The Road Ahead - Reinventing the Approach

to Diabetic Retinopathy in the Era of AI

Eye – Primary Human Cognition

Visual perception of our surroundings gives us the sense of reality around us. Interpretation

of light from surrounding medium gives us visual perception. Eyes are our source to process

light from our surroundings, to create visual perception. The Eye is a major sensory organ

and is an important medium in the human cognition system. Up to 80% of human cognition

data is consumed through visual medium. Vision, being our dominant sense, combined with

other sensory organs provides us with a sense of being and reality.

Diseases of the eye not only affect the vision but also

coordination of our cognitive abilities. Blindness

reduces people’s ability to perform daily tasks and

move about unaided, affecting their quality of life and

ability to interact with the surrounding world. It is the

most severe form of visual impairment. Most of the

diseases and conditions causing blindness can be

prevented or treated with known and cost-effective

interventions, if detected early.

Blindness – worrying statistics

Blindness and vision impairment are a major health problem and 80% of all blindness and

vision impairment is preventable or treatable. Some related facts are illustrated in table

below:

Blindness Facts

232.5 Million4 people in the world are visually impaired

• People aged 50+ year make up 81% of global population who are blind or have

moderate to severe vision impairment

• Among children an estimated 19 million are vision impaired.

• Worldwide, 425 million adults1 (1 in 11) have diabetes; half the cases are

undiagnosed. This number is expected to reach 629 million by 2045.

• Of Indian citizens, 72.9 million2, or nearly one in thirteen, have diabetes and by

2025 the it would be astonishing 134.3 million.

• Of all visual impairment 4.19% is caused by DR

Approximately 80%3 of all vision impairment globally is considered

avoidable.

Leading causes of blindness

Cataract, refractive error and diabetic retinopathy are the most common causes of blindness.

They all fall under the category of vision impairment that are preventable and treatable.

Intervention by ophthalmology methods to improve eye health have been found to be the

most cost-effective in tackling them.

CataractRefractive Error

DiabeticRetinopathy

Blindness - leading causes

Ophthalmology & Inverted Healthcare Pyramid

Ophthalmology has the potential to provide solutions for the cause of blindness. But this

area suffers from a few shortcomings. In India there are only about 35K+ ophthalmologists

for its 1 billion-plus population, resulting in a ratio of 1 ophthalmologist for every 70,000

people, while an adequate ratio is ideally 1 ophthalmologist for every 15,800 people.

On top of it Urban: Rural divide has increased this ratio further, hence it has led to a steady

increase in the numbers of patients with blindness in India i.e 1: 99000 ophthalmologist

This is further accentuated by the inverted healthcare pyramid.

The inverted healthcare pyramid, three layered government health centre model is tuned for

graded care and brings health and medical care closer to patient’s home but hinders timely

detection in case of eye diseases affecting blindness.

Among the causes that lead to blindness Diabetic Retinopathy is the leading cause for the

most productive age, 21 to 60, in the working population of India.

The shortcomings of the inverted healthcare pyramid are illustrated in the diagram below

with diabetic retinopathy representing the predicted growth in cases in India on the right side

and operational factors affecting the health care model on the left.

Visual interaction with digital devices, in the growing digital economy, will play the dominant

role amongst all the cognitive abilities. And to have a large population in the working age

affected by this disease will hamper their ability to benefit from digital interactions in the

newer economy. The health care model specifically and industry in general is not fully

geared to tackle the growth in diabetic retinopathy cases.

Operationally more than 60% patients with early symptoms would need only initial screening.

These large number of population can be screened through AI – Deep Learning Technology

which is revolution in Healthcare industry. The inverted health care model even though

beneficial in other disease handling, lacks resources trained to diagnose diabetic

retinopathy, at the health centers.

In cases where trained resources are available, they are spread thin geographically and

patients in turn suffer from delay in follow-ups. Eventually patients lose traceable and graded

treatment for diabetic retinopathy.

The problem is compounded by the lack of coordination between diabetic care and eye care.

