July 2019
Volume 60, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2019
A Study of Feature-based Consensus Formation for Glaucoma Risk Assessment
Author Affiliations & Notes
  • Naama Hammel
    Google AI Healthcare, Google LLC, Mountain View, California, United States
  • Mike Schaekermann
    Google AI Healthcare, Google LLC, Mountain View, California, United States
  • Sonia Phene
    Google AI Healthcare, Google LLC, Mountain View, California, United States
  • Carter Dunn
    Google AI Healthcare, Google LLC, Mountain View, California, United States
  • Lily Peng
    Google AI Healthcare, Google LLC, Mountain View, California, United States
  • Dale R Webster
    Google AI Healthcare, Google LLC, Mountain View, California, United States
  • Rory Sayres
    Google AI Healthcare, Google LLC, Mountain View, California, United States
  • Footnotes
    Commercial Relationships   Naama Hammel, Google LLC (E); Mike Schaekermann, Google LLC (E); Sonia Phene, Google LLC (E); Carter Dunn, Google LLC (E); Lily Peng, Google LLC (E); Dale Webster, Google LLC (E); Rory Sayres, Google LLC (E)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 164. doi:
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    • Get Citation

      Naama Hammel, Mike Schaekermann, Sonia Phene, Carter Dunn, Lily Peng, Dale R Webster, Rory Sayres; A Study of Feature-based Consensus Formation for Glaucoma Risk Assessment. Invest. Ophthalmol. Vis. Sci. 2019;60(9):164.

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

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Abstract

Purpose : A reliable reference standard is critical for training and evaluation of deep learning models. This is especially relevant in glaucoma, as guidelines for diagnosis are not well-defined. This study investigates the extent to which agreement on individual optic nerve head (ONH) features is associated with agreement on overall glaucoma risk assessment.

Methods : A dataset of 508 color fundus photos (508 patients) was graded by a rotating panel of 3 glaucoma specialists (out of 10). Images were assessed for 12 glaucomatous ONH features (see Table 1) and the overall glaucoma risk. Images were first independently graded by each specialist. In case of disagreement, the same 3 specialists reviewed the image a second time, this time with access to the annotations and comments from the other 2 specialists. Each image was reviewed up to a maximum of 6 times.To investigate the relative importance of individual ONH features in the consensus formation process for overall glaucoma risk assessment, we used a logistic regression model. For each individual review (N=1123), we determined whether agreement was reached for each of the 12 features. The resulting 12 binary agreement states in a given round were treated as independent predictor variables. Agreement on the overall glaucoma risk assessment for that round was used as the dependent outcome variable.

Results : For 5 out of 12 features, panel agreement was a significant positive predictor for panel agreement on overall glaucoma risk assessment in the same round, listed in decreasing order by relative importance based on Odds Ratio (OR): notch (p = 0.006, OR = 2.157), retinal nerve fiber layer (RNFL) defect (p < 0.001, OR = 1.678), baring (p < 0.001, OR = 1.622), vertical cup-to-disc (p < 0.001, OR = 1.621), and laminar dot sign (p = 0.003, OR = 1.557).

Conclusions : We identified 5 features for which agreement among panel members is positively associated with panel agreement on overall glaucoma risk assessment. Our results contribute towards a more nuanced understanding of the relative importance of individual evaluation criteria for consensus-based glaucoma risk assessment.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

 

Abbreviations: RNFL, Retinal Nerve Fiber Layer; CDR, Cup-to-Disc Ratio; I, Inferior; S, Superior; FOV, Field Of View; PPA, Para Papillary Atrophy; T, Temporal.

Abbreviations: RNFL, Retinal Nerve Fiber Layer; CDR, Cup-to-Disc Ratio; I, Inferior; S, Superior; FOV, Field Of View; PPA, Para Papillary Atrophy; T, Temporal.

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