV for detecting DME was 79.1%, significantly higher than 56.0% of CMT (P=0.002). Those DME cases missed by CMT but detected by CMFV had a significantly higher proportion of previous macular focal laser treatment (44% vs. 19%, P=0.016). The Pearson correlation coefficient between CMFV and the best-corrected visual acuity (BCVA) was -0.321, similar to -0.327 between CMT and BCVA.

Conclusions : Automated CMFV quantification provides a significant higher diagnostic accuracy than CMT for DME. CMFV is a useful biomarker for assessment of DME, particularly in previously focal laser treated eyes.

This is a 2020 Imaging in the Eye Conference abstract.

 

 

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