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Purpose: A comprehensive image-based characterization ofwhite matter should include the ability to quantify myelin and axo-nal attributes i rrespective of the complexity of fibre organizationwithin the voxel. While progress has been made with diffusionMRI-based approaches to measure axonal morphology, to dateavailable myelin metrics simply assign a single scalar value to thevoxel, reflecting some form of average of its constituent fibres.Here, a new experimental framework that combines diffusi on MRIand r elaxometry is intr oduced. It provides, for the first time, theability to assign to each un ique fibre system within a voxel, aunique value of the longitudinal relaxation time, T1, which is largelyinfluenced by the myelin content.Methods: We demonstrate the method through simulations, ina crossing fibres phantom, in fixed brains and in vivo.Results: The method is capable of recovering unique valuesof T1for each fibre population.Conclusion: The ability to extract fibr e-specific relaxometry prop-erties will provide enhanced specificity and, therefore, sensitivityto differ ences in white matter architecture, which will be invaluablein many neur oimaging studies. Further the enhanced specificitysho ul d ultimately lead to earlier diagnosis and access to treatmentin a range of white matter diseases where axon s are affected.Magn Reson Med 75:372–380, 2016.VC2015 The Authors. Mag-netic Resonance in Medicine Published by Wiley Periodicals,Inc. on behalf of International Society of Medicine in Reso-nance. This is an open access article under the terms of theCreative Commons Attribution License, which permits use,distribution, and reproduction in any medium, provided theoriginal work is properly cited.

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