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AI-4-Child “Chaire” research consortium: innovative tools to fight against childhood cerebral palsy

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In conjunction with the GIS BeAChild, the AI-4-Child team is using artificial intelligence to analyze images related to cerebral palsy in children. This could lead to better diagnoses, innovative therapies and progress in patient rehabilitation. But also a real breakthrough in medical imaging.

The original version of this article was published on the IMT Atlantique website, in the News section.

Cerebral palsy is the leading cause of motor disability in children, affecting nearly two out of every 1,000 newborns. And it is irreversible. The AI-4-Child chaire (French research consortium), managed by IMT Atlantique and the Brest University Hospital, is dedicated to fighting this dreaded disease, using artificial intelligence and deep learning, which could eventually revolutionize the field of medical imaging.

“Cerebral palsy is the result of a brain lesion that occurs around birth,” explains François Rousseau, head of the consortium, professor at IMT Atlantique and a researcher at the Medical Information Processing Laboratory (LaTIM, INSERM unit). “There are many possible causes – prematurity or a stroke in utero, for example. This lesion, of variable importance, is not progressive. The resulting disability can be more or less severe: some children have to use a wheelchair, while others can retain a certain degree of independence.”

Created in 2020, AI-4-Child brings together engineers and physicians. The result of a call for ‘artificial intelligence’ projects from the French National Research Agency (ANR), it operates in partnership with the company Philips and the Ildys Foundation for the Disabled, and benefits from various forms of support (Brittany Region, Brest Metropolis, etc.). In total, the research program has a budget of around €1 million for a period of five years.

Chaire AI-4-Child, François Rousseau
François Rousseau, professor at IMT Atlantique and head of the AI-4-Child chaire (research consortium)

Hundreds of children being studied in Brest

AI-4-Child works closely with BeAChild*, the first French Scientific Interest Group (GIS) dedicated to pediatric rehabilitation, headed by Sylvain Brochard, professor of physical medicine and rehabilitation (MPR). Both structures are linked to the LaTIM lab (INSERM UMR 1101), housed within the Brest CHRU teaching hospital. The BeAChild team is also highly interdisciplinary, bringing together engineers, doctors, pediatricians and physiotherapists, as well as psychologists.

Hundreds of children from all over France and even from several European countries are being followed at the CHRU and at Ty Yann (Ildys Foundation). By bringing together all the ‘stakeholders’ – patients and families, health professionals and imaging specialists – on the same site, Brest offers a highly innovative approach, which has made it a reference center for the evaluation and treatment of cerebral palsy. This has enabled the development of new therapies to improve children’s autonomy and made it possible to design specific applications dedicated to their rehabilitation.

“In this context, the mission of the chair consists of analyzing, via artificial intelligence, the imagery and signals obtained by MRI, movement analysis or electroencephalograms,” says Rousseau. These observations can be made from the fetal stage or during the first years of a child’s life. The research team is working on images of the brain (location of the lesion, possible compensation by the other hemisphere, link with the disability observed, etc.), but also on images of the neuro-musculo-skeletal system, obtained using dynamic MRI, which help to understand what is happening inside the joints.

‘Reconstructing’ faulty images with AI

But this imaging work is complex. The main pitfall is the poor quality of the images collected, due to camera shake or artifacts during the shooting. So AI-4-Child is trying to ‘reconstruct’ them, using artificial intelligence and deep learning. “We are relying in particular on good quality views from other databases to achieve satisfactory resolution,” explains the researcher. Eventually, these methods should be able to be applied to routine images.

Significant progress has already been made. A doctoral student is studying images of the ankle obtained in dynamic MRI and ‘enriched’ by other images using AI – static images, but in very high resolution. “Despite a rather poor initial quality, we can obtain decent pictures,” notes Rousseau.  Significant differences between the shapes of the ankle bone structure were observed between patients and are being interpreted with the clinicians. The aim will then be to better understand the origin of these deformations and to propose adjustments to the treatments under consideration (surgery, toxin, etc.).

