The application of advanced magnetic resonance imaging (MRI) techniques enables an objective and quantitative characterization of the progression of various neurological diseases. This research focuses on developing imaging biomarkers to identify radiological patterns. For neuromuscular diseases, the aim is to identify specific patterns of fat replacement and muscle inflammation, as well as to correlate these changes with motor function and other clinical parameters. For patients with movement disorders, specific imaging patterns will be studied to establish efficacy biomarkers for deep brain stimulation. This will contribute to better patient stratification and evaluation of responses to different experimental treatments.

Application of new genetic diagnostic tools such as Whole Genome Sequencing, RNAseq, or Optical Genome Mapping to optimize the diagnosis of patients with various motor disorders, including neuromuscular diseases, dystonias, and other movement disorders.

Digital tools provide a unique opportunity to continuously and objectively monitor pediatric patients with neurological disorders. This project aims to identify and validate digital biomarkers using wearable sensors, video analysis, movement pattern analysis, and artificial intelligence applied to clinical data. The ultimate goal is to improve diagnosis, monitoring, and personalized treatment for children with complex neurological diseases.

The application of advanced magnetic resonance imaging (MRI) techniques enables an objective and quantitative characterization of the progression of various neurological diseases. This research focuses on developing imaging biomarkers to identify radiological patterns. For neuromuscular diseases, the aim is to identify specific patterns of fat replacement and muscle inflammation, as well as to correlate these changes with motor function and other clinical parameters. For patients with movement disorders, specific imaging patterns will be studied to establish efficacy biomarkers for deep brain stimulation. This will contribute to better patient stratification and evaluation of responses to different experimental treatments.