Dementia and AI

Today, more than 55 million people worldwide have been diagnosed with dementia and it is believed that the number will increase by 10 million every year according to new data published by the World Health Organization (WHO)¹. Dementia has also become the 7^th leading cause of death worldwide². This makes it one of the biggest healthcare challenges we face as a society. A healthcare challenge that is still surrounded by a great deal of stigma. 

Figure 1: The numbers of Dementia^1,2.

Every September is World Alzheimer’s Month, in order to destigmatize dementia and raise awareness around Alzheimer’s Disease (AD) and dementia³. Organizations all over the world prepare educational resources and other activities to provide information and support to patients and families⁴.

With that in mind, we wanted to support the cause by creating this guide to show the latest developments of artificial intelligence (AI) in the field of Dementia and how AI can support the whole diagnostic process as well as the day-to-day life of people living with dementia or AD.

Dementia and Alzheimer's Disease

Before we dive into the different applications of AI for dementia, let’s summarize dementia.

Dementia is characterized by the atrophy of different regions of the brain, and with that, the deterioration of cognitive function greater than the one expected from normal aging. Depending on the specific regions that are most affected, we can encounter different types of dementia, AD being the most common form as it represents 60% to 70% of the diagnosed cases⁵.

Can we treat dementia?

Although there has been research and development regarding medication to mitigate dementia^6,7, currently there is no cure. Because of that, the treatment route chosen by specialists all over the world are strategies to help mitigate the symptoms, improve the quality of life, and offer support and care to those affected by dementia⁵.

How does dementia impact the life of those affected and their surroundings?

Dementia not only deeply affects the lives of those who suffer from it, but it also heavily impacts the lives of their support system. The amount of care needed can become very disruptive for families and friends as they are often the ones that become principal caregivers spending, at least in the first stages, on average up to 5 hours per day attending to their loved ones⁵.

As a result, the process can be very overwhelming and stressful, physically, mentally, and financially⁵ for both patient and family and can lead in some cases to less-than-ideal environments for the necessary care.

AI applied to dementia

For these reasons we believe in the importance of education and research to improve the process and the quality of life of those affected by dementia. When it comes to dementia, and particularly, AD, there is ample research that applies AI algorithms to the clinical pathway with different goals. For example, improving early diagnosis through automating, standardizing and improving the accuracy of the predictions, or developing effective treatments⁸.

AI applied to the diagnosis of dementia 

As we have covered above, there are different types of dementia that have different symptoms, prognoses, and treatments. For that reason, an accurate and early diagnosis will improve the quality of care for those who suffer. When it comes to the diagnostic process, there has been plenty of research evaluating the use of AI models and algorithms for different diagnostic paths. 

AI applications to AD were first explored in the field of neuroimaging. Throughout the years, researchers have focused on trying to extract as much information as possible from brain scans in an effort to track volume changes in the brain, and therefore, track brain atrophy^9,10. Some early examples include an AI algorithm that was able to classify AD based on MRI scans with an accuracy of 92.36%¹¹ or an AI algorithm that was able to give a prediction more than 75 months earlier than the final diagnosis with 82% specificity and 100% sensitivity¹². 

Besides neuroimaging, neurologists use certain cognitive tests during consultations and yearly checkups to assess symptoms or conditions, such as aphasia, related to dementia and AD¹³. AI research has been conducted with the goal of making cognitive tests¹⁴, speech assessments^15,16, and dementia screenings like the clock drawing tests¹⁷ reproducible on a larger scale so that they can reach a larger, even remote, population. Recently, a Canadian medical imaging company has developed a technology that takes retina scans on an optometrist camera, the AI algorithm can then check if there is amyloid buildup, a protein that has been commonly linked to AD and that is present in its early stages¹⁸.

Clinical implementation of AI for the diagnosis of dementia

Today, the development of these type of algorithms has reached clinical practice with multiple available AI solutions cleared by regulatory bodies like the FDA.The general belief in this technology is also shown by other medical institutions, like the American Medical Association which has recently issued reimbursement codes¹⁹ physicians could apply to when using these types of AI algorithms in their clinical practice. 

Discover Quantib's FDA cleared and CE marked AI-driven software for brain atrophy and WMH quantification. 

However, there are still concerns about critical issues regarding the implementation of AI models in clinical practice. Researchers²⁰ believe there are 3 areas that need some work in order to implement these AI models: the questions defined for the algorithms to solve need to be clear and relevant to the memory clinic; the heterogeneity of the algorithms makes it very difficult to compare their performance, and the lack of available of representative data to test the algorithms. 

AI applied to find the prognosis of dementia 

Prognosis has been a large part of AI research into AD. It primarily looks at the progression of mild cognitive impairment to AD⁸ with two different approaches, either using single-time-point data or doing a longitudinal analysis of imaging scans²⁰. The results differ greatly, however, one specific study was able to conclude that using longitudinal data provide better accuracy (88.61%) than using fixed baseline data (78.48%)²¹.

AI software for dementia treatment research

As mentioned before, there is no cure for dementia or AD at the moment. However, it is believed that there are different ways in which AI could promote the research involved in potential pharmacological treatments, that generally aim to improve symptoms and delay progression of the disease.

AI has the potential of creating tailored treatments for different clinical phenotypes of dementia and AD patients through predictive models that include expertise from an array of different fields, from neurology and clinical signs, to geriatric medicine and statistics⁸. This might allow prediction of which medication works best for each individual patient. Researchers also believe AI software has a lot of potential to select drugs to be used for the treatment of AD, for example by attacking the effects the disease has in the brain (e.g., plaques)^8,22,23.

One reason for the limited amount of treatment options might be the difficulty within clinical trials to enroll early dementia sufferers. Most participants in clinical trials are too far along in the disease for differences to be easily perceived¹⁰. AI could help clinical trials not only by providing earlier diagnosis and therefore enrolling patients that might yield better outcomes, but also by simplifying the selection and/or the implementation of those clinical trials thanks to optimizing steps such as participant selection or real-time diagnostics⁸.

AI software for post-diagnostic support

It is believed that AI can also be used after the AD or dementia diagnosis, for example, by creating a smart environment that can monitor the person’s behavior and movement¹⁴ or smart technologies on day-to-day items, like socks²⁴, and alert healthcare professionals to help when it is needed^25,26. 

Figure 2: The healthy home adapted from UK Dementia Research Institute, 2022²⁵.

This is said to improve the quality of life of those affected by dementia and their families as it can potentially ensure a safe environment in which they can stay independent and in their own homes for longer²⁷.

AI and technology to support day-to-day tasks

The use of virtual home assistants, like Google Home or Google Assistant, or even smartphones allows the personalization of reminders and alarms that can be extremely useful to avoid people forgetting important daily tasks, such as going to the toilet, having a drink, or taking their medication²⁸. 

Conclusion

The already dramatic number of cases of dementia is expected to increase by millions each year. Due to the characteristics of the disease and its burden, it is of the utmost importance to find new ways in which we can improve each step within the clinical pathway of dementia. This could allow them to live with dignity, and greatly improve the day-to-day life of patients and their loved ones.

We believe that further research utilizing AI can advance the field and ultimately provide better support to those who need it.