The second area of work for AI-4-Child is rehabilitation. Here again, imaging plays an important role: during rehabilitation courses, patients’ gait is filmed using infrared cameras and a system of sensors and force plates in the movement laboratory at the Brest University Hospital. The ‘walking signals’ collected in this way are then analyzed using AI. For the moment, the team is in the data acquisition phase.

Several areas of progress

The problem, however, is that a patient often does not walk in the same way during the course and when they leave the hospital. “This creates a very strong bias in the analysis,” notes Rousseau. “We must therefore check the relevance of the data collected in the hospital environment… and focus on improving the quality of life of patients, rather than the shape of their bones.”

Another difficulty is that the data sets available to the researchers are limited to a few dozen images – whereas some AI applications require several million, not to mention the fact that this data is not homogeneous, and that there are also losses. “We have therefore become accustomed to working with little data,” says Rousseau. “We have to make sure that the quality of the data is as good as possible.” Nevertheless, significant progress has already been made in rehabilitation. Some children are able to ride a bike, tie their shoes, or eat independently.

In the future, the AI-4-Child team plans to make progress in three directions: improving images of the brain, observing bones and joints, and analyzing movement itself. The team also hopes to have access to more data, thanks to a European data collection project. Rousseau is optimistic: “Thanks to data processing, we may be able to better characterize the pathology, improve diagnosis and even identify predictive factors for the disease.”

* BeAChild brings together the Brest University Hospital Centre, IMT Atlantique, the Ildys Foundation and the University of Western Brittany (UBO). Created in 2020 and formalized in 2022 (see the French press release), the GIS is the culmination of a collaboration that began some fifteen years ago on the theme of childhood disability.

Digital innovations in health

Innovation in health: towards responsibility

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Digital innovations are paving the way for more accurate predictive medicine and a more resilient healthcare system. In order to establish themselves on the market and reduce their potential negative effects, these technologies must be responsible. Christine Balagué, a researcher in digital ethics at Institut Mines-Télécom Business School, presents the risks associated with innovations in the health sector and ways to avoid them.

“Until now, the company has approached technology development without looking at the environmental and social impacts of the digital innovations produced. The time has come to do something about this, especially when it comes to human lives in the health sector”, says Christine Balagué, a researcher at Institut Mines-Telecom Business School and co-holder of the Good in Tech Chair [1]. From databases and artificial intelligence for detecting and treating rare diseases, to connected objects for monitoring patients; the rapid emergence of tools for prediction, diagnosis and also business organization is making major changes in the healthcare sector. Similarly, the goal of a smarter hospital of the future is set to radically change the healthcare systems we know today. The focus is on building on medical knowledge, advancing medical research, and improving care.

However, for Christine Balagué, a distinction must be made between the notion of “tech for good” – which consists of developing systems for the benefit of society – and “good in tech”. She says “an innovation, however benevolent it may be, is not necessarily devoid of bias and negative effects. It’s important not to stop at the positive impacts but to also measure the potential negative effects in order to eliminate them.” The time has come for responsible innovation. In this sense, the Good in Tech chair, dedicated to responsibility and ethics in digital innovations and artificial intelligence, aims to measure the still underestimated environmental and societal impacts of technologies on various sectors, including health.

Digital innovations: what are the risks for healthcare systems?

In healthcare, it is clear: an algorithm that cannot be explained is unlikely to be commercialized, even if it is efficient. Indeed, the potential risks are too critical when human lives are at stake. However, a study published in 2019 in the journal Science on the use of commercial algorithms in the U.S. health care system demonstrated the presence of racial bias in the results of these tools. This discrimination between patients, or between different geographical areas, therefore gives rise to an initial risk of unequal access to care. “The more automated data processing becomes, the more inequalities are created,” says Christine Balagué. However, machine learning is increasingly being used in the solutions offered to healthcare professionals.

