Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

T1 relaxometry of crossing fibres in the human brain

De Santis, Silvia ORCID:, Assaf, Yaniv, Jeurissen, Ben, Jones, Derek K. ORCID: and Roebroeck, Alard 2016. T1 relaxometry of crossing fibres in the human brain. NeuroImage 141 , pp. 133-142. 10.1016/j.neuroimage.2016.07.037

[thumbnail of 1-s2.0-S1053811916303445-main.pdf]
PDF - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview


A comprehensive tract-based characterisation of white matter should include the ability to quantify myelin and axonal attributes irrespective of the complexity of fibre organisation within the voxel. Recently, a new experimental framework that combines inversion recovery and diffusion MRI, called inversion recovery diffusion tensor imaging (IR-DTI), was introduced and applied in an animal study. IR-DTI provides the ability to assign to each unique fibre population within a voxel a specific value of the longitudinal relaxation time, T1, which is a proxy for myelin content. Here, we apply the IR-DTI approach to the human brain in vivo on 7 healthy subjects for the first time. We demonstrate that the approach is able to measure differential tract properties in crossing fibre areas, reflecting the different myelination of tracts. We also show that tract-specific T1 has less inter-subject variability compared to conventional T1 in areas of crossing fibres, suggesting increased specificity to distinct fibre populations. Finally we show in simulations that changes in myelination selectively affecting one fibre bundle in crossing fibre areas can potentially be detected earlier using IR-DTI.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Neuroscience and Mental Health Research Institute (NMHRI)
Publisher: Elsevier
ISSN: 1053-8119
Funders: Wellcome Trust
Date of First Compliant Deposit: 4 October 2016
Date of Acceptance: 15 July 2016
Last Modified: 05 May 2023 02:32

Citation Data

Cited 36 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics