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June 6, 2024 Expert Opinions by Scott C 0 Comments

Tele-ophthalmology

Virtual health care has rapidly expanded across Canada in recent years. Dr. Vivian Yin explains its role in ophthalmology and how it’s being used to increase access to eye care.

Dr. Vivian Yin
Ophthalmologist and oculoplastic surgeon
University of British Columbia, Vancouver, BC

What is tele-ophthalmology?

Tele-ophthalmology is a way of delivering eye care remotely, using any form of telecommunications technology or digital medical equipment. It offers the opportunity for ophthalmologists to attend to patients who may have limited access to eye care, like patients living in remote or rural areas.

The impact of the COVID-19 pandemic on virtual eye care

While tele-ophthalmology isn’t new, the COVID-19 pandemic led to a rapid uptake of virtual eye care visits out of necessity.

Due to public health restrictions, virtual visits were encouraged/legalized in many jurisdictions

Patient acceptance of virtual health care grew

Physician billing codes for virtual visits were introduced by health authorities

While many in-clinic visits have resumed, tele-ophthalmology has proved valuable in addressing barriers related to accessing in-person care. The infrastructure is now in place to support its use in ophthalmic practice moving forward.

What might a typical virtual care journey look like?

See how tele-ophthalmology was used to help Tara, 61, receive the eye care she needed.

Tara, 61

Patient of Dr. Yin from Fort St. John, BC

Tara is a 61-year-old from Fort St. John, BC. She felt a lump on her eye and had some intermittent double vision for over a year. She is seen by a visiting ophthalmologist as recommended by her GP.

The visiting ophthalmologist arranges for a CT scan of her orbits and determines that Tara has a tumour behind her left eye in the lacrimal gland. She is referred to Dr. Yin, an oculoplastic surgeon in Vancouver, to discuss surgical treatment options.

Tara has a virtual consult with Dr. Yin via Zoom. During this appointment, Dr. Yin reviews Tara’s CT images (taken locally in Fort St. John). Dr. Yin explains to Tara the most likely diagnosis is a lacrimal gland tumour and suggests that Tara proceeds with a biopsy for diagnosis.

Tara travels to Vancouver for surgery. She meets with Dr. Yin right before the surgery for any additional questions.

Tara’s surgery is performed by Dr. Yin. She returns home to Fort St. John.

Tara’s follow-up appointment with Dr. Yin is conducted virtually.

Once Tara’s condition is considered stabilized, her care is managed by her local ophthalmologist.

Thanks to tele-ophthalmology, Tara only needs to travel to Vancouver once – for her surgery with Dr. Yin.

“I don’t think a virtual exam can replace an in-person appointment. Rather, virtual exams are an adjunct to help coordinate patient care in certain specific scenarios so that everything that needs to be done can be arranged in one trip.”

– Dr. Vivian Yin

How is tele-ophthalmology being used to improve access to care on a population level?

Tele-ophthalmology has a long history in Canada. Several provinces have established successful tele-ophthalmology programs for disease screening and management in remote and underserved populations.

Diabetic retinopathy (DR) screening in Northern British Columbia

In a program that ran successfully for many years, collaboration between the local community and ophthalmologists was key to a successful diabetes care program. The First Nation community took ownership of a diabetes screening clinic, with ophthalmologists acting as consultants and providing imaging cameras, training, and data collection. In addition to providing retinal screening, the program provided comprehensive diabetes care that was valuable to the community, with nurses and point-of-care labs doing additional assessments and education about diabetes management.

Retinoblastoma care in Ontario

Retinoblastoma is the most common form of childhood eye cancer. Since specialists are available in only a few centres of excellence, access to care remains an issue for many affected families. The retinoblastoma team at SickKids hospital in Toronto provides service to 100% of children with retinoblastoma in Ontario, as well as Alberta and Manitoba.

Inner city Ottawa

To help reach a highly vulnerable recent immigrant population in Ottawa, standing imaging cameras at drop-in community health centres can allow patients to get an eye exam at times and in ways that are more convenient to them, when there may not be an eye care professional available.

