|Year : 2018 | Volume
| Issue : 1 | Page : 54-57
Review of recent innovations in ophthalmology
John Davis Akkara1, Anju Kuriakose2
1 Department of Glaucoma, Westend Eye Hospital, Cochin, Kerala; Department of Glaucoma, Aravind Eye Hospital, Pondicherry, India
2 Department of Ophthalmology, Jubilee Mission Medical College, Thrissur, Kerala, India
|Date of Web Publication||7-Jun-2018|
John Davis Akkara
Westend Eye Hospital, Kacheripady, Kochi - 682 018, Kerala
Source of Support: None, Conflict of Interest: None
Necessity and opportunity in the form of rapidly advancing technology has made affordable innovations possible at a fast pace in ophthalmology. This article tries to cover a few of the recent frugal innovations which have a clinical potential for ophthalmologists.
Keywords: Artificial intelligence, frugal innovations, smartphone fundus photography, three-dimensional printing, virtual reality perimetry
|How to cite this article:|
Akkara JD, Kuriakose A. Review of recent innovations in ophthalmology. Kerala J Ophthalmol 2018;30:54-7
| Introduction|| |
We are in a fast changing world, and rapid advancements are taking place in the field of ophthalmology. It is difficult for a busy doctor to keep up with the technological advances and innovations taking place, so we will try to give a short summary here in this section.
Innovations happen in screening, diagnostics, medications, and surgical techniques. There are low cost innovations and expensive innovations. Some require advanced technologies, and others depend more on human skills. Every one of us will have ideas to innovate which can help a lot of people – doctors, patients, and policymakers.
Low-cost or frugal innovations are most useful in a country like India where large numbers of people need to be screened, diagnosed, and treated at a price they can afford. Jugaad, a word taken from Hindi, captures the Indian spirit of affordable innovation.
We now have easy access to knowledge over the internet, and technologies such as 3D printing, artificial intelligence, machine learning, and making smartphone apps can be learnt quite easily from free online courses. All these have accelerated the pace of innovation over the past several years.
Let us look at a few of the recent innovations in ophthalmology.
| Smartphone Slit-Lamp Imaging|| |
Much of the learning in ophthalmology is visual learning and requires good photographs for the learner to grasp the subject. It would also be useful to have slit-lamp images of interesting cases for presentation in conferences and publications. Conventional slit-lamp imaging systems are expensive, most hospitals do not have access to it, or even if they do, junior doctors have difficulty in accessing it.
For several years, ophthalmologists have tried using digital cameras held to the eyepiece of the slit lamp to take slit-lamp photographs. With rapid progress in smartphone camera technology in recent years, this so called barehanded slit-lamp photography without using any adapter has become easier. There are now several affordable adapters on the market to attach your smartphone to the eyepiece of the slit lamp which enables you to take slit-lamp photographs and videos, including gonioscopy videos and 90D/78D fundus examinations. The convenience of photo editing and sharing on smartphones has made digital camera obsolete in this scenario.
The adapters available include a few universal adapters available on Amazon (online shopping) [Figure 1]. There are also quite a few specialized ones made for slit lamps available including Dr. Biju Raju's DIYretcam, which you can make yourself from the instructions published. Jaiz AIM (Anterior Segment Imaging Module) also holds a smartphone to the slit-lamp eyepiece. There are also a few 3D printed adapters which are being developed. There is also a smartphone adapter to take anterior segment photographs without a slit lamp.
| Fundus on Phone|| |
Fundus photography is more technically challenging and more interesting for an ophthalmologist and that too can now be done with smartphones. Adapters available include MIIretcam, DIYretcam, and Jaiz Retcam. A review article by Barikian and Haddock covers various methods of smartphone fundus imaging – using a slitlamp with 90D; direct devices like D-eye or iExaminer; and using a 20D with adapters like DIYretcam  [Figure 2]. Excellent images and videos of the fundus can be obtained and shared easily. Even, fundus fluorescein angiography has been done on smartphone  though it is technically still very challenging.
| Smartphone Apps|| |
There are now several smartphone apps that help the ophthalmologist in vision testing including visual acuity, contrast sensitivity, color vision, and even stereo acuity. In addition, several calculations in ophthalmology can be done on the apps including intraocular lens power, central corneal thickness-corrected intraocular pressure, and conversion between various visual acuity systems and transposition calculations [Figure 3].
