Glaucoma is the leading cause of irreversible blindness in the world, but blindness from glaucoma can often be prevented with early treatment. The eye disease damages your eye’s optic nerve and usually happens when the fluid inside the eye
(aqueous humour) has difficulty circulating. Mainly, the difficulty for its exit increases the pressure in your eye, damaging the optic nerve. Assessing the risk of getting glaucoma is a critical first step towards reducing the likelihood of a patient suffering from its blinding effects.
“In 2013, the number of people with glaucoma worldwide was estimated to be 64,3 million, increasing to 76 million in 2020 and to 111,8 million in 2040."[1]
To perform this assessment, doctors consider multiple parameters/risk factors such as symptoms, genetics, family history, other diseases and medication. However, the only sure way to screen for glaucoma is with a complete eye exam which includes several examinations of the eye. These examinations utilize hardware such as visual perimetry and OCTs, which are considered time-consuming and expensive for screening purposes.
A common and easily available method of screening for glaucoma is measuring the internal eye pressure, which in many cases causes the blinding damage to the optic nerve head. While the method is economical, it’s not very accurate as use of tonometry on its own results in a high number of false positives and because it is possible to have glaucoma without it affecting the eye pressure.
Until now, assessing glaucoma using a fundus/retinal image of the optic nerve head has been a time-consuming and complicated task reserved for ophthalmologists due to the many parameters involved and the necessary background knowledge.
A team of Spanish researchers decided to work on an objective, fast and economical method for glaucoma screening. Fundus cameras are relatively accessible devices, both in terms us and procurement, and therefore an algorithm was developed for instant analysis of a simple color photograph of the retina of the eye.
The algorithm, named RetinaLyze Glaucoma, compares the color of the optic nerve to the color of the veins and arteries of the retina, and deduces its degree of perfusion. This process is carried out in 24 optic nerve sectors, since perfusion defects caused by glaucoma affect some areas more than others. The joint analysis of the information obtained in these 24 areas, in more than 2500 cases of normal and abnormal subjects, makes it possible to obtain a mathematical function that defines the normal eye by looking at the distribution of the Blood Globin Protein (GDF) and detecting abnormal cases, such as glaucoma.
In layman’s terms, the algorithm uses machine learning (AI) to assess the damage to a vital part of the eye (the optic nerve head) to deduce if a patient should be referred to a manual assessment for glaucoma.
According to the main researcher of the project and clinical software developer, Prof.Manuel González de la Rosa M.D. Ph.D., it is “a technology that seeks to become a simple and economical diagnostic alternative that can be applied to the general public to improve the prevention of vision loss. This technology detects incipient forms of eye diseases that can be asymptomatic and, therefore, go unnoticed in examinations carried out by optometrists or other health professionals. This situation occurs in cases in which the diseases has not yet affected the central part of the retina or macula, so the patient does not perceive them and cannot warn their doctor of the symptoms.”
Prof. Manuel González de la Rosa, who has led the project, has highlighted the "objectivity" of this detection method, which only requires the patient to take photographs of the retina of the eye in a hospital, clinic and even an optometrist store setting.
The algorithm has been clinically validated in studies involving over 2500 cases and has found to be as reliable as human examinations of fundus images. The algorithm has also been compared with alternative methods such as assessment using OCT or Visual perimetry, where it achieved similar and better performance.
In a study involving 7 different fundus cameras and over 1.800 normal and glaucomatous cases, the algorithm reached a specificity of 95,5 % and a sensitivity of 86,5 % in detecting glaucoma at a stage that can be confirmed by other methods.
The algorithm has been made commercially available through the platform, RetinaLyze, in May 2018 after over a year of clinical and commercial validations and test performed by a group of doctors, optometrists and engineers.
RetinaLyze already offers screening algorithms for signs of Diabetic Retinopathy and AMD (Age-related Macular Degeneration) and tele-medicine services to eye-care specialists such as ophthalmologists and optometrists. The platform automatically presents instant results of suspicious lesions in three colors that indicate whether there is basis for a referral to an eye specialist (green, yellow, and red).
Chief Commercial Officer and co-founder of RetinaLyze System A/S (Ltd.), Ganesh Ram,welcomes the new cooperation and adds: “Our goal with RetinaLyze is to make eye-screenings accessible to receive and perform.The cooperation with Prof. de la Rosa about RetinaLyze Glaucoma, further reduces the price and complexity of the equipment as well as the competences necessary to perform eye-screenings while maintaining a high performance. The ease-of-use, as well as the simplicity of the eye exam and the speed of theresult, makes the RetinaLyze service an ideal eye-screening tool for hospitals,clinics and optometry practices”.
RetinaLyze System A/S is a medical technology company established in 2013, which is represented in 35 countries all over the world. The company delivers groundbreaking decision support tools to eye-screening professionals to enable efficient, accessible and fast eye-screenings. All our algorithms and services are CE-marked, clinically validated and patented.
Lasse Bundgaard
Head of Global Sales
Tel. +45 42 70 12 03
Email: lbu@retinalyze.com
Ganesh Ram
Chief Commercial Officer
Tel. +45 25 94 44 08
Email: gr@retinalyze.com
[1]http://www.aaojournal.org/article/S0161-6420(14)00433-3/abstract
