Artificial Intelligence in the Evolution of Multiple Sclerosis

Using data from the first MRI scans of patients with multiple sclerosis, obtained from the Neurology Service of the Santiago de Compostela Hospital, the program uses artificial intelligence to very accurately predict the development of these patients over 10 years, with a confidence of almost 90%. The study analyzed a total of 446 records of affected people with a follow-up period of at least one year.

This machine learning model predicts disability progression in patients with multiple sclerosis using baseline magnetic resonance imaging (MRI) data and clinical assessments using Expanded Disability Status Scale.

“The work proposes new models to describe the progression of patients using artificial intelligence programs that predict their trajectories using these descriptors, and also gives us an idea of ​​what factors contribute to this evolution, such as age of onset or injury,” explains Silvia Campanioni, first author of the work.

The study will thus enable the optimization of the dosage of MS treatment in terms of dose and duration of treatment, as well as the optimization of its use depending on the profile of each patient or treatment methods, while improving the trajectory through the use of custom ML predictors.

Age of onset and injuries, keys to evolution

Among the most notable findings, the study found that “age of onset” was one of the most influential characteristics of the developed regressor models. Moreover, the number of brain lesions greater than or equal to 9 on the initial MRI was found to be the most influential variable in the decisions of the classifier model.

“This work has a significant impact not only in scientific and technical terms, but also in economic and social terms, since it affects health, quality of life and development cooperation,” says researcher Roberto Agis from the Santiago de Compostela Health Research Institute (IDIS), the final author of the project. “We could obtain objective data and indicators of preventive measures that would help predict the therapeutic effectiveness of treatment,” he explains.

Sclerosis and artificial intelligence

Multiple sclerosis is a chronic inflammatory and neurodegenerative disease that causes demyelination and accumulation of long-term disability. In MS, autoreactive activation of the adaptive immune system plays a leading role. Although the cause of the disease is unknown, everything points to an interaction between genes and environmental risk factors, viruses and lifestyle.

He MS Atlas 2020, shows that about 3,800 patients are diagnosed in Galicia and 55,000 in Spain, with a prevalence of 75% among women and an average diagnosis age of 32 years.

According to the findings of the research team, research using artificial intelligence (AI) can provide versatile and powerful tools for the treatment of multiple sclerosis. “Artificial intelligence technologies such as deep learning and machine learning can facilitate the integration of biological, psychological and social factors in the prevention, diagnosis and treatment of multiple sclerosis, including other diseases,” explains Cesar Veiga.

Treatment decision making in multiple sclerosis continues to rely on the integration of the same patient demographic, clinical, and paraclinical variables observed many years ago, such as resonance imaging and the presence of oligoclonal bands.

“There are still many open problems in this area, and improvements are coming from several areas of convergence, such as the integration of data sets that can improve personalization and the predictive power of AI algorithms in healthcare,” says IDIS ITEN Group Director José María Prieto.

Investigation teams

The first author of the paper is PhD student Silvia Campanioni, and the project is led by doctors José María Prieto, head of the Santiago Neurology Service and head of the ITEN group; César Veiga, an artificial intelligence researcher at IIS Galicia Sur, both corresponding authors; and Dr. Roberto Agis Balboa, the last author of the paper and a researcher in the ITEN IDIS group.

The study involves the Translational Research Group on Neurological Diseases (ITEN) and the Neuroepigenetics Laboratory of the Health Research Institute of Santiago de Compostela (IDIS); the Neurology Service of the Clinical Hospital of Santiago de Compostela (CHUS); and the Cardiovascular Research Group and the Artificial Intelligence Platform for Biomedical Analysis of IIS Galicia Sur.