Both are also yet to exploit advances made in technology driven diagnosis.

India to have 134.3 million people with Diabetes by 2025

Diabetic Retinopathy is leading cause of blindness in working age (21 - 60)

Expected to affect 27 miiion people by 2025

Early detection & timely treatment can prevent vision loss due to Diabetic

Retinopathy by 95%

> 60% patients at tertiary centers need only intial screening

Lack of trained resources

Delay in follow-ups across health centres

Lack of coordination between eye care and diabetic care

Inverted Healthcare Pyramid

Op

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in H

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R

Gro

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Sub-Centers

Community Health Centers

Primary Health Centers

District Hospitals

Diabetic Retinopathy (DR)

What causes diabetic retinopathy

Chronically high blood sugar from diabetes is associated with damage to the blood vessels

in the retina, leading to diabetic retinopathy. The retina detects light and converts it to signals

and send through the optic nerve to the brain. Diabetic retinopathy can cause blood vessels

in the retina to leak fluid or hemorrhage (bleed) leading to decrease in vision. In its most

advanced stage, new abnormal blood vessels proliferate (increase in number) along with

fibrous proliferations on the surface of the retina, which can lead to tractional retinal

detachment with or without vitreous hemorrhage.

Diabetic retinopathy is the most common cause of irreversible blindness in working-age

people. Elevated sugar levels from diabetes can damage the small blood vessels that

nourish the retina leading to leakage of fluid, exudates or blood from them and at times may

even block them completely. Diabetic retinopathy occurs in at least 25 % of the people who

develop diabetes(5).

The tragedy is even greater when one considers that this

blindness is largely avoidable, with regular screening.

Diabetic Retinopathy (DR) Stages

Diabetic retinopathy may progress through four stages:

1. No DR /Normal – A healthy retina

2. Mild Non-proliferative DR (NPDR) - The earliest stage of the disease consists of

microaneurysms caused by localized swelling (aneurysmal outpouching of the

capillaries) in the blood vessels of the retina.

3. Moderate NPDR - Blood vessel wall may be damaged as the disease progresses

and causes it to leak its contents (leads to hemorrhage, exudation, edema). At times

they may also lose their ability to transport blood (leading to axonal infarcts – cotton

wool spots). Both conditions cause characteristic changes to the appearance of the

retina and may contribute to DME – Diabetic Macular Edema.

4. Severe NPDR – The process of the disease seen in moderate stage is exaggerated

leading to more hemorrhages in the all the quadrants of the retina or venous beading

or the presence of communication between arterioles and venules are noted in this

stage. Cells in areas of retinal ischaemia (inadequate blood supply) secrete growth

factors that signal the retina to grow new blood vessels.

5. Proliferative DR (PDR) - At this advanced stage, Growth factors secreted by the

retina trigger the proliferation of new blood vessels, which grow along the inside

surface of the retina and into the vitreous gel that fills the eye. The new blood

vessels that start developing are likely to leak blood into the vitreous cavity. If

associated with development of fibrous proliferations may cause traction on the retina

causing permanent vision loss due to retinal detachment - the pulling away of the

retina from underlying tissue, like wallpaper peeling away from a wall. Retinal

detachment can lead to permanent vision loss and even after surgery vision recovery

is partial.

Diagnosis & Examination

Doctors have long used an ophthalmoscope to

look at the back of your eye for screening for

Diabetic Retinopathy. However, even if an

adequate number of ophthalmologists are

available, using ophthalmologists to screen

every person usually is not feasible and is likely

to be an inefficient use of resources. A

screening examination theoretically could

include a complete ophthalmic examination with

best-corrected visual acuity after refraction,

pupil dilation, and latest retinal imaging, such

as with wide-field retinal photography and optical coherence tomography (OCT).

Retinal imaging takes a digital picture of the

back of your eye. It shows the retina, the optic

disk, and blood vessels. This helps

ophthalmologists find certain diseases and

check on the health of your eyes. Retinal

imaging allows doctors to get a much wider

digital view of the retina. It doesn’t replace a

regular eye exam but adds another layer of

precision to it.

