June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
Artificial intelligence algorithm may improve performance of retinal specialists in detection of retinal fluid on OCT in age-related macular degeneration: AREDS2 10-Year follow-on Study
Author Affiliations & Notes
  • Michael J Elman
    Elman Retina Group PA, Baltimore, Maryland, United States
  • Tiarnan D L Keenan
    Division of Epidemiology and Clinical Applications, NEI/NIH, Bethesda, Maryland, United States
  • Traci E Clemons
    The EMMES Company, LLC, Rockville, Maryland, United States
  • Amitha Domalpally
    Fundus Photographic Reading Center, University of Wisconsin, Madison, Wisconsin, United States
  • Moshe Havilio
    Notal Vision Ltd., Tel Aviv, Israel
  • Gidi Benyamini
    Notal Vision Ltd., Tel Aviv, Israel
  • Emily Chew
    Division of Epidemiology and Clinical Applications, NEI/NIH, Bethesda, Maryland, United States
  • Footnotes
    Commercial Relationships   Michael Elman, Notal Vision Ltd. (C), Notal Vision Ltd. (I), Notal Vision Ltd. (F); Tiarnan Keenan, None; Traci Clemons, None; Amitha Domalpally, None; Moshe Havilio, Notal Vision Ltd. (E); Gidi Benyamini, Notal Vision Ltd. (E); Emily Chew, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 5275. doi:
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    • Get Citation

      Michael J Elman, Tiarnan D L Keenan, Traci E Clemons, Amitha Domalpally, Moshe Havilio, Gidi Benyamini, Emily Chew; Artificial intelligence algorithm may improve performance of retinal specialists in detection of retinal fluid on OCT in age-related macular degeneration: AREDS2 10-Year follow-on Study. Invest. Ophthalmol. Vis. Sci. 2020;61(7):5275.

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

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Abstract

Purpose : To evaluate the performance of retinal specialists in detecting retinal fluid presence in spectral domain OCT macular volume scans from eyes with age-related macular degeneration (AMD), and to compare performance with the artificial intelligence (AI)-based Notal OCT Analyzer (NOA).

Methods : In this prospective study, OCT scans were acquired from all Age-Related Eye Disease Study 2 10-year follow-on (AREDS2-10Y) participants with Cirrus or Spectralis devices. Masked investigators graded each scan for intraretinal and subretinal fluid. The same scans underwent masked grading by (i) NOA, and (ii) reading center (RC) graders, used as ground truth. The primary outcome measure was accuracy.

Results : 1,127 eyes (651 participants) were eligible (mean age 80 y). 50% required RC senior adjudication for fluid presence. Retinal fluid was present in 370 eyes. For detecting retinal fluid, the AREDS2-10Y investigators’ performance was: accuracy 0.805 (95% CI 0.780-0.828), sensitivity 0.468 (0.416-0.520), and specificity 0.970 (0.955-0.981). NOA performance was: 0.851 (0.829-0.871), 0.822 (0.779-0.859), 0.865 (0.839-0.889). For intraretinal fluid, investigator performance was 0.815 (0.792-0.837), 0.403 (0.349-0.459), 0.978 (0.966-0.987); NOA performance was 0.877 (0.857-0.896), 0.763 (0.713-0.808), 0.922 (0.902-0.940). Comparing the investigator true positive (n=173) and false negative (n=197) cases, the mean NOA-calculated fluid volume was 156 vs 33 nl (p<0.001), with fluid present in 32% vs 11% B-scans (p<0.001).

Conclusions : In this large and challenging sample of SD-OCT scans obtained with two commonly used devices, retinal specialists had imperfect accuracy in detecting retinal fluid, with low sensitivity. This was particularly true for (i) intraretinal fluid and (ii) low fluid volume appearing on fewer B-scans (i.e., harder to identify). AI-based detection achieved a higher level of accuracy. This AI software tool could assist physicians in detecting retinal fluid, which is important for diagnostic, retreatment, and prognostic tasks in AMD.

This is a 2020 ARVO Annual Meeting abstract.

 

Figure 1. ROC curve of NOA in detecting retinal fluid; AUC = 0.925; retinal specialists’ performance (green dot)

Figure 1. ROC curve of NOA in detecting retinal fluid; AUC = 0.925; retinal specialists’ performance (green dot)

 

Figure 2. OCT scan with low volume intraretinal fluid: missed by retinal specialist but correctly detected by NOA (red)

Figure 2. OCT scan with low volume intraretinal fluid: missed by retinal specialist but correctly detected by NOA (red)

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