Multimodal Quantification of white matter in CN, AD, FTD, LBD

 
   Lead Investigator:    Alberto Redolfi
   Institution      :    IRCCS Centro San Giovanni di Dio Fatebenefratelli
   E-Mail           :    aredolfi@fatebenefratelli.eu
   Proposal ID      :    1630



   Proposal Description:
   The data requested will be used to train an advanced machine learning tool  called MUQUBIA (in Italian, MUltimodale QUantificazione sostanza BIAnca - in  English, Multimodal Quantification of white matter), aiming at improving the  differential diagnosis among AD, DLB, and FTD vs CN by using multimodal MRI  data (T13D, FLAIR, DTI, QSM).  MUQUBIA classifier will pry on automatically determined MRI features (extracted  by Freesurfer, Tracula, LPA, etc..) combined with the available clinical,  neuropsychological, and biological information.  The final goal is to develop and publish the MUQUBIA classifier results.