Detailed T1-Weighted Profiles from the Human Cortex Measured in Vivo at 3 Tesla MRI

Abstract

Studies into cortical thickness in psychiatric diseases based on T1-weighted MRI frequently report on aberrations in the cerebral cortex. Due to limitations in image resolution for studies conducted at conventional MRI field strengths (e.g. 3 Tesla (T)) this information cannot be used to establish which of the cortical layers may be implicated. Here we propose a new analysis method that computes one high-resolution average cortical profile per brain region extracting myeloarchitectural information from T1-weighted MRI scans that are routinely acquired at a conventional field strength. To assess this new method, we acquired standard T1-weighted scans at 3 T and compared them with state-of-the-art ultra-high resolution T1-weighted scans optimised for intracortical myelin contrast acquired at 7 T. Average cortical profiles were computed for seven different brain regions. Besides a qualitative comparison between the 3 T scans, 7 T scans, and results from literature, we tested if the results from dynamic time warping-based clustering are similar for the cortical profiles computed from 7 T and 3 T data. In addition, we quantitatively compared cortical profiles computed for V1, V2 and V7 for both 7 T and 3 T data using a priori information on their relative myelin concentration. Although qualitative comparisons show that at an individual level average profiles computed for 7 T have more pronounced features than 3 T profiles the results from the quantitative analyses suggest that average cortical profiles computed from T1-weighted scans acquired at 3 T indeed contain myeloarchitectural information similar to profiles computed from the scans acquired at 7 T. The proposed method therefore provides a step forward to study cortical myeloarchitecture in vivo at conventional magnetic field strength both in health and disease.Electronic supplementary materialThe online version of this article (10.1007/s12021-018-9356-2) contains supplementary material, which is available to authorized users.

Mapping Cortical Laminar Structure in the 3D BigBrain

“…Instead, future extensions of this approach to fully segment the six layers of the cortex will require more flexible algorithms such as deep learning and could incorporate areal identification alongside laminar segmentation. Importantly, although these techniques were here applied to histological profiles, a similar approach could be used for laminar analysis of cortical profiles derived from MRI ( Ferguson et al 2018 ).…”

Two distinct feedback codes in V1 for ‘real’ and ‘imaginary’ internal experiences

“…We used FSL to upsample the anatomical data to 0.4mm( 40 ) (FMRIB’s Software Library, www.fmrib.ox.ac.uk/fsl). For a preliminary white matter-gray matter segmentation, we then processed anatomical imaging data using a custom-written pipeline described previously( 41, 42 ). The pipeline uses R( 43 ), AFNI( 44 ), and nighres( 45 ).…”

Exercise and microstructural changes in the motor cortex of older adults

“…In this study, we probed cortical microstructure using quantitative R 1 (1/T 1 ), as T 1 values have previously been shown to be spatially correlated with intracortical myelin levels in the common marmoset (Bock, Kocharyan, Liu, & Silva, ). Quantitative R 1 imaging and its related qualitative parameter T 1 ‐weighted imaging (T 1 W) have been previously used to study cortical microstructure, often in reference to intracortical myelin, in humans (Dinse et al, ; Ferguson et al, ; Fracasso et al, ; Lutti, Dick, Sereno, & Weiskopf, ; Rowley et al, ; Sehmbi et al, ; Sereno, Lutti, Weiskopf, & Dick, ). A benefit of R 1 over T 1 W imaging is that it provides a quantitative value that at a given MRI field strength is independent of the method of measurement and similar across studies (Trampel, Bazin, Pine, & Weiskopf, ).…”