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Comment
. 2019 Sep 1;137(9):1022-1028.
doi: 10.1001/jamaophthalmol.2019.2433.

Monitoring Disease Progression With a Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning

Stanford Taylor  1 , James M Brown  2 , Kishan Gupta  1 , J Peter Campbell  1 , Susan Ostmo  1 , R V Paul Chan  3 , Jennifer Dy  4 , Deniz Erdogmus  4 , Stratis Ioannidis  4 , Sang J Kim  1   5 , Jayashree Kalpathy-Cramer  2   6 , Michael F Chiang  1   7 ; Imaging and Informatics in Retinopathy of Prematurity Consortium
Affiliations
Comment

Monitoring Disease Progression With a Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning

Stanford Taylor et al. JAMA Ophthalmol. .

Abstract

Importance: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide, but clinical diagnosis is subjective and qualitative.

Objective: To describe a quantitative ROP severity score derived using a deep learning algorithm designed to evaluate plus disease and to assess its utility for objectively monitoring ROP progression.

Design, setting, and participants: This retrospective cohort study included images from 5255 clinical examinations of 871 premature infants who met the ROP screening criteria of the Imaging and Informatics in ROP (i-ROP) Consortium, which comprises 9 tertiary care centers in North America, from July 1, 2011, to December 31, 2016. Data analysis was performed from July 2017 to May 2018.

Exposure: A deep learning algorithm was used to assign a continuous ROP vascular severity score from 1 (most normal) to 9 (most severe) at each examination based on a single posterior photograph compared with a reference standard diagnosis (RSD) simplified into 4 categories: no ROP, mild ROP, type 2 ROP or pre-plus disease, or type 1 ROP. Disease course was assessed longitudinally across multiple examinations for all patients.

Main outcomes and measures: Mean ROP vascular severity score progression over time compared with the RSD.

Results: A total of 5255 clinical examinations from 871 infants (mean [SD] gestational age, 27.0 [2.0] weeks; 493 [56.6%] male; mean [SD] birth weight, 949 [271] g) were analyzed. The median severity scores for each category were as follows: 1.1 (interquartile range [IQR], 1.0-1.5) (no ROP), 1.5 (IQR, 1.1-3.4) (mild ROP), 4.6 (IQR, 2.4-5.3) (type 2 and pre-plus), and 7.5 (IQR, 5.0-8.7) (treatment-requiring ROP) (P < .001). When the long-term differences in the median severity scores across time between the eyes progressing to treatment and those who did not eventually require treatment were compared, the median score was higher in the treatment group by 0.06 at 30 to 32 weeks, 0.75 at 32 to 34 weeks, 3.56 at 34 to 36 weeks, 3.71 at 36 to 38 weeks, and 3.24 at 38 to 40 weeks postmenstrual age (P < .001 for all comparisons).

Conclusions and relevance: The findings suggest that the proposed ROP vascular severity score is associated with category of disease at a given point in time and clinical progression of ROP in premature infants. Automated image analysis may be used to quantify clinical disease progression and identify infants at high risk for eventually developing treatment-requiring ROP. This finding has implications for quality and delivery of ROP care and for future approaches to disease classification.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Campbell reported receiving grants from Genentech and personal fees from Allergan outside the submitted work. Dr Chan reported receiving personal fees from Alcon, Allergan, Beyeonics, Visunex, and Genentech outside the submitted work and is a cofounder of Paire Health. Dr Dy reported receiving grants from the National Science Foundation during the conduct of the study. Dr Ioannidis reported receiving grants from the National Science Foundation, Defense Advance Research Projects Agency, and the US Department of Defense outside the submitted work. Dr Kalpathy-Cramer reported receiving grants from the National Institutes of Health and the National Science Foundation during the conduct of the study and receiving personal fees from Infotech outside the submitted work. Dr Chiang reported receiving grants from the National Institutes of Health, National Science Foundation, and Genentech; receiving nonfinancial support from Clarity Medical Systems and receiving personal fees from Novartis and Inteleretina outside the submitted work. Drs Campbell, Ioannidis, Kalpathy-Cramer, and Chiang report a patent pending for DeepROP. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Serial Wide-Angle Retinal Images and Corresponding Quantitative Vascular Severity Score From Deep Learning in an Infant Who Did Not Require Treatment
Images are from an infant with a gestational age of 260/7 weeks and a birth weight of 830 g. The retinopathy of prematurity vascular severity score (range, 1-9) was 1.04 in A, 1.44 in B, and 1.36 in C.
Figure 2.
Figure 2.. Serial Wide-Angle Retinal Images and Corresponding Quantitative Vascular Severity Score From Deep Learning in Infant Who Required Treatment
Images are from an infant with a gestational age of 260/7 weeks and a birth weight of 783 g. The retinopathy of prematurity vascular severity score (range, 1-9) was 1.04 in A, 5.00 in B, and 8.64 in C.
Figure 3.
Figure 3.. Box Plots of Retinopathy of Prematurity (ROP) Vascular Severity Score Based on Reference Standard Diagnosis (RSD) in International Classification of ROP Categories
P < .001 by Wilcoxon rank sum test with Bonferroni correction. Dots indicate medians; and boxes, IQRs.
Figure 4.
Figure 4.. Violin Plot of Distribution of Retinopathy of Prematurity (ROP) Vascular Severity Scores in Eyes That Never Required Treatment Compared With Eyes That Developed Treatment-Requiring Disease
P < .001 for all comparisons.
Figure 5.
Figure 5.. Mean (SD) Rate of Retinopathy of Prematurity (ROP) Vascular Severity Score Change per Week by Postmenstrual Age in Eyes That Never Required Treatment Compared With Eyes That Developed Treatment-Requiring Disease
Controlling for birth weight and gestational age, multivariable logistic regression found the rate of change in the ROP vascular severity score was independently associated with future treatment. Error bars indicate SDs.
See this image and copyright information in PMC

Comment on

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