Background: Methylphenidate (MPH) is highly effective in treating attention-deficit/hyperactivity disorder (ADHD). However, not much is known about its effect on the development of human brain white matter (WM). Purpose: To determine whether MPH modulates WM microstructure in an age-dependent fashion in a randomized double-blind placebo-controlled trial (Effects of Psychotropic Medication on Brain Development-Methylphenidate, or ePOD-MPH) among ADHD referral centers between October 13, 2011, and June 15, 2015, by using diffusion-tensor imaging (DTI). Materials and Methods: In this prospective study (NTR3103 and NL34509.000.10), 50 stimulant treatment-naive boys and 49 young adult men diagnosed with ADHD (all types) according to Diagnostic and Statistical Manual of Mental Disorders, 4th Edition criteria were randomized to undergo treatment with MPH or placebo for 16 weeks. Before and 1 week after treatment cessation, study participants underwent MRI, including DTI. The outcome measure was change in fractional anisotropy (FA), which was assessed in three regions of interest (ROIs), as well as in a voxel-based analysis in brain WM. Data were analyzed by using intentionto- treat linear mixed models for ROI analysis and a permutation-based method for voxel-based analysis with family-wise error correction. Results: Fifty boys (n = 25 MPH group, n = 25 placebo group; age range, 10-12 years) and 48 men (n = 24 MPH group, n = 24 placebo group; age range, 23-40 years) were included. ROI analysis of FA yielded no main effect of time in any of the conditions. However, voxel-based analysis revealed significant (P , .05) time-by-medication-by-age interaction effects in several association tracts of the left hemisphere, as well as in the lateral aspect of the truncus of the corpus callosum, due to greater increase in FA (standardized effect size, 5.25) in MPH-treated boys. Similar changes were not present in boys receiving a placebo, nor in adult men. Conclusion: Four months of treatment with methylphenidate affects specific tracts in brain white matter in boys with attentiondeficit/ hyperactivity disorder. These effects seem to be age dependent, because they were not observed in adults treated with methylphenidate.@en

In this paper, we propose the use of Recurrent Inference Machines (RIMs) to perform T1 and T2 mapping. The RIM is a neural network framework that learns an iterative inference process based on the signal model, similar to conventional statistical methods for quantitative MRI (QMRI), such as the Maximum Likelihood Estimator (MLE). This framework combines the advantages of both data-driven and model-based methods, and, we hypothesize, is a promising tool for QMRI. Previously, RIMs were used to solve linear inverse reconstruction problems. Here, we show that they can also be used to optimize non-linear problems and estimate relaxometry maps with high precision and accuracy. The developed RIM framework is evaluated in terms of accuracy and precision and compared to an MLE method and an implementation of the Residual Neural Network (ResNet). The results show that the RIM improves the quality of estimates compared to the other techniques in Monte Carlo experiments with simulated data, test-retest analysis of a system phantom, and in-vivo scans. Additionally, inference with the RIM is 150 times faster than the MLE, and robustness to (slight) variations of scanning parameters is demonstrated. Hence, the RIM is a promising and flexible method for QMRI. Coupled with an open-source training data generation tool, it presents a compelling alternative to previous methods.@en

Given the restricted total scanning time for clinical neuroimaging, it is unclear whether clinical diffusion MRI protocols would benefit more from higher spatial resolution or higher angular resolution. In this work, we investigated the relative benefit of improving spatial or angular resolution in diffusion MRI to separate two parallel running white matter tracts that are targets for deep brain stimulation: the anterior thalamic radiation and the supero-lateral branch of the medial forebrain bundle. Both these tracts are situated in the ventral anterior limb of the internal capsule, and recent studies suggest that targeting a specific tract could improve treatment efficacy. Therefore, we scanned 19 healthy volunteers at 3T and 7T according to three diffusion MRI protocols with respectively standard clinical settings, increased spatial resolution of 1.4 mm, and increased angular resolution (64 additional gradient directions at b = 2200s/mm2). We performed probabilistic tractography for all protocols and quantified the separability of both tracts. The higher spatial resolution protocol improved separability by 41% with respect to the clinical standard, presumably due to decreased partial voluming. The higher angular resolution protocol resulted in increased apparent tract volumes and overlap, which is disadvantageous for application in precise treatment planning. We thus recommend to increase the spatial resolution for deep brain stimulation planning to 1.4 mm while maintaining angular resolution. This recommendation complements the general advice to aim for high angular resolution to resolve crossing fibers, confirming that the specific application and anatomical considerations are leading in clinical diffusion MRI protocol optimization.@en

Sub-millimeter imaging at 7T has opened new possibilities for qualitatively and quantitatively studying brain structure as it evolves throughout the life span. However, subject motion introduces image blurring on the order of magnitude of the spatial resolution and is thus detrimental to image quality. Such motion can be corrected for, but widespread application has not yet been achieved and quantitative evaluation is lacking. This raises a need to quantitatively measure image sharpness throughout the brain. We propose a method to quantify sharpness of brain structures at sub-voxel resolution, and use it to assess to what extent limited motion is related to image sharpness. The method was evaluated in a cohort of 24 healthy volunteers with a wide and uniform age range, aiming to arrive at results that largely generalize to larger populations. Using 3D fat-excited motion navigators, quantitative R1, R2* and Quantitative Susceptibility Maps and T1-weighted images were retrospectively corrected for motion. Sharpness was quantified in all modalities for selected regions of interest (ROI) by fitting the sigmoidally shaped error function to data within locally homogeneous clusters. A strong, almost linear correlation between motion and sharpness improvement was observed, and motion correction significantly improved sharpness. Overall, the Full Width at Half Maximum reduced from 0.88 mm to 0.70 mm after motion correction, equivalent to a 2.0 times smaller voxel volume. Motion and sharpness were not found to correlate with the age of study participants. We conclude that in our data, motion correction using fat navigators is overall able to restore the measured sharpness to the imaging resolution, irrespective of the amount of motion observed during scanning.@en