The retinal examination may be accomplished in the

following ways: (1) direct or indirect ophthalmoscopy

(2) retinal (fundus) photography. This could be done

with or without accompanying OCT. Low-cost

cameras are now widely available. The retinal

examination could also include telemedicine

approaches. Using retinal imaging, several

abnormalities can be identified – microaneurysms,

hemorrhages, macular oedema, exudates, and cotton-wool spots. The earliest

manifestations of diabetic retinopathy are focal, saccular dilations of the retinal capillary bed,

classically termed microaneurysms. These have the appearance of small red dots.

Artificial Intelligence (AI) – The augmentation between DR growth and healthcare

pyramid

AI-assisted medical screening and diagnosis based on retinal images can be used for

auxiliary screening in detection of DR and diagnostic enhancement technique for severe

cases.

The automatic and augmented identification of DR allows the health care pyramid discussed

earlier to be scaled at all levels.

Existing health care workforce can be trained to take retinal images with minimal training at

health care centers. Initial screening can be performed at community or primary health care

centers to segregate cases of DR vs Non-DR. DR cases can be referred to the next levels

with the AI augmented retinal images helping the ophthalmologists to prepare diagnosis

plans at scale.

The augmentation from AI also helps to bridge the coordination gap that exists across

diabetic and eye care verticals in healthcare. AI driven technology devices deployed across

diabetic and eye care centers allow them to perform DR screening at either of the vertical

centers and cross refer the patients with relevant medical history with traceability being

passed on.

In order to exploit AI technology at scale and be able to be used by last mile health care

worker there exists a need to develop an AI platform that can use industry wide standard

retinal images and augment the health care pyramid with traceable and explainable

diagnose for eye care by simplifying the use of complex systems needed to use AI.

AISeon Healthcare Technologies is focused on the developments of the solution for

ophthalmology platform named Dhi Ajna [i.e Intelligent Eye], with vision to become part of

leading force to fight against preventable blindness across the world.

It aims to reach out to indigent individuals suffering from curable eye

ailments and uses Assisted Augmented Intelligence to enable

Ophthalmologist to take informed decision with power of cutting-edge

technologies.

Its solution is developed on the bedrock of technologies using Artificial Intelligence, Machine

Learning and Deep Learning and is geared for “AI for Good” initiative. It has adopted an

AI

Deep Learnig

Machine Learning

Ethical approach to using Artificial Intelligence. Its solutions are geared towards achieving

automation of retinal imaging and analysis and delivering this at scale.

Dhi Ajna Platform

Dhi Ajna Platform is an automated AI [Artificial / Assisted Intelligent platform] which will help

ophthalmologist to diagnose and treat preventable blindness. This platform can be used to

sense not only retinal problems but also can be used to detect Diabetic Retinopathy,

Cataract, Glaucoma, Macular Degeneration as we scale our platform.

The platform uses an innovative approach of cross feeding dual cycle pattern to automate

the diagnosis of DR and cross feeds this diagnosis with industry standards and policy for

adaptive decision making based on the diagnosis. This dual cycle is a unique approach to

allow the use of AI technologies in a responsible and ethical manner. The diagnosis and

decisions provided by this AI driven approach allow for the process of diagnosis to be

transparent and empowers the human by keeping them in the loop adhering to policies and

regulations.

The dual AI cycles in the platform are the Autonomic Augmentation cycle and Adaptive

Decision cycle.

The Autonomic Augmentation cycle uses retinal images to produce a knowledge graph. This

knowledge graphs represents salient features in retinal images and establishes relations of

features in respect to retinal images.

