The program can detect small changes -which are inappreciable during the visual observation- that could predict the risk of developing a degenerative disease.
Identifying signs of neurodegeneration before symptoms appear in the brain is the main objective of Single Subject Brain Analysis Toolbox (SeSBAT), a computer program to allow the quantitative analysis of magnetic resonance imaging in a quick and adaptable manner for any brain affectation.
This innovative technology, which could shed light towards a more efficient and personalized medicine, has been designed by the researchers Estela Cámara, from the Faculty of Psychology and the Institute of Neurosciences (UBNeuro) of the University of Barcelona, and Alicia Palomar, member of the Bellvitge Biomedical Research Institute (IDIBELL) together with Cámara.
Magnetic resonance is the most sensitive and reliable technique to diagnose neurodegenerative diseases and to monitor them. This technology provides images that allow a complete anatomical analysis of the brain to detect any atrophy in specific areas. However, magnetic resonance imaging is usually observed visually, which makes some neurodegenerative signs –invisible to the human eye– to be ignored until the damage has advanced.
SeSBAT integrates different imaging analysis protocols that allow the measurement of the volume of specific brain regions and to make a general exploration of the organ. The program can detect small changes –which are inappreciable during the visual observation– that could predict the risk of developing a degenerative disease. Therefore, this computer program leads to the identification of new biomarkers that could help improve the early detection and monitoring of neurodegenerative diseases.
The precision in SeSBAT has been confirmed in an article published in the journal Frontiers in Systems Neuroscience. It states how the new biomedical tool is able to identify patients in early stages of Huntington's disease, even without showing the first symptoms of the disease.