For example, French start-ups such as Aiintense, incubated at IMT Starter, and BrainTale use it for diagnostic purposes. Aiintense is developing decision support tools for all pathologies encountered in intensive care units. BrainTale is looking at the quantification of brain lesions. These two examples raise the question of possible discrimination by algorithms. “These cases are interesting because they are based on work carried out by researchers and have been recognized internationally by the scientific peer community, but they use deep learning models whose results are not entirely explainable. This therefore hinders their application by intensive care units, which need to understand how these algorithms work before making major decisions about patients,” says the researcher.

Furthermore, genome sequencing algorithms raise questions about the relationship between doctors and their patients. Indeed, the limitations of the algorithm, the presence of false positives or false negatives are rarely presented to patients. In some cases, this may lead to the implementation of unsuitable treatments or operations. It is also possible that an algorithm may be biased by the opinion of its designer. Finally, unconscious biases associated with the processing of data by humans can also lead to inequalities. Artificial intelligence in particular thus raises many ethical questions about its use in the healthcare setting.

What do we mean by a “responsible innovation”? It is not just a question of complying with data processing laws and improving the health care professional’s way of working. “We must go further. This is why we want to measure two criteria in new technologies: their environmental impact and their societal impact, distinguishing between the potential positive and negative effects for each. Innovations should then be developed according to predefined criteria aimed at limiting their negative effects,” says Christine Balagué.

Changing the way innovations are designed

Liability is not simply a layer of processing that can be added to an existing technology. Thinking about responsible innovation implies, on the contrary, changing the very manner in which innovations are designed. So how do we ensure they are responsible? Scientists are looking for precise indicators that could result in a “to do list” of criteria to be verified. This starts with the analysis of the data used for learning, but also by studying the interface developed for the users, through the architecture of the neural network that can potentially generate bias. On the other hand, existing environmental criteria must be refined by taking into account the design chain of a connected object and the energy consumption of the algorithms. “The criteria identified could be integrated into corporate social responsibility in order to measure changes over time,” says Christine Balagué.

In the framework of the Good In Tech chair, several research projects, including a thesis, are being carried out on our capacity to explain algorithms. Among them, Christine Balagué and Nesma Houmani (a researcher at Télécom SudParis) are interested in algorithms for electroencephalography (EEG) analysis. Their objective is to ensure that the tools use interfaces that can be explained to health care professionals, the future users of the system. “Our interviews show that explaining how an algorithm works to users is often something that designers aren’t interested in, and that making it explicit would be a source of change in the decision-making process,” says the researcher. The ability to explain and interpret results are therefore two key words guiding responsible innovation.

Ultimately, the researchers have identified four principles that an innovation in healthcare must follow. The first is anticipation in order to measure the potential benefits and risks upstream of the development phase. Then, a reflexive approach allows the designer to limit the negative effects and to integrate into the system itself an interface to explain how the technological innovation works to physicians. It must also be inclusive, i.e. reaching all patients throughout the territory. Finally, responsive innovation facilitates rapid adaptation to the changing context of healthcare systems. Christine Balagué concludes: “Our work shows that taking into account ethical criteria does not reduce the performance of algorithms. On the contrary, taking into account issues of responsibility helps to promote the acceptance of an innovation on the market”.

[1] The Chair is supported by the Institut Mines-Télécom Business School, the School of Management and Innovation at Sciences Po, and the Fondation du Risque, in partnership with Télécom Paris and Télécom SudParis.

Anaïs Culot

Also read on I’MTech :

Healthcare: what makes some connected objects a success and others a flop?
e-VITA

e-VITA, a virtual coach for seniors

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Virtual coaching can play a crucial role in maintaining healthy and active ageing through early detection of risks and intervention tailored to the individual needs of senior citizens. However, current technologies do not meet these requirements. Instead they offer limited interaction and are often intrusive. The 22 European and Japanese partners of the e-VITA project will develop a “multi-modal personal voice coach” to assist and safeguard the elderly person at home. With a budget of €4m funded by the European Union and of an equivalent amount funded by the Japanese MIC (Ministry of Internal Affairs and Communications), the project began in January 2021 for a duration of 3 years. Interview with Jérôme Boudy, researcher at Télécom SudParis, and project partner.

How did the European e-VITA project come about?

Jérôme Boudy – In a context of ageing populations, the idea of this project gradually took shape from 2016 onwards. Initially, there were ongoing projects such as EMPATHIC, of which Télécom SudParis is a partner, followed by a collaboration with Brazil, and finally the e-VITA (European-Japanese virtual coach for smart ageing) project with Japan, which aims to develop tools to ensure active and healthy ageing (AHA) through the early detection of the risks associated with old age. 

Read more on I’MTech: AI to assist the elderly

What is the goal of e-VITA?

JB – The aim is to keep the elderly at home in a secure environment. Founded on international cooperation between Europe and Japan, e-VITA offers an innovative approach to “virtual coaching” that addresses the crucial areas of active and healthy ageing: cognition, physical activity, mobility, mood, social interaction, leisure… enabling older people to better manage their own health and daily activities.

What method will be used?

JB – By taking  into account different cultural factors in European countries and in Japan, in particular the acceptability of interfaces used preferentially in these countries (smartphones, 3D holograms, social robots, etc.) e-VITA will develop an automatic multi-modal human-machine interface. Based on Natural Language Processing (NLP) and automatic spoken dialog management, it will also be equipped with several complementary non-verbal modalities such as recognition of a person’s gestures, emotions, and situation.

This “virtual coach” will detect potential risks in the user’s daily environment and how these risks could be prevented by collecting data from external sources and non-intrusive sensors. It will provide individualized profiling and personalized recommendations based on big data analytics and socio-emotional informatics. Interoperability and data confidentiality will be guaranteed through FIWARE and a federated data AI platform.

What expertise will Télécom SudParis and IMT Atlantique researchers involved in e-VITA bring to the table?

JB – Researchers from IMT schools will mainly ensure the interoperability and processing of the data provided by the different sensors, as well as the automatic monitoring of emotions on the face. In addition, our two living labs – Experiment’HaaL for IMT Atlantique and Evident for Télécom SudParis –  will be made available to project partners. Finally, we will be in charge of the management of the “dissemination and exploitation” work package.

The project brings together a large number of partners. What are their roles in this project?

JB – The consortium brings together 12 partners in Europe and 10 in Japan, each with their respective complementary roles. Siegen University (Germany) and Tohoku University, are co-ordinating the project for Europe and for Japan, which brings together three major groups: end users responsible for needs specification and field assessment, such as APHP (France), AGE Platform Europe (Belgium), IRNCA (Italy), Caritas Germany, NCGG and IGOU (Japan); Academics and research organizations specializing in AI algorithms (automatic learning, fusion, expression recognition, etc.): alongside the IMT schools are Fraunhofer and INFAI (Germany), UNIVPM (Italy), Tohoku University, AIST, Waseda University (Japan)… ; and lastly, industrialists in charge of technical definition and process integration, mainly SMEs: IXP (Germany), Ingegneria Informatica (Italy), Delta Dore (France), Gatebox and NEU (Japan), and a single large group: Misawa (Japan)

What are the expected results?

JB – The creation of a “multi-modal personal voice coach” whose job is to assist, accompany and safeguard the elderly at home, and the operation of this system through several physical interfaces (smart-phones, robots, etc…) thanks to the integration of start-up incubators in our living labs and structures.

The coaching system will be installed into the living environments of healthy elderly people in France, Germany, Italy, and Japan to evaluate its feasibility and effectiveness. The results of the e-VITA project also include new standards and policies beyond technology, and will therefore be explored and transferred across Europe, Japan and worldwide.

What are the next big steps for the e-VITA project?

JB – The next step is the phase of specifying user needs according to cultural factors, and defining the architecture of the targeted system, which requires the organization of several workshops.

Find out more about e-VITA

Interview by Véronique Charlet

appli sante, health apps

Will health apps soon be covered by health insurance?

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Charlotte Krychowski, Télécom École de Management – Institut Mines-Télécom ;
Meyer Haggège, Grenoble École de Management (GEM) and Myriam Le Goff-Pronost, IMT Atlantique – Institut Mines-Télécom

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[dropcap]“A[/dropcap]pproval”. It has now been a year since the French National Authority for Health (HAS) reached a positive conclusion on whether the Diabeo application could be reimbursed by national health insurance. The application is designed to help diabetic patients in dosage and ongoing treatment. This is a first for mobile applications!

The actual ruling of whether the application can be reimbursed, however, depends on the publication of results of a medical and economic study being carried out on the tool. The Telesage study, launched in 2015, includes 700 diabetic patients in France and should indicate the effectiveness of the measure.

Over recent years, there has been a worldwide explosion of mobile applications dedicated to health. Research 2 Guidance, a company specializing in analyzing this market, estimates their number at 259,000 in 2016, compared with 100,000 a year earlier.

Apps for physical exercise, counting calories and making doctor’s appointments

They have many different uses: coaching to encourage physical exercise or healthy eating, calorie counting, making doctor’s appointments, monitoring performance in sports, offering diagnoses, monitoring chronic diseases such as diabetes and soon, cancer with Moovcare, an application designed to detect relapses after a lung tumor. Of course, not all these applications carry the possibility of being reimbursed by Social Security Services. At this point, those recognized by health authorities as medical devices, are rare. These are applications that have received a CE marking, issued by ANSM (Agence Nationale de Sécurité du Médicament et des produits de santé). Their use is reserved for diagnostic or therapeutic means. For such applications the technical requirements are higher, as the health of patients is at stake. For example, an application that allows users to take a photo of a mole so that they can evaluate the risk of a melanoma (skin cancer) has not been considered a medical device, as the editor didn’t commit any validity to the result and explained that the application was solely educational.

health apps

Sports performance monitoring applications are very popular amongst jogging fans. Shutterstock

 

Diabéo, an app used by both patients and nurses

Diabeo is an application monitoring diabetes, labelled a class IIb medical device, and available only by prescription. It was developed by French company Voluntis, in collaboration with the Center for Study and Research into Improving Treatment of Diabetes (CERITD) and a French pharmaceutical lab, Sanofi-Aventis. It provides patients with a “connected” record of their blood sugar levels (glycaemia). The application is coupled with a patch which is to be stuck to the arm, and a small device, a blood sugar level reader. It is used by both the patient and the nursing team. Diabeo allows the patient to adjust the dose of insulin they need to inject, especially at meal times, using the treatment prescribed by their doctor. The application also acts as a motivator, supplying patients with health practices to follow that will help keep their illness under control.

The nursing team, on the other hand, receives reports on the patient’s blood sugar levels in real time. Alerts are triggered when they go over certain thresholds. This system facilitates continuous monitoring of the patient, allowing them to arrange appointments if their treatment needs adjusting.

This app is particularly useful as we find ourselves in an era where the incidence of diabetes is skyrocketing, whilst the number of doctors is on the decline.

Patient empowerment

The example of Diabeo illustrates the benefits we can draw from mobile health, or “m-health”. In the first instance, this allows us to improve the effectiveness of treatment through a personalized monitoring system and increased involvement of the patient in their own treatment, something we call “patient empowerment”. M-health also improves the patient’s quality of life as well as that of those around them.