Knowledge

Graph

AI Diagnose

Graph

Ground Truth

Retina ImagesDe-biasing

Feature Collation

Retinal Image

Capture

Image Decision

Map

Industry Standard

Mapping

Augumented

Diagnose Report

AI Diagnose

Module

Autonomic Augmentation Cycle Adaptive Decision Cycle

This knowledge graph helps the system designers to have “Human in The Loop”

functionality. Due to its “Human in The Loop” functionality, the knowledge graph can be

configured and tuned for different demographic profiles. It can also help the ophthalmologist

to get a better understanding on how the Dhi Ajna platform uses retinal data to arrive at a

diagnosis

The Autonomic Augmentation cycle has an in-built mechanism to de-bias the data it uses to

build its knowledge graph. This cycle builds a weighted graph from knowledge graph so that

it can be used in the next cycle.

The Adaptive Decision cycle has the ability to embed the ever-evolving AI Diagnosis Graph

into its AI Diagnosis module and apply that to retinal image captured through portable or

mobile devices.

This cycle produces decision map based on captured retinal image input and this is mapped

to the current industry standard, policies and regulations adopted by practitioners to produce

an augmented diagnose report.

The augmented diagnosis report helps the ophthalmologist to make informed and guided

decisions. The report helps to establish a digital traceability of decision cycle and quickens

the referrals in severe cases.

Dhi Ajna can parallelize processing pipelines of the dual cycle and thus the platform is

geared to auto scale for mass screening. The dual cycles act as feeders to each other to

provides continuous improvisations mechanism of knowledge base as well as diagnosis

module.

Dhi Ajna – Backbone to Octave methodology

AISeon has built proven OCTAVE methodology for seamless end to end integration from the

stage of capturing the data and retina images up to integration of Dhi Ajna produced and

validated reports being pushed to an EMR system.

Dhi Ajna platform will form the backbone of the workflow for this methodology to provide AI

driven diagnose, analysis, integrations and scale for comprehensive eye screening and care.

Features and Benefits

What Next – Way Ahead

Approximately 80% of vision impairment globally is considered avoidable including DR.

Emerging healthcare technologies focus to minimize unnecessary visit to medical

practitioners, minimizing the cost of treatment making the solution portable.

This is step in right direction to benefit mankind and enables us to participate in government

initiatives like Ayushman Bharat, Camp outreach program through government, NGOs, clinic

and hospitals. The solution is poised to help mankind by augmenting doctor’s decision

making and not replacing them…

We aim to Ignite the Vision for Better Tomorrow!!!!

Co

mp

reh

en

sive

E2

E So

luti

on • Camp Management

• Retina Grader

• DR Prediction & Diagnostic Report

• Knowledge Management Fe

atu

res • Human @ the Center

• Trust and Transperacny

• Enhanced Judgement –Augment Medical Professional e.g. Diabetologist , Health Worker

• Scalable & Interfaceable–Cloud and API Economy

• Feedback Loop

• Solution is extensible (e.g., for detection of glaucoma, retinopathy of prematurity, etc.)

Be

nef

its • Early Detection of DR

• Enables early treatment of preventable blindness

• Economy of scale

• Camp Outreach - City , Village , Remote Locations

• Scalable – Support multiple camp, clinic ,hospital (Multitenant),Quick Response Time

References

1. N.H.Cho, J.E. Shaw, S. Karuranga et al. IDF Diabetes Atlas: Global estimates for the

prevalence of diabetes for 2017 and projections for 2045. Diabetes Research and Clinical

Practice. 2018 Apr; 138: 271-281.

2. Report of International Diabetes Federation.

3. Bourne RRA, Flaxman SR, Braithwaite T, Cicinelli MV, Das A, Jonas JB et al. Vision Loss

Expert Group. Magnitude, temporal trends and projections of the global prevalence of

blindness and distance and near vision impairment: a systemic review and meta-analysis.

Lancet Global Health. 2017 Sep; 5(9): e888-97.

4. World Health Organization, the Global Burden of Disease Study 2010,2012..

5. Salil S. Gadkari, Quresh B Maskati, Barun Kumar Nayak, Prevalence of diabetic

retinopathy in India: The All India Ophthalmological Society Diabetic Retinopathy Eye

Screening Study 2014. Indian Journal of Ophthalmology. 2016; 64(1):38-44.

