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Demyelination is the key pathological process in multiple sclerosis (MS). The extent of demyelination can be quantified with magnetic resonance imaging by assessing the myelin water fraction (MWF). However, long computation times and high noise sensitivity hinder the translation of MWF imaging to clinical practice. In this work, we introduce a more efficient and noise robust method to determine the MWF using a joint sparsity constraint and a pre-computed B1+-T2 dictionary.A single component analysis with this dictionary is used in an initial step to obtain a B1+ map. The T2 distribution is then determined from a reduced dictionary corresponding to the estimated B1+ map using a combination of a non-negativity and a joint sparsity constraint.The non-negativity constraint ensures that a feasible solution with non-negative contribution of each T2 component is obtained. The joint sparsity constraint restricts the T2 distribution to a small set of T2 relaxation times shared between all voxels and reduces the noise sensitivity.The applied Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm can be implemented efficiently, reducing the computation time by a factor of 50 compared to the commonly used regularized non-negative least squares algorithm. The proposed method was validated in simulations and in 8 healthy subjects with a 3D multi-echo gradient- and spin echo scan at 3 ​T. In simulations, the absolute error in the MWF decreased from 0.031 to 0.013 compared to the regularized NNLS algorithm for SNR ​= ​250. The in vivo results were consistent with values reported in literature and improved MWF-quantification was obtained especially in the frontal white matter. The maximum standard deviation in mean MWF in different regions of interest between subjects was smaller for the proposed method (0.0193) compared to the regularized NNLS algorithm (0.0266). In conclusion, the proposed method for MWF estimation is less computationally expensive and less susceptible to noise compared to state of the art methods. These improvements might be an important step towards clinical translation of MWF measurements.

Magnetic resonance imaging (MRI) provides a means to non-invasively investigate the neurological links with dyslexia, a learning disability that affects one’s ability to read. Most previous brain MRI studies of dyslexia and reading skill have used structural or diffusion imaging to reveal regional brain abnormalities. However, volumetric and diffusion MRI lack specificity in their interpretation at the microstructural level. Myelin is a critical neural component for brain function and plasticity, and as such, deficits in myelin may impact reading ability. MRI can estimate myelin using myelin water fraction (MWF) imaging, which is based on evaluation of the proportion of short T2 myelin-associated water from multi-exponential T2 relaxation analysis, but has not yet been applied to the study of reading or dyslexia. In this study, MWF MRI, intelligence, and reading assessments were acquired in 20 participants aged 10–18 years with a wide range of reading ability to investigate the relationship between reading ability and myelination. Group comparisons showed markedly lower MWF by 16–69% in poor readers relative to good readers in the left and right thalamus, as well as the left posterior limb of the internal capsule, left/right anterior limb of the internal capsule, left/right centrum semiovale, and splenium of the corpus callosum. MWF over the entire group also correlated positively with three different reading scores in the bilateral thalamus as well as white matter, including the splenium of the corpus callosum, left posterior limb of the internal capsule, left anterior limb of the internal capsule, and left centrum semiovale. MWF imaging from T2 relaxation suggests that myelination, particularly in the bilateral thalamus, splenium, and left hemisphere white matter, plays a role in reading abilities. Myelin water imaging thus provides a potentially valuable in vivo imaging tool for the study of dyslexia and its remediation.