Mobile health can also facilitate the transfer of information to a medical organization, allowing health professionals to concentrate on their core activity: providing healthcare. Continuously monitoring the patient ultimately reduces the risk of hospitalization, and should it occur, the average length of their stay. This could have a significant impact on public spending, especially as hospitals are being pushed to tighten the belt.

With treatments getting better and the average lifespan getting longer, chronic illnesses now form a growing part, and now even the majority, of our spending on healthcare. This means that it is necessary that public healthcare changes its mentality o purely providing healthcare to focusing on prevention and coordination of care.

Mobile health solutions may ease this transition. For example, Belgium released €3.5 million at the start of 2017 for a six-month experiment in reimbursing 24 health apps and mobile devices that allow users to monitor or treat patients from a distance. The Belgian government’s objective is to learn from these pilot projects before extending the reimbursement program in 2018.

The Medical Board gives its position

Until now, France has been falling behind in the use of digital health technology or “e-health”, but it now seems ready for a fresh approach. The country is taking on board the advice given by HAS on Diabeo, as well as the report to the National Assembly in January, stating that Social Security will partially cover the cost of connected objects for high-risk populations. Along the same lines, the French National Medical Board (CNOM) has stated it is in favor of national health insurance coverage, provided that the evaluation of the applications and connected objects shows benefits for health.

Nevertheless, several conditions are necessary for mobile applications to be able to generate the expected health benefits. In terms of the State, an absolute prerequisite is the regulation of health-related data, to guarantee confidentiality.

Additionally, health authorities must endeavor to evaluate the connected medical devices faster. In total, it has been ten years since Diabeo was developed (clinical tests started in 2007) and the positive response on its reimbursement was issued by the National Authority for Health (HAS). The current time taken for evaluations to be completed are out of sync with the rapid rate at which digital technology is progressing. This is an issue that is also being faced by the American equivalent of HAS, the Food and Drug Administration (FDA).

 

health apps

The application Diabeo is aimed at people suffering from diabetes, but also at doctors, who can receive blood sugar level reports from their patients in real time. Shutterstock

Introducing digital technology when training doctors

We must also amend the payment system for health professionals. Fee-for-service, as is practiced today, forms part of a treatment-based mentality, and does not encourage investment in prevention.

Using health apps requires us to reorganize training systems, for example by introducing teaching on digital technology in medicine studies and by creating training courses for future professions that may emerge in digital healthcare. For example, in the case of Diabeo, there will be a need to train nurses in distance monitoring of diabetes.

In terms of businesses, first and foremost, structuring of the sector must continue. France is a dynamic breeding ground for start-ups in the e-health sector, which will surely mean that better coordination will be required. The creation of structures such as the e-Health France Alliance or France eHealthTech is a first step towards allowing French businesses to gain visibility abroad and establishing a dialogue with public authorities in France.

Linking start-ups with pharmaceutical labs

Fundamentally speaking, beyond technological innovation, these companies must also innovate according to their economic models. This may occur through the alliance with major pharmaceutical labs that are searching for new paths for growth. This is the strategy that Voluntis successfully followed not only when they collaborated closely with Sanofi to produce Diabeo, but also in other therapeutic sectors, collaborating with Roche and AstraZeneca.

New economic models may call for private funding, for example from health insurance companies. These models may implement variable reimbursement rates, depending on results obtained by the app designers for a target population on predefined criteria, for example, a lower rate of hospitalization or better health stability in patients.

It seems likely that the State, by expanding the legislative framework and rethinking traditional economic models, will benefit from the potential offered by these technological advances, as will the public.

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Charlotte Krychowski, Lecturer in strategic management, Télécom École de Management – Institut Mines-Télécom ; Meyer Haggège, Post-Doctorate Researcher in strategic management and innovation, Grenoble École de Management (GEM) and Myriam Le Goff-Pronost, Associate Professor, IMT Atlantique – Institut Mines-Télécom

The original version of this article was published in French on The Conversation.