Open AccessAge‐related mapping of intracortical myelin from late adolescence to middle adulthood using T 1 ‐weighted MRI
Author(s) -
Rowley Christopher D.,
Sehmbi Manpreet,
Bazin PierreLouis,
Tardif Christine L.,
Minuzzi Luciano,
Frey Benicio N.,
Bock Nicholas A.
Publication year - 2017
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.23624
Subject(s) - white matter , neuroscience , premotor cortex , psychology , magnetic resonance imaging , cortex (anatomy) , myelin , trajectory , ventromedial prefrontal cortex , prefrontal cortex , medicine , physics , central nervous system , anatomy , cognition , radiology , dorsum , astronomy
Magnetic resonance imaging (MRI) studies in humans have reported that the T 1 ‐weighted signal in the cerebral cortex follows an inverted “U” trajectory over the lifespan. Here, we investigated the T 1 ‐weighted signal trajectory from late adolescence to middle adulthood in humans to characterize the age range when mental illnesses tend to present, and efficacy of treatments are evaluated. We compared linear to quadratic predictors of age on signal in 67 healthy individuals, 17–45 years old. We investigated ¼, ½, and ¾ depths in the cortex representing intracortical myelin (ICM), in the superficial white matter (SWM), and in a reference deep white matter tract. We found that the quadratic fit was superior in all regions of the cortex, while signal in the SWM and deep white matter showed no global dependence on age over this range. The signal trajectory in any region followed a similar shape regardless of cortical depth. The quadratic fit was analyzed in 70 cortical regions to obtain the age of maximum signal intensity. We found that visual, cingulate, and left ventromedial prefrontal cortices peak first around 34 years old, whereas motor and premotor areas peak latest at ∼38 years. Our analysis suggests that ICM trajectories over this range can be modeled well in small cohorts of subjects using quadratic functions, which are amenable to statistical analysis, thus suitable for investigating regional changes in ICM with disease. This study highlights a novel approach to map ICM trajectories using an age range that coincides with the onset of many mental illnesses. Hum Brain Mapp 38:3691–3703, 2017 . © 2017 Wiley Periodicals, Inc.