Literature DB >> 29090061

Use of the Smart Phone as a Diagnostic Interface for Detecting Severe Retinopathy of Prematurity: A Pilot Study.

Sucheta Kulkarni1, Nilesh Kakade1, Rajiv Khandekar2, Pravin Narwadkar1, M Deshpande1.   

Abstract

Entities:  

Year:  2017        PMID: 29090061      PMCID: PMC5644418          DOI: 10.4103/jovr.jovr_207_16

Source DB:  PubMed          Journal:  J Ophthalmic Vis Res        ISSN: 2008-322X


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Dear Editor, We would like to report a pilot study to establish the use of smart phone as a diagnostic tool for detecting severe retinopathy of prematurity (ROP) compared to digital wide-field photographic images. ROP is fast emerging as an important cause of childhood blindness in India.[123] In spite of recommendations for screening of preterm babies to rule out ROP,[4] there is no evidence of universal ROP screening programs in India. Lack of awareness and limited trained manpower are important barriers in implementing screening programs for ROP. Assigning the task of performing retinal photography to a trained technician and implementing telemedicine models for ROP screening are methods that can be used to overcome these barriers. In 2012, a hospital-based observational study was conducted at a tertiary eye care center in Pune, West India, after approval from the Institution Ethics Committee. Severe ROP was defined as any ROP in zone I or plus disease or any stage 3 ROP. Poor quality images due to hazy media and patients with non-dilating pupils were excluded from the study. Digital wide-field photography (Retcam Shuttle, Clarity Medical systems, USA) was performed by a trained ophthalmic technician. The images were uploaded on a server using a unique software (i2i CARE Tele Ophthalmology Software, i2i Telesolutions Pvt. Ltd., Bangalore, India). These images could be viewed on a smart phone using a viewer software. Two ophthalmologists experienced in ROP diagnosis and management participated in this study. One ophthalmologist diagnosed severe ROP based on images viewed on Retcam monitor whereas the other diagnosed same images as seen on a smart phone screen. The screen size of the phone was 3.5 inches diagonally and resolution was 960 × 640 pixels. The sensitivity, specificity, and positive and negative predictive values for smart phone based diagnosis were calculated. Images of 206 eyes of 103 infants were included in the study. Severe ROP was diagnosed in 27 (13.1%) and 30 (14.6%) eyes using the smart phone and Retcam images, respectively. The sensitivity and specificity of reading images on smart phone were found to be 90% (95% confidence interval [CI]: 85.9–94.1) and 100%, respectively. The positive and negative predictive values were 100% and 98.3% (95% CI: 96.5–100), respectively. In a study conducted in South India,[5] a similar method of ROP screening along with competency-based training for management decisions was utilized and the diagnostic sensitivity by non-physician graders was reported to be 95.7%. Thus, the high sensitivity of this tool implies that transmitted images captured by a trained technician can be read on a smart phone for diagnosis of severe ROP and can substitute bedside assessment by an ophthalmologist, optimizing utilization of this highly-skilled and scarce resource. Utilizing a technician in ROP screening programs with simultaneous use of readily and easily accessible tools, such as smart phones by ophthalmologists to interpret retinal images, can aid in overcoming barriers of distance and accessibility, especially for Neonatal Intensive Care Unit (NICU) population in rural/semi-urban areas, that would otherwise go unscreened. Therefore, our study findings suggest that a smart phone can be used as a valid tool for detection of severe ROP in a telemedicine model of ROP screening.

Financial Support and Sponsorship

Nil.

Conflicts of Interest

There are no conflicts of interest.
  4 in total

Review 1.  Programme planning and screening strategy in retinopathy of prematurity.

Authors:  Subhadra Jalali; Raj Anand; Harsh Kumar; Mangat R Dogra; Rajvardhan Azad; Lingam Gopal
Journal:  Indian J Ophthalmol       Date:  2003-03       Impact factor: 1.848

Review 2.  Retinopathy of prematurity.

Authors:  Deepak Chawla; Ramesh Agarwal; Ashok K Deorari; Vinod K Paul
Journal:  Indian J Pediatr       Date:  2008-01       Impact factor: 1.967

3.  Characteristics of infants with severe retinopathy of prematurity in countries with low, moderate, and high levels of development: implications for screening programs.

Authors:  Clare Gilbert; Alistair Fielder; Luz Gordillo; Graham Quinn; Renato Semiglia; Patricia Visintin; Andrea Zin
Journal:  Pediatrics       Date:  2005-04-01       Impact factor: 7.124

4.  The KIDROP model of combining strategies for providing retinopathy of prematurity screening in underserved areas in India using wide-field imaging, tele-medicine, non-physician graders and smart phone reporting.

Authors:  Anand Vinekar; Clare Gilbert; Mangat Dogra; Mathew Kurian; Gangadharan Shainesh; Bhujang Shetty; Noel Bauer
Journal:  Indian J Ophthalmol       Date:  2014-01       Impact factor: 1.848

  4 in total
  2 in total

1.  Development of 3D Printed Smartphone-Based Multi-Purpose Fundus Camera (MultiScope) for Retinopathy of Prematurity.

Authors:  Arivazhagan Pugalendhi; Rajesh Ranganathan
Journal:  Ann Biomed Eng       Date:  2021-11-12       Impact factor: 3.934

2.  MII RetCam assisted smartphone based fundus imaging for retinopathy of prematurity.

Authors:  T Lekha; S Ramesh; Ashish Sharma; G Abinaya
Journal:  Indian J Ophthalmol       Date:  2019-06       Impact factor: 1.848

  2 in total

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