Telemedicine For Retinopathy Of Prematurity Research Articles

Multinational External Validation of Autonomous Retinopathy of Prematurity Screening

Retinopathy of prematurity (ROP) is a leading cause of blindness in children, with significant disparities in outcomes between high-income and low-income countries, due in part to insufficient access to ROP screening. To evaluate how well autonomous artificial intelligence (AI)-based ROP screening can detect more-than-mild ROP (mtmROP) and type 1 ROP. This diagnostic study evaluated the performance of an AI algorithm, trained and calibrated using 2530 examinations from 843 infants in the Imaging and Informatics in Retinopathy of Prematurity (i-ROP) study, on 2 external datasets (6245 examinations from 1545 infants in the Stanford University Network for Diagnosis of ROP [SUNDROP] and 5635 examinations from 2699 infants in the Aravind Eye Care Systems [AECS] telemedicine programs). Data were taken from 11 and 48 neonatal care units in the US and India, respectively. Data were collected from January 2012 to July 2021, and data were analyzed from July to December 2023. An imaging processing pipeline was created using deep learning to autonomously identify mtmROP and type 1 ROP in eye examinations performed via telemedicine. The area under the receiver operating characteristics curve (AUROC) as well as sensitivity and specificity for detection of mtmROP and type 1 ROP at the eye examination and patient levels. The prevalence of mtmROP and type 1 ROP were 5.9% (91 of 1545) and 1.2% (18 of 1545), respectively, in the SUNDROP dataset and 6.2% (168 of 2699) and 2.5% (68 of 2699) in the AECS dataset. Examination-level AUROCs for mtmROP and type 1 ROP were 0.896 and 0.985, respectively, in the SUNDROP dataset and 0.920 and 0.982 in the AECS dataset. At the cross-sectional examination level, mtmROP detection had high sensitivity (SUNDROP: mtmROP, 83.5%; 95% CI, 76.6-87.7; type 1 ROP, 82.2%; 95% CI, 81.2-83.1; AECS: mtmROP, 80.8%; 95% CI, 76.2-84.9; type 1 ROP, 87.8%; 95% CI, 86.8-88.7). At the patient level, all infants who developed type 1 ROP screened positive (SUNDROP: 100%; 95% CI, 81.4-100; AECS: 100%; 95% CI, 94.7-100) prior to diagnosis. Where and when ROP telemedicine programs can be implemented, autonomous ROP screening may be an effective force multiplier for secondary prevention of ROP.

Ocular Pigmentation Impact on Retinal Versus Choroidal Optical Coherence Tomography Imaging in Preterm Infants.

To evaluate the association of fundus pigmentation with the visibility of retinal versus choroidal layers on optical coherence tomography (OCT) in preterm infants. For infants enrolled in BabySTEPS, ophthalmologists recorded fundus pigmentation (blond, medium, or dark) at the first retinopathy of prematurity (ROP) examination. Bedside OCT imaging was performed at each examination, and a masked grader evaluated all OCT scans from both eyes of each infant for visibility (yes/no) of all retinal layers and of the chorio-scleral junction (CSJ). Multivariable logistic regression was used to assess associations between fundus pigmentation and visibility of all retinal layers and CSJ, controlling for potential confounders (i.e., birth weight, gestational age, sex, OCT system, pupil size, and postmenstrual age at imaging). Among 114 infants (mean birth weight, 943 grams; mean gestational age, 27.6 weeks), 43 infants (38%) had blond, 56 infants (49%) had medium, and 15 infants (13%) had dark fundus pigmentation. Of 1042 scans, all retinal layers were visible in 977 (94%) and CSJ in 895 (86%). Pigmentation was not associated with retinal layer visibility (P = 0.49), but medium and dark pigmentation were associated with decreased CSJ visibility (medium: odds ratio [OR] = 0.34, P = 0.001; dark: OR = 0.24, P = 0.009). For infants with dark pigmentation, retinal layer visibility increased (OR = 1.87 per week; P ≤ 0.001) and CSJ visibility decreased (OR = 0.78 per week; P = 0.01) with increasing age. Although fundus pigmentation was not associated with the visibility of all retinal layers on OCT, darker pigmentation decreased CSJ visibility, and this effect increased with age. The ability of bedside OCT to capture retinal layer microanatomy in preterm infants, regardless of fundus pigmentation, may represent an advantage over fundus photography for ROP telemedicine.

