UNITY: A low-field magnetic resonance neuroimaging initiative to characterize neurodevelopment in low and middle-income settings.

Measures of physical growth, such as weight and height have long been the predominant outcomes for monitoring child health and evaluating interventional outcomes in public health studies, including those that may impact neurodevelopment. While physical growth generally reflects overall health and nutritional status, it lacks sensitivity and specificity to brain growth and developing cognitive skills and abilities. Psychometric tools, e.g., the Bayley Scales of Infant and Toddler Development, may afford more direct assessment of cognitive development but they require language translation, cultural adaptation, and population norming. Further, they are not always reliable predictors of future outcomes when assessed within the first 12-18 months of a child's life. Neuroimaging may provide more objective, sensitive, and predictive measures of neurodevelopment but tools such as magnetic resonance (MR) imaging are not readily available in many low and middle-income countries (LMICs). MRI systems that operate at lower magnetic fields (< 100mT) may offer increased accessibility, but their use for global health studies remains nascent. The UNITY project is envisaged as a global partnership to advance neuroimaging in global health studies. Here we describe the UNITY project, its goals, methods, operating procedures, and expected outcomes in characterizing neurodevelopment in sub-Saharan Africa and South Asia.

Quantitative MRI findings indicate diffuse white matter damage in Susac Syndrome.

BACKGROUND: Susac Syndrome (SuS) is an autoimmune endotheliopathy impacting the brain, retina and cochlea that can clinically mimic multiple sclerosis (MS). OBJECTIVE: To evaluate non-lesional white matter demyelination changes in SuS compared to MS and healthy controls (HC) using quantitative MRI. METHODS: 3T MRI including myelin water imaging and diffusion basis spectrum imaging were acquired for 7 SuS, 10 MS and 10 HC participants. Non-lesional white matter was analyzed in the corpus callosum (CC) and normal appearing white matter (NAWM). Groups were compared using ANCOVA with Tukey correction. RESULTS: SuS CC myelin water fraction (mean 0.092) was lower than MS(0.11, p = 0.01) and HC(0.11, p = 0.04). Another myelin marker, radial diffusivity, was increased in SuS CC(0.27µm2/ms) compared to HC(0.21µm2/ms, p = 0.008) and MS(0.23µm2/ms, p = 0.05). Fractional anisotropy was lower in SuS CC(0.82) than HC(0.86, p = 0.04). Fiber fraction (reflecting axons) did not differ from HC or MS. In NAWM, radial diffusivity and apparent diffusion coefficient were significantly increased in SuS compared to HC(p < 0.001 for both measures) and MS(p = 0.003, p < 0.001 respectively). CONCLUSIONS: Our results provided evidence of myelin damage in SuS, particularly in the CC, and more extensive microstructural injury in NAWM, supporting the hypothesis that there are widespread microstructural changes in SuS syndrome including diffuse demyelination.

Diffusely abnormal white matter in clinically isolated syndrome is associated with parenchymal loss and elevated neurofilament levels.

We characterized the frequency of diffusely abnormal white matter (DAWM) across a broad spectrum of multiple sclerosis (MS) participants. 35% of clinically isolated syndrome (CIS), 57% of relapsing remitting and 64% of secondary progressive MS participants demonstrated DAWM. CIS with DAWM had decreased cortical thickness, higher lesion load and a higher concentration of serum neurofilament light chain compared to CIS without DAWM. DAWM may be useful in identifying CIS patients with greater injury to their brains. Larger and longitudinal studies are warranted.

Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T2 decay data.

Multi-compartment T2 mapping has gained particular relevance for the study of myelin water in the brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non-negative least squares fitting of multi-echo T2 data has been widely employed for the computation of the myelin water fraction (MWF), and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B1+ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi-compartment T2 and MWF maps. We generated multi-echo spin-echo T2 decay curves following the Carr-Purcell-Meiboom-Gill approach for various myelin concentrations and myelin T2 scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra-/extracellular water geometric mean T2 (gmT2 ). MWF estimates were more stable than myelin water gmT2 time across different settings of the T2 analysis. We observed that the lower limit of the T2 distribution grid should be slightly shorter than TE1 . Both TE1 and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T2 signal. Among all parameters of interest, the estimated MWF and intra-/extracellular water gmT2 differed by approximately 0.13-4 percentage points and 3-4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B1+ inhomogeneities and at lower signal-to-noise ratio. Tailoring acquisition strategies may allow us to better characterize the T2 distribution, including the myelin water, in vivo.

Gadolinium Deposition in Deep Brain Structures: Relationship with Dose and Ionization of Linear Gadolinium-Based Contrast Agents.

BACKGROUND AND PURPOSE: Dose-dependent association between hyperintensity in deep brain structures on unenhanced T1WIs and gadolinium-based contrast agent administrations has been demonstrated with subsequent histopathological confirmation of gadolinium deposition. Our aim was to determine whether greater exposure to linear gadolinium-based contrast agent administration is associated with higher signal intensity in deep brain structures on unenhanced T1-weighted MR imaging. Secondary objective was to compare signal intensity differences between ionic and nonionic linear gadolinium-based contrast agents. MATERIALS AND METHODS: Subjects with secondary-progressive MS originally enrolled in a multicenter clinical trial were studied retrospectively. Eighty subjects (high-exposure cohort) received 9 linear gadolinium-based contrast agent administrations (30 nonionic/50 ionic) between week -4 and year 1 and a tenth administration by year 2. One hundred fifteen subjects (low-exposure cohort) received 2 administrations (40 nonionic/75 ionic) between week -4 and year 1 and a third administration by year 2. Signal intensities were measured on unenhanced T1WIs by placing sample-points on the dentate nucleus, globus pallidus, caudate, thalamus, pons, and white matter, and they were normalized using the following ratios: dentate/pons, globus pallidus/white matter, caudate/white matter, and thalamus/white matter. RESULTS: Between week -4 and year 1, subjects in the high-exposure cohort showed increased signal intensity ratios in all regions (P < .01), while the low-exposure cohort showed only an increase in the dentate nucleus (P = .003). Between years 1 and 2, when both cohorts received only 1 additional gadolinium-based contrast agent, no significant changes were observed. In the high-exposure cohort, significantly higher changes in signal intensity ratios were observed in subjects receiving linear nonionic than in those receiving linear ionic gadolinium-based contrast agents. CONCLUSIONS: Hyperintensity in deep brain structures from gadolinium deposition is related to the number of doses and the type of linear gadolinium-based contrast agent (nonionic greater than ionic) administration.

Progressive multiple sclerosis exhibits decreasing glutamate and glutamine over two years.

BACKGROUND: Few biomarkers of progressive multiple sclerosis (MS) are sensitive to change within the two-year time frame of a clinical trial. OBJECTIVE: To identify biomarkers of MS disease progression with magnetic resonance spectroscopy (MRS) in secondary progressive MS (SPMS). METHODS: Forty-seven SPMS subjects were scanned at baseline and annually for two years. Concentrations of N-acetylaspartate, total creatine, total choline, myo-inositol, glutamate, glutamine, and the sum glutamate+glutamine were measured in a single white matter voxel. RESULTS: Glutamate and glutamine were the only metabolites to show an effect with time: with annual declines of (95% confidence interval): glutamate -4.2% (-6.2% to -2.2%, p < 10(-4)), glutamine -7.3% (-11.8% to -2.9%, p = 0.003), and glutamate+glutamine -5.2% (-7.6% to -2.8%, p < 10(-4)). Metabolite rates of change were more apparent than changes in clinical scores or brain atrophy measures. CONCLUSIONS: The high rates of change of both glutamate and glutamine over two years suggest they are promising new biomarkers of MS disease progression.

Localization of the subthalamic nucleus: optimization with susceptibility-weighted phase MR imaging.

BACKGROUND AND PURPOSE: On clinical MR images, the subthalamic nuclei (STN) are poorly delineated from adjacent structures, impeding safe direct targeting for placement of electrodes in the treatment of Parkinson disease. Susceptibility-weighted MR phase imaging offers improved contrast and spatial resolution at reduced imaging times relative to clinically used T2-weighted spin-echo imaging for STN visualization. Our purpose was to assess STN visibility by using phase imaging, comparing phase and magnitude images obtained concurrently by using susceptibility-weighted imaging (SWI). The goal was to identify an efficient scanning protocol for high-quality phase images of STN. MATERIALS AND METHODS: Seventy-eight SWI scans were acquired at 3T by using different TEs and acceleration factors. STN visibility and delimitation from adjacent structures were scored from 0 (not interpretable) to 5 (excellent). Regression analyses assessed the relationship of STN visibility to scanning parameters RESULTS: STN were identified at all studied TEs on phase images. Visibility and delimitation of STN were consistently superior on phase images compared with magnitude images. Good visualization (score of >or=4) of STN on phase imaging occurred at a mean TE of 20.0 ms and a sensitivity encoding (SENSE) of 1.40. Scores of STN visualization on phase images were dependent on SENSE (P < .002) and TE (P < .031). Good delimitation of the STN on phase imaging occurred at a mean TE of 21.6 ms and a SENSE of 1.36. CONCLUSIONS: Visualization and delimitation of STN was superior on phase images and was achieved at 3T in <2.5 minutes. A TE of 20 ms and an acceleration factor of

MR relaxation in multiple sclerosis.

This article provides an overview of relaxation times and their application to normal brain and brain and cord affected by multiple sclerosis. The goal is to provide readers with an intuitive understanding of what influences relaxation times, how relaxation times can be accurately measured, and how they provide specific information about the pathology of MS. The article summarizes significant results from relaxation time studies in the normal human brain and cord and from people who have multiple sclerosis. It also reports on studies that have compared relaxation time results with results from other MR techniques.