Plus Disease in Retinopathy of Prematurity: Diagnostic Trends in 2016 Versus 2007

Initiation of retinopathy of prematurity screening examinations in extremely premature infants

PURPOSE

To determine whether extremely premature infants require screening for retinopathy of prematurity (ROP) if <31 weeks' postmenstrual age (PMA).

METHODS

The medical records of infants born in community hospital settings at <31 weeks' gestational age (GA) were reviewed retrospectively. Prevalence and progression of ROP in infants born at <24 weeks' GA were compared with infants born at 24-30 weeks' GA.

RESULTS

A total of 2,061 records were reviewed: 1,969 infants were born at 24-30 weeks' GA; 92, at <24 weeks. Infants born <24 weeks' GA were more likely to develop pre-plus and plus disease or require treatment than infants born 24-30 weeks' GA (P < 0.0001) and did so earlier (P = 0.0001). Eight infants developed pre-plus or greater ROP <31 weeks' PMA; 6 were born <24 weeks' GA. Three infants developed plus disease or required treatment <31 weeks' PMA, the earliest at 27 and 3/7 weeks.

CONCLUSIONS

Clinicians should consider initiating ROP screening examinations before 31 weeks' PMA, particularly for infants born <24 weeks' GA and those with lower birth weights.

Use of an Artificial Intelligence-Generated Vascular Severity Score Improved Plus Disease Diagnosis in Retinopathy of Prematurity

PURPOSE

To evaluate whether providing clinicians with an artificial intelligence (AI)-based vascular severity score (VSS) improves consistency in the diagnosis of plus disease in retinopathy of prematurity (ROP).

DESIGN

Multireader diagnostic accuracy imaging study.

PARTICIPANTS

Eleven ROP experts, 9 of whom had been in practice for 10 years or more.

METHODS

RetCam (Natus Medical Incorporated) fundus images were obtained from premature infants during routine ROP screening as part of the Imaging and Informatics in ROP study between January 2012 and July 2020. From all available examinations, a subset of 150 eye examinations from 110 infants were selected for grading. An AI-based VSS was assigned to each set of images using the i-ROP DL system (Siloam Vision). The clinicians were asked to diagnose plus disease for each examination and to assign an estimated VSS (range, 1-9) at baseline, and then again 1 month later with AI-based VSS assistance. A reference standard diagnosis (RSD) was assigned to each eye examination from the Imaging and Informatics in ROP study based on 3 masked expert labels and the ophthalmoscopic diagnosis.

MAIN OUTCOME MEASURES

Mean linearly weighted κ value for plus disease diagnosis compared with RSD. Area under the receiver operating characteristic curve (AUC) and area under the precision-recall curve (AUPR) for labels 1 through 9 compared with RSD for plus disease.

RESULTS

Expert agreement improved significantly, from substantial (κ value, 0.69 [0.59, 0.75]) to near perfect (κ value, 0.81 [0.71, 0.86]), when AI-based VSS was integrated. Additionally, a significant improvement in plus disease discrimination was achieved as measured by mean AUC (from 0.94 [95% confidence interval (CI), 0.92-0.96] to 0.98 [95% CI, 0.96-0.99]; difference, 0.04 [95% CI, 0.01-0.06]) and AUPR (from 0.86 [95% CI, 0.81-0.90] to 0.95 [95% CI, 0.91-0.97]; difference, 0.09 [95% CI, 0.03-0.14]).

CONCLUSIONS

Providing ROP clinicians with an AI-based measurement of vascular severity in ROP was associated with both improved plus disease diagnosis and improved continuous severity labeling as compared with an RSD for plus disease. If implemented in practice, AI-based VSS could reduce interobserver variability and could standardize treatment for infants with ROP.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Implementation of optical coherence tomography in retinopathy of prematurity screening

PURPOSE OF REVIEW

In this review, we explore the investigational applications of optical coherence tomography (OCT) in retinopathy of prematurity (ROP), the insights they have delivered thus far, and key milestones for its integration into the standard of care.

RECENT FINDINGS

While OCT has been widely integrated into clinical management of common retinal diseases, its use in pediatric contexts has been undermined by limitations in ergonomics, image acquisition time, and field of view. Recently, investigational handheld OCT devices have been reported with advancements including ultra-widefield view, noncontact use, and high-speed image capture permitting real-time en face visualization. These developments are compelling for OCT as a more objective alternative with reduced neonatal stress compared to indirect ophthalmoscopy and/or fundus photography as a means of classifying and monitoring ROP.

