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We conducted a whole\u2010brain voxel\u2010based multicompartment diffusion MRI study on 316 participants (i.e., 158 patients and 158 matched healthy controls) employing four diffusion metrics: the mean diffusivity (<jats:italic>MD<\/jats:italic>) and <jats:italic>FA<\/jats:italic> estimated from DTI, and the intra\u2010axonal signal fraction (<jats:italic>IASF<\/jats:italic>) and microscopic axonal parallel diffusivity (<jats:italic>Dpar<\/jats:italic>) derived from the spherical mean technique. Our findings provide novel evidence about widespread abnormalities in other diffusion metrics in BD. An extensive overlap between the <jats:italic>FA<\/jats:italic> and <jats:italic>IASF<\/jats:italic> results suggests that the lower <jats:italic>FA<\/jats:italic> in patients may be caused by a reduced intra\u2010axonal volume fraction or a higher macromolecular content in the intra\u2010axonal water. We also found a diffuse alteration in <jats:italic>MD<\/jats:italic> involving white and grey matter tissue and more localised changes in <jats:italic>Dpar<\/jats:italic>. A Machine Learning analysis revealed that <jats:italic>FA<\/jats:italic>, followed by <jats:italic>IASF<\/jats:italic>, were the most helpful metric for the automatic diagnosis of BD patients, reaching an accuracy of 72%. Number of mood episodes, age of onset\/duration of illness, psychotic symptoms, and current treatment with lithium, antipsychotics, antidepressants, and antiepileptics were all significantly associated with microstructure abnormalities. 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