Assessment of Retinopathy of Prematurity Regression and Reactivation Using an Artificial Intelligence–Based Vascular Severity Score

Abstract

ImportanceOne of the biggest challenges when using anti–vascular endothelial growth factor (VEGF) agents to treat retinopathy of prematurity (ROP) is the need to perform long-term follow-up examinations to identify eyes at risk of ROP reactivation requiring retreatment.ObjectiveTo evaluate whether an artificial intelligence (AI)–based vascular severity score (VSS) can be used to analyze ROP regression and reactivation after anti-VEGF treatment and potentially identify eyes at risk of ROP reactivation requiring retreatment.Design, Setting, and ParticipantsThis prognostic study was a secondary analysis of posterior pole fundus images collected during the multicenter, double-blind, investigator-initiated Comparing Alternative Ranibizumab Dosages for Safety and Efficacy in Retinopathy of Prematurity (CARE-ROP) randomized clinical trial, which compared 2 different doses of ranibizumab (0.12 mg vs 0.20 mg) for the treatment of ROP. The CARE-ROP trial screened and enrolled infants between September 5, 2014, and July 14, 2016. A total of 1046 wide-angle fundus images obtained from 19 infants at predefined study time points were analyzed. The analyses of VSS were performed between January 20, 2021, and November 18, 2022.InterventionsAn AI-based algorithm assigned a VSS between 1 (normal) and 9 (most severe) to fundus images.Main Outcomes and MeasuresAnalysis of VSS in infants with ROP over time and VSS comparisons between the 2 treatment groups (0.12 mg vs 0.20 mg of ranibizumab) and between infants who did and did not receive retreatment for ROP reactivation.ResultsAmong 19 infants with ROP in the CARE-ROP randomized clinical trial, the median (range) postmenstrual age at first treatment was 36.4 (34.7-39.7) weeks; 10 infants (52.6%) were male, and 18 (94.7%) were White. The mean (SD) VSS was 6.7 (1.9) at baseline and significantly decreased to 2.7 (1.9) at week 1 (P < .001) and 2.9 (1.3) at week 4 (P < .001). The mean (SD) VSS of infants with ROP reactivation requiring retreatment was 6.5 (1.9) at the time of retreatment, which was significantly higher than the VSS at week 4 (P < .001). No significant difference was found in VSS between the 2 treatment groups, but the change in VSS between baseline and week 1 was higher for infants who later required retreatment (mean [SD], 7.8 [1.3] at baseline vs 1.7 [0.7] at week 1) vs infants who did not (mean [SD], 6.4 [1.9] at baseline vs 3.0 [2.0] at week 1). In eyes requiring retreatment, higher baseline VSS was correlated with earlier time of retreatment (Pearson r = −0.9997; P < .001).Conclusions and RelevanceIn this study, VSS decreased after ranibizumab treatment, consistent with clinical disease regression. In cases of ROP reactivation requiring retreatment, VSS increased again to values comparable with baseline values. In addition, a greater change in VSS during the first week after initial treatment was found to be associated with a higher risk of later ROP reactivation, and high baseline VSS was correlated with earlier retreatment. These findings may have implications for monitoring ROP regression and reactivation after anti-VEGF treatment.

Addressing the Challenges of Smartphone-Based Telescreening for Retinopathy of Prematurity—Reply

“…Typically, only 5% to 10% of a screened ROP population will need treatment, so to power a study for using images to identify reactivation (a small subset of treated patients) would require an order of magnitude more patients. That said, we are encouraged that we could assess vascular severity score using the smartphone system, which in previous work by our group was shown to aid in monitoring for reactivation . Lastly, we completely agree that there are limitations to the work and further validation of this approach is needed at least until low-cost widefield digital fundus imaging systems are available worldwide.…”

Multinational External Validation of Autonomous Retinopathy of Prematurity Screening

“…Autonomous screening can provide real-time feedback to NICU teams and families, facilitating educational efforts aimed at maximizing follow-up rates up on discharge. Previous work has also demonstrated other clinical benefits of using AI-based assessment of ROP severity, including longitudinal disease monitoring before and after treatment . That is, for eyes that screen positive, the VSS can be used as an objective biomarker to aid clinicians in identifying infants’ progression to type 1 ROP.…”

Convolutional neuronal network for identifying single‐cell‐platelet–platelet‐aggregates in human whole blood using imaging flow cytometry

“…For example, medical applications of deep learning for image recognition can be found in diagnosing diabetic retinopathy or retinopathy of prematurity regression using images of the back of the eye [26][27][28].…”

“…We also believe our deep learning approach to be advantageous in medical sciences in general, aligning with recent innovations. For example, medical applications of deep learning for image recognition can be found in diagnosing diabetic retinopathy or retinopathy of prematurity regression using images of the back of the eye [26–28]. When applied to tissues, deep learning enables the segmentation of individual cancer cells [29].…”