|Figure 3: Screenshot from Eye HandBook App showing some of the eye tests available|
Click here to view
| Perimetry|| |
Visual field perimetry is one of the cornerstones of glaucoma diagnosis and monitoring. However, it is a cumbersome and difficult procedure for the patient. Computer-based and electronic tablet-based visual field measurement had been available for a few years, and they are useful especially in neurological field defects where the defect is deep. Recently, Virtual Reality based visual field testing has been developed such as the VirtualEye  and PeriScreener  which chart visual fields in a pattern similar to the Humphrey field analyzer [Figure 4].
| Three-Dimensional Printing|| |
The technology of three-dimensional (3D) printing involves designing virtual 3D models of devices which can then be “printed” into a solid real-life object in plastic. There are several potential applications of 3D printing in ophthalmology including teaching models, devices such as smartphone fundus camera adapter, spectacles, surgical planning, and even the pupil dilator Canabrava ring. Two of the easily available open source 3D models are the oDocs smartphone fundus camera adapter  and the Open Indirect Ophthalmoscope  from LV Prasad Eye Institute. The stereolithography (.STL) files can be downloaded and printed into plastic components using the 3D printer and then assembled [Figure 5].
|Figure 5: Three-dimensional printed smartphone fundus photography adapter|
Click here to view
| Artificial Intelligence and Machine Learning|| |
These technologies help to assist the doctor by analyzing data and arriving at a probable diagnosis. Currently, a lot of work in artificial intelligence is being done on automatically analyzing fundus photographs and optical coherence tomographies to look for abnormal fundus, grade diabetic  retinopathy, and glaucoma. Corneal topography  is being analyzed for early detection of keratoconus. Furthermore, machine learning is being used to predict progression of refractive errors such as myopia  from previous data.
| Conclusion|| |
Innovation is happening at a rapid pace, and there is potential for incorporation of several new technologies in the field of ophthalmology.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Raju B, Raju NS, Akkara JD, Pathengay A. Do it yourself smartphone fundus camera-DIYretCAM. Indian J Ophthalmol 2016;64:663-7.
] [Full text]
Mohammadpour M, Mohammadpour L, Hassanzad M. Smartphone assisted slit lamp free anterior segment imaging: A novel technique in teleophthalmology. Cont Lens Anterior Eye 2016;39:80-1.
Sharma A, Subramaniam SD, Ramachandran KI, Lakshmikanthan C, Krishna S, Sundaramoorthy SK, et al.
Smartphone-based fundus camera device (MII ret cam) and technique with ability to image peripheral retina. Eur J Ophthalmol 2016;26:142-4.
Barikian A, Haddock LJ. Smartphone assisted fundus fundoscopy/photography. Curr Ophthalmol Rep 2018;6:46-52.
Suto S, Hiraoka T, Oshika T. Fluorescein fundus angiography with smartphone. Retina 2014;34:203-5.
Wroblewski D, Francis BA, Sadun A, Vakili G, Chopra V. Testing of visual field with virtual reality goggles in manual and visual grasp modes. Biomed Res Int 2014;2014:206082.
Xie P, Hu Z, Zhang X, Li X, Gao Z, Yuan D, et al.
Application of 3-dimensional printing technology to construct an eye model for fundus viewing study. PLoS One 2014;9:e109373.
Myung D, Jais A, He L, Blumenkranz MS, Chang RT. 3D printed smartphone indirect lens adapter for rapid, high quality retinal imaging. J Mob Technol Med 2014;3:9-15.
Schubert C, van Langeveld MC, Donoso LA. Innovations in 3D printing: A 3D overview from optics to organs. Br J Ophthalmol 2014;98:159-61.
Canabrava S, Diniz-Filho A, Schor P, Fagundes DF, Lopes A, Batista WD, et al.
Production of an intraocular device using 3D printing: An innovative technology for ophthalmology. Arq Bras Oftalmol 2015;78:393-4.
Gulshan V, Peng L, Coram M, Stumpe MC, Wu D, Narayanaswamy A, et al.
Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 2016;316:2402-10.
Rajalakshmi R, Subashini R, Anjana RM, Mohan V. Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence. Eye (Lond) 2018. doi:10.1038/s41433-018-0064-9.
Grewal DS, Jain R, Grewal SP, Rihani V. Artificial neural network-based glaucoma diagnosis using retinal nerve fiber layer analysis. Eur J Ophthalmol 2008;18:915-21.
Kovács I, Miháltz K, Kránitz K, Juhász É, Takács Á, Dienes L, et al.
Accuracy of machine learning classifiers using bilateral data from a scheimpflug camera for identifying eyes with preclinical signs of keratoconus. J Cataract Refract Surg 2016;42:275-83.
Smadja D, Touboul D, Cohen A, Doveh E, Santhiago MR, Mello GR, et al.
Detection of subclinical keratoconus using an automated decision tree classification. Am J Ophthalmol 2013;156:237-460.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]