Whole‐Brain Water Content Mapping Using Super‐Resolution Reconstruction with MRI Acquisition in 3 Orthogonal Orientations

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Purpose: Brain water content provides rich tissue contrast comparable to that of longitudinal relaxation time T1, but mapping is usually performed at modest resolution. In particular, the slice thickness in 2D mapping methods is limited. Here, we combine super‐resolution reconstruction techniques with a fast water content mapping method to acquire high and isotropic resolution (0.75 mm) water content maps at 3 Tesla.Methods: A high‐resolution multi‐echo gradient echo image is super‐resolution–reconstructed from 3 low‐resolution, orthogonal multi‐echo gradient echo image acquisitions, followed by water content mapping. The mapping accuracy and SNR of the proposed method are assessed using numerical simulations, phantom studies, and in vivo data acquired from 6 healthy volunteers at 3 Tesla. A high‐resolution acquisition with an established mapping method is used as a reference.Results: Whole‐brain water content maps with 0.75 mm isotropic resolution are demonstrated. No bias in the water content values was seen following super‐resolution reconstruction. In the in vivo experiments, a lower SD of the mean water content values was observed with the proposed method compared to the reference method.Conclusions: Super‐resolution reconstruction of multi‐echo gradient echo data is demonstrated, enabling whole‐brain water content mapping with high and isotropic resolution. The accuracy of the proposed method is shown using phantoms and 6 healthy volunteers and was found to be unchanged compared to the conventional acquisition. The proposed method could increase the sensitivity of water content mapping sufficiently to enable the detection of very small lesions, such as cortical lesions in multiple sclerosis.
Funding Information
  • MSCA (764513)
  • Horizon 2020 Framework Programme
  • European Commission

This publication has 38 references indexed in Scilit: