Literature DB >> 30635644

Smartphone-based application improves the detection of retinoblastoma.

Amit Khedekar1,2, Bharanidharan Devarajan3, Kim Ramasamy4, Veerappan Muthukkaruppan5, Usha Kim1.   

Abstract

PURPOSE: To 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.
METHODS: Two 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.
RESULTS: Modification 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.
CONCLUSION: Improved methodology in smartphone-based app enhanced the detection of RB and this may translate into better outcome after treatment with respect to vision salvage.

Entities:  

Mesh:

Year:  2019        PMID: 30635644      PMCID: PMC6707147          DOI: 10.1038/s41433-018-0333-7

Source DB:  PubMed          Journal:  Eye (Lond)        ISSN: 0950-222X            Impact factor:   3.775


  16 in total

1.  Diagnostic inaccuracy of smartphone applications for melanoma detection.

Authors:  Joel A Wolf; Jacqueline F Moreau; Oleg Akilov; Timothy Patton; Joseph C English; Jonhan Ho; Laura K Ferris
Journal:  JAMA Dermatol       Date:  2013-04       Impact factor: 10.282

2.  The International Classification of Retinoblastoma predicts chemoreduction success.

Authors:  Carol L Shields; Arman Mashayekhi; Angela K Au; Craig Czyz; Ann Leahey; Anna T Meadows; Jerry A Shields
Journal:  Ophthalmology       Date:  2006-09-25       Impact factor: 12.079

Review 3.  Intraocular retinoblastoma: the case for a new group classification.

Authors:  A Linn Murphree
Journal:  Ophthalmol Clin North Am       Date:  2005-03

4.  Unilateral leukocoria in off axis flash photographs of normal eyes.

Authors:  Jodie Marshall; Glen A Gole
Journal:  Am J Ophthalmol       Date:  2003-05       Impact factor: 5.258

5.  Screening for retinoblastoma: presenting signs as prognosticators of patient and ocular survival.

Authors:  David H Abramson; Katherine Beaverson; Poorab Sangani; Robin A Vora; Thomas C Lee; Hilary M Hochberg; James Kirszrot; Murali Ranjithan
Journal:  Pediatrics       Date:  2003-12       Impact factor: 7.124

6.  Incidence of retinoblastoma from 1958 to 1998 in Northern Europe: advantages of birth cohort analysis.

Authors:  Stefan Seregard; Göran Lundell; Helena Svedberg; Tero Kivelä
Journal:  Ophthalmology       Date:  2004-06       Impact factor: 12.079

7.  The role of education in the promotion of red reflex assessments.

Authors:  Wj Muen; M Hindocha; Ma Reddy
Journal:  JRSM Short Rep       Date:  2010-10-26

8.  Photoleukocoria with smartphone photographs.

Authors:  Víctor Manuel Asensio-Sánchez; Lucía Díaz-Cabanas; Alba Martín-Prieto
Journal:  Int Med Case Rep J       Date:  2018-05-16

9.  Current therapy and recent advances in the management of retinoblastoma.

Authors:  Rachna Meel; Venkatraman Radhakrishnan; Sameer Bakhshi
Journal:  Indian J Med Paediatr Oncol       Date:  2012-04

10.  Detection of leukocoria using a soft fusion of expert classifiers under non-clinical settings.

Authors:  Pablo Rivas-Perea; Erich Baker; Greg Hamerly; Bryan F Shaw
Journal:  BMC Ophthalmol       Date:  2014-09-09       Impact factor: 2.209

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  1 in total

1.  EyeScreen: Development and Potential of a Novel Machine Learning Application to Detect Leukocoria.

Authors:  Alec Bernard; Shang Zhou Xia; Sahal Saleh; Tochukwu Ndukwe; Joshua Meyer; Elliot Soloway; Mandefro Sintayehu; Blen Teshome Ramet; Bezawit Tadegegne; Christine Nelson; Hakan Demirci
Journal:  Ophthalmol Sci       Date:  2022-04-15
  1 in total

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