SUMMARY

OCT may become a viable modality in management of ROP. Ongoing innovation surrounding handheld devices should aim to optimize patient comfort and image resolution in the retinal periphery. Future clinical investigations may seek to objectively characterize features of peripheral stage and explore novel biomarkers of disease activity.

Artificial Intelligence for Retinopathy of Prematurity: Validation of a Vascular Severity Scale against International Expert Diagnosis

PURPOSE

To validate a vascular severity score as an appropriate output for artificial intelligence (AI) Software as a Medical Device (SaMD) for retinopathy of prematurity (ROP) through comparison with ordinal disease severity labels for stage and plus disease assigned by the International Classification of Retinopathy of Prematurity, Third Edition (ICROP3), committee.

DESIGN

Validation study of an AI-based ROP vascular severity score.

PARTICIPANTS

A total of 34 ROP experts from the ICROP3 committee.

METHODS

Two separate datasets of 30 fundus photographs each for stage (0-5) and plus disease (plus, preplus, neither) were labeled by members of the ICROP3 committee using an open-source platform. Averaging these results produced a continuous label for plus (1-9) and stage (1-3) for each image. Experts were also asked to compare each image to each other in terms of relative severity for plus disease. Each image was also labeled with a vascular severity score from the Imaging and Informatics in ROP deep learning system, which was compared with each grader's diagnostic labels for correlation, as well as the ophthalmoscopic diagnosis of stage.

MAIN OUTCOME MEASURES

Weighted kappa and Pearson correlation coefficients (CCs) were calculated between each pair of grader classification labels for stage and plus disease. The Elo algorithm was also used to convert pairwise comparisons for each expert into an ordered set of images from least to most severe.

RESULTS

The mean weighted kappa and CC for all interobserver pairs for plus disease image comparison were 0.67 and 0.88, respectively. The vascular severity score was found to be highly correlated with both the average plus disease classification (CC = 0.90, P < 0.001) and the ophthalmoscopic diagnosis of stage (P < 0.001 by analysis of variance) among all experts.

CONCLUSIONS

The ROP vascular severity score correlates well with the International Classification of Retinopathy of Prematurity committee member's labels for plus disease and stage, which had significant intergrader variability. Generation of a consensus for a validated scoring system for ROP SaMD can facilitate global innovation and regulatory authorization of these technologies.

Federated learning for multi-center collaboration in ophthalmology: implications for clinical diagnosis and disease epidemiology

OBJECTIVE OR PURPOSE

To utilize a deep learning (DL) model trained via federated learning (FL), a method of collaborative training without sharing patient data, to delineate institutional differences in clinician diagnostic paradigms and disease epidemiology in retinopathy of prematurity (ROP).

DESIGN

Evaluation of a diagnostic test or technology SUBJECTS, PARTICIPANTS, AND/OR CONTROLS: 5,245 patients with wide-angle retinal imaging from the neonatal intensive care units of 7 institutions as part of the Imaging and Informatics in ROP (i-ROP) study. Images were labeled with the clinical diagnosis of plus disease (plus, pre-plus, no plus) that was documented in the chart, and a reference standard diagnosis (RSD) determined by three image-based ROP graders and the clinical diagnosis.

METHODS, INTERVENTION OR TESTING

Demographics (birthweight [BW], gestational age [GA]), and clinical diagnoses for all eye exams were recorded from each institution. Using a FL approach, a DL model for plus disease classification was trained using only the clinical labels. The three class probabilities were then converted into a vascular severity score (VSS) for each eye exam, as well as an "institutional VSS" in which the average of the VSS values assigned to patients' higher severity ("worse") eyes at each exam was calculated for each institution.

MAIN OUTCOME MEASURES

We compared demographics, clinical diagnosis of plus disease, and institutional VSS between institutions using the McNemar Bowker test, two-proportion Z test and one-way ANOVA with post-hoc analysis by Tukey-Kramer test. Single regression analysis was performed to explore the relationship between demographics and VSS.

RESULTS

We found that the proportion of patients diagnosed with pre-plus disease varied significantly between institutions (p<0.00l). Using the DL-derived VSS trained on the data from all institutions using FL, we observed differences in the institutional VSS, as well as level of vascular severity diagnosed as no plus (p<0.001) across institutions. A significant, inverse relationship between the institutional VSS and the mean GA was found (p=0.049, adjusted R²=0.49).

CONCLUSIONS

A DL-derived ROP VSS developed without sharing data between institutions using FL identified differences in the clinical diagnosis of plus disease, and overall levels of ROP severity between institutions. FL may represent a method to standardize clinical diagnosis and provide objective measurement of disease for image-based diseases.

Assessment and management of retinopathy of prematurity in the era of anti-vascular endothelial growth factor (VEGF)

The incidence of retinopathy of prematurity (ROP) continues to rise due to the improved survival of very low birth weight infants in developed countries. This epidemic is also fueled by increased survival of preterm babies with variable use of oxygen and a lack of ROP awareness and screening services in resource-limited regions. Improvements in technology and a basic understanding of the disease pathophysiology have changed the way we screen and manage ROP, educate providers and patients, and improve ROP awareness. Advancements in imaging techniques, expansion of telemedicine services, and the potential for artificial intelligence-assisted ROP screening programs have created opportunities to improve ROP care in areas with a shortage of ophthalmologists trained in ROP. To address the gap in provider knowledge regarding ROP, the Global Education Network for Retinopathy of Prematurity (GEN-ROP) created a web-based tele-education training module that can be used to educate all providers involved in ROP, including non-physician ROP screeners. Over the past 50 years, the treatment of severe ROP has evolved from limited treatment modalities to cryotherapy and laser photocoagulation. More recently, there has been growing evidence to support the use of anti-vascular endothelial growth factor (VEGF) agents for the treatment of severe ROP. However, VEGF is known to be important in organogenesis and microvascular maintenance, and given that intravitreal anti-VEGF treatment can result in systemic VEGF suppression over a period of at least 1-12 weeks, there are concerns regarding adverse effects and long-term ocular and systemic developmental consequences of anti-VEGF therapy. Future research in ophthalmology to address the growing burden of ROP should focus on cost-effective fundus imaging devices, implementation of artificial intelligence platforms, updated treatment algorithms with optimal use of anti-VEGF and careful investigation of its long-term effects, and surgical options in advanced ROP. Addressing these unmet needs will aid the global effort against the ROP epidemic and optimize our understanding and treatment of this blinding disease.

Impact of Artificial Intelligence on Medical Education in Ophthalmology

Clinical care in ophthalmology is rapidly evolving as artificial intelligence (AI) algorithms are being developed. The medical community and national and federal regulatory bodies are recognizing the importance of adapting to AI. However, there is a gap in physicians’ understanding of AI and its implications regarding its potential use in clinical care, and there are limited resources and established programs focused on AI and medical education in ophthalmology. Physicians are essential in the application of AI in a clinical context. An AI curriculum in ophthalmology can help provide physicians with a fund of knowledge and skills to integrate AI into their practice. In this paper, we provide general recommendations for an AI curriculum for medical students, residents, and fellows in ophthalmology.

Variability in Plus Disease Identified Using a Deep Learning-Based Retinopathy of Prematurity Severity Scale

PURPOSE

Retinopathy of prematurity is a leading cause of childhood blindness worldwide, but clinical diagnosis is subjective, which leads to treatment differences. Our goal was to determine objective differences in the diagnosis of plus disease between clinicians using an automated retinopathy of prematurity (ROP) vascular severity score.

DESIGN

This retrospective cohort study used data from the Imaging and Informatics in ROP Consortium, which comprises 8 tertiary care centers in North America. Fundus photographs of all infants undergoing ROP screening examinations between July 1, 2011, and December 31, 2016, were obtained.

PARTICIPANTS

Infants meeting ROP screening criteria who were diagnosed with plus disease and treatment initiated by an examining physician based on ophthalmoscopic examination results.

METHODS

An ROP severity score (1-9) was generated for each image using a deep learning (DL) algorithm.

MAIN OUTCOME MEASURES

The mean, median, and range of ROP vascular severity scores overall and for each examiner when the diagnosis of plus disease was made.

RESULTS

A total of 5255 clinical examinations in 871 babies were analyzed. Of these, 168 eyes were diagnosed with plus disease by 11 different examiners and were included in the study. The mean ± standard deviation vascular severity score for patients diagnosed with plus disease was 7.4 ± 1.9, median was 8.5 (interquartile range, 5.8-8.9), and range was 1.1 to 9.0. Within some examiners, variability in the level of vascular severity diagnosed as plus disease was present, and 1 examiner routinely diagnosed plus disease in patients with less severe disease than the other examiners (P < 0.01).

CONCLUSIONS

We observed variability both between and within examiners in the diagnosis of plus disease using DL. Prospective evaluation of clinical trial data using an objective measurement of vascular severity may help to define better the minimum necessary level of vascular severity for the diagnosis of plus disease or how other clinical features such as zone, stage, and extent of peripheral disease ought to be incorporated in treatment decisions.

Changing consumption of resources for respiratory support and short-term outcomes in four consecutive geographical cohorts of infants born extremely preterm over 25 years since the early 1990s

OBJECTIVES

It is unclear how newer methods of respiratory support for infants born extremely preterm (EP; 22-27 weeks gestation) have affected in-hospital sequelae. We aimed to determine changes in respiratory support, survival and morbidity in EP infants since the early 1990s.

DESIGN

Prospective longitudinal cohort study.

SETTING

The State of Victoria, Australia.

PARTICIPANTS

All EP births offered intensive care in four discrete eras (1991-1992 (24 months): n=332, 1997 (12 months): n=190, 2005 (12 months): n=229, and April 2016-March 2017 (12 months): n=250).

OUTCOME MEASURES

Consumption of respiratory support, survival and morbidity to discharge home. Cost-effectiveness ratios describing the average additional days of respiratory support associated per additional survivor were calculated.

RESULTS

Median duration of any respiratory support increased from 22 days (1991-1992) to 66 days (2016-2017). The increase occurred in non-invasive respiratory support (2 days (1991-1992) to 51 days (2016-2017)), with high-flow nasal cannulae, unavailable in earlier cohorts, comprising almost one-half of the duration in 2016-2017. Survival to discharge home increased (68% (1991-1992) to 87% (2016-2017)). Cystic periventricular leukomalacia decreased (6.3% (1991-1992) to 1.2% (2016-2017)), whereas retinopathy of prematurity requiring treatment increased (4.0% (1991-1992) to 10.0% (2016-2017)). The average additional costs associated with one additional infant surviving in 2016-2017 were 200 (95% CI 150 to 297) days, 326 (183 to 1127) days and 130 (70 to 267) days compared with 1991-1992, 1997 and 2005, respectively.

CONCLUSIONS

Consumption of resources for respiratory support has escalated with improved survival over time. Cystic periventricular leukomalacia reduced in incidence but retinopathy of prematurity requiring treatment increased. How these changes translate into long-term respiratory or neurological function remains to be determined.

The genetics of retinopathy of prematurity: a model for neovascular retinal disease

TOPIC

Retinopathy of prematurity (ROP) is a proliferative retinal vascular disease in premature infants, and is a major cause of childhood blindness worldwide. In addition to known clinical risk factors such as low birth weight and gestational age, there is a growing body of evidence supporting a genetic basis for ROP.

CLINICAL RELEVANCE

While comorbidities and environmental factors have been identified as contributing to ROP outcomes in premature infants, most notably gestational age and oxygen, some infants progress to severe disease despite absence of these clinical risk factors. The contribution of genetic factors may explain these differences and allow better detection and treatment of infants at risk for severe ROP.

METHODS

To comprehensively review genetic factors that potentially contribute to the development and severity of ROP, we conducted a literature search focusing on the genetic basis for ROP. Terms related to other heritable retinal vascular diseases like "familial exudative vitreoretinopathy", as well as to genes implicated in animal models of ROP, were also used to capture research in diseases with similar pathogenesis to ROP in humans with known genetic components.

RESULTS

Contributions across several genetic domains are described including vascular endothelial growth factor, the Wnt signaling pathway, insulin-like growth factor 1, inflammatory mediators, and brain-derived neurotrophic factor.

CONCLUSIONS

Most candidate gene studies of ROP have limitations such as inability to replicate results, conflicting results from various studies, small sample size, and differences in clinical characterization. Additional difficulty arises in separating the contribution of genetic factors like Wnt signaling to ROP and prematurity. Although studies have implicated involvement of multiple signaling pathways in ROP, the genetics of ROP have not been clearly elucidated. Next-generation sequencing and genome-wide association studies have potential to expand future understanding of underlying genetic risk factors and pathophysiology of ROP.

Plus Disease in Retinopathy of Prematurity: More Than Meets the ICROP?

Retinopathy of prematurity (ROP), a vasoproliferative retinal disease affecting premature infants, is a leading cause of childhood blindness throughout the world. Plus disease, defined as venous dilatation and arteriolar tortuosity within the posterior retinal vessels greater than or equal to that of a standard published photograph, is the most critical finding in identifying treatment-requiring ROP. Despite an internationally accepted definition of plus disease, there is significant variability in diagnostic process and outcome, producing variable levels of reported intra- and interexpert agreement. Several potential explanations for poor agreement have been proposed, including attention to undefined vascular features such as venous tortuosity, focus on narrower or wider field of view, unfamiliarity with digital images, the magnification and apparent severity of the standard photograph, and cut-off point differences among experts as to the level of tortuosity and dilation sufficient for "plus disease" along a continuum. Moreover, differences in diagnostic consistency among groups of experts separated both geographically and chronologically have been reported. These findings have implications for clinical care, research, and education, and highlight the need for a more precise definition of plus disease and objective diagnostic methods for ROP.