June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
Ability of eye-care professionals in grading retinal fluid volumes and change in age-related macular degeneration assessed by automated fluid monitoring
Author Affiliations & Notes
  • Martin Michl
    Ophthalmology and Optometry, Medizinische Universitat Wien, Vienna, Vienna, Austria
  • Bianca S Gerendas
    Ophthalmology and Optometry, Medizinische Universitat Wien, Vienna, Vienna, Austria
  • Anastasiia Gruber
    Center for Medical Statistics, Medizinische Universitat Wien, Wien, Wien, Austria
  • Philipp Seeboeck
    Computational Imaging Research Lab, Medizinische Universitat Wien, Wien, Wien, Austria
  • Felix Goldbach
    Ophthalmology and Optometry, Medizinische Universitat Wien, Vienna, Vienna, Austria
  • Georgios Mylonas
    Ophthalmology and Optometry, Medizinische Universitat Wien, Vienna, Vienna, Austria
  • Oliver Leingang
    Optima Study Group, Medizinische Universitat Wien, Wien, Wien, Austria
  • Wolf Bühl
    Ophthalmology and Optometry, Medizinische Universitat Wien, Vienna, Vienna, Austria
  • Stefan Sacu
    Ophthalmology and Optometry, Medizinische Universitat Wien, Vienna, Vienna, Austria
  • Hrvoje Bogunovic
    Optima Study Group, Medizinische Universitat Wien, Wien, Wien, Austria
  • Ursula Schmidt-Erfurth
    Ophthalmology and Optometry, Medizinische Universitat Wien, Vienna, Vienna, Austria
  • Footnotes
    Commercial Relationships   Martin Michl None; Bianca S Gerendas Bayer, Zeiss, Novartis, Roche, Code C (Consultant/Contractor), DXS, Code F (Financial Support); Anastasiia Gruber None; Philipp Seeboeck None; Felix Goldbach None; Georgios Mylonas None; Oliver Leingang None; Wolf Bühl None; Stefan Sacu Roche, Novartis, Bayer, Code C (Consultant/Contractor); Hrvoje Bogunovic None; Ursula Schmidt-Erfurth Genentech, Kodiak, Novartis, Apellis, RetInSight, Code C (Consultant/Contractor), Apellis, Code C (Consultant/Contractor), RetInSight, Code P (Patent)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 2167. doi:
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      Martin Michl, Bianca S Gerendas, Anastasiia Gruber, Philipp Seeboeck, Felix Goldbach, Georgios Mylonas, Oliver Leingang, Wolf Bühl, Stefan Sacu, Hrvoje Bogunovic, Ursula Schmidt-Erfurth; Ability of eye-care professionals in grading retinal fluid volumes and change in age-related macular degeneration assessed by automated fluid monitoring. Invest. Ophthalmol. Vis. Sci. 2023;64(8):2167.

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

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Abstract

Purpose : To use an AI-based fluid algorithm to determine the discriminative ability of eye-care professionals in grading intra- and subretinal fluid (IRF, SRF) presence and volume change in real-world OCT images of patients with nAMD.

Methods : Patients with nAMD treated at our retina department between 2007 and 2018 were included in the Vienna Imaging Biomarker Eye Study (VIBES) registry. 5 retinologists (RET), 3 ophthalmology residents (RES), 3 general ophthalmologists (GENO), 3 orthoptists (ORTH) and 3 certified graders from the Vienna Reading Center (VRC) graded the presence of IRF/SRF at two consecutive visits as well as the change (increase/no change/decrease) on Spectralis OCT images. Intervals ranged from 28 to 120 days between visits and anti-VEGF injections were given between the two visits. The Vienna Fluid Monitor Version 2 (RetInSight, Vienna, Austria) was applied to automatically segment and quantify IRF/SRF volumes. ROC curves were then generated to determine volume cut-offs (nl) for fluid presence and change that provided the best tradeoff between sensitivity (Sen) and specificity (Spe) (=Youden Index).

Results : 124 visit pairs of 59 eyes were included. For IRF presence, fluid volumes between 3,3-6nl were most accurately detected across all groups with 0,79-0,87 (Sen) and 0,92-0,97 (Spe). For SRF presence, volumes between 4-7,1nl correlated with 0,82-0,95 (Sen) and 0,92-0,97 (Spe). In terms of fluid change, an IRF increase as small as 1,7-3nl was detected with 0,91-1,0 (Sen) and 0,88-0,93 (Spe) and an IRF decrease of 2,8-16,9nl with 0,83-0,9 (Sen) and 0,9-0,96 (Spe). SRF increases of 0,6-6,4nl were detected with 0,84-0,94 (Sen) and 0,89-0,96 (Spe), SRF decreases of 6,4-9,3nl with 0,93-0,98 (Sen) and 0,87-0,95 (Spe). The AUC was high for both fluid presence and fluid change with values consistently over 0,89 across all groups.

Conclusions : AI-based fluid analysis permits to determine the accuracy of human experts from different professional backgrounds in grading retinal fluid types and their changes over time. The introduction of such objective, quantitative parameters results in a consistent and exact management, irrespective of the treating physicians’ background.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

 

ROC curves showing the classification performance of each group in discriminating between eyes with IRF/SRF increase or decrease.

ROC curves showing the classification performance of each group in discriminating between eyes with IRF/SRF increase or decrease.

 

AUC values to the shown ROC curves.

AUC values to the shown ROC curves.

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