ABOUT THE AUTHORS

Bhavin Mehta is Managing Director @ Accenture Technology Solutions in India. Bhavin

in his role as Global Data Solution Architect Lead and AAPAC Lead for Accenture’s IBM

Practice drives the thought leadership on driving platform adoption by providing all

required supports to client teams across the globe in selling and delivering solution based

on Data In the New and IBM Technologies. He is certified Master technology Architect

(MTA), through his engagement with clients and being a part of their journey to stay

relevant in extremely competitive world. He is Digital and AI Transformation Expert along

with his key focus on Hybrid Cloud Architecture as Evangelist. Unique blend of

Executive and Technology Skills to Drive Transformation & Digital Business

Solutions at scale. Experienced Enterprise Architect with overall 20 years of IT

experience includes 18 years with Accenture.

His passion to drive the innovation and work with Gen Y, he is playing key role as

Technology Mentor for AISeon Healthcare Technologies, to Reinvent the

differentiated approach to cater to Diabetic Retinopathy in the Era of AI.

He can be reached at Bhavin@aiseon.in |Linkedin:

https://in.linkedin.com/in/bhavinpmeta

Vishal Chahal is the Chief Architect for Data and AI technologies at Global System Integrators lab @ IBM. He is also the Technical Lead for IBM Machine Learning Hub at IBM Software Labs @ Bangaluru. Vishal is a Thought Leader on Cognitive products & platforms and in above roles drives the adoption of IBM Data and AI technologies in partner ecosystem by advising, mentoring and supporting partners across the globe. He is Level 3 Certified IT specialist from The Open Group. He specializes in Watson Cognitive Products, Advanced Analytics, Advanced Visualization, DataWarehous and Data Integration technologies. Through his client engagements, he has architected Cognitive and Analytics solutions for multiple customers across Telco, Banking, Insurance, Aviation and Healthcare Industries. He has a rich background of product architecture and development experience on portfolio across Watson, SPSS, Cognos, DB2 and Websphere. Vishal is passionate about driving innovation through developer advocacy and adoption of AI solutions. He constantly contributes to the developer community through his Tech Talks on AI & Robotics and machine learning code published on Github. He is playing a key role as AI mentor to Aiseon Healthcare Technologies on Watson platform. He can be reached at vishal@aiseon.in | LinkedIn: https://in.linkedin.com/in/vishalchahal

Dr Ashish Ahuja is Ophthalmology, Vitreo-Retina Specialist, Innovator. He completed his

MBBS, DNB, FICO, FAICO(Retina), F.A.I.CO.(UVEA) F.V.R.S.(Aravind eye hospital, Madurai). He has more than 5 years of experience and is currently working as a Consultant at Sadhu Kamal Eye Hospital, Mumbai

He is a passionate innovator with several publications on low cost devices in Eye care with a focus on technology integration with ophthalmology and is an Advisor to AISeon Healthcare technologies. He has also won several Awards for his innovative work at

national and international conferences.

He has also filed a patent for post vitrectomy recovery system to help patient’s recovery after retinal surgeries. His area of interest is to develop low cost devices to impact rural healthcare delivery and to improve access of healthcare to all. He can be reached at ashish@aiseon.in

Dr. Kushal Agrawal is a Vitreo- Retina Surgeon, he is working as a domain expert in

AISeon Healthcare Technologies and he is consultant in Jupiter Hospital, Thane.

He has Completed his MBBS from 2006 – 2012 from V.S Hospital, Ahmedabad. Post that he has completed his M.S. in Ophthalmology from 2012 – 2015 from Civil Hospital, Ahmedabad.

He has done his fellowship in Retina from Prestigious LV Prasad Eye Institute,

Hyderabad. He has published scientific papers in American Journal of Ophthalmology,

British journal of Ophthalmology and various Indian Journals.

His team has been awarded best Surgical Video award by American Academy of

Ophthalmology in 2017. He has presented in various conferences in India. He is keen to

do research and involved in academic activities.

He is well versed with all kind of Retinal Surgeries and having special interest in Diabetic

Retinopathy.

He can be reached at kushal@aiseon.in