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Gilles de la Tourette syndrome (GTS) is a neuropsychiatric movement disorder with reported abnormalities in various neurotransmitter systems. Considering the integral role of iron in neurotransmitter synthesis and transport, it is hypothesized that iron exhibits a role in GTS pathophysiology. As a surrogate measure of brain iron, quantitative susceptibility mapping (QSM) was performed in 28 patients with GTS and 26 matched controls. Significant susceptibility reductions in the patients, consistent with reduced local iron content, were obtained in subcortical regions known to be implicated in GTS. Regression analysis revealed a significant negative association of tic scores and striatal susceptibility. To interrogate genetic mechanisms that may drive these reductions, spatially specific relationships between susceptibility and gene-expression patterns from the Allen Human Brain Atlas were assessed. Correlations in the striatum were enriched for excitatory, inhibitory, and modulatory neurochemical signaling mechanisms in the motor regions, mitochondrial processes driving ATP production and iron‑sulfur cluster biogenesis in the executive subdivision, and phosphorylation-related mechanisms affecting receptor expression and long-term potentiation in the limbic subdivision. This link between susceptibility reductions and normative transcriptional profiles suggests that disruptions in iron regulatory mechanisms are involved in GTS pathophysiology and may lead to pervasive abnormalities in mechanisms regulated by iron-containing enzymes.

Multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons with respect to the main static field. Although analytical solutions have been able to predict some of the white matter (WM) signal behaviour of the hollow cylinder model, it has been shown that realistic models of WM offer a better description of the signal behaviour observed.In this work, we present a pipeline to (i) generate realistic 2D WM models with their microstructure based on real axon morphology with adjustable fiber volume fraction (FVF) and g-ratio. We (ii) simulate their interaction with the static magnetic field to be able to simulate their MR signal. For the first time, we (iii) demonstrate that realistic 2D WM models can be used to simulate a MR signal that provides a good approximation of the signal obtained from a real 3D WM model derived from electron microscopy. We then (iv) demonstrate in silico that 2D WM models can be used to predict microstructural parameters in a robust way if ME-GRE multi-orientation data is available and the main fiber orientation in each pixel is known using DTI. A deep learning network was trained and characterized in its ability to recover the desired microstructural parameters such as FVF, g-ratio, free and bound water transverse relaxation and magnetic susceptibility. Finally, the network was trained to recover these micro-structural parameters from an ex vivo dataset acquired in 9 orientations with respect to the magnetic field and 12 echo times. We demonstrate that this is an overdetermined problem and that as few as 3 orientations can already provide comparable results for some of the decoded metrics.

The knowledge of relaxation times is essential for understanding the biophysical mechanisms underlying contrast in magnetic resonance imaging. Quantitative experiments, while offering major advantages in terms of reproducibility, may benefit from simultaneous acquisitions. In this work, we demonstrate the possibility of simultaneously recording relaxation-time and susceptibility maps with a prototype Multi-Echo (ME) Magnetization-Prepared 2 RApid Gradient Echoes (MP2RAGE) sequence. T1 maps can be obtained using the MP2RAGE sequence, which is relatively insensitive to inhomogeneities of the radio-frequency transmit field, [Formula: see text]. As an extension, multiple gradient echoes can be acquired in each of the MP2RAGE readout blocks, which permits the calculation of [Formula: see text] and susceptibility maps. We used computer simulations to explore the effects of the parameters on the precision and accuracy of the mapping. In vivo parameter maps up to 0.6 mm nominal resolution were acquired at 7 T in 19 healthy volunteers. Voxel-by-voxel correlations and the test-retest reproducibility were used to assess the reliability of the results. When using optimized paramenters, T1 maps obtained with ME-MP2RAGE and standard MP2RAGE showed excellent agreement for the whole range of values found in brain tissues. Simultaneously obtained [Formula: see text] and susceptibility maps were of comparable quality as Fast Low-Angle SHot (FLASH) results. The acquisition times were more favorable for the ME-MP2RAGE (≈ 19 min) sequence as opposed to the sum of MP2RAGE (≈ 12 min) and FLASH (≈ 10 min) acquisitions. Without relevant sacrifice in accuracy, precision or flexibility, the multi-echo version may yield advantages in terms of reduced acquisition time and intrinsic co-registration, provided that an appropriate optimization of the acquisition parameters is performed.