Background: Deep brain stimulation (DBS) of the superolateral branch of the medial forebrain bundle (slMFB) emerges as a - yet experimental - treatment for major depressive disorder (MDD) and other treatment refractory psychiatric diseases. First experiences have been reported from two open label pilot trials in major depression (MDD) and long-term effectiveness for MDD (50 months) has been reported. Objective: To give a detailed description of the surgical technique for DBS of the superolateral branch of the medial forebrain bundle (slMFB) in MDD. Methods: Surgical experience from bilateral implantation procedures in n = 24 patients with MDD is reported. The detailed procedure of tractography-assisted targeting together with detailed electrophysiology in 144 trajectories in the target region (recording and stimulation) is described. Achieved electrode positions were evaluated based on postoperative helical CT and fused to preoperative high resolution anatomical magnetic resonance imaging (MRI; Philips Medical Systems, Best, Netherlands), including the pre-operative diffusion tensor imaging (DTI) tractographic information (StealthViz DTI, Medtronic, USA; Framelink 5.0, Medtronic, USA). Midcommissural point (MCP) coordinates of effective contact (EC) location, together with angles of entry into the target region were evaluated. To investigate incidental stimulation of surrounding nuclei (subthalamic nucleus, STN; substantia nigra, SNr; and red nucleus, RN) as a possible mechanism, a therapeutic triangle (TT) was defined, located between these structures (based on MRI criteria in T2) and evaluated with respect to EC locations. Results: Bilateral slMFB DBS was performed in all patients. We identified an electrophysiological environment (defined by autonomic reaction, passive microelectrode recording, acute effects and oculomotor effects) that helps to identify the proper target site on the operation table. Postoperative MCP-evaluation of effective contacts (EC) shows a significant variability with respect to localization. Evaluation of the TT shows that responders will typically have their active contacts inside the triangle and that surrounding nuclei (STN, SNr, RN) are not directly hit by EC, indicating a predominant white matter stimulation. The individual EC position within the triangle cannot be predicted and is based on individual slMFB (tractography) geometry. There was one intracranial bleeding (FORESEE I study) during a first implantation attempt in a patient who later received full bilateral implantation. Typical oculomotor side effects are idiosyncratic for the target region and at inferior contacts. Conclusion: The detailed surgical procedure of slMFB DBS implantation has not been described before. The slMFB emerges as an interesting region for the treatment of major depression (and other psychiatric diseases) with DBS. So far it has only been successfully researched in open label clinical case series and in 15 patients published. Stimulation probably achieves its effect through direct white-matter modulation of slMFB fibers. The surgical implantation comprises a standardized protocol combining tractographic imaging based on DTI, targeting and electrophysiological evaluation of the target region. To this end, slMFB DBS surgery is in technical aspects comparable to typical movement disorder surgery. In our view, slMFB DBS should only be performed under tractographic assistance. Keywords: Deep brain stimulation, Depression, Diffusion tensor imaging, Fiber tracking, Medial forebrain bundle, OCD, slMFB, Stereotactic surgery, Tractography

Introduction: The histopathological basis of “unidentified bright objects” (UBOs) (hyperintense regions seen on T2-weighted magnetic resonance (MR) brain scans in neurofibromatosis-1 (NF1)) remains unclear. New in vivo MRI-based techniques (multi-exponential T2 relaxation (MET2) and diffusion MR imaging (dMRI)) provide measures relating to microstructural change. We combined these methods and present previously unreported data on in vivo UBO microstructure in NF1. Methods: 3-Tesla dMRI data were acquired on 17 NF1 patients, covering 30 white matter UBOs. Diffusion tensor, kurtosis and neurite orientation and dispersion density imaging parameters were calculated within UBO sites and in contralateral normal appearing white matter (cNAWM). Analysis of MET2 parameters was performed on 24 UBO–cNAWM pairs. Results: No significant alterations in the myelin water fraction and intra- and extracellular (IE) water fraction were found. Mean T2 time of IE water was significantly higher in UBOs. UBOs furthermore showed increased axial, radial and mean diffusivity, and decreased fractional anisotropy, mean kurtosis and neurite density index compared to cNAWM. Neurite orientation dispersion and isotropic fluid fraction were unaltered. Conclusion: Our results suggest that demyelination and axonal degeneration are unlikely to be present in UBOs, which appear to be mainly caused by a shift towards a higher T2-value of the intra- and extracellular water pool. This may arise from altered microstructural compartmentalization, and an increase in ‘extracellular-like’, intracellular water, possibly due to intramyelinic edema. These findings confirm the added value of combining dMRI and MET2 to characterize the microstructural basis of T2 hyperintensities in vivo.