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An automated tool for cortical feature analysis: Application to differences on 7 T esla T 2 * ‐weighted images between young and older healthy subjects
Author(s) -
Doan Nhat Trung,
van Rooden Sanneke,
Versluis Maarten J.,
Buijs Mathijs,
Webb Andrew G.,
van der Grond Jeroen,
van Buchem Mark A.,
Reiber Johan H.C.,
Milles Julien
Publication year - 2015
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.25397
Subject(s) - white matter , contrast (vision) , cortex (anatomy) , cerebral cortex , pattern recognition (psychology) , nuclear medicine , neuroscience , nuclear magnetic resonance , magnetic resonance imaging , medicine , artificial intelligence , biology , computer science , physics , radiology
Purpose High field T 2 * ‐weighted MR images of the cerebral cortex are increasingly used to study tissue susceptibility changes related to aging or pathologies. This paper presents a novel automated method for the computation of quantitative cortical measures and group‐wise comparison using 7 Tesla T 2 * ‐weighted magnitude and phase images. Methods The cerebral cortex was segmented using a combination of T 2 * ‐weighted magnitude and phase information and subsequently was parcellated based on an anatomical atlas. Local gray matter (GM)/white matter (WM) contrast and cortical profiles, which depict the magnitude or phase variation across the cortex, were computed from the magnitude and phase images in each parcellated region and further used for group‐wise comparison. Differences in local GM/WM contrast were assessed using linear regression analysis. Regional cortical profiles were compared both globally and locally using permutation testing. The method was applied to compare a group of 10 young volunteers with a group of 15 older subjects. Results Using local GM/WM contrast, significant differences were revealed in at least 13 of 17 studied regions. Highly significant differences between cortical profiles were shown in all regions. Conclusion The proposed method can be a useful tool for studying cortical changes in normal aging and potentially in neurodegenerative diseases. Magn Reson Med 74:240–248, 2015. © 2014 Wiley Periodicals, Inc.