DR screening in Northern and Eastern Ontario

Artificial intelligence (AI) technology is being used to screen rural, remote, and Indigenous populations in Northern and Eastern Ontario for DR. The AI-based system can take and interpret retinal images without the need for an eye care specialist. Patients who fail the screening are referred to an ophthalmologist for further evaluation and care.

Quebec

Tele-ophthalmology programs have been successfully implemented to serve patients across various regions, including remote areas like Nunavik and Cree territories. These initiatives aim to address the unique healthcare needs of these populations, considering their geographical isolation and limited access to specialized eye care services. By connecting patients to ophthalmologists, optometrists, and family doctors, these underserved communities receive critical eye care services and screening for DR.

Tele-ophthalmology has evolved rapidly over the last 25 years. Rudimentary retinal photography used in the early days has been replaced by increasingly sophisticated imaging that can provide a more holistic eye exam, with the potential to detect diseases like glaucoma and macular degeneration.

What’s the future of tele-ophthalmology in Canada?

Home-based disease monitoring

New technology is allowing for certain diseases, like glaucoma, to be monitored at home

A device can be used by patients at home to measure their intraocular eye pressure
Their eye doctor can access the data and use it to help inform their treatment plan

Virtual eye clinics

Linking a centre in a rural community to a major centre via tele-ophthalmology could help increase access to eye care for many Canadians

Patients in remote towns could visit a local centre staffed by an eye technician
The technician would measure their vision, conduct assessments, and obtain slit lamp photos/other imaging
In real time, an ophthalmologist could virtually review the
scans, consult with the patient, and prescribe treatment (initiated by the technician)

"My hope is that the COVID-19 pandemic has launched us into a new era where acceptance of unique virtual care models is more widespread, giving many more Canadians timely access to high-quality eye care.”

- Dr. Vivian Yin

May 9, 2024 Expert Opinions by Scott C 0 Comments

Artificial Intelligence

With all the recent buzz about artificial intelligence (AI) in medicine, you might be wondering how it might be used to support eye care. Dr. Fares Antaki shares his perspectives on the potential role of AI technology in the field of ophthalmology.

Dr. Fares Antaki
Ophthalmologist
Centre hospitalier de l’Université de Montréal,
Montréal, Québec

Why does ophthalmology need AI?

More patients

An aging population means more patients who require eye care

Fewer ophthalmologists

The number of ophthalmologists in Canada isn’t expected to keep up with the growing patient load

Limited access to care

Patients in remote or rural areas face barriers to accessing eye care

“I believe we need to build AI systems that are useful for the clinician, for the patient, and for the healthcare system. It’s important for us to determine what the bottlenecks are for providing efficient and high-quality care for our patients and using AI to address those issues.”

– Dr. Fares Antaki

Tapping into AI to positively impact eye care in Canada

While still in its infancy, AI has the potential to be integrated into ophthalmologic clinical practice with the goal of supporting three main areas:

PATIENT SCREENING

Provide large-scale, low-cost screening for some Big 5 eye diseases, like diabetic retinopathy (DR) and in the future, AMD and glaucoma

AI-assisted screening may help:

Allow more patients to be assessed for eye disease
Speed earlier detection of serious eye conditions
Reduce workload on busy clinics and hospitals, allowing more time for patients who require treatment

Eventually, there’s a potential to reinvent eye exams using AI-based tools at every step to:

Take patient history
Measure visual acuity
Identify eye disease through automated slit lamps and imaging

This could transform the clinic waiting room into a pre-testing space or give ophthalmologists the ability to take care of patients in remote areas

DIAGNOSTICS

Assist eye care professionals in making a diagnosis or predicting risk of disease progression with better accuracy

AI models are in development that can help:

Diagnose diseases like glaucoma, AMD, and DR from retinal fundus images
Identify and follow conditions of the front of the eye such as cataracts, keratitis, and conjunctival conditions

Optometry clinics
could employ AI models that help detect signs of eye disease and triage patients for referral to their nearest ophthalmologist based on the urgency

Ophthalmology clinics
could have more advanced clinical decision-making tools (for example, an AI system that considers patient demographics, optic nerve appearance, and visual fields to inform risk of glaucoma or risk of progression)

TREATMENT

Advance precision medicine – choosing the best treatment for each unique patient

Cataract surgery
AI algorithms already allow ophthalmologists to select the best power of intraocular lens for each patient based on their eye dimensions

AMD/DR
A smart AI agent is in development that informs the specialist performing anti-VEGF injections whether they need to switch medications or adjust the treatment interval, based on the appearance on imaging and patient’s visual acuity

Retinal surgery
In the future, AI systems could allow ophthalmologists to determine the ideal surgical technique and post-operative instructions for each patient for the best possible outcome

“There are many ways to fix a retinal detachment – which technique is right for this patient?”

High tech gizmos and gadgets on the horizon

Visual assessment devices equipped with a virtual assistant that can coach patients through a visual field assessment without a technician

Smart contact lenses that continuously monitor intraocular pressure and can inform the risk of glaucoma

RETFound – the first ophthalmic foundation model

A foundation model for retinal images
It is trained (through self-supervised learning) on over 1.6 million unlabelled optical coherence tomography (OCT) and colour fundus photography images
The model can then be fine-tuned for a variety of disease-related clinical tasks such as:
- Detecting or classifying eye diseases such as DR, glaucoma, and AMD
- Predicting AMD progression
- Predicting occurrence of cardiovascular or neurodegenerative diseases based on retinal images

Foundation models are a novel paradigm for building AI systems. They can be multimodal – so they can understand different types of data, including text and images. Since ophthalmology is a speciality that is multimodal (relying on imaging from different machines to make a diagnosis), foundation models have a benefit over traditional deep learning models that can only take one modality at a time.

Chatbot technologies (like GPT-4 or Google Gemini)

Large-language models (text-based)
They have shown impressive capabilities in answering questions related to ophthalmology
Many potential applications are possible, including helping clinicians:
- Triage patients
- Assist in the diagnosis of eye diseases
- Assist in clinical documentation

Bringing an AI-based care model into routine clinical practice

While AI has the potential to transform many areas of eye care, there are several barriers to widespread adoption in Canada. Rolling out an effective AI system requires:

Electronic health records
(many provinces don’t have them, or they aren’t shared across healthcare settings)

IT infrastructure to support sophisticated AI technology & tools

Clinical guidance and strong frameworks to support ophthalmologists so they understand how to use AI tools effectively and responsibly

Even once these hurdles are addressed, AI won’t be adopted overnight. There are important questions to answer and steps to take before AI technology can be put into practice.

The pathway toward implementing an AI-based care model

IS THE MODEL EFFECTIVE AND RELIABLE?

Find an AI model with
good performance
metrics

DOES IT WORK IN OUR PATIENTS?

Validate the model in
the local patient
population

HOW DOES IT FIT INTO THE CURRENT CARE MODEL?

Integrate the model
into the current care
pathway

IS IT COST-EFFECTIVE?

Ensure the new
pathway is in line
with the cost of the
current standard of
care, while staying
safe and effective
for patients

HOW DO WE MAXIMIZE OUR CHANCE OF SUCCESS?

Put the right
mechanisms in place
to maintain patient
data confidentiality,
perform audits to
maintain
performance of the
system, etc.

Balancing the art and science of medicine

There’s certainly a place for AI in the future of eye care. AI offers opportunities to complement and support the expertise of ophthalmologists, ultimately leading to delivery of better care.

“As AI will continue to get better; we have to invest in two things: surgery and compassion. I don’t see any automated tool replacing ophthalmologists performing any type of surgery anytime soon. And I don’t think AI is here to make medicine inhumane, on the contrary. It will give us time to spend with patients that really need us, but for us to be good at that we need to invest in compassion and in our ability to care for patients as a whole.”

– Dr. Fares Antaki