ArticleEye (London, England)2019
Smartphone-based application improves the detection of retinoblastoma.
Article in Eye (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 34 citations in OpenAlex.
- Smartphone applications for early screening of retinoblastoma: a scoping review.BMC ophthalmology · 2026Article
- The Fundus Red Reflex Test Using a Smartphone Showed High Accuracy Compared to an Autorefractor to Detect Refractive Errors in Children.Journal of ophthalmic & vision research · 2026Article
- Automatic diagnosis of retinoblastoma and quantitative analysis of retinal vascular morphology using deep learning.Frontiers in cell and developmental biology · 2026Article
- Global health inequities in retinoblastoma: a 1990-2021 analysis across socio-demographic index regions.Frontiers in public health · 2025Article
- Semi-supervised segmentation of retinoblastoma tumors in fundus images.Scientific reports · 2023Article
- Detection and Diagnosis of Retinoblastoma: Can Mobile Devices Be the Next Step Toward Early Intervention?Cureus · 2022Review
- EyeScreen: Development and Potential of a Novel Machine Learning Application to Detect Leukocoria.Ophthalmology science · 2022Article
- Smart phone apps every ophthalmologist should know about.International journal of ophthalmology · 2020Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo improve and validate the smartphone-based leukocoria detection application so that non-ophthalmologists could make use of the smartphone for early detection of Retinoblastoma (RB) in young children without anesthesia and pharmacological dilatation of the pupil.
methodsTwo apps, MDEyeCare and CRADLE, developed for red reflex based leukocoria detection were used in iPhone 6s. MDEyeCare methodology was modified with respect to ambient lighting, the distance between camera and eye and different gazes for better performance. We analyzed totally 34 eyes of 23 RB patients and four normal children. Each of the RB patients was confirmed with clinical examination and radiological investigations.
resultsModification in the methodology of MDEyeCare app could detect the leukocoria in early stages of RB (50% of Group B, 83% of Group C). In late stages (Group D and E), 100% of tumors were detected. The CRADLE app failed to provide adequate leukocoria detection except four late stage RB eyes. Among the 14 normal eyes (6 from unilateral RB and eight from normal children), pseudo-leukocoria was observed in three eyes only at lateral gaze even with MDEyeCare app.
conclusionImproved methodology in smartphone-based app enhanced the detection of RB and this may translate into better outcome after treatment with respect to vision salvage.
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Registered trials
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