Abstract
Pathological changes in the cortical lamina can cause several mental disorders. Visualization of these changes in vivo would enhance their diagnostics. Recently a framework for visualizing cortical structures by magnetic resonance imaging (MRI) has emerged. This is based on mathematical modeling of multi-component T1 relaxation at the sub-voxel level. This work proposes a new approach for their estimation. The approach is validated using simulated data. Sixteen MRI experiments were carried out on healthy volunteers. A modified echo-planar imaging (EPI) sequence was used to acquire 105 individual volumes. Data simulating the images were created, serving as the ground truth. The model was fitted to the data using a modified Trust Region algorithm. In single voxel experiments, the estimation accuracy of the T1 relaxation times depended on the number of optimization starting points and the level of noise. A single starting point resulted in a mean percentage error (MPE) of 6.1%, while 100 starting points resulted in a perfect fit. The MPE was <5% for the signal-to-noise ratio (SNR) ≥ 38 dB. Concerning multiple voxel experiments, the MPE was <5% for all components. Estimation of T1 relaxation times can be achieved using the modified algorithm with MPE < 5%.
Highlights
The highest functions of the brain are enabled by the complex functional architecture of the cerebral cortex
We endeavor to increase the accuracy of the mathematical modeling, which forms an integral part of the overall method
Current MR imaging of cortical layers mostly focuses on increasing the spatial resolution of the images [14,15,16]
Summary
The highest functions of the brain are enabled by the complex functional architecture of the cerebral cortex. The above-mentioned imaging procedure was made to better reflect the natural curvature of the cerebral cortex This was accomplished via sub-sampling of individual voxels and their mapping onto a grid of virtual spheres, spanning the cortical gray matter [19]. An alternative approach to imaging the cortical layers is based on the acquisition of a multitude of images—surprisingly—with lower resolutions at lower field strengths. The low-resolution images are subjected to a complex modeling and visualization pipeline resulting in high-detail maps of cortical lamination. This approach is limited due to the need for estimation of T1 relaxation times, the process of which is a tradeoff between computational complexity, time constraints, and estimation accuracy [18,19]. The Discussion compares the results with results of similar research endeavors in estimating T1 relaxation and concludes the paper
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