Smartphone-based fundus imaging for evaluation of Retinopathy of Prematurity in a low-income country: A pilot study.

To evaluate the feasibility of a novel and simple smart phone-based Retinopathy of Prematurity (ROP) screening approach in a resource-constrained setting. This cross-sectional validation study was conducted at the Department of Ophthalmology and Neonatal Intensive Care Unit (NICU) of The Aga Khan University Hospital, Pakistan, from January 2022 to April 2022. A total of 63 images of eyes with active ROP (stage-1, 2, 3, 4 and/or plus or pre-plus disease) were included in this study. The stage of ROP was documented by the principal investigator using an indirect ophthalmoscope and retinal images were obtained using this novel technique. These images were shared with two masked ROP experts who rated the image quality and determined the stage of ROP and presence of plus disease. Their reports were compared with the initial findings reported by principal investigator using indirect ophthalmoscope. We reviewed 63 images for image quality, stage of ROP and presence of plus disease. There was significant agreement between the gold standard and the Rater-1 and 2 for the presence of plus disease (Cohen's kappa was 0.84 and 1.0) and the stage of the disease (Cohen's kappa 0.65 and 1.0). There was significant agreement between the Rater for presence of plus disease and any stage of ROP (Cohen's κ: 0.84 and 0.65 for plus disease and any stage of the ROP, respectively). Rater-1 and 2 rated 96.83% and 98.41% images as excellent / acceptable respectively. High quality retinal images can be captured with a smartphone and 28D lens without using any additional adapter equipment. This approach of ROP screening can form basis of telemedicine for ROP in resource constrained areas.

Telemedicine in retinopathy of prematurity: Crossing borders in pediatric vision health. TELEROP study

General objectiveTo evaluate the accuracy and validity of images with smartphone compared to the RetCam® system for the diagnosis of retinopathy of prematurity (ROP). MethodologyObservational, longitudinal and masked study carried out at the Dr. Elías Santana hospital. Infants with birth weight ≤1500 g, gestational age ≤30 weeks and/or patients exposed to risk factors or complications linked to ROP were included. These subjects were screened using images with smartphone or RetCam®, both compared to conventional fundoscopy. The ICROP classification was used for staging. The main results analyzed were sensitivity, specificity, positive predictive values and kappa index. Results915 images (n = 121) were obtained, distributed in smartphone group (50.4%) and RetCam® group (49.6%) between August 2020 and March 2021. Subjects with ROP had lower gestational age (30.2 sem ± 2.8), birth weight (1361 g ± 398), and greater exposure to oxygen therapy (12.8 days ± 11.3). The RetCam® group presented sensitivity = 80%, specificity = 78%, positive predictive value = 90% and kappa index = 0.70. The smartphone group presented sensitivity = 88%, specificity = 90%, positive predictive value = 93.75% and kappa index = 0.81. ConclusionsBoth diagnostic methods were accurate to identify ROP. The smartphone group obtained superior results with excellent resolution, representing a cost-effective method to create a global impact on reducing preventable blindness in the pediatric population.

Multimodal Imaging, Tele-Education, and Telemedicine in Retinopathy of Prematurity.

Retinopathy of prematurity (ROP) is a disease that affects retinal vasculature in premature infants and remains one of the leading causes of blindness in childhood worldwide. ROP screening can encounter some difficulties such as the lack of specialists and services in rural areas. The evolution of technology has helped address these issues and led to the emergence of state-of-the-art multimodal digital imaging devices such fundus cameras with its variable properties, optical coherence tomography (OCT), OCT angiography, and fluorescein angiography which has helped immensely in the process of improving ROP care and understanding the disease pathophysiology. Computer-based imaging analysis and deep learning have recently been demonstrating promising outcomes in regard to ROP diagnosis. Telemedicine is considered an acceptable alternative to clinical examination when optimal circumstances for ROP screening in certain areas are lacking, and the expansion of these programs has been reported. Tele-education programs in ROP have the potential to improve the quality of training to physicians to optimize ROP care.

Saudi Arabian retinopathy of prematurity national telemedicine program: Achievements and challenges.

The Saudi Arabian Retinopathy of Prematurity National Telemedicine programme (SAROP) is a product of the National Committee for Retinopathy of Prematurity (ROP). The program includes ROP telescreening, diagnosis, and management of cases requiring treatment. Digital retinal images and filled ROP software requests were uploaded from 20 level-3 neonatal intensive care units (NICU) in the Kingdom of Saudi Arabia (KSA) to the King Khaled Eye Specialist Hospital server and the ROP telemedicine website. The data were accessed and reported by qualified retinal and pediatric ophthalmologists. Currently, retinal wide-angle digital cameras are available in 20 of the 31 level-3 NICUs of the Ministry of Health, Kingdom of KSA. This telemedicine approach is practical and effective in detecting and managing ROP cases. In the first 2.5 years, encouraging results were noticed with no unfavorable outcomes in the participating NICUs. Technical challenges were resolved promptly to ensure that the program ran smoothly. Therefore, this ideal state-of-the-art ROP telemedicine program could be also applied to similar and neighboring countries.

Applications of Artificial Intelligence for Retinopathy of Prematurity Screening.

Childhood blindness from retinopathy of prematurity (ROP) is increasing as a result of improvements in neonatal care worldwide. We evaluate the effectiveness of artificial intelligence (AI)-based screening in an Indian ROP telemedicine program and whether differences in ROP severity between neonatal care units (NCUs) identified by using AI are related to differences in oxygen-titrating capability. External validation study of an existing AI-based quantitative severity scale for ROP on a data set of images from the Retinopathy of Prematurity Eradication Save Our Sight ROP telemedicine program in India. All images were assigned an ROP severity score (1-9) by using the Imaging and Informatics in Retinopathy of Prematurity Deep Learning system. We calculated the area under the receiver operating characteristic curve and sensitivity and specificity for treatment-requiring retinopathy of prematurity. Using multivariable linear regression, we evaluated the mean and median ROP severity in each NCU as a function of mean birth weight, gestational age, and the presence of oxygen blenders and pulse oxygenation monitors. The area under the receiver operating characteristic curve for detection of treatment-requiring retinopathy of prematurity was 0.98, with 100% sensitivity and 78% specificity. We found higher median (interquartile range) ROP severity in NCUs without oxygen blenders and pulse oxygenation monitors, most apparent in bigger infants (>1500 g and 31 weeks' gestation: 2.7 [2.5-3.0] vs 3.1 [2.4-3.8]; P = .007, with adjustment for birth weight and gestational age). Integration of AI into ROP screening programs may lead to improved access to care for secondary prevention of ROP and may facilitate assessment of disease epidemiology and NCU resources.

Telemedicine for Retinopathy of Prematurity.

Background: Retinopathy of prematurity (ROP) is a disease of the retinal vasculature that remains a leading cause of childhood blindness worldwide despite improvements in the systemic care of premature newborns. Screening for ROP is effective and cost-effective, but in many areas, access to skilled examiners to conduct dilated examinations is poor. Remote screening with retinal photography is an alternative strategy that may allow for improved ROP care. Methods: The current literature was reviewed to find clinical trials and expert consensus documents on the state-of-the-art of telemedicine for ROP. Results: Several studies have confirmed the utility of telemedicine for ROP. In addition, several clinical studies have reported favorable long-term results. Many investigators have reinforced the need for detailed protocols on image acquisition and image interpretation. Conclusions: Telemedicine for ROP appears to be a viable alternative to live ophthalmoscopic examinations in many circumstances. Standardization and documentation afforded by telemedicine may provide additional benefits to providers and their patients. With continued improvements in image quality and affordability of imaging systems as well as improved automated image interpretation tools anticipated in the near future, telemedicine for ROP is expected to play an expanding role for a uniquely vulnerable patient population.

Telemedicine for Retinopathy of Prematurity in 2020.

Purpose: Retinopathy of prematurity (ROP) is the leading cause of visual impairment in premature infants, and middle-income nations are currently experiencing the “third epidemic” of ROP. Screening programs are essential to prevent negative visual outcomes, but screening efforts require a great amount of resources from healthcare systems and are difficult to marshal, particularly in geographically isolated or resource-limited settings. Telemedical screening programs using remote digital fundus imaging (RDFI) systems hold the promise of alleviating many of the burdens that currently make screening for ROP logistically challenging. Methods: Literature review of the current evidence for RDFI telescreening for ROP, with editorial discussion and recommendations. Results: In this review, we summarize the robust body of literature regarding the efficacy of RDFI, the feasibility of telescreening programs, and experiences from current live telescreening programs. We discuss the strengths and limitations of the current evidence and of the screening programs and consider the best practices in developing de novo telemedical screening programs for ROP. The review concludes with a discussion of promising future areas of research and development. Conclusions: RDFI ROP screening programs can be accurate and reliable. They show promise in improving many current challenges in screening infants for ROP, may be able to improve some aspects of care, and have been demonstrated to be cost-effective.

Use of a Deep Learning-Based Disease Severity Scale for Assessment of Retinopathy of Prematurity Primary Prevention in India

Background: There is an epidemic of retinopathy of prematurity (ROP) in low- and middle-income countries (LMIC) in part due to heterogeneity in adherence to best practices for oxygen monitoring in neonatal care units (NCU). The purpose of this study was to determine whether a deep learning based ROP severity score obtained from fundus images in a telemedicine program could be applied at the population level to compare epidemiologic differences between NCUs in South India. Methods: Fundus photos were obtained from at-risk infants at participating hospitals in the Aravind Eye Hospital ROP telemedicine system. An ROP severity score from 1-9 was calculated for each eye examination using methods previously published. Population (NCU) level ROP severity was compared across hospitals using multivariate linear regression adjusting for demographic risk factors for ROP. Masked ROP technicians assessed adherence to best practices using a quality score (1-5) for oxygen monitoring in each NCU. Findings: Images from initial screening exams of 128 infants at 11 hospitals were analyzed. Mean ROP severity was significantly different between hospitals (P=0.003). In multivariate regression controlling for birth weight, gestational age, and postnatal age, a higher NCU quality score was associated with lower ROP severity (P=0.001). Of note, the NCU with the lowest quality score had the highest ROP severity score (1.6 points above the mean, P=0.001), while the NCU with the highest quality score had the lowest ROP severity score (1.2 points below the mean, P=0.001). Interpretation: We identified variability in ROP severity between NCUs that correlated with best practices for oxygen monitoring. These findings suggest the potential utility of using image-based deep learning not just for patient-level diagnosis, but also for population-level epidemiologic surveillance of primary prevention practices, and may have broader applicability for a variety of medical conditions beyond ROP. Funding Statement: This project was supported by grants R01EY19474, K12EY027720, and P30EY10572 from the National Institutes of Health (Bethesda, MD), by grants SCH1622679, SCH-1622542, and SCH-1622536 from the National Science Foundation (Arlington, VA), and by unrestricted departmental funding and a Career Development Award (JPC) from Research to Prevent Blindness (New York, NY). Declaration of Interests: Michael F. Chiang is an unpaid member of the Scientific Advisory Board for Clarity Medical Systems (Pleasanton, CA), a Consultant for Novartis (Basel, Switzerland), and an initial member of Inteleretina (Honolulu, HI). R. V. Paul Chan is on the Scientific Advisory Board for Visunex Medical Systems (Pleasanton, CA), and a Consultant for Genentech (South San Francisco, CA). Michael Chiang and J. Peter Campbell receive research support from Genentech. J. Peter Campbell, James M. Brown, Susan Ostmo, R.V.P. Chan, Jayaskhree Kalpathy-Cramer, and Michael F. Chiang have a patent application pending on the described technology. All other authors have no conflicts of interest. Ethics Approval Statement: This study was conducted in accordance with Health Insurance Portability and Accountability Act (HIPAA) guidelines, and Institutional Review Board (IRB) approval was obtained at both Oregon Health & Science University and the Aravind Eye Hospital.

Ophthalmoscopy and Telemedicine in Retinopathy of Prematurity

Ophthalmoscopy and Telemedicine in Retinopathy of Prematurity

Telemedicine for retinopathy of prematurity: why and how

Telehealth programs have been developed for detection of eye disease in populations that lack traditional resources for screening. Retinopathy of prematurity (ROP) is a vasoproliferative retinal disease found in premature infants that can lead to blindness without timely detection and treatment. Even in developed countries, a lack of ophthalmologists with expertise in ROP screening and treatment for ROP has resulted in interest and implementation of digital image analysis as a screening modality.

Outpatient, Wide-Field, Digital Imaging of Infants With Retinopathy of Prematurity.

Eight infants were closely monitored for retinopathy of prematurity (ROP) while in the neonatal intensive care unit (NICU); two required laser therapy. After discharge from the NICU, they had outpatient examination with dilated, scleral depressed ROP staging, and each had digital widefield retinal imaging (Optos, Dunfermline, United Kingdom) without lid speculum, or with lid speculum if not cooperative. Images were shared remotely using ROP-Check software (Glacier Medical Software, Anchorage, AK), from which ophthalmologists made clinical impressions. The images did not afford clear view of maturity to the ora serrata; however, posterior zone 3 was viewed, and confirmation that each eye did not need therapy was consistent. Outpatient wide-field retinal imaging may help facilitate telemedicine for ROP. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:494-497.].

Current Trends in Telemedicine for Retinopathy of Prematurity

Retinopathy of Prematurity (ROP) is a vasoproliferative disease of the retina in premature infants that can progress to blindness. Clinical ROP management standards have been established by seminal studies such as the Cryotherapy for ROP (CRYO-ROP) and Early Treatment for ROP (ET-ROP) trials, and have significantly decreased the incidence of poor visual outcomes in ROP. However, ROP continues to be a leading cause of childhood blindness worldwide.

Телемедицина в скрининге, диагностике и лечении активной ретинопатии недоношенных

The literature review provides information on the use of special research and clinical tool – telemedicine in ophthalmology. The importance of telemedicine services for the early detection and timely treatment of such diseases as retinopathy of prematurity (ROP) is shown based on the data of a number of studies. Many studies indicate the value of retinal pediatric system RetCam and digital images of the fundus obtained with their help for screening, diagnosis and tactics of patients with ROP via telemedicine technologies. This, according to many researchers, promotes the timely detection of children with the stages of the disease, requiring the consultation of ophthalmologists, treatment, and referring them to specialized clinics. Thereat this demonstrates a high accuracy of the interpretation of fundus images during the telemedicine screening. Foreign authors note a significant economic efficiency of ROP telemedicine compared with the standard diagnostic methods, such as the indirect binocular ophthalmoscopy during the direct consultation of the patient by an ophthalmologist, they also noted that the use of this technology promotes to reduce time-consuming of ophthalmologists involved in the management of patients with ROP. According to various authors, the incidence of ROP worldwide continues to grow, and the use of telemedicine for screening, diagnosis, and training of medical personnel will become increasingly important in the organization of eye care in preterm infants. Nowadays the subject of ROP telemedicine is reflected in the national pediatric ophthalmology only in a few publications. However, this trend begins to develop rapidly and is one of the most promising tools to solve the problem of retinopathy of prematurity in Russian pediatric ophthalmic practice.

Influence of Computer-Generated Mosaic Photographs on Retinopathy of Prematurity Diagnosis and Management

Telemedicine is becoming an increasingly important component of clinical care for retinopathy of prematurity (ROP), but little information exists regarding the role of mosaic photography for ROP telemedicine diagnosis. To examine the potential effect of computer-generated mosaic photographs on the diagnosis and management of ROP. In this prospective cohort study performed from July 12, 2011, through September 21, 2015, images were acquired from ROP screening at 8 academic institutions, and ROP experts interpreted 40 sets (20 sets with individual fundus photographs with ≥3 fields and 20 computer-generated mosaic photographs) of wide-angle retinal images from infants with ROP. All experts independently reviewed the 40 sets and provided a diagnosis and management plan for each set presented. The primary outcome measure was the sensitivity and specificity of the ROP diagnosis by experts that was calculated using a consensus reference standard diagnosis, determined from the diagnosis of fundus photographs by 3 experienced readers in combination with the clinical diagnosis based on ophthalmoscopic examination. Mean unweighted κ statistics were used to analyze the mean intergrader agreement among experts for diagnosis of zone, stage, plus disease, and category. Nine ROP experts (4 women and 5 men) who have been practicing ophthalmology for a mean of 10.8 years (range, 3-24 years) consented to participate. Diagnosis by the mosaic photographs compared with diagnosis by multiple individual photographs resulted in improvements in sensitivity for diagnosis of stage 2 disease or worse (95.9% vs 88.9%; difference, 7.0; 95% CI, 3.5 to 10.5; P = .02), plus disease (85.7% vs 63.5%; difference, 22.2; 95% CI, 7.6 to 36.9; P = .02), and treatment-requiring ROP (84.4% vs 68.5%; difference, 15.9; 95% CI, 0.8 to 31.7; P = .047). With use of the κ statistic, mosaic photographs, compared with multiple individual photographs, resulted in improvements in intergrader agreement for diagnosis of plus disease or not (0.54 vs 0.40; mean κ difference, 0.14; 95% CI, 0.07 to 0.21; P = .004), stage 3 disease or worse or not (0.60 vs 0.52; mean κ difference, 0.06; 95% CI, -0.06 to 0.18; P = .04), and type 2 ROP or not (0.58 vs 0.51; mean κ difference, 0.07; 95% CI, 0.03 to 0.11; P = .04). After viewing the mosaic photographs, experts altered their choice of management in 42 of 180 responses (23.3%; 95% CI, 17.1%-29.5%). Compared with multiple individual photographs, computer-generated mosaic photographs were associated with improved accuracy of image-based diagnosis for certain categories (eg, plus disease, stage 2 disease or worse, and treatment-requiring ROP) of ROP by experts. It is unclear, however, whether these findings are generalizable, and the results of this study may not be relevant to mosaic grading of other retinal vascular conditions.

Analysis of Discrepancy Between Diagnostic Clinical Examination Findings and Corresponding Evaluation of Digital Images in the Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity Study

As effective treatments for potentially blinding retinopathy of prematurity (ROP) have been introduced, the importance of consistency in findings has increased, especially with the shift toward retinal imaging in infants at risk of ROP. To characterize discrepancies in findings of ROP between digital retinal image grading and examination results from the Telemedicine Approaches to Evaluating Acute-Phase Retinopathy of Prematurity study, conducted from May 2011 to October 2013. A poststudy consensus review of images was conducted by 4 experts, who examined discrepancies in findings between image grades by trained nonphysician readers and physician examination results in infants with referral-warranted ROP (RW-ROP). Images were obtained from 13 North American neonatal intensive care units from eyes of infants with birth weights less than 1251 g. For discrepancy categories with more than 100 cases, 40 were randomly selected; in total, 188 image sets were reviewed. Consensus evaluation of discrepant image and examination findings for RW-ROP components. Among 5350 image set pairs, there were 161 instances in which image grading did not detect RW-ROP noted on clinical examination (G-/E+) and 854 instances in which grading noted RW-ROP when the examination did not (G+/E-). Among the sample of G-/E+ cases, 18 of 32 reviews (56.3%) agreed with clinical examination findings that ROP was present in zone I and 18 of 40 (45.0%) agreed stage 3 ROP was present, but only 1 of 20 (5.0%) agreed plus disease was present. Among the sample of G+/E- cases, 36 of 40 reviews (90.0%) agreed with readers that zone I ROP was present, 23 of 40 (57.5%) agreed with readers that stage 3 ROP was present, and 4 of 16 (25.0%) agreed that plus disease was present. Based on the consensus review results of the sampled cases, we estimated that review would agree with clinical examination findings in 46.5% of the 161 G-/E+ cases (95% CI, 41.6-51.6) and agree with trained reader grading in 70.0% of the 854 G+/E- cases (95% CI, 67.3-72.8) for the presence of RW-ROP. This report highlights limitations and strengths of both the remote evaluation of fundus images and bedside clinical examination of infants at risk for ROP. These findings highlight the need for standardized approaches as ROP telemedicine becomes more widespread.

Timely implementation of a retinopathy of prematurity telemedicine system

To examine the feasibility of a retinopathy of prematurity (ROP) telemedicine evaluation system of providing timely feedback to a neonatal intensive care unit (NICU) with at-risk premature infants. This was a prospective observational study of premature infants with birth weights of <1251g in five NICUs in the United States. Infants scheduled for clinically indicated ROP evaluations underwent indirect ophthalmoscopic examinations and digital imaging on the same day. Imaging was performed by nonphysician retinal imagers. Times required were determined from obtaining digital images of both eyes to submission via web-based system to a secure server for grading by trained readers at a central reading center to sending back grading results to the clinical center. A total of 1,642 image sets of eyes of 292 infants were obtained, from 823 imaging sessions. The mean turnaround time from submission of image sets of both eyes to return of the grading results to the clinical center was 10.1±11.3hours (standard deviation), with a median of 12.0hours (1st quartile, 0.9hours; 3rd quartile, 16hours). Overall, 95.5% of gradings (95% CI, 93.9%-96.7%) were returned within 24hours. Subgroup analyses found, for image sets submitted to the reading center before 2 p.m. Eastern Standard Time, median time to report was 1.7hours (1st quartile, 0.7hours; 3rd quartile, 15.5hours) compared with those submitted after 2pm (median, 14.1hours; 1st quartile, 11.2, hours; 3rd quartile, 16.3hours). An ROP telemedicine approach can provide timely feedback to the NICU regarding the detection of potentially serious ROP and thus referral to an ophthalmologist for examination and consideration of treatment.

Screening and treatments using telemedicine in retinopathy of prematurity.

Several studies have validated the role of telemedicine as a new powerful screening and diagnostic tool for retinal disorders, such as diabetic retinopathy and retinopathy of prematurity. With regard to retinopathy of prematurity, bedside examination with binocular indirect ophthalmoscopy has been the gold standard technique for screening, yet with several limitations. Herein, we review the current evidence that supports the role of telemedicine for the screening of infants with retinopathy of prematurity.

Smartphone fundoscopy for retinopathy of prematurity

PurposeThe utility of digital fundus images in retinopathy of prematurity (ROP) screening has been established. A smartphone can be a device available to most ophthalmologists to capture digital fundus photographs. In this study, fundus images were captured with original camera settings for ROP documentation. MethodsThe examination was performed under topical anesthesia. An assistant held a glass stick against the eye movement if infants moved their eyes too frequently. A hand-held smartphone and a 30D lens were used to record the fundus in video mode. A continuous flash was turned on to provide almost constant coaxial illumination. Fundus photographs were captured from the video film. ResultsFundus photographs can be captured successfully with a smartphone and a 30D lens under original camera settings. ConclusionFundus photographs of acceptable diagnostic quality can be obtained in ROP patients conveniently and inexpensively using a portable hand-held smartphone. It might be a useful tool in documentation, education, consultation, and telemedicine in ROP.