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Ground truth hardware phantoms for validation of diffusion‐weighted MRI applications
Author(s) -
Pullens Pim,
Roebroeck Alard,
Goebel Rainer
Publication year - 2010
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.22243
Subject(s) - imaging phantom , diffusion mri , voxel , tracking (education) , computer science , tractography , fractional anisotropy , anisotropy , segmentation , gaussian , diffusion , fiber , artificial intelligence , physics , computer vision , materials science , optics , magnetic resonance imaging , medicine , radiology , psychology , pedagogy , quantum mechanics , composite material , thermodynamics
Abstract Purpose: To quantitatively validate diffusion‐weighted MRI (DW‐MRI) applications, a hardware phantom containing crossing fibers at a sub‐voxel level is presented. It is suitable for validation of a large spectrum of DW‐MRI applications from acquisition to fiber tracking, which is an important recurrent issue in the field. Materials and Methods: Phantom properties were optimized to resemble properties of human white matter in terms of anisotropy, fractional anisotropy, and T 2 . Sub‐voxel crossings were constructed at angles of 30, 50, and 65 degrees, by wrapping polyester fibers, with a diameter close to axon diameter, into heat shrink tubes. We show our phantoms are suitable for the acquisition of DW‐MRI data using a clinical protocol. Results: The phantoms can be used to succesfully estimate both the diffusion tensor and non‐Gaussian diffusion models, and perform streamline fiber tracking. DOT (Diffusion Orientation Transform) and q‐ball reconstruction of the diffusion profiles acquired at b = 3000 s/mm 2 and 132 diffusion directions reveal multimodal diffusion profiles in voxels containing crossing yarn strands. Conclusion: The highly purpose adaptable phantoms provide a DW‐MRI validation platform: applications include optimisation of acquisition schemes, validation of non‐Gaussian diffusion models, comparison and validation of fiber tracking algorithms, and quality control in multi‐center DWI studies. J. Magn. Reson. Imaging 2010;32:482–488. © 2010 Wiley‐Liss, Inc.