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

Stanford Taylor, James M. Brown, Kishan Gupta, John Campbell, Susan Ostmo, R. V.Paul Chan, Jennifer Dy, Deniz Erdogmus, Stratis Ioannidis, Sang J. Kim, Jayashree Kalpathy-Cramer, Michael Chiang

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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.

Original languageEnglish (US)
JournalJAMA ophthalmology
DOIs
StatePublished - Jan 1 2019

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ASJC Scopus subject areas

  • Ophthalmology

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Taylor, S., Brown, J. M., Gupta, K., Campbell, J., Ostmo, S., Chan, R. V. P., Dy, J., Erdogmus, D., Ioannidis, S., Kim, S. J., Kalpathy-Cramer, J., & Chiang, M. (2019). Monitoring Disease Progression with a Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning. JAMA ophthalmology. https://doi.org/10.1001/jamaophthalmol.2019.2433