Michael G. Dwyer1, Niels Bergsland2,
Claudiu Schirda2, Mari Heininen-Brown, Ellen Carl, David Wack, Guy
U. Poloni, Robert Zivadinov3
1Buffalo Neuroimaging Analysis Center; 2University
at Buffalo, Buffalo Neuroimaging Analysis Center, Buffalo, NY, United States;
3Neurology, Buffalo Neuroimaging Analysis Center, Buffalo , NY ,
United States
Susceptibility-weighted
imaging (SWI) has gained much interest recently as a sensitive means for
detecting iron deposition in a variety of diseases, including multiple
sclerosis (SM). We propose a fast and reproducible analysis pipeline to
extract detailed quantitative SWI data and to combine it with other
established indicators of disease state (including magnetization transfer and
perfusion imaging).