Diagnostics of memory disorders is complicated, as multiple reasons can explain the degeneration of cognitive capacity. Alzheimer’s disease is the most common reason explaining 60-70% of cases. Today no single test or biomarker can predict whether a particular person will develop Alzheimer's disease.
On top of that, clinicians experience an overload of information: they need to combine information from multiple tests and biomarkers in order to find the correct reason and name for the disease.
The PredictND research project, co-funded under the European 7thFramework Programme, will not only develop new, cost-efficient methods for enabling earlier and more reliable diagnostics of different memory disorders in clinical practice; PredictND will also provide computer-based tools that help clinicians form a holistic view of the patient by combining information from several sources, such as clinical tests, imaging and blood samples, and by comparing these measurements to previously diagnosed cases available in hospital databases.
"Alongside the better prediction of memory disorders, PredictND wants to provide a completely new approach for clinicians to systematically manage the information load that they are facing in current clinical practice," says Dr Jyrki Lötjönen, Scientific Coordinator of PredictND, VTT. "For that, we intend to transfer state-of-the-art computer-based technologies, for example for image analysis and machine learning, to a modern hospital environment in order to assist clinicians in their daily work. At the earliest, the new diagnostics tool could enter the market in a couple of years."
The novel approach will be tested on 800 patients in four top hospitals in Europe: Kuopio (Finland), Copenhagen (Denmark), Amsterdam (the Netherlands) and Perugia (Italy), and compared with the existing diagnostic procedures.
"This project has been granted European funding because increasing the quality of life in Europe is high on our agenda, and memory disorders affect this seriously," explains Project Officer Amalia Vlad of the European Commission. "To treat these disorders, early detection and an accurate diagnosis are essential."
It is important to predict memory disorders before the symptoms start, especially in Alzheimer's disease where the pathological process leads to the death of brain cells. New cost-efficient methods are needed for detecting persons at high risk and corroborating this with new ways of intervention. PredictND will develop novel cost-efficient biomarkers for the early detection of persons at high risk.
One of the project partners, GE Healthcare, has already developed a PET amyloid imaging agent, a potentially powerful tool in aiding the diagnosis of Alzheimer's disease. "But results from this tool must be combined with other types of information to fully characterise the patient," says Dr Lennart Thurfjell, Head of Biomarkers and Software, Medical Diagnostics at GE Healthcare.
The use of modern machine learning techniques and the exploitation of large databases, i.e., "big data" as it is called nowadays, is still relatively limited in clinical practice. Hilkka Soininen, professor of neurology at the University of Eastern Finland, says: "The innovation of the project is to test the decision-making tool for the detection and differentiation of memory diseases at earliest phases. Detecting signs of progressive memory disease in time will allow earlier interventions and treatments. Tools which support decision-making will be common into tomorrow's clinical practice. These tools can help a clinician to extract the most important information and profiles among the multitude of data."
Dementia is a health priority in Europe. Alzheimer's disease alone accounts for costs equivalent to about 1% of the gross domestic product (GDP) of the whole world and the number of persons affected will double in the next 20 years. Alzheimer's disease affects more than five million people in Europe.
The PredictND research consortium is formed of eight top-level research, academic, industrial and medical organisations from five different European countries: VTT Technical Research Centre of Finland, GE Healthcare (UK), Imperial College London (UK), the University of Eastern Finland, Rigshospitalet (Denmark), VU Medical Center Amsterdam (the Netherlands), the University of Perugia (Italy) and Alzheimer Europe (Luxembourg).
The project will run for four years with a total budget of €4,219,646, to which the EU will contribute €3,148,000.
About VTT Technical Research Centre of Finland
VTT is a leading multitechnological applied research organization in Northern Europe. VTT creates new technology and science-based innovations in co-operation with domestic and foreign partners. Every third Finnish technology innovation contains VTT expertise. VTT's turnover is EUR 310 million and its personnel totals 2,900.