Source – https://www.iol.co.za/
Louis C H Fourie
Alzheimer’s disease and other forms of dementia (a collective name for brain syndromes which affect memory, thinking, behaviour and emotion) are a growing public health problem all over the world – with 10 million new cases worldwide every year or one new case every 2.6 seconds.
According to the World Alzheimer Report of 2020, there are more than 50 million people worldwide living with dementia in 2020, of which 60-80% are people with Alzheimer’s. This number doubles every 20 years and will reach 152 million in 2050. Unfortunately, 59.8% of people with dementia (29.83 million) are living in developing countries with a low or middle income. This will rise to 70.9% (107.94 million) by 2050. What exacerbates the situation is the economic impact of dementia, which is estimated at a global annual cost of about R14 trillion.
Research has shown that approximately three-quarters of people living with dementia have not received a formal diagnosis, especially in low- and middle-income countries. Since it is of critical importance to diagnose dementia as early as possible to enable appropriate and timely intervention, a cost-effective way of identifying dementia has become a high priority.
Paper-based dementia tests
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Until now a variety of paper-based tests have been used, such as the Community Screening Instrument for Dementia (CSID), often in combination with the Five Words Test, Animal Fluency, the Ten Word Delayed Recall Test, Stick Design Test, and Blessed Dementia Scale. Some other screening protocols that are used are the Ten Item Semi-Structured Home Interview (CHIF), the Mini-Mental State Exam (MMSE) or Folstein Test, The Addenbrookes’ Cognitive Examination 3 (ACE-3), the Montreal Cognitive Assessment (MoCA), and the Tygerberg Cognitive Battery (TCB). The screening phase is usually followed by clinicians applying the Diagnostic and Statistical Manual of mental disorders (DSM-5) criteria to confirm dementia diagnoses.
Innovative artificial intelligence (AI) test
Now two Cambridge University PhD graduates, through their company Cognetivity, came up with an innovative new smart phone app to help diagnose Alzheimer’s Disease and other forms of dementia, which takes only five minutes to execute and is more accurate than current paper-based tests.
The test uses explainable artificial intelligence (AI) to assess a person’s brain function by presenting them several black and white photos and requesting them to identify which ones contain an animal. The images are black and white so as not to disadvantage people who may be colour blind, as well as to remove any hidden clues present in colour, such as the specific colour of certain animals.
The AI-based Integrated Cognitive Assessment (ICA) test is based on humans’ strong reaction to animal stimuli, and the ability of a healthy brain to process images of animals in less than 200 milliseconds. Various mental disorders, specifically neuro-degenerative disorders, are phenotypically characterised by some degree of cognitive impairment. This rapid visual categorisation test engages brain areas affected in pre-symptomatic stages of Alzheimer’s such as the retina, visual cortex and motor cortex. It can detect subtle impairments in information processing speed, thus detecting early signs of the disease before the onset of memory symptoms.
The images appear very briefly for a split second only. Some images will clearly show an animal, while in others the presence will be less obvious or there will be no animal at all. The reason why animals are used is that research has proven that animals elicit strong reaction in people and thus provide a greater insight into a person’s brain activity. Images are used since it is not subject to linguistic or cultural biases of existing tests and can be used repeatedly to monitor development. Existing tests can be learned by subjects and therefore become less effective over time, according to the proponents of the use of images. The test is also not influenced by educational level.
A highly sensitive test for early detection
What makes the ICA app so valuable is that it gives an objective, highly sensitive measure of cognitive function, as well as an AI explanation of the model prediction. It can identify differences in the neural response speed of visual information processing long before the memory loss that current tests focus on, and thus allows the detection of dementia up to 15 years before the appearance of any symptoms. Although Alzheimer’s cannot be reversed, early detection does provide an opportunity to stop it through a variety of promising new drugs to treat early-stage Alzheimer’s such as aducanumab, lecanemab, donanemab and solanezumab (all monoclonal antibodies recruiting the immune system to remove beta-amyloid plaques in the brain), saracatinib (preventing destruction by reversing memory loss) and beta- and gamma-secretase inhibitors (blockers of beta-amyloid production).
Accuracy and adoption
A study described in a scientific paper currently under peer review, found the app to be 84.2% accurate at identifying people who are cognitively impaired, compared to 81.6% for the standard Montreal Cognitive Assessment (MoCA) test. In another trial, the ICA achieved 92% accuracy compared to 84% of the Addenbrookes’ Cognitive Examination (ACE) test. The developers expect the app to become even more accurate as the AI programme processes more data through machine learning.
In the United Kingdom, the Medicines and Healthcare Products Regulatory Agency (MHRA) has approved the inexpensive smart phone app and it is therefore already used in general practices and hospitals for the screening of cognitive impairment and dementia. According to the developers of the app, it may soon be used in homes on a smart phone to detect cognitive changes in ageing adults remotely and on a large scale. The app is also being used in the Tehran University of Medical Sciences in Iran since 2020, where it was found to be highly accurate, easy to understand even by poorly educated people, and easy to administer with automated scoring and AI to improve classification accuracy.
Until now, doctors had to mostly rely on paper-based assessments and expensive brain scans to support dementia diagnoses. The app test is cost-effective, accessible, simple to use and accurate in identifying people at a much earlier stage than current methods. Until now, it was also not possible to monitor patients with mild cognitive impairment due to time and cost. The efficiency, objectivity and ease-of-use of the app test could bring about a breakthrough in tackling a major health-care and economic problems like dementia.
Detection of multiple sclerosis
According to the researchers, an added benefit is that although the app has been developed for dementia, it could also be used to detect signs of multiple sclerosis (MS) long before any symptoms begin to appear. Cognitive impairment is common in MS patients, which means that the app could be used to detect signs of MS. Dr Masood Nabavi, from the Royal Institute for Stem Cell Biology and Technology, has recently published a study in the BMC Neurology Journal claiming that the test could distinguish between “cognitively normal” and “cognitively impaired” patients with an impressive 95% accuracy. The test could therefore be used as a marker for cognitive impairment in MS and to monitor the response of the patient to therapy.
According to the chief executive of Cognetivity, Dr Sina Habibi, the technology is “capable of revealing underlying physical damage to brain cells without the need for invasive measurement such as blood or spinal fluid sampling” and is therefore a breakthrough for clinicians who need to reliably detect and frequently monitor cognitive ability in MS patients to effectively treat sufferers. However, much more work must be done to refine the test for MS.
The smartphone app is indeed one way forward for a widespread national screening and remote monitoring programme for mild cognitive impairment, Alzheimer’s, and other forms of dementia in South Africa. It could certainly assist in identifying people with a high risk of developing the disease long before the appearance of symptoms so that appropriate steps can be taken to slow the progression of the disease.
It is apparent that in the Fourth Industrial Revolution smart technologies will increasingly transform the early detection and treatment of diseases.