New Paper of the Computer Vision Team at Sano Published in Communications Biology
Scientists from the Computer Vision team at Sano have found that MRI signals within brain tumors lesions are important to understanding reorganization patterns of brain networks.
Scientists from the Computer Vision team at Sano have found that MRI signals within brain tumors lesions are important to understanding reorganization patterns of brain networks. The findings, published in Communications Biology, analyze the characteristics of local functional and diffusion MRI signals and how they relate to global patterns of brain connectivity reorganization.
The study’s findings offer a pathway to more nuanced and effective approaches in treating brain tumors, emphasizing the importance of considering the entire tumor’s impact on brain function and structure in clinical practices.
The research has several practical implications that could significantly impact the field of neurosurgery, neuro-oncology, and personalized medicine:
1. Improve surgical planning and rehabilitation strategies,
2. Establish non-invasive monitoring,
3. Shed light on brain plasticity.
The study was carried out by Joan Falcó-Roget (Sano), Alberto Cacciola M.D. (the University of Messina), Dr. Fabio Sambataro (the University of Padova) and Alessandro Crimi (Sano). Important data was provided by researchers from the University of Ghent.
We invite you to read and discuss the paper “Functional and Structural Reorganization in Brain Tumors: A Machine Learning Approach Using Desynchronized Functional Oscillations”.
