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Anatomical validation of diffusion tensor imaging (DTI)
Author(s) -
Liu Robert Ming,
Hageman Nathan,
Yang Gloria,
Cheng Nathan,
Chan Kelly,
Liu Erica,
Ortiz Jake,
Honarpisheh Helen,
Wong Anita,
Stark M. Elena,
Dong Hongwei,
Vinters Harry,
Toga Arthur,
Wisco Jonathan
Publication year - 2013
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.27.1_supplement.532.3
Subject(s) - diffusion mri , white matter , voxel , fractional anisotropy , orientation (vector space) , computer science , artificial intelligence , magnetic resonance imaging , tractography , image processing , pattern recognition (psychology) , nuclear magnetic resonance , computer vision , medicine , physics , image (mathematics) , mathematics , radiology , geometry
The Magnetic Resonance Image (MRI) based Diffusion Tensor Imaging (DTI) technique reveals brain white matter architecture in vivo by measuring the direction of the diffusion of water molecules along the anisotropic fiber bundles. Validation of DTI at present is limited to qualitative comparisons of previously known connections in the common normal human brain. Anatomical validation of DTI through histological analysis ensures that each image is representative of the inherent white matter architecture, and improves algorithms that create a tractographic image from the tensor signals in each voxel of the image. Human brain samples were imaged at 3 Tesla (T) (2.5 mm voxels) followed by sectioning and histologic processing of the tissue. Results comparing the histologic data to the imaging show good correspondence in white matter areas between both fiber integrity and axonal orientation. Vector coordinates drawn from the tissue image match the principal fiber direction derived from the probability density function of the corresponding image voxel. We anticipate that this will provide a valuable resource for the validation of DTI methods. Grant Funding Source : NIH/NIA 1 R21 AG037843 ‐02, NIH/NCRR P41 RR013642 ‐12S1, Translational Research Fund (UCLA), and the McGinty Family Foundation